REINVIGORATING OLEORESIN COLLECTION IN THE SOUTHEAST … · reinvigorating oleoresin collection in the southeast usa: evaluation of chemical inducers, stand management, tree characteristics,

REINVIGORATING OLEORESIN COLLECTION IN THE SOUTHEAST USA: EVALUATION OF CHEMICAL INDUCERS, STAND MANAGEMENT, TREE

CHARACTERISTICS, AND GENETICS

By

MARIE JENNIFER LAUTURE

A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT

OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY

UNIVERSITY OF FLORIDA

2017

© 2017 Marie Jennifer Lauture

In memory of Joel Baussan, Sarah Lauture, and Marguerite Marie Yolande Lauture “Mamie”

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ACKNOWLEDGMENTS

I would like to thank my very large family for their unconditional love and support

throughout this journey. To my mother, Marie Anne, a woman who sacrificed so much

for her children and the strongest person I know. I thank her for teaching me to be

resilient, humble, kind, patient, and independent. I thank her for her inspiring me to

never give up and accompanying me on all my adventures across rural Haiti. To my

father, Jean Marie, for always providing me with motivation throughout my studies and

all my endeavors. I thank my sisters, Raquel Aïna, Anne Xavière, Stephanie, and Lya,

for your unwavering love, support, and encouragement. I feel very blessed to have three

older sisters that inspire me with their intelligence, creativity, love, passion, and hard

work. I am immensely grateful to my loving partner and adventure buddy, Cody, who

always encouraged me to pursue my dreams, always championed my accomplishments

and has supported me through the difficult times. I thank you for your patience and

dedication.

I would like to share my gratitude with my graduate advisor, Dr. Gary Peter,

without whom this research would have been futile. I started working with him as an

undergraduate student and without his guidance, support, and dedication, I would have

never pursued my graduate studies. I thank Dr. Alan Hodges for his assistance with

statistical analysis, expertise and guidance in the field, and for teaching me the borehole

tapping technique to collect oleoresin. I would like to acknowledge all other members of

my supervisory committee: Dr. Salvador Gezan, Dr. Eric Jokela, and Dr. John Davis, for

their advice and expertise. I want to thank Dr. Gezan for his assistance with data

analysis and helping me learn ASReml.

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Many thanks to the faculty and staff at the School of Forest Resources and

Conservation (SFRC) and the forest genomics lab. I appreciate the funding support

from the Florida Department of Agriculture and Consumer Services Office of Energy

and the Department of Energy Advanced Research Projects Agency (ARPA-E). I want

to thank Rayonier, Weyerhaeuser (formerly Plum Creek Timber Company), and Roberts

Land & Timber Investment Corp. for providing access to the study sites.

I would like to express my gratitude to Chris Dervinis for his help in organizing my

field experiments, his ability to always make me laugh with his nerdy dad jokes, and for

always being available to answer my questions and provide me with advice. I would

also like to sincerely thank Greg Powell for constantly motivating me, providing a

sympathetic ear and for his help in completing my field work. This research would not

have been possible without the hard work from the field technicians and my colleagues.

I want to thank Emery Hauser, Justice Diamond, Cody Godwin, Hemant Patel, Wilson

Peter, Kari Hurst, Joshua Cucinella, Oliver Fleming, and Tom Pratt for spending hours

out in the forest in the Florida heat.

Many thanks go to my friends, especially Fayola Kojo, Jessica Mulvey, Soyini

Kojo, Daniel Durante, Dan Greene, Erick Larsen, and Melissa Carvalho for your love,

support, encouragement, and hospitality throughout my studies. Finally, I thank my

uncle Joel Baussan, for taking me to visit the University of Florida and for always

encouraging my love and appreciation of the outdoors.

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TABLE OF CONTENTS page

ACKNOWLEDGMENTS .................................................................................................. 4

LIST OF TABLES .......................................................................................................... 10

LIST OF FIGURES ........................................................................................................ 15

LIST OF ABBREVIATIONS ........................................................................................... 18

ABSTRACT ................................................................................................................... 19

CHAPTER

1 INTRODUCTION .................................................................................................... 21

Background ............................................................................................................. 21

Problem .................................................................................................................. 22 Research Objectives ............................................................................................... 24

2 REVIEW OF LITERATURE .................................................................................... 25

Introduction to Oleoresin ......................................................................................... 25

Historical Production of Oleoresin .................................................................... 25 Species Used Worldwide of Oleoresin Production ........................................... 26

Oleoresin Composition ..................................................................................... 28 Oleoresin and Insect Pests ..................................................................................... 30

Coevolution of Oleoresin and Insect Pests ....................................................... 30 Host Selection and Colonization Behavior of Insect Pests ............................... 31

Conifer Defenses Against Insect Pests ............................................................ 34 Climate Change and Pine Beetles .................................................................... 35

Genetic Variation in Oleoresin ................................................................................ 37 Variation of Oleoresin Composition Among Species ........................................ 37

Variation of Oleoresin Canal Occurrence, Size and Density ............................ 41 Variation of Oleoresin Yield and Flow Rate Among Species ............................ 45

Oleoresin Viscosity and Crystallization Rate Among Species .......................... 49 Oleoresin Production in Planted Versus Natural Forests.................................. 51

Inducing Oleoresin Flow and Yield ......................................................................... 52 Chemical Inducers ............................................................................................ 52

Physical Inducers ............................................................................................. 57 Morphological Effects ....................................................................................... 59

Exudation Pressure .......................................................................................... 60 Environmental Inducers .................................................................................... 61

Climate and seasons ................................................................................. 61 Water availability ........................................................................................ 64

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Stand density management ....................................................................... 67

Fertilization................................................................................................. 68 Fire ............................................................................................................. 70

Oleoresin tapping techniques ........................................................................... 73 Application .............................................................................................................. 77

Genetic Control and Breeding for Increased Terpene Production .................... 77 Global Uses for Oleoresin ................................................................................ 80

Pine terpenes for commercial products ...................................................... 80 Pine terpenes for biofuels .......................................................................... 81

Distillation ......................................................................................................... 84 Economics of Oleoresin Production ........................................................................ 84

Non-Timber Forest Products ............................................................................ 84 Oleoresin Tapping and Timber Production ....................................................... 86

Global Supply and Demand .............................................................................. 87 Market requirements .................................................................................. 87

Global production ....................................................................................... 87 What Drives the Production Cost? ................................................................... 89

Labor .......................................................................................................... 89 Equipment .................................................................................................. 90

Cost Compared to other Biofuels ............................................................... 91

3 ASSESSING EFFECTS OF STAND MANAGEMENT, TREE

CHARACTERISTICS, AND CHEMICAL STIMULANT ON OLEORESIN PRODUCTION ........................................................................................................ 99

Introduction ............................................................................................................. 99 Methods ................................................................................................................ 101

Study Areas .................................................................................................... 101 Borehole Tapping and In-Tree Injection ......................................................... 103

Chemical Stimulants ....................................................................................... 105 Data Collection ............................................................................................... 105

Tapping Area .................................................................................................. 106 Statistical Analysis .......................................................................................... 108

Results .................................................................................................................. 110 General Summary of Oleoresin Yield ............................................................. 110

Stand Age ....................................................................................................... 112 Collection Days .............................................................................................. 113

Chemical Stimulants ....................................................................................... 113 Tree Size ........................................................................................................ 115

Stand Management ........................................................................................ 115 Tapping Area .................................................................................................. 116

Discussion ............................................................................................................ 117 Summary and Conclusions ................................................................................... 121

4 CHEMICAL STIMULANT DOSAGE AND CARRIER SOLVENTS IN THE BOREHOLE METHOD TO INCREASE OLEORESIN YIELD IN SLASH PINE .... 144

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Introduction ........................................................................................................... 144

Methods ................................................................................................................ 146 Study Areas .................................................................................................... 146

Borehole Tapping ........................................................................................... 147 Chemical Stimulants ....................................................................................... 147

Data Collection ............................................................................................... 148 Statistical Analysis .......................................................................................... 148

Results .................................................................................................................. 149 Discussion ............................................................................................................ 151

Summary and Conclusions ................................................................................... 155

5 GENETIC EFFECTS ON OLEORESIN FLOW OF SLASH PINE CLONES ......... 166

Introduction ........................................................................................................... 166 Methods ................................................................................................................ 167

Study Area ...................................................................................................... 167 Study Design and Genetic Material ................................................................ 168

Oleoresin Collection ....................................................................................... 169 Statistical Analysis .......................................................................................... 170


Summary and Conclusions ................................................................................... 176

6 CONCLUSION ...................................................................................................... 189

APPENDIX

A COMPARING OLEORESIN YIELD BY CHEMICAL TREATMENT FOR

INDIVIDUAL SITES DURING THE 2013 TO 2015 TAPPING SEASONS ............ 195

B COMPARING OLEORESIN YIELD BY CHEMICAL TREATMENT AND IN TREE INJECTION FOR INDIVIDUAL SITES DURING THE 2014 AND 2015 TAPPING SEASONS ............................................................................................ 198

C SLASH PINE OLEORESIN TAPPING OPTIMIZATION TRIALS .......................... 202

Methods ................................................................................................................ 202

Study Areas .................................................................................................... 202 Borehole Tapping ........................................................................................... 203

Chemical Stimulants ....................................................................................... 204 Data Collection ............................................................................................... 206

Statistical Analysis .......................................................................................... 206 Results .................................................................................................................. 210

High Gum Yielding Slash Pine ....................................................................... 210 Big-Small ........................................................................................................ 211

Triple Borehole Test ....................................................................................... 212 Opposing Side ................................................................................................ 212

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Automated Drilling .......................................................................................... 213

Multi-Borehole Tests....................................................................................... 214 Tapping Intensity ............................................................................................ 215

Discussion ............................................................................................................ 216

D PSEUDO BACKCROSS HYBRID STUDY ............................................................ 242

Introduction ........................................................................................................... 242 Methods ................................................................................................................ 242

Study Area ...................................................................................................... 242 Study Design and Genetic Material ................................................................ 244

Phenotypic Measurement ............................................................................... 245 Statistical Analysis .......................................................................................... 245


LIST OF REFERENCES ............................................................................................. 259

BIOGRAPHICAL SKETCH .......................................................................................... 275

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LIST OF TABLES

Table page 2-1 Average annual oleoresin yield in different regions from various pine species

using different tapping methods. A minimum of 2 kg per tree annually is necessary to be economically viable for commercial production. Data retrieved from Hodges 1995, Tadesse et al. 2001, Rodrigues et al. 2011, Cunningham 2012, and Rodríguez-García et al. 2014, Hadiyane et al. 2015..... 94

2-2 Average cost of oleoresin tapping operation in various countries based on hourly wage and quantity of oleoresin collected per resin tapper. Cost is based on United States dollar. Data retrieved from Cunningham 2014. ............. 95

3-1 Summary of treatments for oleoresin tapping during the 2013 to 2015 field study. ................................................................................................................ 122

3-2 Summary of sites selected for oleoresin tapping during the 2013 to 2015 field study. ................................................................................................................ 123

3-3 Summary of main and interactive effects on oleoresin yield in sites using the standard borehole tapping method between 2013 to 2015 based on a general linear model with covariates. ............................................................... 124

3-4 Summary of main effects F-statistic and p-values on oleoresin yield by site using the standard borehole tapping method between 2013 to 2015 based on a general linear model without covariates. ....................................................... 125

3-5 Summary of main effects F-statistic and p-values on oleoresin yield by stand using the standard borehole tapping method between 2013 to 2015 based on a general linear model without covariates. ....................................................... 126

3-6 Summary of main effects F-statistic and p-values on oleoresin yield by chemical treatment using the standard borehole tapping method between 2013 to 2015 based on a general linear model without covariates. .................. 127

3-7 Summary of main effects F-statistic and p-values on oleoresin yields by collection days drilled using the standard borehole tapping method between 2013 to 2015 based on a general linear model without covariates. .................. 128

3-8 Summary of oleoresin yields by stand age from tapping slash pine using the borehole tapping method. ................................................................................. 129

3-9 Summary of oleoresin yields per collection day by age from tapping slash pine trees using the borehole tapping method. ................................................. 130

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3-10 Summary of oleoresin yields per collection day by age from tapping slash pine trees using the borehole tapping method. The trees were tapped between summer and early fall 2013-2015. ...................................................... 131

3-11 Summary of oleoresin yields by chemical treatment from tapping slash pine using the borehole tapping method. ................................................................. 132

4-1 Summary of oleoresin tapping dosage and carrier solvent experiments in 2014-2016. ....................................................................................................... 156

4-2 Effects of methyl jasmonate carrier solvent, DBH, height and crown volume on oleoresin yield (kg) when tapping slash pine trees in 2015 using the standard borehole tapping method. .................................................................. 157

4-3 Estimated cost per tree of borehole tapping method to collect oleoresin. Calculated costs are based on productivity rates of tapping 26.7 trees per hour and applying 400 mM of methyl jasmonate diluted in 90% ethanol. ......... 158

5-1 Summary of genotypes selected in each replicate of the CCLONES 2 study. .. 177

5-2 Least square means with standard errors for phenotypic traits measured at the CCLONES 2 study. ..................................................................................... 178

5-3 Tukey significance group letters of the least square means for phenotypic traits measured at the CCLONES 2 study (alpha < 0.05) recorded in Table 5-2. ...................................................................................................................... 179

5-4 Broad sense heritability estimates calculated for phenotypic traits measured at the CCLONES 2 study. ................................................................................. 180

5-5 Summary of main and interactive effects on long-term oleoresin yields at the CCLONES 2 site using the borehole tapping method in 2016 based on a general linear clonal model. .............................................................................. 181

5-6 Summary of variance components of genetic correlation between short-term and long-term oleoresin yield in the CCLONES 2 site. ..................................... 182

A-1 Summary of oleoresin yields by chemical treatment in Union 1 site during the 2013 tapping season. Stand age is 14 years old. ............................................. 195

A-2 Summary of oleoresin yields by chemical treatment in Alachua 1 site during the 2013 tapping season. Stand age is 16 years old. ....................................... 195


A-4 Summary of oleoresin yields by chemical treatment in Bradford 1 site during the 2014 tapping season. Stand age is 11 years old. ....................................... 195

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A-7 Summary of oleoresin yields by chemical treatment in Union 2 site during the 2014 tapping season. Stand age is 15 years old. This stand was managed for pine straw raking. ........................................................................................ 196



A-10 Summary of oleoresin yields by chemical treatment in Bradford 1 site during the 2015 tapping season. Stand age is 12 years old. ....................................... 196



A-13 Summary of oleoresin yields by chemical treatment in Union 2 site during the 2015 tapping season. Stand age is 16 years old. This stand was managed for pine straw raking. ........................................................................................ 197



B-1 Summary of oleoresin yields by chemical treatment and in tree injection in Bradford 1 site during the 2014 tapping season. Stand age is 11 years old. .... 198

B-2 Summary of oleoresin yields by chemical treatment and in tree injection in Alachua 3 site during the 2014 tapping season. Stand age is 15 years old. ..... 198

B-3 Summary of oleoresin yields by chemical treatment and in tree injection in Union 1 site during the 2014 tapping season. Stand age is 15 years old. ........ 198

B-4 Summary of oleoresin yields by chemical treatment and in tree injection in Union 2 site during the 2014 tapping season. Stand age is 15 years old. This stand was managed for pine straw raking. ....................................................... 199

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B-7 Summary of oleoresin yields by chemical treatment and in tree injection in Bradford 1 site during the 2015 tapping season. Stand age is 12 years old. .... 200


B-9 Summary of oleoresin yields by chemical treatment and in tree injection in Union 1 site during the 2015 tapping season. Stand age is 16 years old. ........ 200

B-10 Summary of oleoresin yields by chemical treatment and in tree injection in Union 2 site during the 2015 tapping season. Stand age is 16 years old. This stand was managed for pine straw raking. ....................................................... 201



C-1 Summary of oleoresin tapping optimization experiments for slash pine in 2014-2016. ....................................................................................................... 221

C-2 Chemical treatment and improved genetic effects on average oleoresin yield per tree (kg) from slash pine trees using the standard borehole tapping method in 2014. ................................................................................................ 222

C-3 Summary of main and interactive effect on oleoresin yields in high gum and non-high gum site based on a general linear model. ........................................ 223

C-4 DBH, height, crown volume, and effect of chemical stimulant on oleoresin yield (kg) when tapping slash pine trees in 2015 using the big-small borehole tapping method. ................................................................................................ 224

C-5 Summary of main and interactive effect on oleoresin yields in site drilled using the big-small borehole tapping method based on a general linear model. ............................................................................................................... 225

C-6 Effects of tapping treatment, DBH, height and crown volume on oleoresin yield (kg) when tapping slash pine trees in 2015 using the triple borehole (two inner holes) tapping method and stimulated by methyl jasmonate. .......... 226

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C-7 Effects of chemical stimulant and DBH on oleoresin yield (kg) when tapping slash pine trees in 2014 using the opposing side borehole tapping method. .... 227

C-8 Effects of chemical stimulant and number of boreholes on oleoresin yield (kg) when tapping slash pine trees in 2014 using the automated borehole tapping method. ............................................................................................................ 228

C-9 Effects of chemical stimulant and DBH on total oleoresin yield (kg) and oleoresin yield per borehole (kg) when tapping slash pine trees in 2014 using the 6 borehole and standard borehole tapping method. ................................... 229

C-10 Effects of chemical stimulant on oleoresin yield (kg) when tapping slash pine trees in 2014 using the 8-borehole tapping method. ......................................... 230

C-11 Effects of chemical stimulant, DBH, height and crown volume on oleoresin yield (kg) when tapping slash pine trees in 2015 using the 8-borehole tapping method. ............................................................................................................ 231

C-12 Effects of number of boreholes on tapping intensity and oleoresin yield (kg) when tapping slash pine trees using the 6 and 8 borehole taping method. ...... 232

C-13 Summary of optimization treatments, number of boreholes, collection days, chemical inducers and oleoresin yields. ........................................................... 233

C-14 Estimated cost per tree of borehole tapping method to collect oleoresin. Calculated costs are based on productivity rates of tapping 26.7 trees per hour for the manual drilling and 61 trees per hour for the automated drilling. ... 234

D-1 Summary of genotypes planted in each replicate of the CFGRP pseudo backcross hybrid study. .................................................................................... 250

D-2. Least square means with standard errors for phenotypic traits measured at the pseudo-backcross hybrid study.. ................................................................ 251

D-3 Tukey significance group letters of the least square means for phenotypic traits (alpha < 0.05) recorded in Table D-2. ...................................................... 252

D-4 Disease and mortality observed at the end of the 3rd growing season in the two replicate treatments of the pseudo-backcross hybrid. ................................ 253

D-5 Percentage of trees with stem form issues at the end of the 3rd growing season in the pseudo-backcross hybrid study. ................................................. 254

D-6 Narrow sense heritability estimates calculated for phenotypic traits measured at the end of the 3rd growing season in the pseudo-backcross hybrid study.... 255

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LIST OF FIGURES

Figure page 2-1 Processes of that lead to successful beetle colonization and conifer defenses

with interfering processes used by each organism to prevent the other’s success. Adapted from Wood 1982, Raffa et al. 1993, Phillips and Croteau 1999, Raffa et al. 2005, Faccoli and Schlyter 2007. ........................................... 96

2-2 Diagrams of borehole tapping designs. .............................................................. 97

2-3 Oleoresin distillation process adapted from Coppen 1995. ................................ 98

3-1 Calculations for the cross-sectional tapping area and individual hole area model for the trees with DBH greater than 10.16 cm. ....................................... 133

3-2 Calculations for the cross-sectional tapping area and individual hole area model for the trees with DBH less than 10.16 cm. ............................................ 134

3-3 Age effect on oleoresin yield (kg) with standard errors when tapping slash pine trees in North Florida during the 2013 to 2015 field seasons. ................... 135

3-4 Chemical effect on oleoresin yield (kg) with standard errors when tapping slash pine trees in North Florida during the 2013 to 2015 field seasons .......... 136

3-5 Chemical effects of oleoresin yield (g) per day with standard errors when tapping slash pine trees in North Florida during the 2013 to 2015 field seasons. ........................................................................................................... 137

3-6 Nonlinear regression displaying the actual relationship between average oleoresin yield (kg) in slash pine and DBH in cm for all trees tapped in the 2013 to 2015 tapping season. .......................................................................... 138

3-7 Effect of pine straw management and thinning on oleoresin yield (kg) with standard errors when tapping slash pine trees in North Florida during the 2013 to 2015 field seasons. .............................................................................. 139

3-8 Chemical effect on oleoresin yield (kg) when tapping slash pine trees in North Florida during the 2013 to 2015 field seasons under different management scenarios. ................................................................................... 140

3-9 Bivariate fit of total tree yield of oleoresin (kg) in slash pine by tapping intensity. ........................................................................................................... 141

3-10 Bivariate fit of sector area yield of oleoresin in slash pine by tapping intensity. 142

3-11 Bivariate fit of hole area yield of oleoresin in slash pine by tapping intensity. ... 143

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4-1 Chemical dose effects on oleoresin yield (kg) with standard errors when tapping slash pine trees in 2015 using the standard tapping method. The different doses are methyl jasmonate concentrations (50 mM, 100 mM, and 400 mM) and ethephon percentages (1%, 5%, and 10%) ................................ 160

4-2 Chemical dose effects on oleoresin yield (kg) with standard errors when tapping slash pine trees in 2015 using the standard tapping method. .............. 161

4-3 Cumulative flow rate of oleoresin (g) since day of tapping treatment by chemical treatment at the 2015 dose response test. ........................................ 162

4-4 Cumulative flow of oleoresin (g) and resin flow rate over time since day of tapping treatment in Gainesville at the 2015 methyl jasmonate dose response test. ................................................................................................... 163

4-5 Effect of carrier solvent on oleoresin yield (kg) for 100 Mm methyl jasmonate when tapping slash pine trees in North Florida using the standard borehole drilling method. ................................................................................................. 163

4-6 Chemical dose effects on oleoresin yield (kg) with standard errors when tapping slash pine trees in 2016 using the standard tapping method.. ............. 165

5-1 Layout of the University of Florida’s CCLONES 2. ........................................... 183

5-2 Least square means with standard errors for oleoresin traits measured at the CCLONES 2 study.. .......................................................................................... 184

5-3 Bivariate fit of total long-term tree yield of oleoresin (g) in slash pine by DBH (cm).. ................................................................................................................ 185

5-4 Bivariate fit of total long-term clonal mean oleoresin yield (g) in slash pine by DBH (cm) .......................................................................................................... 186

5-5 Bivariate fit of short-term tree yield of oleoresin (g) in slash pine by DBH (cm). ................................................................................................................. 187

5-6 Bivariate fit of short-term and long-term oleoresin yield (g).. ............................ 188

C-1 Diagrams of borehole tapping designs.. ........................................................... 236

C-2 Calculations for the cross-sectional tapping area and individual hole area model for the trees tapped using the 8-borehole method.. ............................... 237

C-3 Chemical effects on oleoresin yield (kg) with standard errors when tapping slash pine trees in 2015 using the standard method and the big-small tapping method.. ........................................................................................................... 238

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C-4 Chemical effects on oleoresin yield (kg) with standard errors when tapping slash pine trees in North Florida in 2014 using the automated drilling technique.. ........................................................................................................ 239

C-5 Predicted cumulative flow of oleoresin (g) by chemical treatment since day of tapping treatment at the 2014 8 borehole test. ................................................. 240

C-6 Bivariate fit of total tree oleoresin yield (kg) in slash pine by tapping intensity using the 6 and 8 borehole methods. ............................................................... 241

D-1 Pedigree of the genotypes planted in the pseudo backcross hybrid study using a Latinized row-column design. ............................................................... 256

D-2 Layout of the pseudo backcross hybrid study using a Latinized row-column design. .............................................................................................................. 257

D-3 Codes used for the pseudo backcross hybrid study. ........................................ 258

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LIST OF ABBREVIATIONS

CCLONES

CFGRP

Comparing Clonal Lines on Experimental Sites

Cooperative Forest Genetics Research Program at the University of Florida

DAP Diammonium phosphate {(NH4)2HPO4}; with the following formulation: 18-46-0 (N-P-K)

DBH

DI

FBRC

FS

H2

h2

OP

Diameter at breast height (1.4 meters)

Deionized

Forest Biology Research Cooperative

Full-Sib

Broad-sense heritability

Narrow sense heritability

Open pollinated

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Abstract of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy

REINVIGORATING OLEORESIN COLLECTION IN THE SOUTHEAST USA: EVALUATION OF CHEMICAL INDUCERS, STAND MANAGEMENT, TREE

CHARACTERISTICS, AND GENETICS

By

Marie Jennifer Lauture

December 2017

Chair: Gary Frank Peter Major: Forest Resources and Conservation

In conifers, oleoresin evolved as a defense mechanism against insects and

microbes. Upon wounding, oleoresin flows to the wound site. Because oleoresin is pure

terpene it has been collected as a non-timber forest product primarily from Pinus

species and is used globally for various products. This research evaluated the potential

of reinvigorating the oleoresin tapping industry in the southeastern United States to be

competitive in the global market. This dissertation analyzed the effects of chemical

inducers, stand management, tree characteristics, and genetics on oleoresin flow and

yield in slash pine (Pinus elliottii var. elliottii) trees in North Florida, with the goal of

determining the optimal and most sustainable oleoresin collection method for stands

managed for timber production.

The borehole tapping method, which involves drilling a hole into the stem, was

used to collect oleoresin from live trees because of its labor efficiency, oleoresin quality,

and no impact of merchantable timber. In trees between 11 and 22 years, oleoresin

yields averaged 1 to 1.5 kg per tree. Oleoresin yields were positively correlated to DBH

and negatively correlated to tapping intensity; larger diameter trees are preferred.

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Methyl jasmonate was the best chemical stimulant tested and was most effective

diluted in 90% ethanol at a concentration of 400 mM. When 400 mM of methyl

jasmonate was used we recovered an average of 3.0 kg of oleoresin per tree with a 95-

day collection season. Based on this average yield of oleoresin per tree and automation

we conclude that it is possible to have a sustainable and profitable commercial

operation for oleoresin tapping in the southeastern U.S.

The potential of increasing oleoresin productivity in pines through breeding

programs is high and imperative to meet global demands. The broad-sense heritability

estimates of short-term and long-term oleoresin yield in a 15-year-old slash pine clonal

test were moderate (H2 = 0.22 and H2 = 0.19, respectively) and showed potential for

selecting families with higher oleoresin productivity. Although short-term and long-term

yield were uncorrelated phenotypically, the Type A genetic correlation between them

was strong (r2=0.78), supporting the use of short-term yield to accelerate breeding for

improved oleoresin yields.

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CHAPTER 1 INTRODUCTION

Background

In the southern United States, native loblolly pine (Pinus taeda L.) and slash pine

(Pinus elliottii var. elliottii) are planted on about 120,000 km2 and 55,000 km2 of land,

respectively (Xiao et al., 2003). These two species are also planted outside of their

native range in various countries primarily for timber harvest. Slash pine is planted in

South Africa, China, Brazil, and various Central American countries for the harvest of

both timber and non-timber forest products (Aguiar et al., 2012; Burns et al., 1990).

Forestland in the southern U.S. is economically valuable and vital to meeting consumer

demands for timber and non-timber forest products both globally and nationally.

Historically, oleoresin was collected for the naval stores industry in the U.S. to

maintain and repair the hulls and rigging of wooden sailing ships (Harrington, 1969).

Pine oleoresin is a key non-timber forest product collected and used globally for various

renewable chemical products and biofuels. Oleoresin evolved in conifers as a

physiochemical defense mechanism against stem boring insects. Oleoresin is found in

several genera of the Pinaceae family, but is collected commercially from thirteen Pinus

species. Within the Pinus genus, the quality and quantity of oleoresin produced varies

by species; however, various external factors, such as climate, water availability, stand

density, fertilization, and tree morphology. can affect the yield potential of a tree. In the

U.S., slash pine is the best candidate species for collection of oleoresin. Furthermore,

the potential for inducing the higher yields of oleoresin within a tree through chemical

and physical treatments is considerable.

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The objectives of Chapter 2 are to address the role and importance of oleoresin

in conifers, outlines the genetic variation in oleoresin yield and composition, describes

and analyzes the current and potential methods of inducing oleoresin in conifers, and

finally outlines the applicability and economics of oleoresin production.

Problem

Since the 1950s, the widespread use of silvicultural technologies and planting of

improved genotypes of Pinus taeda L. (loblolly pine) and Pinus elliottii var. elliottii (slash

pine) has increased growth and wood yields by more than four-fold (Fox, 2007).

Continued increases in yield for renewable and sustainable materials, chemicals and

energy source are needed to meet the growing demand from an increasing human

population (Omer, 2008). As climate change is increasing pressure on forest trees to

resist water stress, pests and disease outbreaks, the importance to increase

productivity and resilience of forest stands becomes evident. In conifers, a primary

defense against insect pests like the boring beetles and their associated fungi is the

terpene based oleoresin. Oleoresin is synthesized and stored within primary and

secondary resin canal networks, and is composed of a mixture of monoterpenes and

diterpenoids (da Silva Rodrigues-Corrêa et al., 2013). Wounded pine stems exude

oleoresin, which has been collected from live trees for millennia. The importance of pine

oleoresin in defense against pests and its use as a renewable chemical and potential

biofuel have generated strong interest in better understanding what limits production. It

is known that both pine wood growth, and oleoresin yield and composition, are under

genetic and environmental control (Squillace and Bengtson, 1961; Squillace, 1971;

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USDA Forest Service 1971a; Hodges, 1995; Jokela, 2004; Zhang et al., 2006;

Westbrook et al., 2013; Rodriguez-Garcia, 2014).

While oleoresin yield is affected by genetic and environmental components, there

is limited knowledge about how they interact to affect yield. Furthermore, the biological,

environmental, or silvicultural factors causing the variability observed in the flow rate

and yield of oleoresin among trees from operational stands is not well understood. We

know there may be some morphological, anatomical and physiochemical characteristics

of trees that affect oleoresin production, but we are lacking knowledge of which primary

factors are limiting in conifers. The heritability of different traits, such as stem diameter

(DBH), tree height, crown size, and oleoresin yield, can help quantify the importance of

genetics and the environment. Additionally, while there is an established market for

these forest products, the potential for maximizing production of oleoresin within a stand

has yet to be met.

The long-term goal of this research is to understand the factors that affect growth

and yield of forest trees, focusing on loblolly and slash pine, and to maximize the

potential production of timber and non-timber resources, specifically oleoresin. This

project has the potential of reviving the once thriving industry of oleoresin collection in

the U.S. While oil prices in the U.S. have decreased significantly over the past couple of

years, it is still crucial to find alternatives that are more sustainable. This study will

provide an assessment of the feasibility for private landowners to produce oleoresin for

renewable chemicals and biofuels. If economically viable, application of this research

will provide a way for landowners to increase their annual income from slash pine

plantations. By analyzing the genetic influence on oleoresin properties, we gain insight

24

on how to manipulate tree breeding and selection to increase resin flow and decrease

variability within individual trees.

Research Objectives

Several study sites were selected for this research in North Florida, primarily in

Alachua, Union, and Bradford Counties. The main objectives of this research are:

1. Maximize collection and recovery of oleoresin and increase terpene synthesis in slash pine for renewable chemicals and biofuel production by testing different chemical stimulants, stand ages, and stand management practices (Chapter 3);

2. Determine the optimal methyl jasmonate dosage and carrier solvent for oleoresin collection in the southeast United States (Chapter 4);

3. Determine the genotypic and phenotypic correlations between 24-hour resin flow with multi-month resin collection (Chapter 5); and

Application of this research will provide a way for landowners to increase their

annual income from slash pine plantations by creating a cost-effective system for tree

induction and collection to supply large quantities of oleoresin from existing plantations

to the pine chemical industry and advancing the biofuels industry in Florida. Analyzing

the phenotypic growth traits and oleoresin production of loblolly and slash pine

backcross hybrids will provide insight on the potential to increase oleoresin yield and

timber production from southern pines, as well as improving genomic selection

techniques that would benefit tree breeding projects.

25

CHAPTER 2 REVIEW OF LITERATURE

Introduction to Oleoresin

All conifers naturally produce oleoresin as a defense mechanism to protect trees

against insect pests, microbes, and physical damage. Oleoresin is extracted from a

variety of plant species, however, commercially it is primarily collected from Pinus

species. All Pinus species naturally produce oleoresin, though some species produce

better quality and higher quantities of oleoresin. While oleoresin is collected from live

pine trees in the forest for commercial purposes worldwide, the market is currently

dominated by China, which accounts for 74% of global production, while the second

largest producers are Brazil and Indonesia, each with about 9% of world production

(Aguiar et al., 2012).

Historical Production of Oleoresin

While no longer as relevant in the market, the southern U.S., especially Georgia

and North Florida, historically collected and processed pine terpenes from live trees and

harvested wood in chemical pulp mills. The U.S. naval stores industry began in the mid-

19th century in the Southeast, where pine oleoresin was extracted from live longleaf

(Pinus palustris Mill.) and slash pine (Pinus elliottii Engelm. Var. elliottii) trees by

streaking the bark along the stem and attaching a collection cup (Harrington, 1969;

Sullivan, 2014). Historically, gum oleoresin was collected for use on ships for repairs, to

caulk seams, and protect ropes (Harrington, 1969).

From the early 1900s to around 1970s, the annual production of pine gum

turpentine in the U.S. was about 30 million gallons and the production of gum rosin

averaged about 1 billion gallons (Harrington, 1969). However, according to Harrington

26

(1969), production from pine gum began to decrease in the 1950s and by 1967 it

dropped to 10 percent of total gum production. In 1910, steam distillation led to

increases in turpentine recovery from pine stumps and in 1928 the advent of sulfate

pulping also led to a decrease in turpentine and rosin collected from living trees

(Harrington, 1969).

In the mid-1930s, the industry began to reform the resin tapping technique by

using chemical stimulants to increase production, and modernizing the collection

equipment to be more easily removed and reduce negative effects on tree vigor

(Harrington, 1969). Oleoresin tapping stopped in the southeastern U.S. late last century

due to high labor costs, reductions in older slash pine stands, rising competition from

chemical substitutes, as well as the negative effects of over tapping (Sullivan, 2014).

Furthermore, after World War II, tall oil rosin became more prevalent and collection from

live trees decreased (Harrington, 1969). However, similar techniques are currently being

used around the world to collect pine resin. Currently, timber harvesting in the southeast

U.S. is highly efficient, productive and sustainable (Eisenbies et al., 2009). Additionally,

current research shows that timber harvested for biofuel will not have negative long-

term effects on forest growth (Eisenbies et al., 2009). Reinvigorating the oleoresin

tapping industry in the southern U.S. has the potential to be profitable due to the

increase in productivity of pine plantations, the modernized tapping techniques, as well

as the need to find alternative renewable sources of chemicals and fuels.

Species Used Worldwide of Oleoresin Production

The species used for tapping depends on the geographic region in which

collection takes place, and the availability of high yielding species currently in the

27

region, or capable of being grown in the region. In some countries, China in particular,

the industry relies mostly on natural stands of Pinus massoniana trees for tapping, while

others, such as Brazil, use non-native planted pines like P. elliottii for tapping. According

to Aguiar et al. (2012), the Pinus species and varieties that have high resin yielding

capabilities include: P. elliottii Engelm. var. elliottii, P. elliottii Engelm. var. densa, P.

massoniana Lamb., P. caribaea Morelet var. bahamensis Griseb., P. caribaea Morelet

var. hondurensis Sénécl., P. caribaea Morelet var. caribaea, P. yunnanensis Franch., P.

merkusii Jungh. Et De Vriese, P. oocarpa Schiede ex Schltdl., P. kesiya Royle ex

Gordon, P. pinaster Aiton, P. sylvestris L., P. palustris Mill., P. nigra J. F. Arnold, P.

taeda L., P. roxburghii Sarg., P. wallichiana A. B. Jacks., P. nigra J. F. Arnold

subsp. pallasiana (Lamb.) Holmboe, P. sibirica Du Tour, P. pinea L., P. tropicalis

Morelet, and P. halepensis Mill. While all those species can produce large amounts of

oleoresin, they may not be ideal candidates for tapping because they may lack some

important characteristics to increase the flow of oleoresin, such as low crystallization

rate.

The primary species used today for commercial oleoresin production is P.

massoniana, which is native to south, central and east China as well as other southeast

Asian countries and grows at elevations ranging from a few meters to 2000 meters

(Farjon, 2013a). Though it is a productive species, P. massoniana is not usually planted

outside its native range (Farjon, 2013a); therefore, it would not be suitable for the

oleoresin industry in the United States. The other leading species used for commercial

tapping outside of China include P. elliottii var. elliottii, P. caribaea, P. pinaster, and P.

sylvestris (Aguiar et al., 2012). The overall highest yielding oleoresin species is P.

28

elliottii var. elliottii which is native to the southeastern U.S., primarily Florida and

Georgia, and is planted outside of its native range in South Africa, China, Brazil, and

Central America, for the harvest of both timber and non-timber forest products (Aguiar

et al., 2012; Burns et al., 1990). P. caribaea is a species native to Central America and

the Caribbean and is also planted for oleoresin and timber production in South America

(Aguiar et al., 2012; Farjon, 2013b). P. caribaea includes three major varieties

(bahamensis, hondurensis, and caribaea), some of which are more exploited than

others (Farjon, 2013b). To build an oleoresin industry P. elliottii var. elliottii is the ideal

candidate species because of its ability to be planted in a variety of geographic

locations, improved genetics, and high overall productivity. Among the biggest threats to

P. elliottii var. elliottii are bark boring beetles, however, this threat exists only in its

native range (Roberds et al. 2003; Strom et al. 2002).

Oleoresin Composition

The turpentine in oleoresin consists of monoterpene, which includes α and β-

pinene (Rodrigues et al., 2011; da Silva Rodrigues-Corrêa et al., 2013; Rodrigues and

Fett-Neto, 2009). The rosin in oleoresin consists of diterpenoids, which seal wounds

made by boring bark beetles or other predators (Rodrigues and Fett-Neto, 2009;

Rodrigues et al., 2011; da Silva Rodrigues-Corrêa et al., 2013). Oleoresins produced in

traumatic resin ducts tend to include other substances such as phenolics (Nagy et al.,

2000). The oleoresin in conifers is synthesized in resin canals, a specialized tissue that

forms an interconnected network in needles and wood. In resin canals, live epithelial

cells constitutively synthesize oleoresin and secrete it into the luminal space of the

canal (Steele et al., 1995).

29

Normal resin canals occur naturally in conifers; however, when the tree

undergoes significant stress, like wounding or an attack from pests, they develop

traumatic resin canals (Nagy et al., 2000; Lin et al., 2002). Both types of resin canals

are surrounded by epithelial and parenchyma cells (Nagy et al., 2000; Lin et al., 2002).

The structure of normal resin canals is typically a single layer of cells and tubular, while

traumatic resin canals are round and come in one or two rows of cells (Nagy et al. 2000;

Lin et al. 2002). These canals, depending on species and genera, may be found in the

xylem, phloem, roots, stem, leaves, and seeds (Lin et al., 2002). Within the xylem and

phloem of most conifer species, normal resin canals are divided into the vertical (axial)

and horizontal (radial) canals (Lin et al., 2002). Generally, axial resin canals are found in

the secondary xylem of conifers often formed as traumatic ducts (Nagy et al., 2000).

The axial resin canals in the xylem can be divided into canals with thin walls

surrounding the epithelial cells, which only occur in Pinus species, or canals with thick

walls surrounding the epithelial cells, which are found in almost all other genera (Lin et

al., 2002). Resin canal length can vary greatly between and within species and

individual trees (Lapasha and Wheeler, 1990). In Pinus taeda, longitudinal resin canal

lengths ranged from an average of 57 mm to 122 mm for 10-year-old trees, and 74 mm

to 167 mm for 20-year-old trees (Lapasha and Wheeler, 1990). LaPasha and Wheeler

(1990) also reported resin canal lengths of other conifer species of varying ages and

found an average length of 75 mm for 15-year-old P. contorta, 185 mm for 16-year old

P. monticola, 59 mm for 20-year-old P. ponderosa, and 207 mm and 498 mm for 10 and

20-year-old P. elliottii trees, respectively. These differences in lengths of resin canals

have a significant impact on the yield and ability to extract oleoresin from the tree. Thus,

30

noting these differences gives insight on which species is a better candidate for

commercial oleoresin production.

Oleoresin and Insect Pests

Coevolution of Oleoresin and Insect Pests

Forest trees are long lived species and coevolved with their pests and

pathogens. Bark beetles (Curculionidae: Scolytinae) including mountain pine beetle

(Dendroctonus ponderosae) and southern pine beetle (Dendroctonus frontalis) are

responsible for the death of billions of conifer trees worldwide (Ferrenberg et al., 2014).

To defend against insect pests, conifers evolved chemical defenses in oleoresin and

resin canals. Oleoresin is released upon wounding and the sticky monoterpene and

diterpenoid resin repels, weakens and can kill insects and their associated fungi (Raffa

et al., 2005; Ferrenberg et al., 2014). Terpenes are polymers of the five carbon (C)

isopentenyl pyrophosphate, and are the largest and most diverse group of secondary

products and have important roles in chemical defenses of plants (Rodrigues-Corrêa et

al., 2012).

While many insect pests have the ability to kill off entire forest stands, conifers

have successfully persisted in part due to their highly evolved chemical defense

mechanism (Phillips and Croteau, 1999). Oleoresin is composed of C10 monoterpenes

and C15 sesquiterpenes which constitute the turpentine fraction that also contains

toxins, like limonene and 3-carene responsible for fighting off insects and other pests,

and C20 diterpenoids (Phillips and Croteau, 1999; Bohlmann and Keeling, 2008;

Rodrigues-Corrêa, 2012). Understanding the relationship between oleoresin production

in trees for defense and insect infestation is crucial to determine how yield and flow of

31

oleoresin can be increased. These relationships can give insight as to what factors are

most important to control oleoresin flow and what can be manipulated to increase

overall production. Furthermore, if changes in global climate change increases or

worsens bark beetle infestations, it is important to recognize how to increase terpene

production to mitigate the potential negative impacts.

Host Selection and Colonization Behavior of Insect Pests

Conifers have adapted to bark beetle attacks; similarly bark beetles have

adapted their strategies for successfully locating, colonizing, and killing host trees

(Wood, 1982). There are many ecological factors that play a role in determining which

insect pests colonize living or recently dead trees, what parts of the trees get attacked,

as well as physiological characteristics of the host trees that make it easier or more

difficult for colonization, such as oleoresin characteristics. According to Wood (1982),

certain insect pests strictly colonize healthy trees, while others prey on trees in poorer

health due to environmental stressors. Smaller and lateral buds are preferable for

selection by bark beetles because they do not produce enough oleoresin to kill the

larvae (Harris, 1960).

In turn, bark beetles have adapted to tree defenses, enabling colonization. First,

bark beetles work in large numbers, making their joint attacks more exhaustive to the

tree (Raffa et al., 2005). Furthermore, bark beetles use pheromones from oxygenated

terpenes, which are synthesized from metabolized host compounds to increase their

aggression (Raffa et al., 2005). Rhyacionia buoliana (Schiff.) larvae remove small

amounts of resin from their bodies with their mouths and their vomitus (Harris, 1960).

On the other hand, when flooded with larger amounts of resin the R. buoliana larvae

32

either abandon the tree or are drowned in the resin, and thus are incapable of doing too

much damage (Harris, 1960).

Pest species have been successful at colonizing conifer host trees by evolving to

produce aggregation pheromones, which allow pests to communicate with one another

and facilitates mating, host finding and resource utilization (Raffa et al., 1993). Some

species also use aggregation pheromones to attract other beetles from the same

species to their host tree, which allow the group of beetles to kill the host tree by virtue

of strength in numbers (Raffa et al., 1993). Bark beetles may synthesize their

aggregation pheromones from compounds taken from the host tree; for example,

ipsedienol is synthesized from myrcene and verbenone is derived from α-pinene (Raffa

et al., 1993).

Wood (1982) described in detail the process of colonizing a host tree by beetles.

This process begins with dispersal when young beetles emerge from a host tree and

either fly out (long or short distance) or stay in the vicinity of the host tree due to

attractive pheromones (Wood, 1982). This phase is followed by selection of a new host

tree by the pests. Certain beetles may be attracted to volatile compounds that are

released by a tree that is stressed, while others are incapable of detecting prime host

trees prior to landing (Wood, 1982). The time it takes for the tree to be colonized after

this phase depends on how quickly pheromones are produced and how weakened the

host tree is already (Wood, 1982) . Once a beetle selects and establishes itself in the

host tree they begin feeding and release pheromones in order to attract more beetles,

both male and female, which marks the initiation of the concentration phase (Wood,

1982). There is a negative correlation between the time between selection and

33

pheromone release and the survival and success of the bark beetle population; with

shorter elapsed time giving greater success (Wood, 1982). The final phase of colonizing

a tree is termination (Wood, 1982). Proper termination is crucial for the survival of the

bark beetle population because if not executed properly, the population runs the risk of

exceeding its carrying capacity and deteriorating its resources (Wood, 1982). In some

cases, the presence of both male and female beetles decreases the attraction of new

beetles to come to the host tree, because certain males release chemicals that alters

the responses to pheromones, which limits reproduction and keeps the population at a

sustainable level (Wood, 1982). Furthermore, during this phase, some beetles may

jump to adjacent trees and begin establishing themselves and releasing pheromones

(Wood, 1982).

Once dispersal and selection have occurred, and the concentration phase has

begun, the beetles on the host tree begin to bore through the cambial tissue and create

galleries within the tree for reproduction (Phillips and Croteau, 1999). Once the adults

have laid their eggs, they bore through the tree creating exit holes and disperse

elsewhere beginning a new colonization process (Phillips and Croteau, 1999). When

bark beetles attack conifers, their associated fungi are also inoculated, providing access

to host tree carbohydrates (Phillips and Croteau, 1999). Furthermore, these fungi

produce toxins that play a large role in killing the host tree (Phillips and Croteau, 1999).

After the oleoresin reaches the site of wounding, the exposure to the atmosphere

causes it to crystallize and harden, which seals the wound (Phillips and Croteau, 1999).

Most destructive conifer pests, such as bark beetles, only attack live trees and work in

34

groups in order to kill their host tree to successfully reproduce (Phillips and Croteau,

1999).

Conifer Defenses Against Insect Pests

Southern pine beetle (Dendroctonus frontalis) is a destructive native pest that

attacks and kills pine stands in the southeastern U.S. during major outbreaks, especially

P. taeda L. stands (Roberds et al., 2003; Strom et al., 2002). These pine forests use

oleoresin to defend themselves against southern pine beetles as it entraps the attacking

beetles, which prevent them from establishing galleries, and it delivers toxic compounds

to the insect (Roberds et al., 2003). The most important toxic chemicals in oleoresin for

pine tree resistance to insect pests, such as bark beetles, are α-pinene, which works

against the pheromones of D. frontalis, and limonene, which helps increase the tree’s

resistance (Hodges et al., 1979; Strom et al., 2002). The abundance of these two

chemicals, however, are not correlated to tree size including crown dimensions, DBH

and height (Strom et al., 2002).

Individual trees and species differ in their reactions to a pest attack, such as bark

beetles; however, in most cases the concentration of monoterpenes in the tissue

surrounding the entry site increases by a few hundred-fold within a couple weeks (Raffa

et al., 2005; Figure 2-1). Similarly, the percent mortality of pests increases in a

logarithmic fashion because of synthesis of terpenes by the tree (Raffa et al., 2005).

Diterpenoids, on the other hand, do not play a significant role in fighting against boring

bark beetles, but they do fight against fungi (Raffa et al., 2005). Many factors help

increase resistance to insect attacks on conifers; some of which are only successful in

certain species. For example, bark beetle resistance in lodgepole and limber pine,

35

Ferrenberg et al. (2014) found that resistant trees, compared to susceptible trees, had

more resin ducts within the recent 5 to 10 years of tissue growth. This likely increased

resin production and flow, which helped fight against an attack (Ferrenberg et al., 2014).

The density and size of resin ducts was significantly greater in resistant P. flexilis

compared with susceptible trees. In contrast, no significant difference was observed in

P. contorta, between resistant and non-resistant trees (Ferrenberg et al., 2014). In both

P. contorta and P. flexilis, radial tree growth was positively correlated with the quantity

of resin ducts (Ferrenberg et al., 2014). Oleoresin flow has identified trees that are

resistant to southern pine beetle in P. taeda and P. echinata (Hodges et al., 1979).

Phenolics also play a role in bark beetle resistance in certain conifers, such as,

Scots pine (Pinus sylvestris L.) and Norway spruce (Picea abies Karst.) (Faccoli and

Schlyter, 2007). Phenolic compounds increase tree resistance to bark beetles by

reducing the host acceptance and feeding of insects (Faccoli and Schylter, 2007; Figure

2-1). Parenchyma cells in the secondary phloem play a vital role in the constitutive and

inducible defense responses against invasive insects in Norway spruce (Franceschi et

al., 1998; Franceschi et al., 2000). However, due to the coevolution of trees and insects

with their associated fungi, some tree phenolic compounds are not as successful as

non-host compounds to deter insect tunneling of Ips typographus on P. abies Karst.

(Faccoli and Schylter, 2007).

Climate Change and Pine Beetles

It is evident that climate change is occurring, and increases in the amounts of

greenhouse gas emissions by humans are directly and indirectly causing a variety of

issues - including sea level rise, increases in atmospheric temperature, and extreme

36

weather events (IPCC, 2014). These issues can in turn cause a shift in vegetation type,

land use changes, and increase in insect infestations (USGCRP, 2009 and USGCRP,

2014). Climate change can impact conifer forests and bark beetle population dynamics

both directly and indirectly. Climate change can alter tree defense and tolerance of

insect pests, insect physiology, distribution, and abundance, as well as interactions

between abiotic and biotic disturbance agents (Weed et al., 2013).

Pine beetle outbreaks are heavily influenced by climate (Gan, 2004; Bentz et al.,

2010; McNulty et al., 2013). Temperature has a strong influence on population

dynamics and developmental processes of bark beetles (Bentz et al., 2010). Beetles

have become more tolerant to colder temperatures, but there is still significant mortality

due to cold (Bentz et al., 2010). However, with climate change, cold-induced mortality

would be reduced. Temperature increases during the spring and winter are predicted to

promote pine beetle outbreaks, while warmer fall temperatures would reduce beetle

outbreaks (Gan, 2004). Furthermore, warmer winters may promote the overwintering of

beetles which could lead to more severe outbreaks and infestations the following spring

(Gan, 2004). During the 21st century, average global temperatures are predicted to

increase 1.8 to 4.0 degrees Celsius because of an increase in atmospheric CO2 levels

(Bentz et al., 2010). If atmospheric CO2 levels double to about 750 parts per million,

southern pine beetle infestation risks in the U.S. is predicted to increase by 2.5 to 5

times (Gan, 2004).

Climate change is a concern, especially to forest landowners, because as the

global temperatures continue to increase, there is a high risk that conifer forests,

especially planted forest with faster growth rates, will be damaged by increases in pine

37

beetle outbreaks. In the southern U.S. about $1.5 billion worth of timber from 1970 to

1996 were lost as a result of southern pine beetle infestations (Gan, 2004; USGCRP,

2009). With climate change, beetles in the southern U.S. and Central America will have

the potential to move north following increasing temperatures (Bentz et al., 2010; Gillis,

2013). This could be quite detrimental, as the beetles with current ranges limited to the

south could infest northern forests and increase the risks of damage. For example, in

New Jersey, the southern pine beetle has already infested and killed thousands of acres

of pineland due to the warmer winters (Gillis, 2013). While the case in New Jersey was

confined to a small area, and in the northwest U.S. and Canada, tens of millions of

acres of forests have already been destroyed by mountain pine beetle outbreaks made

possible by the warming of those areas, highlighting the severity of the threat (Bentz et

al., 2010; Gillis, 2013). Furthermore, elevated CO2 concentrations in the atmosphere will

indirectly affect the interactions of bark beetles and conifers (Bentz et al., 2010).

Increasing CO2 concentrations increases the ratio between carbon and nitrogen, which

would decrease the number of nutrients available for bark beetle, causing insects to

feed more heavily on conifers (Bentz et al., 2010).

Genetic Variation in Oleoresin

Variation of Oleoresin Composition Among Species

The chemical composition of oleoresin differs among pine species and

geographical ranges (Rezzi et al., 2005). The main constituents found in the oleoresin

of Pinus nigra at various concentrations include abietic acid, dehydroabietic acid,

neoabietic acid, levoprimaric acid, palustric acid, primaric acid, isoprimaric,

sandaracopimaric acid, primaral, isoprimaral, primarol, isocembrol, 4-epi-isocembrol,

38

cembrene, β-pinene and α-pinene (Rezzi et al., 2005). In China, there are over 36

different components found in nine Chinese pine species (Song et al., 1995). The most

common components occurring at higher levels include α-pinene, limonene, communic

acid, palustric acid, abietic acid, and neoabietic acid (Song et al., 1995). Some Chinese

pine species, like P. densata had extremely low levels of α-pinene (4.4%), compared to

the other species which had levels ranging from 14.6 to 39.4% (Song et al., 2005). Most

Chinese species had limonene levels below 2%, while P. densata, P. takahasii, and P.

sylvestritomis oleoresin was composed of 24.8% β-pinene (Song et al., 2005). This kind

of variation was observed with many other components of the oleoresin in Chinese

pines (Song et al., 2005).

Strom et al. (2002) reported that stands where a southern pine beetle outbreak

occurred, progeny trees selected from a population that successfully survived an

outbreak produced 1.65 times the quantity of oleoresin compared to those from the

general population. This study also shows that genetics plays a large role in determining

the resistance of individuals to insect pests. A tree more resistant to insect infestation

and with better defense mechanisms would be a better candidate for oleoresin

production because tapping and disease induced mortality would be lower and yield

would be higher because of better quality production.

Squillace (1971) surveyed the oleoresin monoterpene composition in slash pine

trees and found that the majority of the monoterpenes were composed of β-pinene

(45%), α-pinene (28.7%), myrcene (10.9%), and β-phellandrene (13.4%). Many of these

monoterpenes exhibited some sign of bimodality, especially β-pinene with some trees

being composed of only 2 to 8%, while 98% of trees measured had about 21 to 74%.

39

Additionally, myrcene varied from 0 to 5% in some trees to 6 to 45% in others

(Squillace, 1971).

Sukarno et al. 2015 also looked at the composition of the oleoresin collected

from the different provenances of P. merkusii in Indonesia and found that it consisted

primarily of α-pinene ranging from 73.3 to 87.2% of the total composition. β-pinene, α-

pinene, myrcene, and β-phellandrene all have high levels of narrow-sense heritability

(0.49-0.56, 0.79-0.89, 0.63-0.67, and 0.55-0.71, respectively) (Squillace, 1971). This

shows that there is a strong evidence for Mendellian inheritance for these traits

involving few or multiple genes (Squillace, 1971; Squillace and Fisher, 1966).

While there is a lot of between-species variation in oleoresin composition, there

is equally as much variation observed within-species (Squillace and Fisher, 1966;

Squillace, 1971). Squillace and Fisher (1996) looked at the variation in oleoresin

composition in P. elliottii in the U.S. and how they were inherited. However, in their

study they only analyzed oleoresin samples from 174 trees growing within a 15-mile

radius (Squillace and Fisher, 1966). This geographic and sample size limitation may not

represent accurately the oleoresin composition of slash pine throughout the

southeastern U.S. Compared to Squillace (1971), Squillace and Fisher (1966) found

that the P. elliottii monoterpenes were composed of β-pinene (40.3%), α-pinene

(18.8%), myrcene (15.8%), and β-phellandrene (22%). Both found that the oleoresin

monoterpenes consisted primarily of those four main compounds. The variation in

oleoresin composition among trees within the same species varies not only among trees

from different sites, but also between trees from the same stand (Squillace and Fisher,

40

1966). Furthermore, within individual trees, variation of oleoresin monoterpene

composition was observed between cortex and stem gum (Squillace and Fisher, 1966).

Monoterpene composition within and between populations of P. ponderosa

varies greatly and affects the tree’s ability to defend itself against insect pests

(Sturgeon, 1979). Sturgeon (1979) found that ponderosa pine trees with higher levels of

limonene in the oleoresin, which is toxic to many pests, are more successful at surviving

a beetle attack and not being selected as a host by pests. However, in instances where

all favorable trees have already been depleted, insects may develop a tolerance to

limonene and prey upon trees with higher levels of it (Sturgeon, 1979). Since insect

pests and trees have coevolved with one another, directional selection favoring trees

with higher limonene concentration in resin occurred in a northern California and

southern Oregon population of ponderosa pine because beetle predation occurred more

frequently on trees with lower levels of limonene (Sturgeon, 1979). Numerous studies

have shown variation in oleoresin composition among and within species and

provenances. If establishing a plantation specifically to collect oleoresin commercially, it

would be crucial to select individuals from provenances geographically close to where a

plantation would be established.

Oleoresin composition can also be impacted by climate and seasons (Conners et

al., 1999). During the course of the year, Conners et al. (1999) found that monoterpene

concentrations in P. taeda varied by up to 300 to 500%. This could be the effect of

temperature, precipitation, or other environmental factors (Conners et al., 1999). This

variation was observed in trees planted in both Mississippi and North Carolina (Conner

et al., 1999).

41

Variation of Oleoresin Canal Occurrence, Size and Density

While resin canals can occur in all conifers, their composition, anatomy and

distribution differs among species and genera (Lin et al., 2002). To begin, depending on

species and genera, resin canals are found in certain tissue or organs (Lin et al., 2002).

Because of among species variation in resin canal characteristics, species and

subspecies are able to be distinguished and identified depending on resin canal density

(Lin et al., 2001). Resin canals in the genera Abies, Cedrus, Tsuga, and Pseudolarix

occur only in the event of wounding, pressure, auxin exposure, wind damage, or injury

due to herbivore attack (Fahn, 1988). Axial and radial resin canals occur in the

secondary phloem of Larix and Pinus species, while only radial resin canals occur in the

secondary phloem in Cathaya, Hudus, Picea, and Pseudotsuga (Lin et al., 2002). Some

literature distinguishes between resin canals and resin cavities, which are considered

elongated spherical sacs, though those distinctions are not clear (Lin et al., 2002;

Srivastava, 1963). Species from the genera Abies, Keteleeria, Larix, Nothotsuga, Picea,

Pinus, and Pseudotsuga in addition to resin canals, also have resin cavities (Lin et al.,

2002).

Resin canals are found in the primary xylem of Pseudotsuga species only. In the

secondary xylem, however, resin canals are found in nearly all species in the Pinaceae

family; they occur in Cathaya, Keteleeria, Larix, Nothotsuga, Picea, Pinus, and

Pseudotsuga and are absent in Abies, Tsuga, Pseudolarix, and Cedrus (Lin et al.,

2002). Larger inner resin canals can be found in the stem cortex of Cathaya, Abies,

Keteleeria, Nothotsuga, Picea, Pinus, Pseudotsuga, and Tsuga species (Lin et al.,

2002). In addition to the inner canals, smaller peripheral canals are also found in Pinus

42

species (Lin et al., 2002). All Pinaceae genera have inner resin canals, which occur in

the inner part of the mesophylls around the vascular cylinder; or peripheral resin canals,

which occur near the epidermis (Lin et al., 2002). As in the stems, most Pinaceae

genera have the peripheral resin canals in the leaves, apart from Pinus and Tsuga (Lin

et al., 2002). Species in Abies, Cedrus, Keteleeria, and Pseudolarix have 1 to 5 resin

canals occurring in the sclerenchymatous layer of the seed coat (Lin et al., 2002).

Furthermore, species in the Nothotsuga and Tsuga genera have about 10 to 20 resin

canals occurring in the sclerenchymatous layer of the seed coat (Lin et al., 2002). In the

bracts of the female cone, there are usually 1 to 2 resin canals, depending on the

species, found in all Pinaceae genera (Lin et al., 2002). These resin canals either occur

in the abaxial side of the bract (peripheral) or on both sides of the vascular bundle

(inner) (Lin et al., 2002).

Resin canals can also be found in the seed scales of all 11 Pinaceae genera (Lin

et al., 2002). In Abies, Larix, Pseudotsuga, and Tsuga these canals occur on the adaxial

side of the vascular bundles, while in Cedrus and Pinus they occur in the abaxial side of

the vascular bundles, and in Cathaya, Keteleeria, Nothotsuga, Picea, and Pseudolarix

they are found both on the abaxial and adaxial side of the vascular bundles (Lin et al.,

2002). Lin et al. (2002) found that in general, the Pinaceae genera can be separated

into two groups based on resin canal attributes. The species in Abies, Cedrus,

Keteleeria, Nothotsuga, Pseudolarix, and Tsuga have normal resin canals in the seed

coat and do not have radial resin canals in the secondary xylem or secondary phloem

(Lin et al., 2002). On the contrary, the species in Cathaya, Larix, Picea, Pinus, and

43

Pseudotsuga do not have normal resin canals in the seed coat, but do have radial resin

canals in the secondary xylem and secondary phloem (Lin et al., 2002).

There can also be slight variation in resin canal density within species depending

on individual tree characteristic, such as tree foliage height, crown, and age (Lin et al.,

2001). Lin et al. (2001) looked at these within species variations in resin canal densities

in Pinus sylvestris L. and found that needles collected higher in the tree had a greater

density of resin canals compared to the ones in the mid and lower section. When

analyzing resin canal densities in needles collected on the exterior of the crown

compared to the interior, Lin et al. (2001) found that the ones on the outer portion of the

crown had significantly more resin canals. The number of resin canals in needles also

increased with age (Lin et al., 2001).

The density of radial resin canals can vary tremendously within and among trees

(Stark, 1965). The resin duct density in Pinus species ranges from 35 to 50 per square

cm in P. ponderosa, 35 to 65 per square cm in P. contorta, 50 to 85 per square cm in P.

elliottii, 60 to 70 per square cm in P. sylvestris L., and 60+ per square cm in P. glabra

(Stark, 1965). P. ponderosa tends to have higher natural resin canal densities further up

in the tree while P. contorta has higher duct densities concentrated at the base (Stark,

1965). Species also vary in the size of the resin canals, which can have an impact on

the ability of a tree to produce oleoresin (Stark, 1965). Furthermore, the size and

number of resin canals for species tend to decrease with increasing age (Mergen et al.,

1955).

The ability of a pine tree to successfully resist and defend itself from a bark

beetle attack is also related to size and density of resin ducts (Hood and Sala, 2015;

44

Hood et al., 2015). Pine trees that have greater numbers of resin ducts and/or larger

size tend to be more successful at surviving an attack (Hood et al., 2015). Furthermore,

trees that grow faster tend to be more resistant to pest attack because they produce

more resin ducts (Hood et al., 2015).

There is a positive correlation between oleoresin production, size and area of

resin ducts with the basal area, with the best predictor of resin production being duct

size and stem basal area (Hood and Sala, 2015; Hood et al., 2015). The size and

quantity of resin ducts is greater in faster growing trees, though these trees tend to

invest less proportionally in resin ducts than in wood growth (Hood and Sala, 2015).

Growing trees in higher densities create conditions for slower growth smaller crown size

and limits the amount of potential oleoresin to be produced, which leads to a decrease

in protection against bark beetle attacks (Lorio, 1986). Therefore, thinning stands is

recommended for increasing oleoresin production and improving protection.

Resin flow and production in pine trees varies depending on genetics, site

quality, climate, tree size, disturbance, stand dominance and wounding (Hood and Sala,

2015). Since resin is costly to produce, there are trade-offs between dedicating energy

resources to growth versus defense mechanisms such as oleoresin production (Hood

and Sala, 2015; Strauss et al., 2002). Therefore, certain species invest more resources

on defense while others invest more on growth. Endara and Coley (2011) use the

resource availability hypothesis (RAH) to explain the interspecific variation in tree

defense against herbivores and pests. In their meta-analysis, they concluded that,

compared to slower growing species from resource-poor environments, faster growing

species from rich resource environments experience higher herbivory rates.

45

Furthermore, Endara and Coley (2011) found that fast growing species have higher

inducible defenses because they occur in an environment suitable for inducible factors,

and have higher cost of creating new tissue, whereas slow growing species have higher

constitutive defenses. Tree vigor is also related to the susceptibility of certain pine

species to beetle attack (Larsson et al., 1983). Additionally, tree vigor is negatively

correlated to both leaf area and basal area in a stand (Larsson et al., 1983). As a result,

stand density management practices, such as thinning is beneficial to preventing or

minimizing insect pest attacks (Larsson et al., 1983).

Variation of Oleoresin Yield and Flow Rate Among Species

Conifers naturally produce oleoresin and yield is related to numerous genetic and

environmental factors. Oleoresin yield is positively correlated to tree diameter at breast

height (DBH) and live crown in many different pine species (Hodges, 1995; Hodges,

2000; Strom et al., 2002; Rodrigues et al., 2008; Rodrigues et al., 2013; Rodríguez-

García et al., 2014). The productivity of planted conifers, with respect to DBH, crown

width, branch size, etc. increases with improvement in soil quality and adoption of

intensive management practices, for example, thinning, fertilization, site preparation,

and planting genetically-improved seedlings (Jokela, 2004; Zhang et al., 2006;

Rodríguez-García et al., 2014).

In central Spain, selection intensity for high oleoresin yielding P. pinaster was

found to be great and these high yielding trees produced close to double the quantity of

oleoresin compared to the average for that region (7.2 kg/tree/year compared to 3.65

kg/tree/year) (Tadesse et al., 2001). This shows that genetics has a strong impact on

potential oleoresin yield from a stand and trees could be bred for improved yield.

46

Furthermore, there was a positive linear correlation observed between selection

intensity and mean resin yields in high yielders in Spain (Tadesse et al., 2001).

Stand age has a positive correlation with oleoresin flow; Knebel et al. 2008

observed 1.5 to 4.5 times more resin yield in 12-year-old trees compared to 6-year-old

trees. In some cases, resin flow can be impacted by the interaction of certain trees

characteristics with environmental factors. When the interaction effect of stand age with

fertilizer is tested, Knebel et al. (2008) found that oleoresin collected from younger trees

(6-year-old) had a longer lasting positive response to fertilization compared to older

trees (12-year-old).

The flow rate of oleoresin in conifers is affected by many biological factors such

as species, genetics, size of resin ducts, length of resin canals, exudation pressure, and

viscosity of oleoresin, as well as environmental factors such as temperature and

seasons (USDA Forest Service, 1971a; Hodges, 1995). However, some studies found

that exudation pressure was not significantly correlated to resin flow, though pressure

was not measured properly (Schopmeyer et al., 1954). Flow rate is typically higher

during the late spring and summer, and when average temperatures are above 20°C

(Hodges, 1995). Pine species differ in terms of oleoresin viscosity, and the higher the

viscosity of resin, the slower the flow rate (USDA Forest Service, 1971a). The viscosity

of oleoresin in individual trees was higher right at the beginning of the growing season

and subsequently dropped rapidly (USDA Forest Service, 1971a). Also, viscosity was

found to have a strong broad-sense heritability, which shows that breeding programs to

improve oleoresin flow in slash pine have great potential (Schopmeyer et al., 1954;

USDA Forest Service, 1971a; USDA Forest Service, 1971b). The flow rate is also

47

affected by the chemical compositions of oleoresin, with higher levels of monoterpenes

reducing viscosity and crystallization rate as well as maintaining resin in a fluid state,

which in turn increases flow (Hodges, 1995). Methyl jasmonate, a chemical stimulant,

was found to increase monoterpenes in the stem when applied to Douglas fir (Huber et

al., 2005). During the first 24 hours of collection, flow rate of oleoresin will be greater in

individual trees with larger and higher quantity of resin ducts (Schopmeyer et al., 1954).

Pinus merkusii is native to Sumatra and is planted in Indonesia for timber

products as well as oleoresin production (Sukarno et al., 2015). Within species,

provenances may vary in terms of oleoresin production, which shows that there are

some genetic and environmental impacts on the yield of oleoresin. When tapping 13-

year-old Pinus merkusii Jungh. Et De Vriese trees in Indonesia, Sukarno et al. (2015)

found that the provenances in Jantho yielded 17-73% more oleoresin than the other

provenances in the country. This shows that there is potential for selecting individuals or

subpopulations to plant stands specifically for oleoresin yield and increase potential

yield (Sukarno et al., 2015). In this study, it was also found that oleoresin yield

decreased as elevation of the provenances tapped increased, however turpentine yield

increased with elevation (Sukarno et al., 2015). Individual trees within each provenance

showed high levels of variation in oleoresin yield, but repeatability estimates for all

subpopulations in Indonesia were high with values ranging from 0.57 to 0.74 (Sukarno

et al., 2015). Similar to repeatability estimates, estimates of heritability for oleoresin

were high (0.52), which shows that there is a strong genetic control on yield (Sukarno et

al., 2015).

48

Narrow-sense heritability estimates of oleoresin yield in southern U.S. pine trees

were also high, with Pinus elliottii having an estimate of 0.85, and Pinus taeda having

an estimate ranging from 0.44 to 0.59 in the summer (Franklin et al., 1970; Roberds et

al., 2003). Westbrook et al. (2013) reported a within site narrow-sense heritability

estimate of 0.12-0.30 when comparing constitutive oleoresin flow from various P. taeda

sites in north Florida. Constitutive oleoresin flow is also affected by the site x genetic

interaction; Westbrook et al. (2013) found that additive genetic correlation of yield

decreased from 0.8 to 0.37 as the differences in soil and climate increased. Roberds et

al. (2003) found that growth traits and oleoresin flow in loblolly pine had a broad-sense

heritability value of greater than 0.5, which shows a strong genetic influence on these

traits.

Within native southern U.S. pine trees the number of radial resin canals found in

slash pine is much higher than P. palustris, P. echinata, or P. taeda (Hodges et al.,

1981). In the southeastern U.S., the diameter of resin ducts in P. taeda, P. palustris,

and slash pine did not differ significantly, while the diameter of P. echinata resin canals

was significantly smaller (Hodges et al., 1981). Furthermore, the number of resin canals

per area was significantly higher in slash pine compared to P. palustris, P. echinata, and

P. taeda (Hodges et al., 1981).

Flow duration can also be affected by species of pine trees. In the southeast

U.S., slash pine and P. palustris pine tend to have longer lasting oleoresin flow,

compared to P. echinata and P. taeda (Hodges et al., 1977). Hodges et al. (1977) found

that oleoresin flow in all slash pine trees continued after 24 hours, while 95% of P.

palustris, 70% of P. echinata, and 50% of P. taeda showed flow 24 hours after

49

wounding. Thirty-two to 48 hours after wounding, 90% of slash pine yielded oleoresin,

while only 60% of P. palustris, 25% of P. echinata, and 15% of P. taeda yielded

oleoresin (Hodges et al., 1977).

Species genetics also affects the rate of flow of oleoresin. When comparing four

southern pines, Hodges et al. (1977) found that P. elliottii oleoresin flowed at a rate of

0.56 ml/h, which was significantly slower than that of P. echinata (0.78 ml/h), P. taeda

(1.12 ml/h), and P. palustris (1.55 ml/h). This flow rate can also be affected by

environmental conditions, as well as the viscosity and crystallization rate of the

individual tree, which can in turn differ by species. Furthermore, no chemical stimulant

or inducers were used in this study, and the flow rate and duration of flow can differ

when applying stimulant.

Within-species tree variation contributes to the variation in oleoresin flow in

species within a stand (Roberds and Strom, 2006). Within the major southern U.S. pine

species, variation in oleoresin yields for slash pine was lowest (Roberds and Strom,

2006). Loblolly pine stands was found to have a high repeatability for oleoresin yield

with about two-thirds of the tree variability accounting for oleoresin variability (Roberds

and Strom, 2006). Furthermore, repeatability measurements for oleoresin yield in P.

palustris stands varied from low to high (Roberds and Strom, 2006).

Oleoresin Viscosity and Crystallization Rate Among Species

Oleoresin physical characteristics in most southern pines is not greatly affected

by tree morphological characteristics; however, P. palustris has a slight negative

correlation between crystallization and tree age and height (Hodges et al., 1977).

Schopmeyer et al. (1954) also found that tree morphological characteristics cannot be

50

used to select slash pine trees that produce higher oleoresin yields. In southern pines,

there is a negative correlation between resin flow and oleoresin viscosity (Hodges et al.,

1977). Between 36 to 65 percent variation in oleoresin flow in southern pine can be

accounted for by the viscosity, with 65% of the variation in slash pine (Hodges et al.,

1981). In natural conditions, slash and P. palustris are more resistant to a southern pine

beetle attack compared to P. echinata and loblolly pine (Hodges et al., 1977). This could

be due to the fact that slash and P. palustris tend to produce oleoresin at great

quantities which flow for longer times (Hodges et al., 1977).

Oleoresin viscosity of progenies was influenced by both the mother and father,

thus progenies had a viscosity level somewhere in between both parents (Mergen et al.,

1955). When comparing the four-major southern U.S. pine species, a study found that

the viscosity of P. palustris resin was lower than the viscosity of slash pine resin

(Hodges et al., 1977). Furthermore, the viscosity of P. palustris was greater than both P.

echinata and loblolly pine (Hodges et al., 1977). Another study in Florida found that

slash pine had lower viscosity than that recorded in Hodges et al. (1977) (Schopmeyer

et al. 1954). This shows that the environmental factors also play a role in viscosity of

oleoresin. Viscosity within an individual is fairly uniform, though it may vary slightly at

different vertical positions in the tree (Stark, 1985). Crystallization rate is also affected

by genetics with slash pine having the slowest rate and loblolly and P. echinata having

the quickest rate (Hodges et al., 1977). This can affect resin production, since quicker

crystallization slows down resin flow by sealing the wound (Hodges, 1995).

51

Oleoresin Production in Planted Versus Natural Forests

Today, close to three quarters of the pine oleoresin produced is collected from

natural pine stands in Asia, while the remaining oleoresin is tapped from planted pine

stands (Cunningham, 2012). One of the major differences in areas where natural stands

are tapped compared to those where planted stands are tapped is the type of individual

in charge of the operation (Cunningham, 2012). The countries that operate in natural

stands are usually found in the northern hemisphere, primarily in Asia, and tend to have

individuals that are from rural areas and are not associated with a company that harvest

the product (Cunningham, 2012). Furthermore, European countries, such as Spain,

often work in natural stands that are managed (Cunningham, 2014). This allows the

resin tappers to get more oleoresin yield per tree and visit more trees in a tapping

season; for example, resin tappers in Spain tapped on average 5500 trees and

collected about 2.3 kg per tree compared to workers in China, who only tapped between

1500 to 2000 trees and collected 2.0 kg of oleoresin per tree (Cunningham, 2014). On

the other hand, in the southern hemisphere, as in Brazil, oleoresin collection is

controlled and managed by a company that hires laborers to harvest from planted pine

trees, usually non-native one (Cunningham, 2012). These companies either own

processing mills or sell the product directly to the pine chemical industry (Cunningham,

2012).

Operations in natural stands tend to be inefficient and use outdated tapping

methods that are not sustainable (Cunningham, 2012). Tapping resin in a planted stand

is more advantageous to the resin tappers because the trees are in proximity to one

another, therefore more trees can be visited in a day (Coppen and Hone, 1995). In a

52

planted stand, tappers usually work in stand with 1100 trees per hectare compared to

200 to 400 trees per hectare found in natural stands (Cunningham, 2014). In planted

stands, a single resin tapper is able to tap about 7000 to 1000 trees per year, while a

tapper in a natural stand can only tap between 1500 to 2000 trees per year

(Cunningham, 2014; Morris, 2015).

Inducing Oleoresin Flow and Yield

Chemical Inducers

Resin yields in a variety of conifers may also be improved with the application of

chemical stimulants such as, methyl jasmonate and an ethylene-releasing compound

(Hodges, 1995; Martin et al., 2003; Hudgins et al., 2004; Hudgins and Franceschi, 2004;

Huber et al., 2005; Rodrigues et al., 2008). The two main stimulants used around the

world are a mixture of sulfuric acid with an ethylene precursor (2-chloroethylphosphonic

acid, CEPA) and methyl jasmonate (Hodges, 1995; Hodges, 2000; Martin et al., 2003;

Hudgins et al., 2004; Hudgins and Franceschi, 2004; Huber et al., 2005; Rodrigues et

al., 2008). These two compounds occur naturally in conifers to fight against pests.

Ethylene is an unsaturated hydrocarbon synthesized from S-adenosyl-L-

methionine and catalyzed by the enzymes ACC synthase and ACC oxidase (Bleecker

and Kende, 2000). Ethylene is used to regulate metabolic and developmental processes

in plants, such as stem and petiole growth, as well as facilitating the plants response to

abiotic and biotic stress (Bleecker and Kende, 2000). When inoculated with spores of

fungi, the rate of both ethylene and monoterpenes produced by pine trees increases

(Popp et al., 1995b). This shows that ethylene plays a key role in the tree’s defense

responses to insects and fungi (Popp et al., 1995b). Methyl jasmonate is a volatile

53

compound found in both angiosperms and gymnosperms and is used as a cellular

regular in developmental processes as well as trigger defense mechanisms in response

to abiotic and biotic stresses like insect attacks (Cheong and Choi, 2003). Both ethylene

and methyl jasmonate play a vital role in fruit ripening (Bleecker and Kende, 2000;

Cheong and Choi, 2003). Methyl jasmonate and its jasmonic acid are synthesized

through the octadecanoid pathway and catalyzed through various enzymes including

allene oxide synthase and allene oxide cyclase (Cheong and Choi, 2003).

Methyl jasmonate was found to have a 2-fold effect on the monoterpene and

sesquiterpene production in the needles of Norway spruce (Martin et al., 2003). It was

found that the terpenes released after the application of methyl jasmonate in Norway

spruce wood were products of new resin canals, suggesting this organic compound

promotes the production of new resin ducts (Franceschi et al., 2002; Martin et al.,

2003). Under normal conditions P. menziesii, P. grandis, T. heterophylla, and C. libani

did not have constitutive axial resin canals, however, following treatment with methyl

jasmonate, traumatic resin canals were formed within 8 weeks (Hudgins et al., 2004).

Furthermore, the density of axial resin canals affects oleoresin flow (Nagy et al., 2000).

Another experiment with Norway spruce trees being treated with methyl jasmonate

topically found that following inoculation of the insect Ceratocystis polonica trees treated

with methyl jasmonate had a significantly greater response with oleoresin flow

compared to untreated trees (Franceschi et al., 2002). Franceschi et al. (2002) also

compared the presence of axial resin canals in 2-year-old saplings and found that the

saplings that we not treated had no resin canals, whereas, the trees treated with methyl

jasmonate had a ring of induced traumatic resin canals.

54

Methyl jasmonate application was most successful at promoting the formation of

traumatic resin ducts in P. pungens, P. menziesii, and L. occidentalis compared to

wounding and the application of Tween 20 (Hudgins et al., 2003). Compared to

wounding, methyl jasmonate induced the formation of resin canals that were double the

size of traumatic resin ducts from wounding canals in P. menziesii and one-half the size

of the canals produced by wounding in P. pungens (Hudgins et al., 2003). This shows

that using methyl jasmonate to promote and increase the flow of oleoresin for

commercial production may have varying effects depending on the species used for

tapping. The mean area of the resin canals in P. menziesii formed from methyl

jasmonate application was close to 3500 µm2, compared to about 1100 µm2 for P.

pungens resin canals and less than 500 µm2 for L. occidentalis canals (Hudgins et al.,

2003). Furthermore, higher concentrations of methyl jasmonate (at least 100 mm) was

more successful at creating more flow in Douglas fir and giant redwood trees (Hudgins

and Franceschi, 2004). In that study, methyl jasmonate and ethylene were both better at

promoting oleoresin exudation with higher phenolic area, higher resin duct area, and

greater numbers of resin ducts compared to Tween 20, methyl salicylate, and water

treatments (Hudgins and Franceschi, 2004). Methyl jasmonate was found to not have a

negative effect on growth of treated trees in both the sapling stage and older

(Franceschi et al., 2002). The application of jasmonic acid on plants was found to have

a negative effect on insect pests, with higher concentrations of jasmonic acid leading to

induced plant responses deterring pests (Thaler et al., 2001).

Hudgins and Franceschi (2004) looked at the number of resin duct and average

lumen area responses to giant redwoods and Douglas fir trees treated with varying

55

doses of methyl jasmonate with the greatest concentration being 100 mm. For both

species, the study found that as methyl jasmonate concentration increased, so did the

lumen area both where the chemical stimulant was applied as well as around it

(Hudgins and Franceschi, 2004). Furthermore, the same general trend occurred with

the number of resin canals increasing with the increase in methyl jasmonate

concentration though within the treated area 10 mm and 25 mm concentrations yield the

greatest number of resin ducts in the giant redwoods and Douglas fir, respectively

(Hudgins and Franceschi, 2004).

Applying chemical stimulants makes commercial oleoresin production more

sustainable and feasible as it reduces the overall cost of tapping (Rodrigues et al.,

2011). Paraquat has been used in other countries, like Brazil, to stimulate resin

production (Rodrigues and Fett-Neto, 2009). This compound works to increase yield in

slash pine by disturbing the cellular structure of parenchyma cells in the xylem, which

increase tree response to wounding (Rodrigues and Fett-Neto, 2009). In my research,

however, Paraquat was not found to have much of a significant positive effect on yield.

Increasing the concentrations of CEPA positively affected rein yields in slash pine

(Rodrigues et al., 2008). CEPA and NAA was also found to increase the expression of

candidate genes that promote enzyme activation, which can indirectly increase

oleoresin yield (de Lima et al., 2016). In India, Lekha (2002) also reported an increase

in oleoresin yield with increasing concentrations of both ethephon and sulfuric acid.

Similar results were observed in my study with the increase in methyl jasmonate

concentration. For a commercial operation, it is necessary to find the most ideal and

cost effective chemical concentration that still yields high oleoresin production.

56

Fahn et al. (1979) applied two hormone treatments to C. libani trees, NAA and

NAA+GA3, at different time periods. The area above the treated area for both NAA and

NAA+GA3 had larger resin canals occurring after application (Fahn et al., 1979).

Furthermore, the ideal time to apply hormone stimulant to give larger and more

abundant resin canals after one month of application was between April to August

(Fahn et al., 1979).

Other chemical stimulants used to promote the flow of oleoresin include sulfuric

acid, paraquat, salicylic acid, auxin, benzoic acid, yeast extracts, metal cofactors, and

fungal elicitors (da Silva Rodrigues-Corrêa et al., 2013). Salicylic acid is a phenolic

compound found in plants and important for defense, while paraquat is a photosynthesis

inhibiting herbicide (Silverman et al., 2005). When paraquat is applied to the wound, it

induces the formation of lightwood, which increases oleoresin production in pine trees

(Stubbs et al., 1984). Popp et al. (1995a) found that applying a bark-beetle-vectored

fungus to the wound of conifers induces the production of lesions soaked in

monoterpene. This would also increase the flow of oleoresin to the wound. In Brazil, the

application of a stimulant paste containing metal cofactors such as ferrous sulfate,

potassium sulfate, copper sulfate, and manganese sulfate yields to an equivalent or

higher yield of oleoresin compared to the traditionally used more expensive CEPA

(Rodrigues et al., 2011). The paste typically also includes sulfuric acid, which is known

to promote oleoresin flow (Rodrigues et al., 2011). Ten and 100 mM of salicylic acid and

the synthetic auxin 2,4-dichlorophenoxyacetic acid applied to a wound was found to

yield more oleoresin compared to the CEPA paste in P. elliottii (Rodrigues and Fett-

Neto, 2009). Furthermore, in that same study, yeast extract at various concentrations

57

(5, 50, and 500 mM) was found to promote statistically similar oleoresin yields

compared to CEPA paste (Rodrigues and Fett-Neto, 2009). The auxin 2,4-D was found

to induce slightly greater yields in slash pine compared to sulfuric acid (Clements,

1970).

Physical Inducers

Wounding conifers at any age can increase oleoresin flow, however a greater

increase in resin flow is observed when the trees are subjected to both wounding and

fungal inoculation (Christiansen et al., 1999; Knebel et al., 2008). P. abies trees that

were pretreated by inoculation with Ceratocystis polonica had significantly more resin

canals at breast height compared to control trees (Christiansen et al., 1999). There is a

significant increase in resin flow from trees subjected to mass artificial inoculation

compared to trees that were only wounded in P. taeda and P. resinosa (Klepzig et al.,

2005; Knebel et al., 2008; Lombardero et al., 2006). Christiansen et al. (1999) reported

that wounding and fungal inoculation together can increase the tree’s resistance,

particularly P. abies to mass insect inoculation. Previous wounding has been found to

have an initial negative effect on oleoresin flow followed by a positive effect, with the

side of the tree that has been previously wounded producing significantly less oleoresin

than the unwounded side on the first day of tapping, but producing more by day seven

after tapping (Lombardero et al., 2000).

In Cedrus species of Pinaceae, resin canals only occur after the tree has been

wounded and appear as both vertical and radial ducts in the secondary xylem (Fahn et

al., 1979; Fahn, 1988; Lin et al., 2002). Fahn et al. (1979) found a correlation between

the size and shape of the wound with the size of the resin canals; with longer and wider

58

wounds producing larger and more cyst-like resin canals. The location of the wound, in

terms of height on the tree, can also have an impact on oleoresin yield (Tisdale and

Nebeker, 1992). Tisdale and Nebeker (1992) found that wounding closer to the base

yielded significantly more oleoresin compared to closer to the lowest live branch when

wounding occurred in May and June.

There are different techniques to wound pine trees for oleoresin collection which

will be discussed below. Most countries now use a method which involves scraping the

bark and phloem and attaching a bag or collection bucket to retrieve the oleoresin.

Furthermore, there are several different wound shapes that are used to promote the

flow of oleoresin such as v-shaped, horizontal, or round shaped wounds (da Silva

Rodrigues-Corrêa et al., 2013). Drilling further into the tree is another possible method

for collecting oleoresin. Wounds can be made both manually using various tools as well

as automatically using robots or tractor mounted devices (Hodges, 2000). Hodges

(2000) developed a mechanized system that operated 3 drills which can also intersect

within the tree requiring a single collection spout and bag. Hodges (2000) also

automated the application of chemical stimulants. This system can rotate and align with

boreholes to spray approximately 1.5 ml of chemical inducers into the borehole using a

cone-shaped pattern (Hodges, 2000). This entire system is mounted and operated

through a tractor, and takes about 25 seconds to drill and apply stimulant (Hodges,

2000). Lastly, this system would cost about $0.80 per tree to operate including labor

and equipment (Hodges, 2000).

The size of the wound can also significantly affect the yield of oleoresin, with

larger wounds from scraping the bark and drilling into the tree yielding more oleoresin

59

(Hodges, 1995; Hadiyane et al., 2015). However, the higher yields from larger

boreholes are not proportional to the per unit area of the hole; Hodges (1995) found that

3.49 cm boreholes yielded about 28.1 grams per area compared to 2.54 cm boreholes

yielding 31.9 grams per area. This same trend was also observed with hole depth,

where shallower holes yielded more oleoresin per unit area compared to deeper holes

(Hodges, 1995).

Using the borehole tapping method, Lekha (2002) found that freshening the

boreholes monthly during the tapping season by either increasing the size of the wound

or re-spraying with a chemical stimulant had a positive impact on yield. Boreholes that

were initially tapped at 1.905 cm and 2.54 cm and then re-drilled multiple times to get a

3.175-cm diameter hole yielded significantly more oleoresin (2961 and 2951 g/hole/tree,

respectively) compared to borehole initially tapped at 3.175 cm with no freshening (2905

g/hole/tree). (Lekha, 2002).

Morphological Effects

While a larger crown size allows the tree to grow faster and produce more

carbohydrates, the excess resources available is allocated to growth and storage, rather

than secondary metabolism, such as oleoresin production (Lombardero et al., 2000).

Suppressed trees, though, were found to have significantly lower oleoresin flow

compared to dominant canopy trees (Novick et al., 2012). Gansel (1965) did not find

any significant differences in crown and stem characteristics between high and low

oleoresin yielding trees. In a study in central Spain, Tadesse et al. (2001) found that

compared to control trees, high yielding candidate trees had significant larger diameter,

crown height, crown diameter, and oleoresin yield per tree. On the other hand, control

60

trees were significantly taller and planted at a much greater density although with lower

oleoresin yields (Tadesse et al., 2001). Hadiyane et al. (2015) also observed a positive

correlation with oleoresin yield and tree diameter. However, Lekha (2002) found no

correlation between yield and tree diameter, but reported a significant positive

correlation between needle length and tree height with oleoresin yield. Needle thickness

was also reported to be positively correlated to oleoresin yield (Lekha, 2002; Bhat,

2015).

Exudation Pressure

Oleoresin exudation pressure (OEP) has been found to have some effect on

resin flow rate in certain cases, and in others, has not been found to be significant

(Schopmeyer et al., 1954; Hodges, 1995; Mason, 1971; Rodríguez-García et al., 2014).

Rissanen et al. (2016) measured OEP rates in an even-aged 50-year-old Scots pine

stand in southern Finland. OEP varies considerably diurnally, with highest pressure

rates occurring from 1 to 3 p.m. and lowest rates occurring between 3 and 6 a.m.

(Rissanen et al., 2016). In general, as ambient temperature and precipitation increases,

the OEP also increases exponentially, which allows the tree to exude more resin

(Harris, 1960; Rissanen et al., 2016).

There is a slight negative correlation with xylem diameter and OEP as well as a

slight positive correlation between OEP and monoterpene emissions (Rissanen et al.,

2016). The results obtained in this study conflict other experiments with OEP, which

found that OEP is negatively correlated with temperature and is lowest in the afternoon

and highest just before sunrise (Schopmeyer et al., 1954; Vité, 1961; Lorio and Hodges,

1968; Helseth and Brown, 1970; Rissanen et al., 2016). These results may be

61

contrasting because all the other studies were conducted in warmer climates with

significantly higher average temperatures while Rissanen et al. (2016) conducted their

experiment in Finland which has much lower high temperatures. Moreover, OEP was

positively correlated to relative humidity, and negatively correlated to water stress

(Helseth and Brown, 1970).

Environmental Inducers

Climate and seasons

Resin flow and production differs seasonally depending on climate (Hood and

Sala, 2015). Resin flow increases during drought periods when tree growth is limited

due to water stress (Hood and Sala, 2015). This outcome can be explained by the

growth-differentiation balance (GDB) hypothesis (Herms and Mattson, 1992). The GDB

hypothesis predicts that environmental resource limitations, whether water stress from

droughts or poor nutrient availability, results in carbohydrate accumulation and increase

secondary metabolism, which will then increase plant defenses against herbivory

without compensating growth (Herms and Mattson, 1992). Moreover, in thinned sites,

where competition for resources is not as prevalent, higher resin flow was observed

since there were enough resources to allocate for growth and plant defenses (Hood and

Sala, 2015).

Oleoresin production is maximized when conifers are tapped during the summer

months because of the higher temperatures and higher pest activity, which would

require more production for protection (Lorio, 1986; Gaylord et al., 2007; Davis et al.,

2011). Pine stands are more susceptible to attack by pests during warmer summer

months. European trees, compared to American pine trees are less susceptible to pest

62

attack because European trees experience cooler summers (Harris, 1960). While trees

are more susceptible to insect attacks during the summer, it is still beneficial to tap trees

during that time because of increases in oleoresin flow. The flow rate may be higher

during the summer months because the tree must naturally produce higher levels of

oleoresin to defend against a seasonal increased in pest abundance.

Depending on the climate, the resin tapping season can range between eight

months out of the year to all year round (Coppen and Hone, 1995). In temperate

climates, when using the more common bark streaking method, tapping usually occurs

eight to nine months out of the year, however in tropical countries, tapping may occur all

year round (Coppen and Hone, 1995). If using the borehole tapping method, tapping

usually occurs at the beginning of the growing season and the bags are collected at the

start of winter.

High levels of prolonged rainfall are not beneficial to the flow of oleoresin

(Coppen and Hone, 1995). Oleoresin flow rate is ideal when the average outside

temperatures are above 20°C (Hodges, 1995). Oleoresin canal density is positively

correlated to outside temperatures while it is negatively correlated to precipitation rates

(Rigling et al., 2003). Initial oleoresin flow during early summer is significantly higher

than that of late summer (Lombardero et al., 2000). Temperature has been found to

affect the viscosity of oleoresin (Stark, 1965).

Elevated atmospheric carbon dioxide levels induce an increase in temperatures

(Novick et al., 2012). This elevated CO2 levels have a significant positive impact on

oleoresin flow in canopy dominant P. taeda in nutrient poor soils but has no significant

effect on resin flow of suppressed P. taeda trees or those dominant trees in nutrient rich

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sites (Novick et al., 2012). Elevated CO2 levels can also lead to higher rates of

photosynthesis, though that may not necessarily lead to increase productivity (McNulty

et al., 2013).

Axial resin canals in the xylem typically form during late spring around the first

week of June to early summer around the first week of July, which is about 12 weeks

after cambial reactivation (Blanche et al., 1992). Cells in the early wood and late wood

had a positive correlation to tree growth, with faster growing trees having more cells

(Blanche et al., 1992). The timing of vertical resin duct formation could be to a certain

extent due to the season or year with the longest photoperiod (Blanche et al., 1992).

Resin flow in loblolly pine was positively correlated to axial resin canal density, but not

radial resin canal density (Blanche et al., 1992; Hodges et al., 1981).

While the induction of new resin canal formation is caused by wounding, the size

and timing of formation of these ducts are heavily influenced by the month of wounding

(Fahn et al., 1979). Larger ducts are typically a result from wounding end of April

(largest ducts) and between May and August (Fahn et al., 1979). These resin canals

usually appear one month after wounding (Fahn et al., 1979). In trees sampled one to

two months after wounding between December and March, only some resin canals

were visible, and they were mostly small, whereas tree wounded between September

and November had most samples with small resin canals present after one to two

months (Fahn et al., 1979).

Climate change is also predicted to cause land cover changes. Within the next

50-60 years, southeastern U.S. land cover is projected to change from primarily

longleaf-slash pine forests in North Florida to oak-gum-cypress forests (USGCRP,

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2009). If these projections become a reality, pine forests in the southeast would be

reduced and a decrease in pines would lead to a decrease in availability of oleoresin

flow from a stand. This also highlights the importance of increasing the value and

overall productivity of the forest. If the forest is more productive, less acreage is needed,

and if the forest becomes more economically valuable, there is an incentive for

protection, investment, and research. Climate change can have numerous negative

impacts on forests, but there is still the potential of mitigating those future negative

projections.

Water availability

Water availability in a stand is important for proper tree physiological function and

growth. The lack of water can be quite problematic for trees as it creates ideal

conditions for a successful insect outbreak (Stark, 1965). Plant growth is more limited

by water deficiencies than it is by photosynthesis (Lombardero et al., 2000). When tree

growth is limited by the lack of a resource, such as water or light, carbohydrates that are

available and cannot be used for growth due to resource limitations are used to invest in

secondary metabolism, such as oleoresin flow (Lombardero et al., 2000). Slight water

stress can limit pine tree growth more than photosynthesis, and causes more carbon to

be allocated to secondary metabolism (Reeve et al., 1995). Additionally, more severe

water stress limits assimilation of carbon, which causes less to be allocated to

secondary metabolism, thus making it easier for insect pests to successfully attack a

tree (Reeve et al., 1995). In the southeast U.S., pine stands are typically planted in

raised planting beds because the soil is typically poorly drained (Wilhite and Jones,

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1981). Trees planted in beds tend to grow better initially compared to trees planted

without beds because of the better drainage they receive (Wilhite and Jones, 1981).

Since tree growth is limited more by water deficiencies compared to

photosynthesis, when water is deficient, more carbohydrates remain due to lack of

growth, and thus the availability of carbohydrates for secondary metabolism is higher

(Lombardero et al., 2000). Lombardero et al. (2000) and Westbrook et al. (2013) found

that constitutive resin flow was increased with water deficiencies. Similarly, Gaylord et

al. (2007) found that oleoresin flow was highest in early summer when trees are

exposed to more water stress. However, over time, as a result of long term water deficit

and increased tree stress from extreme drought, oleoresin flow decreased (Lorio and

Hodges, 1968; Lombardero et al., 2000). This shows that though water shortages can

push the tree to allocate more resources to resin production, it is only beneficial in the

short term and water availability is still crucial to proper tree function and growth.

Furthermore, if oleoresin flow is key to determining susceptibility of pine trees to insect

pest attack, trees planted on flat sites during a period of drought would be more

susceptible than those planted on mounds (Lorio and Hodges, 1968).

Understanding the impacts of water stress of insect attacks and oleoresin

production of conifer forests is important to predicting effects of climate change on

oleoresin flow. Predictive models indicate an increase in the severity, duration and

frequencies of droughts is likely to occur in certain areas as a result of climate change

and the associated increase in surface heating (Seager et al., 2007; Allen et al., 2009;

Seager et al., 2009; Trenberth et al., 2013). Furthermore, the Intergovernmental Panel

on Climate Change (IPCC) predicts a decrease in rainfall in subtropical climates during

66

the 21st century (Seager et al., 2007). While not much information is available it is highly

likely that droughts will occur in new areas, and that natural droughts will set in quicker

and be more intense (Trenbeth et al., 2013). If these droughts occur as predicted, the

viability of an oleoresin industry decreases as severe stress will lead to a reduction of

resin production, and beetle infestations will become more severe.

Increases in tree mortality as a result of drought and severe heat linked to

climate change has been observed in Africa, Asia, Australasia, Europe and the

Americas (Allen et al., 2009). In North America, most cases of mortality have occurred

in the west coast, with millions of acres of Pinus and Populus species dying in Alaska,

British Columbia, and Alberta (Allen et al., 2009). However, mortality among Quercus

and Acer species has occurred in Quebec and the eastern U.S. from Missouri to South

Carolina as a result of drought and warmer spring temperatures (Allen et al., 2009).

Moreover, the southeast U.S. is exceptionally vulnerable to extreme heat and a

decrease in water availability (USGCRP, 2014). While the Pinus species in the

southeastern U.S. have not yet been directly negatively affected by climate change,

current predictions are not favorable and any increase in mortality from climate related

factors would prevent the success of oleoresin tapping in the southeast U.S. Short term

water stress may be beneficial to oleoresin production in Pinus species, but severe

drought like those predicted will not only reduce inducible and constitutive resin flow, but

it will also increase pest infestations and tree mortality. Increase in atmospheric

temperatures may also play a role in forest die-off, though the extent of that role and

predictions in mortality is not yet fully understood (Allen et al., 2009).

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When comparing P. sylvestris trees that were grown under natural conditions

with trees grown under irrigated conditions, Rigling et al. (2003) found that the resin

canal density of the control pines was significantly higher. However, once irrigation

ceased, the resin canals densities of the trees grown under formerly irrigated conditions

increased significantly (Rigling et al., 2003). This shows that water stress can cause an

immediate positive impact on resin duct density, and therefore oleoresin flow.

Soil moisture was found to influence oleoresin flow in P. taeda (Mason, 1971).

Thirty-four percent of the variation in oleoresin flow was caused by fluctuations in soil

moisture levels (Mason, 1971). If heavy rains occur after a period of drought, soil

moisture levels would increase, which would lead to a substantial increase in oleoresin

flow in pines (Mason, 1971). In a study on loblolly pine, recharge of a half inch of

available water led to a 40% increase in oleoresin yield (Mason, 1971).

Stand density management

Stand density can also effect the yield of oleoresin (Mason, 1971). Stand

productivity is heavily influenced by size-density relationships, thus thinning a stand is

beneficial (Jokela, 2004). Reineke (1933) first discussed the negative correlation

between the maximum number of trees in a stand and the quadratic DBH. Keeping the

stand within the stand density index for that species is crucial to maintain maximum

productivity (Reineke, 1933). When abiotic resources, such as light, water and nutrients,

become limiting in a stand, density limitations as a result of tree-to-tree competition

become apparent. As a result, monospecific stands typically follow the self-thinning

model proposed by Yoda et al. (1963) which describes the linear relationship between

density and plant size using with a -3/2 slope. If the tree measurements go above the -

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3/2 slope, the stand will go through self-thinning, and mortality would occur (Yoda et al.,

1963).

Thinning a stand ahead can positively impact crown width, branch diameter,

increase photosynthesis rates, water and nitrogen uptake, and stimulates tree growth,

as well as gain revenue from the stand prior to harvest (Mason, 1971; Wallin et al.,

2004; Zhang et al., 2006). Furthermore, when the stand is thinned, undesirable,

suppressed and intermediate trees are usually removed; and these trees usually have a

lower oleoresin exudation flow rate (Mason, 1971). Thinning may also help fight against

insect colonization by increasing pheromone distribution (Larsson et al., 1983; Olsen et

al., 1996; Wallin, 2004).

Mason (1971) found that the oleoresin yields in the stand that was not thinned

was significantly lower compared to the thinned stands, even the stands that

experienced drought. This shows that the negative effects of higher stand density are

more detrimental to oleoresin productivity than the effects of low water availability.

Thinned stands produced as much as 40% more oleoresin compared to unthinned

stands (Mason, 1971).

Fertilization

Knebel et al. (2008) measured oleoresin flow in fertilized and unfertilized trees

before and after wounding and fungal inoculation in P. taeda located in North Carolina.

Prior to wounding 6-year-old loblolly pine trees, trees that were fertilized had about two

to four times more oleoresin than those trees that were unfertilized (Knebel et al., 2008).

This shows the strong positive effect fertilization can have on oleoresin yield. However,

these results were not observed in older stands as the 12-year-old trees that were

69

tapped did not have a significant fertilizer effect on oleoresin yield (Knebel et al., 2008).

Furthermore, both six and 12-year-old stand did not have the same fertilizer effect in

consecutive year (Knebel et al., 2008). These results are contrary to those obtained in

other studies where fertilization did not have any significant effects on resin yield

(Lombardero et al., 2000; Klepzig et al., 2005). Other studies have found that fertilizer

application did not have any impact on the yield of oleoresin, even in nutrient poor sites

(Wei et al., 2014). The effect on oleoresin yield to fertilization may be impacted by the

initial site nutrient deficiencies; if the site already lacks necessary nutrients which

negatively impacts the growth of the trees, fertilization may prove to have a positive

impact, however, if the site does not lack proper resources, fertilization may be

unnecessary. Furthermore, stand age may have a significant effect on whether

oleoresin yields in trees responds to fertilizer application. More mature stands do not

grow as much and thus do not need as much fertilization as younger trees. This was

observed in the Knebel et al. (2008) study, where younger stands had a positive

significant effect on oleoresin yield to fertilization, whereas older stands did not. Under

potential future elevated atmospheric CO2 levels, fertilization may have a negative or no

impact on oleoresin flow (Novick et al., 2012).

If the results obtained in the studies by Lombardero et al. and Klepzig et al.,

where constitutive resin flow is negatively impacted by fertilization occurs, intensive pine

management, like what happens in the southeastern U.S., will lead to more trees

becoming more susceptible to insect pest, such as bark beetles (Lombardero et al.,

2000; Klepzig et al., 2005; Knebel et al., 2008). However, in Knebel et al. (2008)

constitutive resin flow was positively impacted by fertilization, which would increase the

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potential of trees to survive insect attacks. The lack of available nutrients for individual

trees caused by overcrowding in a stand can have a negative impact on oleoresin yield

(Lorio, 1986). Therefore, fertilization could counter high density planting by adding more

nutrients necessary for better tree growth, which would give the tree more resources to

invest in oleoresin production.

Besides nutrient levels, other soil properties, such as acidity, may influence the

oleoresin yield from pine trees. Wei et al. (2014) compared the effect of lime application

on oleoresin yields in P. elliottii and P. massoniana stands with acidic soils in southern

China. In both species, a significant effect of lime application on the yield of oleoresin

was observed (Wei et al., 2014). The effect lime dosage for both species was different,

with P. elliottii responding better to higher dosages compared to P. massoniana (Wei et

al., 2014). P. elliottii and P. massoniana are both adapted to growing in acidic soils (Wei

et al., 2014), so this significant positive effect may be greater for pine species not

adapted to acidic soils.

Fire

Oleoresin flow in Ponderosa pine (Pinus ponderosa) as well as Corsican pine

(Pinus nigra subspecies laricio (Poir.) Maire var. corsicana) increased and viscosity

decreased after a prescribed burn (Wallin et al., 2003; Cannac et al., 2009; Davis et al.,

2011). This is most likely caused by the additional stress of fire triggering the formation

of new traumatic resin canal formation and the preparation against insect pest attack.

Wallin et al. (2003) found that in ponderosa pine, both constitutive and induced resin

flow improved in lightly scorched and moderately scorched trees. However, this study

did not compare oleoresin yield to trees that were not burned. While oleoresin volume

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after burning and thinning a ponderosa pine stand was initially greater than the

untreated control pine stands, in August, several months after the prescribed burn,

oleoresin yield in the control stand was greater than the thinned and burned stand

(Wallin et al., 2004). Heavy and severe crown scorch negatively affected oleoresin yield

in ponderosa pine (Wallin et al., 2003). In stands that are treated with prescribed fire,

tree diameter, basal area, and percent live crown affected oleoresin yield (Davis et al.,

2011). As the diameter and percent live crown in a tree increases, the quantity of

oleoresin flow increases as well, however, as basal area increases in a stand, oleoresin

flow decreases (Davis et al., 2011).

The study on Corsican pine found that yield increased in trees that were burned

multiple times up to 14 months after initial burn (Cannac et al., 2009). Lombardero et al.

(2006) observed a short term decrease in resin flow with a long-term increase in flow of

P. resinosa trees that were burned compared to unburned adjacent trees. Hood et al.

(2015) found that low-severity fire acts as an inducer of resin duct production and that

ponderosa pine trees exposed to fire had an increase in resin ducts and these defenses

decrease with the cessation of fire. Within burned trees, the burn side of an individual

tree can yield significantly higher amounts of oleoresin than the unburned side

(Lombardero et al., 2006). This result lasted up to 55 days after treatment and the

burned trees on both burned and unburned tapped sites had twice as much oleoresin

yield compared to unburned trees, however, initially there was a reduction in oleoresin

flow immediately following burning (Lombardero et al., 2006). Santoro et al. (2000) also

found that following a fire in Spring 1998, oleoresin flow in trees damaged by the fire

72

increased significantly and linearly with height of charring compared to those trees that

were not damaged.

Fire, however, increases the attractiveness of the pine trees to insect pests by

releasing some volatile compounds, which can have a severe negative impact to the

burned tree (Santoro et al., 2000; Lombardero et al., 2006). This increased in

attractiveness can be caused by the immediate decline in oleoresin flow after a burn,

which allows more pests to successfully attack, especially from wildfires (Lombardero et

al., 2006). Santoro et al. 2000 found an increased in abundance of Ips pini in the burned

site one month after the fire occurred, however, Ips grandicollis and Ips perroti

abundance were not significantly different in burned and unburned sites. During mid-

summer, a few months after being burned, I. pini abundance was significantly less in the

unburned site and by September the pest abundance in the burned and unburned site

did not differ (Santoro et al., 2000). The results from Lombardero et al. were contrary to

those from a P. larico study that found that fire did not provoke or increase insect pest

attack on burned stands (Cannac et al., 2009).

Tree physiological characteristics following a fire event are also important in

determining oleoresin yield and can affect viscosity (Davis et al., 2011). After being

scorched, trees with more percent live crown were found to produce more oleoresin with

a higher viscosity (Davis et al., 2011). This is most likely due to the fact that trees with

large amounts of scorched foliage have lower rates of photosynthesis, which in turn

means less resources to use as a defense mechanism against pests (Wallin et al.,

2003). Furthermore, trees that are more heavily damaged by a fire become more

susceptible to an insect pest attack and colonization (Wallin et al., 2003). Pine species

73

that have evolved with and are adapted to fire, such as P. palustris and P. resinosa (red

pine), yield more oleoresin when subjected to fire (Harper, 1944; Santoro et al., 2000;

Davis et al., 2011).

Oleoresin tapping techniques

Pine trees around the world are being tapped using several techniques to collect

oleoresin for various commercial products, such as medicinal products, adhesives, and

biofuels. It is possible to successfully tap a pine tree for over 20 years without posing

much risk to the health of the tree and stand (Coppen, 1995). The pine chemical

industry supplies crude tall oil and crude sulfate turpentine by extracting form pulpwood

in the pulp mills, wood rosin pinenes by extracting from stumps processed in rosin mills,

and raw oleoresin collected from tapping live trees (American Chemistry Council, 2011).

The raw oleoresin collected from pine trees in the forest is processed and converted

into gum rosin and gum turpentine (Cunningham, 2012).

Physical wounding of slash pine automatically triggers defense mechanisms

causing the increase in the production of oleoresin in both normal and traumatic resin

canals in order to protect the tree from any form of attack. Cunningham (2012)

describes four major techniques used for tapping pine trees around the world: the

“Chinese method”, the “American method”, the “French or Hugues method” and the

“Mazek or Rill method”. All of these methods involve scraping the bark and phloem and

attaching a bag or container to have the oleoresin flow into. These extraction methods

are all open-based and therefore allow for contaminants to enter the collection vessel.

In addition to this, there is the borehole tapping method that is not as common,

but is being used in certain places, like the U.S., and has a lot of promise to tap trees in

74

a sustainable manner in conjunction with timber harvest (Hodges, 1995; Lekha, 2002).

The borehole tapping method involves drilling boreholes into the tree to reach the resin

canals in the xylem of the tree and attaching a PVC pipe spout with a collection bag

attached to retrieve the oleoresin over a several months period (Hodges, 1995).

Boreholes may be places in a variety of way around the base of the tree, but the most

time efficient method is having two boreholes parallel to one another (Figure 2-2). One

of the advantages to the borehole tapping method is that the oleoresin is collected in a

closed container and thus the final raw product is purer and not filled with contaminants,

such as bark. The borehole tapping method was used to tap P. roxburghii trees in India

(Lekha, 2002). It is also possible to repeatedly tap trees for resin using the borehole

method to obtain two to three collection seasons in one stand (Hodges, 2000). The

technique patented by Barranx et al. (2002) also allows for oleoresin to be collected in a

purer state without many contaminants by using a closed collection bag. Another

advantage of the borehole tapping method is that it reduces the viscosity of the

oleoresin and captures the volatile terpenes thanks to the closed collection container

(Lekha, 2002).

The Chinese method, mostly used in China, involves cutting a v-shaped wound

that reaches and exposes the secondary xylem around 1.2 meters from the ground and

a bag is attached to collect the resin flowing down (Cunningham, 2012). Workers then

re-visit the tree every day to make another similar shaped wound right below that initial

wound until the base of the tree is met (Cunningham, 2012). In China, the tapping

season is usually only six months long compared to the eight-month season in Spain

and Argentina and 10-month season in Brazil (Cunningham, 2014). The American

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method, which is used in Brazil, Argentina, Portugal, and Spain involves making a

horizontal wound the length of one-third the circumference of the tree and removing the

phloem (Cunningham, 2012). Unlike the Chinese method, with the American method

the initial wound is made at the base of the tree, about 20 cm above the ground, and

each subsequent wound is made above that wound (Cunningham, 2012). Wound shape

and type can affect resin yield. However, in Brazil, Rodrigues et al. found no significant

difference in yield when streaking the bark in a V-shape compared to a horizontal line,

though the line wound was more time effective (Rodrigues et al., 2008). The American

method is also less labor intensive because the tree is re-visited every 15 to 18 days,

compared to every single day using the Chinese method (Cunningham, 2012;

Rodrigues et al., 2008; Rodrigues et al., 2011). Unlike the Chinese method, the

American method involves the application of a stimulant paste or chemical, usually an

ethylene precursor or salicylic acid, to increase resin yields (Cunningham, 2012). When

trees are tapped using these methods all sides of the tree can be wounded in order to

tap consecutively, for up to two decades (Coppen, 1995). In addition to the Hugues

method, a study in Indonesia also tapped P. merkusii using the borehole method by

drilling a 16-mm hole 2 cm into the tree at 20 cm from the ground, and found that the

drill method was more successful at yielding oleoresin per wound per tree (Hadiyane,

2015). Contrary to all these methods, when using the borehole method, resin tappers

only need to visit the tree twice during the season; once to tap the tree and another to

collect the bags at the end of the season (Hodges, 1995).

The borehole tapping method allows landowners to collect oleoresin from pine

trees while not damaging the quality of the wood for timber harvest because the tree is

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taping solely at the base of the tree. Barranx et al. (2002) patented a method for

harvesting oleoresin while also not diminishing the quality of the wood. This method

also reduces the amount of volatile products that would normally be lost from

evaporation, and does not use metal containers that are unfavorable for tree harvest

and often used in other techniques (Barranx et al., 2002). Resin tapping has not been

found to have a negative impact on overall tree growth, health quality and value at time

of harvest for timber and pulpwood (Coppen, 1995). While there is a slight decrease in

the growth during time of tapping, the amount of revenue made from collecting oleoresin

during that period would make up for the loss, and may be even more profitable

(Coppen, 1995).

Streaking the bark can yield higher quantity of oleoresin during a season

compared to the borehole method, although it is not as cost effective and is more labor

intensive, thus not viable for a U.S. commercial production (Hodges, 1995; Rodrigues et

al., 2008; Rodrigues et al., 2011). Within the borehole method there are many different

prospective drilling designs. There is the potential for deeper or shallower holes, wider

or narrower holes, or drilling at different angles. These different designs allow for the

access of multiple resin canal networks. While borehole depth and width was positively

correlated the average resin yield and the yield based on unit hole area were higher for

normal width and shallower boreholes (Hodges, 1995).

To be economically viable, oleoresin yields per tree should be around 2 kg or

higher (Coppen, 1995). The various collection techniques and pine species used for

tapping around the world yield varying amounts of oleoresin annually (Table 2-1).

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Application

Genetic Control and Breeding for Increased Terpene Production

Unlike agricultural crops, many trees, like conifers, take around 20-25 years to

reach rotation age. Because of this, tree breeders rely on progeny tests to make

inferences based on comparative performances of individual families at a younger age

(Squillace and Gansel, 1974). When selecting top performing progenies, it is crucial to

select an age in which growth and yield is strongly correlated to that at the end of the

rotation age. Squillace and Gansel (1974) found that progeny test results of slash pines

at age 10 could be used to predict yields at age 25, which would allow breeders to

increase genetic gains within a shorter period of time. There is always the possibility

that younger progeny tests are able to accurately predict wood production and oleoresin

yield at the rotation age.

Maximizing capacity of oleoresin yields may be possible through tree breeding

programs, since traits that affect resin flow rate, as well as overall oleoresin yields have

been found to be heritable (Schopmeyer et al., 1954; Mergen et al., 1955; USDA Forest

Service, 1971a; USDA Forest Service, 1971b; Tadesse et al., 2001; Westbrook et al.,

2013). Progeny tests using open-pollinated sources had greater within family variation

in oleoresin yields compared to control-pollinated ones (Mergen et al., 1955). Narrow

sense heritability of oleoresin yield in southern U.S. pines ranges from 45 to 90 % and

broad sense heritability varies from 67 to 90% (Mergen et al., 1955; Squillace and

Doman, 1959; Squillace and Bengtson, 1961; Squillace, 1965). These estimates of

heritability were much higher for gum yield compared to DBH, stem volume, height,

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crown width and bark thickness, which had weak to moderately strong estimates

(Squillace and Bengtson, 1961).

Schopmeyer et al. (1954) found that when crossing a tree that has a high factor

of significantly correlated with resin flow, such as lower viscosity, with a tree with

another correlating factor, like high numbers of resin ducts, it is possible to produce a

progeny with a potential to yield more oleoresin than either parent. Mergen et al. (1955)

also found that oleoresin viscosity was controlled heavily by genetics. Oleoresin yield

and tree growth seem to be controlled by pleiotropic gene with a positive correlation;

therefore, selecting for better growing trees can simultaneously yield to trees that

produce more resin (Squillace, 1965). All in all, the best way to increase oleoresin

production in a stand through breeding is to select the high yielding trees (Tadesse,

2001).

A high gum yielding slash pine progeny test was established in June 1946 on the

Olustee Experimental Forest in Baker County, Florida (McReynolds and Gansel, 1985).

This study also found that increase gum content within slash pine trees is heritable, with

high gum trees producing about 10% more wood volume and 30% more oleoresin

yields (McReynolds and Gansel, 1985). While this study focused on the improvement of

trees for resin production, it is possible to breed trees for better growth, straighter

stems, smaller branches in addition to higher gum yields (Squillace, 1965). Genetic

engineering and genomic selection allows for the enhancement of oleoresin production

in conifers while also predicting genetic variation in performance in different

environments (Westbrook et al., 2013). Through breeding and selection, oleoresin flow

in southern pines was increased 1.4-fold and number of resin canals in trees was

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increased by 1.1-fold (Morris, 2015). Furthermore, based on their research, Westbrook

et al. 2013 predict it would be possible to increase oleoresin flow 1.5 to 2.4-fold through

clonal breeding. Overall, achieving genetic gains with southern pines, especially slash

pine, could be beneficial for both timber and oleoresin production. Bhat (2015) analyzed

various genetic markers in P. roxburghii and found no association between them and

oleoresin yield. However, since many traits strongly associated with oleoresin yield have

high heritability and genetic gain, early selection can improve overall oleoresin

production in a stand (Bhat, 2015).

The calculation of heritability shows the amount of total variance caused by a

difference in breeding values (Klug et al., 2011). There are two main types of heritability;

broad sense heritability, which is the phenotypic variation due to genetic causes and is

used to compare clones, and narrow sense heritability, which is used to compare the

similarities among relatives by showing how much phenotypes are determined by

parental genes (Gezan, 2016).

Breeding hybrid species for increased resin production compared to parent

species is also feasible (Coppen and Hone, 1995). One such hybrid is P. elliottii x P.

caribaea, tested in South Africa and currently being used in for commercial resin

production in Brazil (Coppen and Hone, 1995). When considering breeding hybrid or

non-hybrid pines for increased terpene and resin production it is important to consider

the quality and quantity of the species, which is affected by genetic factors. P. elliottii

naturally has good quality resin and produces a good quantity, while P. pinaster

produces good quality resin at a poor quantity (Coppen and Hone, 1995). P.

massoniana, which is used in China for resin production produces poor quantity and

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quality resin (Coppen and Hone, 1995). P. caribaea produces poor quality resin at very

good quantities, while the converse is true for P. radiata (Coppen and Hone, 1995).

Given this information it would be possible to use tree breeding to create a hybrid

species with P. caribaea and P. elliottii or P. radiata that produces better quantities of

resin at higher quality.

When breeding pine trees for terpenes, or any phenotypic trait, repeatability

studies are important, as they provide crucial data and insight on the variation between

and within individual trees (Roberds and Strom, 2006). Furthermore, in cases where

genetic information is unavailable or it is difficult to calculate heritability, repeatability

studies can be used to determine the levels of variation (Roberds and Strom, 2006).

Global Uses for Oleoresin

Pine terpenes for commercial products

Presently, turpentine is collected around the world as a source of chemical

isolates to be used or various commercial products, such as, cleaning agents, medicine,

paints, and pine oil used for fragrance and flavor (Coppen, 1995). The raw oleoresin is

cleaned and then steam distilled at a factory to make turpentine and rosin (Coppen,

1995). The main derivative compounds extracted from oleoresin for commercial

purposes include anethole, isobornyl acetate, camphor, citral, citrinellal, linalool, and

menthol (Coppen, 1995).

Within the international market, the standard used by the chemical industry that

converts derivative compounds to pine oil and fragrances considers turpentine with a

total pinene content of 90% to be “good”, while a beta-pinene content of 30-40% is

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“excellent” (Coppen, 1995). If the collected turpentine consists of less than 70% of

pinenes, it would not succeed in the international market (Coppen, 1995).

Rosin is the main product obtained after distilling pine oleoresin (Coppen and

Hone, 1995). The quality of the rosin varies and depends primarily on color, with the

lightest yellow shades being the best (Coppen and Hone, 1995). Unlike turpentine, rosin

cannot be used in its raw state and is chemically modified in order to make inks,

adhesive, detergents, etc. (Coppen and Hone, 1995). Turpentine can be used in its raw

form to make paint solvent or act as a cleaning agent, and can be processed chemically

to make a variety of derivatives (Coppen and Hone, 1995).

Pine terpenes for biofuels

One of the goals of collecting oleoresin from pine trees is to provide a potential

alternative to petroleum at a competitive price (Barranx et al., 2002). The pure and

mixed pine monoterpenes can be dimerized efficiently to make a good replacement for

petroleum derived jet fuel (Meylemans et al., 2012, Meylemans et al., 2013). Biofuels

are energy sources originated from renewable biomass sources, such as agricultural

crops or trees, which can be used for fuel and electricity (Jessup, 2011). Currently, the

most widely used form of biofuel globally is ethanol, derived primarily from sugar cane

(Goldemberg, 2007, Somerville et al., 2010). Ethanol actively competes with the

petroleum industry, with Brazil producing about 16 billion liters every year (Goldemberg,

2007). In Brazil, there is the potential of sugarcane biomass producing the energy

equivalent of 14% of the fuel used for transportation (Somerville et al., 2010). Brazil has

about 2.9 million hectares of planted sugarcane that is used solely for ethanol

production (Goldemberg, 2008). However, if demand for ethanol as a biofuel increases,

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more agricultural land in Brazil, such as pastureland, could get converted into

sugarcane plantations, which could in turn increase the pressure of the cattle industry

on the Amazon (Goldemberg, 2008).

Biofuels can provide the same benefits as fossil fuels without the negative

impacts of high net greenhouse gas emissions, and they are also renewable,

sustainable resources that promote energy security (Smith et al., 2013). With biofuels,

the amount of energy mined and extracted below ground is limited and replaced with

energy obtained from above-ground sources (Borak et al., 2013). One of the big

controversies with biofuels is that land that could be used to grow food is getting

diverted to grow fuel; also, there is the fear that as oil prices increase, so will the price of

grain, because it would become more profitable for farmers to grow biomass for fuel

(Kovarik, 2013).

In areas like the southern U.S., where biofuel crops, including P. palustris, P.

taeda, and P. elliottii var. elliottii, that are high in gum turpentine grow naturally, biofuel

production from oleoresin could reasonably be promoted. Most pine and other biofuel

crop plantations are genetically engineered or selected to increase efficiency and

production. Over the past few decades, studies have shown that there are no negative

environmental impacts on genetically engineered trees (Häggman et al., 2013). If pine

trees can be bred and selected to increase terpene content, forests in the southeast

U.S. could provide abundant feedstock for ethanol production (Singh, 2013). There has

already been advancement in increasing oleoresin production in pine trees through

breeding, inoculation, and the application of chemical stimulants (Squillace, 1965;

McReynolds and Gansel, 1985; Hodges, 1995; Popp et al., 1995b; Hodges, 2000,

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Martin et al. 2003 Hudgins et al. 2004, Hudgins and Franceschi 2004, Huber et al.,

2005, Rodrigues et al., 2008; Morris, 2015). On average, P. taeda has about 2.3%

terpene content in heartwood, 0.77% in the inner sapwood, and 0.35% in the outer

sapwood (Thompson et al., 2006). Furthermore, the quality of terpenes from conifers

are superior to ethanol and other biodiesel sources (Zerbe and Bohlmann, 2014).

While biofuels from agricultural crops are fast growing, highly resistant to pests,

highly adaptable, and high yielding, pine trees take approximately 20 years to reach

rotation age (Smith et al., 2013). Faster growing trees allow for faster genetic selection

and gains, which can improve composition of feedstock for bioenergy. Through

breeding trials, pine trees have become more and more resistant to pests, but remain

severely affected by them in certain areas. As a result of the much longer rotation age,

the net energy yield potential of pine terpenes is lower than that of other agricultural and

woody biomass sources (Hinchee et al., 2011). There is a potential for these yields to

increase with the advancement in breeding strategies.

The net energy balance, which is unit of energy produced for every unit of energy

utilized, of slash pine is higher at 5.7 than that of other feedstock, such as corn (1.25),

corn stover (1.7) or switch grass (5.4) (Nesbit, 2008). The net energy balance for

ethanol production from sugarcane is between 8.2 and 10, which is much higher than all

the other feedstocks discussed (Goldemberg 2008). Pine terpenes in their reduced

forms, such as myrcene, limonene, farnesene, and bisabolene have properties and

energy content similar to that of diesel fuel (Harvey et al., 2010; Zerbe and Bohlmann,

2014). This shows the potential of pine terpenes for biofuel production, with a potential

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of 5.5 billion gallons of ethanol capable of being produced in the U.S. from pine

plantations (Nesbit, 2008).

Distillation

Oleoresin collected from live trees is converted into rosin and turpentine through

steam distillation (Coppen, 1995; Rezzi, 2005; Figure 2-3). Figure 2-3 outlines the

distillation process used to obtain gum turpentine and gum rosin. Rosin and turpentine

are further processed into a variety of different chemical products (Rezzi, 2005). After

the distillation process, 1000 tonnes of raw resin collected in one year will yield about

650 to 700 tonnes of rosin and 150 tonnes of turpentine (Coppen, 1995).

Economics of Oleoresin Production

Non-Timber Forest Products

Non-timber forest products (NTFP) are harvested around the world in both

natural and plantation forests, and are an important income source for millions of

people, especially indigenous populations (Ticktin, 2004; Stanley et al., 2012). NTFP

range from medicinal products to aromatic resins, oleoresin, pine straw, fruit, rubber,

etc. The main advantage of NTFP is that if the demand for these products is high, the

deforestation and land use changes will decrease. However, in developing countries

people may become dependent on forest resources for economic security, which may

be problematic in the long run (Stanley et al., 2012). Though presently, out of 71 NTFP

studies sampled, over two-thirds of NTFP researched met the threshold for economic

sustainability (Stanley et al., 2012). In tropical rainforests, for example the Brazilian

Amazon, Brazil nut and natural rubber were NTFP historically important to people living

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in the forest and were promoted as an incentive to protect the native ecosystem

(Belcher and Schreckenberg, 2007).

In industrialized countries, like the U.S., NTFP are collected primarily in

plantations. Landowners in the Southeast U.S. actively manage their pine plantations

(loblolly, P. palustris, and slash) for pine straw as well as timber production (Dickens et

al., 2011). In intensively managed plantations, landowners can make an income, even if

they are absent, for about 5 to 10 years prior to final timber harvest and increase their

total net revenue from the stand (Dickens et al., 2011). In Georgia, the economic benefit

of pine straw raking was close to $81 million in 2009 (Dickens et al., 2011). Pine straw

collection is a wonderful NTFP for both small and large landowners. Management

strategies that benefit pine straw collection, such as fertilization and weed control, is

also beneficial to timber harvest, as it increases the overall production of the stand,

making it more economically profitable (Duryea, 1989; Dickens et al., 2011).

Oleoresin is one of the oldest NTFP, is renewable, and has undergone significant

improvement in collection methods (Tadesse et al., 2001). Economically, re-adding

NTFP to the forest management portfolio in the U.S. would be very beneficial and

oleoresin production can easily be included. However, excessive resin tapping,

especially using the traditional method of streaking or chipping the bark, may cause tree

mortality (Stanley et al., 2012; Susaeta et al., 2014). Formerly, the U.S. was the world’s

leading producer of oleoresin, with 50% of production, though that title now belongs to

China (Tadesse et al., 2001). With modern techniques of tapping that are less

damaging to trees, combined with the increase in tree productivity for resin and timber

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due to breeding, selection, and intensive management, the U.S. can get back into the

market and potentially return to being the leading producer of oleoresin.

Oleoresin Tapping and Timber Production

Pine oleoresin is an important NTFP collected and used around the world to

increase the economic value of the forest. To be more economically viable, it is

important to be able to collect oleoresin from live pine trees while still being able to

harvest the timber from that same stand. Wang et al. (2006) reported an increase in the

optimal rotation age of their Simao pine plantation in China from oleoresin tapping. This

occurs because trees produce more oleoresin as they increase in age (Wang et al.,

2006). However, in the U.S., with slash pine, the optimal rotation age did not increase

due to tapping (Susaeta et al., 2014).

With all else equal, a plantation that includes resin tapping and timber production

in the management portfolio is more profitable than one with only timber production, as

long as the site index is greater than 12 (Wang et al., 2006). The net present value of a

resin and timber plantation is higher compared to timber plantations, and is also

profitable in cases when only timber is not, such as interest rates of 12% (Wang et al.,

2006). Furthermore, adding oleoresin tapping to a timber stand is most beneficial when

the discount rate is low (Wang et al., 2006). Including oleoresin with timber production

was found to increase the land expectation value (LEV) by 20.5-42.7% (Susaeta et al.,

2014). The intensity of resin tapping must also be considered. If stands are tapped at

higher intensity rates there is the potential of negatively affecting growth of trees, which

would diminish the profits from timber harvest while increasing those from resin

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collection (Wang et al., 2006). However, with management and control of tapping, this

added commodity can be lucrative without damaging forest ecosystems.

Global Supply and Demand

Market requirements

A small processing plant that produces 1,000 tonnes annually would need resin

tapped from about 330,000 mature pines if annual production is 3 kg per tree (Coppen

and Hone, 1995). Oleoresin quality is important when selling in the international market

(Coppen, 1995). In general, higher levels of beta-pinene, at least 30%, are preferable,

and total pinene content above 90% is considered good quality (Coppen, 1995). The

presence of certain compounds like 3-carene would lower the quality of resin (Coppen,

1995).

Global production

Production of oleoresin globally averages at about 1,100,000 metric tonnes

annually, and in 2008 China produced 849,205 tonnes (Rodrigues-Corrêa et al., 2012;

Susaeta et al., 2014; FAO, 2014). Between 2006 and 2007, Brazil produced about

106,000 tonnes of oleoresin primarily from P. elliottii (Rodrigues et al., 2008). Since

2000, Chinese exports of rosin, resin acids and resin derivatives have steadily

increased from about 181.68 million U.S. Dollars (USD) in 2000 to about 551.85 million

USD in 2014 (World Trade Atlas, 2016). The quantity of rosin and resin acids and

derivatives exported by China has fluctuated from around 335,642 metric tons in 2000,

to around 503,273 metric tons in 2007, and then steadily decreased to about 208,744

metric tons in 2014 (World Trade Atlas, 2016). While the quantity of resin being

exported by China has decreased over the years, the value of resin has increased. The

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average price of rosin and resin in 2000 was about 0.54 USD per kilogram compared to

the current average price of 2.64 USD per kg (World Trade Atlas, 2016). Since China

uses the bark streak method of tapping with an open collection system, the resin

collected by China is of lower quality to the oleoresin that could be produced in the U.S.

through the closed system of the borehole tapping method proposed. Therefore, the

value of U.S. oleoresin would potentially be higher and thus could be sold at a higher

price compared to China.

Over the past 1.5 decades, the U.S. has steadily imported about 30 million USD

to 83 million USD, with a peak of 119 million USD, worth of rosin and resin acids and

derivatives annually (United States Census Bureau, 2016). This equates to about

30,000 to 57,000 metric tons of rosin and resin acids and derivatives annually (United

States Census Bureau, 2016). Furthermore, the U.S. has also imported between 5 to 11

million USD worth of turpentine and pine oil annually, while importing 21.85 and 20.78

million USD of this commodity in 2011 and 2012, respectively (United States Census

Bureau, 2016). The U.S. imported between 6.5 to 14.5 metric tons annually of

turpentine and pine oil between 2000 and 2014; with the recent few years seeing a

reduction in imports from over 12 metric tons in 2012 to 6.5 and 8.6 metric tons in 2013

and 2014, respectively (United States Census Bureau, 2016). The average price of

turpentine oil has increased over the years from 0.29 USD/kg in 2000 to 1.14 USD/kg in

2014; pine oil prices have also increased from 1.04 USD/kg in 2000 to 1.54 USD/kg in

2006 (United States Census Bureau, 2016). The U.S. spends a significant amount of

money on importing these commodities which could be sourced domestically.

Reinvigorating the oleoresin industry in this country to supply the pine chemical

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companies, would allow the U.S. to reduce their imports, and also potentially increase

their exports, while supplying jobs to many Americans.

What Drives the Production Cost?

Labor

The different methods of oleoresin tapping require different organization and

labor (Coppen and Hone, 1995). When using the bark streaking methods such as the

Chinese, American and French, the resin tapper must visit the tree more frequently

throughout the season. Under the Chinese method, because no chemical stimulant is

used, the resin tapper must visit the tree approximately every one to three days

(Coppen and Hone, 1995). This would mean more working hours and thus more pay for

the worker per season. However, the countries that typically use this method have lower

labor costs, like China compared to the U.S. The American and French methods require

a visit to the tree every 1 to 2 weeks, which lowers the number of total working hours

per laborer but can still be costly depending on minimum wage levels (Coppen and

Hone, 1995). The borehole method is the most cost-effective method in terms of labor

because the resin tapper only needs to revisit the tree twice in one season, though

tapping takes more time per tree (Hodges, 1995). Cunningham presented the average

wage per hour for resin tappers in Brazil, Argentina, Spain and China as well as the

labor cost per ton based on the quantity of oleoresin collected by each worker

(Cunningham, 2014; Table 2-2). Developing countries have much cheaper labor

compared to developed countries, and thus are able to produce more (Cunningham,

2014; Table 2-2). However, the average resin produced per laborer in China compared

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to Brazil and Argentina show the importance of investing in better, more sustainable

tapping techniques regardless of cost of labor (Cunningham, 2014; Table 2-2).

When using the bark streaking methods, prior to the beginning of the tapping

season, additional labor is required to prepare the stand by shaving the trees and

installing collection vessels (Coppen and Hone, 1995). Furthermore, at the end of the

season, labor is required to clean-up and collect all the vessels (Coppen and Hone,

1995). As an incentive to be more productive and work more efficiently, some

companies pay their laborers based on how much resin they collect, or establish

systems in order to reward people who collect more with bonuses, and penalize those

that do not produce as much (Coppen and Hone, 1995). In some countries, laborers do

not work with a company and are allocated a certain number of trees, and can then

decide whether or not they want to hire help using their own finances (Coppen and

Hone, 1995). In the U.S., both small landowners and large companies could enter the

resin collection business. Since the minimum wage in the U.S. is higher than in many

developing countries, resin tappers would have more of an incentive to work even if it

requires hard labor. A tapping method requiring an individual to re-visit the tree multiple

times within one season would not be cost effective in this country, because of the

higher labor cost, which is why borehole tapping appears to be the best method for this

country.

Equipment

The following is a list of equipment that is required to complete resin tapping

following the bark streaking methods (Coppen and Hone, 1995).

• Tool to shave off the bark

• Bark hack to remove bark

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• Collection vessel

• Material to make gutters

• Support nail for the gutters

• Hammer or mallet

• Sharpening tool for bark hack

• Chemical stimulant

• Bottle or container to hold and apply stimulant

• Bucket to empty resin from collection vessel

• Barrel or drum to collect and transport resin

• Protective equipment for resin tappers

Similarly, the following is a list required to collect oleoresin using the manual borehole

tapping method.

• Boring auger drill bit (2.54 cm or bigger)

• Gasoline powered drill

• Sharpening tool for drill bit

• Gasoline tank

• Gasoline and 2-cycle engine oil

• PVC pipe fitting

• Mallet

• Polyethylene collection bags

• Cable ties to attach bags to fittings

• Spray bottle to hold and apply stimulant

• Chemical stimulant

• Wire hooks to drain oleoresin from bags to barrels

• Barrel or drum to collect and transport resin

• Protective equipment for resin tappers Cost Compared to other Biofuels

Feedstock costs of pine terpenes for biofuels compared to other sources

including sugarcane, soybeans, and corn, is much lower at around $25 versus around

$200 per barrel of oil equivalent (Peter, 2013). Also, this cost has remained fairly stable

over the past 10 years, whereas other feedstock costs have fluctuated tremendously

(Peter, 2013). The lower feedstock costs are advantageous because it increases the

profitability of the biofuel. However, the cost of establishing agricultural plantations is

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much lower than that of establishing pine plantations. Frederick et al. (2008a) reported

that ethanol from lignocellulosic loblolly pine can be produced at about $1.53 per gallon

if 75% of the carbohydrates in the wood can be converted to sugars for ethanol. This

cost can be reduced if conversion technology is improved and 95% of carbohydrates

can be converted (Frederick et al. 2008a). In addition to this, other co-products, such as

tall oil and acetic acid can be recovered for additional profits while processing loblolly

carbohydrates for ethanol (Frederick et al. 2008b). This particular cost analysis is based

on pine terpene collected from dead trees and not the oleoresin collected from live

trees.

Another advantage to using pine terpenes as feedstock for biofuels is that

production is scalable due to the large available land area and stable $3-billion-dollar

market that is already established (Peter, 2013). Pine terpenes consist of many different

compounds that can be used to replace or add into petroleum products (Peter, 2013).

However, the ethanol cost of sugarcane feedstock produced in Brazil is about $0.81

versus, $2.89 for European sugar beet, $1.03 for U.S. corn, and $2.12 for U.S. slash

pine terpenes (Goldemberg, 2007; Nesbit, 2008). While pine terpenes are more

expensive, they are still competitive and with improvements in genetics and technology,

they have the potential to become more cost effective. The market for pine terpenes is

already established; in 2010 the U.S. spent $940.8 million buying this product

internationally and produced $1.92 billion (Peter, 2013). This means using southern

pine plantations in the U.S. for pine terpene production could provide products not only

for biofuels but also for the pine chemicals industry.

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Besides the economic costs of agricultural crops as biofuels, there can be a

detrimental environmental cost. While biofuels can work to reduce greenhouse gas

emissions by sequestering carbon through growth, it can also increase emissions from

land use changes (Searchinger et al., 2008). Increasing biofuel production from

agricultural crops such as corn, switchgrass, or sugarcane could promote the

conversion of forestland to cropland by farmers (Searchinger et al., 2008). Depending

on the types of land-use changes, biofuels from corn can double emissions while

biofuels from switchgrass has the potential to increase emissions by 50% (Searchinger

et al., 2008). In Brazil, the expansion of agricultural land was reported to lead to

deforestation in the amazon and averaged about two times the size of land cleared

cattle production (Morton et al., 2006). While the production of agricultural crops for

biofuel, animal feed, and human consumption can be improved through more intensive

and efficient agricultural practices, as the demand increases, more forestland will be

cleared to meet consumption needs. On the other hand, if pine terpenes are used for

biofuel production, there will not be as much of a need for land-use changes because of

the already established productive pine plantations, but if there are changing land-use

from cropland or pastureland to forests would reduce greenhouse gas emissions.

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Table 2-1. Average annual oleoresin yield in different regions from various pine species using different tapping methods. A minimum of 2 kg per tree annually is necessary to be economically viable for commercial production. Data retrieved from Hodges 1995, Tadesse et al. 2001, Rodrigues et al. 2011, Cunningham 2012, and Rodríguez-García et al. 2014, Hadiyane et al. 2015.

Country Tree Species Tapping Technique Average Oleoresin Yield (kg/tree/yr)

Spain P. pinaster American 2.39-3.8 United States P. elliottii Borehole 1.8

Brazil P. elliottii American 2.1-6.0 China P. massoniana Chinese 2.0

Indonesia P. merskusii French 2.32

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Table 2-2. Average cost of oleoresin tapping operation in various countries based on hourly wage and quantity of oleoresin collected per resin tapper. Cost is based on United States dollar. Data retrieved from Cunningham 2014.

Country Average Wage (USD/Hour)

Average Resin per Worker (ton)

Average Labor Cost (USD/ton)

Spain 10.34 18.2 1170 Argentina 3.34 14.4 477

Brazil 4.52 32.3 288 China 3.70 3.5 2060

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Figure 2-1. Processes of that lead to successful beetle colonization and conifer

defenses with interfering processes used by each organism to prevent the other’s success. Adapted from Wood 1982, Raffa et al. 1993, Phillips and Croteau 1999, Raffa et al. 2005, Faccoli and Schlyter 2007.

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Figure 2-2. Diagrams of borehole tapping designs. A) Standard boreholes drilled

manually with a gas-powered drill. B) Standard boreholes drilled manually on opposite sides of the tree. C) Boreholes drilled using a tractor mounted automated system, (d) borehole drilled manually with two shallower wide holes and two longer holes drilled with a 0.9525 cm drill bit. E) Six boreholes drilled manually in two levels, the black-marked holes drilled at the base and the grey-marked holes drilled 10.16 cm higher. F) Eight boreholes drilled manually in two levels, the black-marked holes drilled at the base and the grey-marked holes drilled 10.16 cm higher. G) Three borehole system drilled manually with one central borehole and two interior boreholes. All boreholes were drilled using a 2.54 cm drill bit; apart from the longer borehole in D which was drilled using a 0.9525 cm drill bit, the central borehole in the automated system (B) which was drilled with a 3.175 cm bit and the boreholes in the triple borehole experiment (G) which had a counterbore drilled with a 3.175 cm bit and a 2.54 cm drill bit.

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Figure 2-3. Oleoresin distillation process adapted from Coppen 1995.

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CHAPTER 3 ASSESSING EFFECTS OF STAND MANAGEMENT, TREE CHARACTERISTICS,

AND CHEMICAL STIMULANT ON OLEORESIN PRODUCTION

Introduction

In the United States, the naval stores industry began in the mid-19th century with

the extraction of pine oleoresin from longleaf (Pinus palustris Mill.) and slash pine

(Pinus elliottii Engelm. Var. elliottii) trees (Harrington, 1969; Sullivan, 2014). In the U.S.,

oleoresin collection from live trees, stopped in the 1980’s and is principally recovered in

chemical pulp mills processing pine pulpwood (Harrington, 1969; American Chemistry

Council, 2011). Today, oleoresin is harvested from live pine trees in countries like China

and Brazil to supply the pine chemical industry. Natural stands of Pinus massoniana

Lamb. and planted stands of slash pine are primarily used for tapping (Aguiar et al.,

2012). Raw oleoresin is an important pine product as it is processed into various

commercial products such as medicine, paint, fragrances, flavoring, and cleaning

agents (Coppen, 1995; Coppen and Hone, 1995). In addition, pine terpenes can be

used for biofuel, providing an alternative to petroleum (Barranx et al., 2002).

Oleoresin is a naturally produced by all conifers as a defense against pests and

any physical damage. Oleoresin production can be induced in various ways; by using

chemical inducers, by physical tapping, and by many environmental factors, such as

fire, fertilization, water availability, and climate (see Chapter 2). While there are several

tapping techniques used to collect oleoresin from live pine trees (see Chapter 2), for a

commercial operation, the primary method for increasing the production of and

collecting oleoresin from live pine trees is by wounding and applying a chemical

stimulant (Hodges, 1995; Martin et al., 2003; Rodrigues et al., 2008). The primary

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method of wounding used globally involves streaking the bark several times during a

tapping season, as frequent as every day to every two weeks. This method, however, is

not suitable for the U.S. because of higher labor costs. This study used the borehole

tapping method, which involves drilling holes into the base of the tree (Hodges, 1995;

Hodges, 2000; Hadiyane et al., 2015).

With multiple tapping techniques, chemical inducers are applied to increase

yields (Hodges, 1995; Martin et al., 2003; Hudgins et al., 2004; Hudgins and

Franceschi, 2004, Huber et al., 2005; Rodrigues et al., 2008). As discussed in Chapter

2, methyl jasmonate and ethylene releasing compounds are the two most used

stimulants for oleoresin production. Here, we compare the oleoresin yield of trees

treated with these two chemical stimulants as well as a combination of inducers. The

working hypothesis is that when applied to a wound site on the slash pine stem,

chemical stimulants promote the flow of oleoresin towards the wound, stimulate the

formation of new resin canals, and increase overall capacity of tree to synthesize and

release oleoresin.

Tree diameter at breast height (DBH), height and crown size were reported to

have a significant positive effect on oleoresin yield in certain studies (Tadesse et al.,

200; Novick et al., 2012), but not all of these factors had significant effects in other

studies (Gansel, 1965; Lekha, 2002). The hypothesis is that trees with larger DBH more

leaf area have greater xylem tissue growth, which allows for formation of new resin

canals and terpene synthesis. In the southeastern U.S., the best way to accelerate

planted pine tree growth is to use various silvicultural practices, including thinning,

fertilization, and weed control. All the stands sampled in this study were managed using

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conventional silvicultural practices, including fertilization and herbicide application. Here,

we compare the oleoresin yields of stands of differing ages and thinning regimes, while

also comparing yields of individual trees based on tree size. We hypothesize that slash

pine trees grown in more intensely managed stands will produce more oleoresin when

tapped then those with less management, because more photosynthate can be

allocated to growth and oleoresin production. Since oleoresin production is maximized

when trees are tapped during the summer months (Lorio, 1986; Gaylord et al., 2007;

Davis et al., 2011), oleoresin tapping for this study occurred in the summer, except for

the 2013 tapping season which began in early fall.

The objectives of this study were 1) to compare oleoresin yield in slash pine

under different silvicultural management scenarios and with various chemical

stimulants, and 2) to determine the influence of tree characteristics, including age, DBH,

height, and crown volume on the yield of oleoresin.

Methods

Study Areas

Planted slash pine (P. elliottii) trees between the ages of 11 and 23 years were

selected from privately owned and managed stands in Alachua, Bradford, and Union

counties in Florida, U.S. The forestry companies that provided land for this study

included: Rayonier, Roberts Land & Timber Investment Corp., and Weyerhaeuser

(formerly Plum Creek Timber Company). Throughout the study, 10 stands were

selected, some of which were used for consecutive years. All stands were managed

using similar conventional silvicultural practices such as bedding, fertilization, weed

control and contained open pollinated seedlings from genetically improved slash pine

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seed orchards. The criteria used to select stands for tapping included: not easily

accessed by the public, sufficient number of live trees available to tap, appropriate age,

and thinned/unthinned management. Within a stand, trees with prominent physical signs

and symptoms of diseases such as fusiform rust (Cronartium fusiforme Hedgcock &

Hunt ex Cummins), pitch canker (Fusarium circinatum Nirenberg & O’Donnell), bark

beetles, and pitch moth were not selected. Furthermore, within a stand, dead trees and

those damaged from abiotic factors were not selected. Also, trees with a DBH less than

12.7 cm were not selected to prevent tapping a borehole through the tree.

One of the goals of this study was to analyze the production of oleoresin from

trees of varying ages and management strategies. Stand ages from 11 to 22 years were

selected and within these age classes, unthinned and thinned stands were selected,

except for the 11-year-old stand. The selected unthinned stands were not thinned until

the completion of the study.

The Union 1 slash pine experimental site is located near Lake Butler in Lake

Butler, Florida (30°04’N latitude and 82°18’W longitude) at an elevation 43 meters from

average sea level (Table 3-2). The Alachua 1 experimental site is located just outside of

Gainesville, Florida (29°43’N latitude and 82°17’W longitude) at an elevation 48 meters

from average sea level (Table 3-2). The Alachua 2 experimental site is located near

Newnans Lake east of Gainesville, Florida (29°42’N latitude and 82°11’W longitude) at

an elevation 32 meters from average sea level (Table 3-2). The Bradford 1 experimental

site is in Hampton, Florida (29°53’N latitude and 82°15’W longitude) at an elevation 48

meters from average sea level (Table 3-2). The Union 2 experimental site is in Lake

Butler, Florida (30°03’N latitude and 82°21’W longitude) at an elevation 41 meters from

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average sea level (Table 3-2). The Alachua 3 experimental site is located just outside of


from average sea level (Table 3-2). The Alachua 4 experimental site is located just

outside of Gainesville, Florida (29°43’N latitude and 82°11’W longitude) at an elevation

33 meters from average sea level (Table 3-2). The Alachua 5 experimental site is

located just outside of Gainesville, Florida (29°42’N latitude and 82°15’W longitude) at

an elevation 42 meters from average sea level (Table 3-2).

All study sites share a humid subtropical climate with hot wet summers and mild

dry winters, and the topography was primarily flat with a 1-2% slope. The soils in the

study sites ranged from poorly drained to moderately well drained. The site indices of

the stands selected ranged from 70 to 90 meters (Table 3-1). The understory vegetation

varied throughout the different sites but was primarily sparse compared to natural

forests in North Florida. Understory vegetation included saw palmetto (Serenoa repens

(B.) Small.), blackberries (Rubus L. spp.), bluestems (Andropogon spp.), gallberry (Ilex

glabra (L.)), and greenbriers (Smilax L. spp.), among others.

Borehole Tapping and In-Tree Injection

The borehole tapping method was used to collect oleoresin from living slash pine

trees (Hodges; 1995). This method involves drilling a hole into the xylem of a tree and

attaching a bag for long-term collection. In the standard tapping method, two boreholes

are drilled parallel to one another at the base of the tree using a Stihl BT45 gasoline

powered drill at about 1000 rpm. The boreholes were drilled to a depth of 10 cm, 2.54

cm in diameter, and approximately 10 cm apart from one another (Figure 2-2). The

holes were drilled at a slight upward angle to facilitate the oleoresin flow downward into

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the collection bag. An Irwin auger bit 2.54 cm diameter, 15 cm twist, and 20 cm overall

length was used. The drill bit was sharpened using a triangular file sharpener two to

three times a day to ensure effective drilling and cutting of the oleoresin canals.

Immediately after the boreholes were drilled, a chemical stimulant was applied to

the hole using a handheld pump compression sprayer. Several chemical stimulants

were tested in this study. The compression sprayer was equipped with a cone shaped

nozzle that allowed for the application of the chemical solution on the entire surface

inside the hole. Approximately 2 ml of the chemical solution was sprayed into each

borehole. The chemical treatments were assigned randomly to the trees in the

experiment prior to visiting the field site. Each treatment had a sample size of 40 trees

and 320 trees per site were tapped. These treatments were replicated across three

different age groups and across three tapping seasons between 2013 and 2015 (Table

3-1).

Following the chemical application, a 1.905 cm PVC Lasco male adapter fitting

was inserted into the borehole using a mallet to seal it securely. A 3-ply

polyethylene/nylon laminate bag with a 2-liter capacity was attached to the fitting and

secured using a cable tie. The collection bags were left in the field for 60 to 120 days

until weighed and collected once.

During the 2014 tapping season, tapped trees were also injected about 30 days

after tapping with an additional chemical stimulant above and in between the two

boreholes using an Arbojet Quikjet in-tree injector. During the 2015 tapping season,

trees were injected two weeks prior to drilling the boreholes at select sites. These

treatments were replicated across 6 sites and across all chemical treatments.

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Chemical Stimulants

Several chemical solutions were tested to stimulate the production of oleoresin in

slash pine. At each site, 320 trees were selected and four chemical inducers were

tested. Each chemical stimulant treatment had 80 replicates per site. In the 2013 field

season, a combination of deionized water, sulfuric acid (H2SO4) and Tween 20

(surfactant) was applied as the control treatment. In addition to this solution, methyl

jasmonate with a concentration of 100 mM, 10% ethephon (2-chloroethyl-phosphonic

acid, an ethylene precursor), and a combination of the two were added as a stimulant

treatment.

During the 2014 to 2015 field seasons, sulfuric acid was no longer used in the

chemical solutions. The control treatment consisted of deionized water and Tween 20.

For the stimulant treatments, 100 mM methyl jasmonate, 10% ethephon, and a

combination of methyl jasmonate and ethephon were used. During the 2014 field

season, a stimulant treatment of iron sulfate with methyl jasmonate was used instead of

the methyl jasmonate and ethephon combination treatment. These same stimulants

were also injected into the appropriate tapped trees using an in-tree injector after

borehole drilling in 2014 and prior to borehole drilling in 2015. Each chemical treatment

with and without an in-tree injection had 40 replicate trees, conforming a total of eight

treatment combinations.

Data Collection

DBH, tree height, crown height, and crown width was measured for each tree

selected for tapping within two weeks of tapping. Table 3-2 summarizes the statistics for

all sites tapped from 2013 through 2015. The DBH was measured using a standard

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fabric diameter tape. The tree and crown heights were measured using a Haglöf Vertex

IV Hypsometer (Sweden), which was recalibrated daily. Crown width was measured

both along and across the bed using a measuring tape and two field assistants. To

measure crown, the longest branch on each side of the tree that was part of the crown

was selected. If the longest branch was isolated and not part of the main tree crown it

was not selected. Crown volume was then calculated based on the crown height, tree

height, and crown width measurement using the standard formula for the volume of a

cone:

Volume = π * r2 * (h/3); where r is the radius based on the arithmetic average radius of the crown width measurements, and h is the height of the live crown calculated by subtracting lower crown height from total tree height.

Two to three months after tapping the trees, the bags containing oleoresin were

collected from the field and weighed. Net oleoresin yield for each borehole was

measured using a digital scale with a hook, a 50 kg capacity, and a 5 g or 10 g accuracy

at the end of the tapping season. Once all the measurements were taken, the bags

were then drained into plastic barrels for collection.

Tapping Area

The oleoresin yields per unit area tapped were calculated from the cross-

sectional area of the individual borehole as well as the estimated sector-shaped tapping

area of the tree stem. The cross-sectional area of the borehole was estimated as a

polygon with sides a-b-c-d (Figure 3-1). The tapping area was considered as the area in

which there is access to resin canals from the borehole tapped. The projected area was

estimated from the extremities of the borehole and the center of the tapped tree (Figure

3-1; Figure 3-2). The areas were estimated using trigonometric formulas for the area of

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a triangle. The predicted stump diameter was calculated using the taper equation

developed by Bailey (1994) for slash pine trees. To estimate the outer bark stump

diameter in cm for slash pine trees the equation used was: Db = D (137.16

hb)β

, where Db is

the stump diameter, D is the DBH calculated at breast height (1.37 m), hb is the height

of the stump which is equal to the height of borehole (assumed to be 15.24 cm for all

tapped trees), and β is the constant parameter for slash pine trees (0.094138) based on

a fitted equation (Bailey, 1994).

The following are the formulas used to calculate the angles to determine the area

in cm2 of the projected triangle (c-x-y) or shaded tapping area in cases where the

borehole depth (10.16 cm) was less than the stump radius (Figure 3-1):

<β = sin-1 [

3.81

r]

<λ = tan-1 [

6.35

r-bd]

<α = <λ -<β

Tapped Sector Area (cm2) =

α

360 × r2× π

Where r is the radius in cm calculated from the estimated stump diameter (Db/2),

bd is the depth of the borehole (10.16 cm for all tapped trees).

The following formulas were used to calculate the angles to determine the

tapping area in cm2 in cases where the borehole depth (10.16 cm) was greater than the

stump radius (Figure 3-2):

<β = sin-1 [

3.81

r]

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<λ = tan-1 [

bd-r

3.81]

<α = (<λ +<90) − <β

Tapped Sector Area (cm2) =

α

360 × r2× π

Where r is the radius calculated from the estimated stump diameter (d), bd is the

depth of the borehole (10.16 cm for all tapped trees).

The following are the formulas used to calculate the tapping intensity (Figure 3-1;

Figure 3-2):

Tree Basal Area (cm2) = (0.00007854 × d2) × 10000

Tree Tapping Intensity (%) = Tapped Sector Area

Tree Basal Area× 10000

Statistical Analysis

To assess the main effects of chemical treatment, DBH, number of collection

days, site, age, and crown volume on oleoresin yield, a general linear model was fitted

using R 3.1.1 and ASReml-R v.3 (R Development Core Team, 2016; Gilmour et al.,

2015). The data were analyzed by site, by stand, by chemical treatment, and by number

of collection days. The following example model, with covariates, was used:

Y = µ + T + Co + D + A + CV + S + St + e

where, µ is the overall mean; T is the fixed effect of chemical treatment; Co is the fixed

effect of number of collection days; D is the fixed effect of DBH (cm); A is the fixed

effect of age (years); CV is the fixed effect of crown volume (m3); S is the fixed effect of

site; St is the fixed effect of stand; and e is the random error.

To assess the individual and interactive effects of treatment, number of collection

days, DBH, age, and crown volume on oleoresin yield, a general linear model was fitted

http://www.r-project.org/

109

using R 3.1.1 and ASReml-R v.3 (R Development Core Team, 2016; Gilmour et al.,

2015). Since the number of collection days varied by site, it was standardized for this

analysis. The following model, with covariates, was used:

Y = µ + T + Co + D + A + CV + T:Co + T:D + T:A

+ T:CV + Co:D + Co:A + Co:CV + D:A + D:CV + A:CV

+ T:Co:D + T:D:CV + S + S:T + e

where, µ is the overall mean; T is the fixed effect of chemical treatment; Co is the fixed

effect of number of collection days; D is the fixed effect of DBH; A is the fixed effect of

age; CV is the fixed effect of crown volume; T:Co is the fixed interaction effect of

chemical treatment and number of collection days; T:D is the fixed interaction effect of

chemical treatment and DBH; T:A is the fixed interaction effect of chemical treatment

and age; T:CV is the fixed interaction effect of chemical treatment and crown volume;

Co:D is the fixed interaction effect of number of collection days and DBH; Co:A is the

fixed interaction effect of number of collection days and age; Co:CV is the fixed

interaction effect of number of collection days and crown volume; D:A is the fixed

interaction effect of DBH and age; D:CV is the fixed interaction effect of DBH and crown

volume; A:CV is the fixed interaction effect of age and crown volume; T:Co:D is the

fixed interaction effect of chemical treatment, number of collection days, and DBH;

T:D:CV is the fixed interaction effect of chemical treatment, DBH and crown volume;

S is the random effect of site; S:T is the random interaction effect of site and chemical

treatment; and e is the random error.

A one-way analysis of variance (ANOVA) was used to compare the mean

oleoresin yields across sites, stand ages, chemical inducers, pine straw management,


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and tree size, using the JMP software from SAS (SAS Institute, 2016). Tukey’s

studentized range (HSD) test was used to test for significant differences among

treatment means at an α-level of 0.05. The non-linear relationship between tree DBH

(cm) and oleoresin yield (kg) was modelled using the JMP software from SAS (SAS

Institute, 2016). A p-value, which calculates the probability of an equal or greater than

the actual results when the null hypothesis is true, was also calculated for each model.

Results

General Summary of Oleoresin Yield

The complete general linear model (GLM) analysis with covariates and an error

effect by site showed significant main effects for chemical treatment, number of

collection days, DBH, and crown volume (p-values <0.0001, <0.0001, <0.0001, 0.02,

respectively) (Table 3-3). Age did not significantly affect oleoresin yield. The GLM

analysis with covariates also detected significant two-way interactions between

chemical treatment and number of collection days, DBH, and crown volume (p-values

<0.0001, 0.049, 0.009, respectively), and between DBH and crown volume on oleoresin

yield (p-value <0.0001) (Table 3-3). Significant three-way interactions among chemical

treatment, number of collection days, and DBH, as well as among chemical treatment,

DBH, and crown volume were observed (p-values <0.0001, and 0.02, respectively)

(Table 3-3).

The individual effects of chemical treatment, number of collection days, DBH,

age, crown volume, and site on total tree oleoresin yield were fitted for each site using a

general linear model without covariates. When comparing by sites, chemical treatment

and tree size (DBH) were significantly correlated with oleoresin yield (Table 3-4). For all

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sites, chemical treatment significantly affected the yield of oleoresin (p-values all

<0.0001) (Table 3-4). Apart from the Alachua 2 site (p-value 0.13), DBH had a

significant effect on yield (p-values all <0.0001) (Table 3-4). Crown volume was

significant only at four of the eight sites: Alachua 2, Union 1, Union 2, and Bradford 1

sites (p-values <0.0001, 0.02, <0.0001, and 0.04, respectively) (Table 3-4).

For all stands, chemical treatment had a highly significant effect on yield (p-

values all <0.0001) (Table 3-5). Apart from the 2013 Alachua 2 stand and the 2014

Bradford 1 stand (p-values 0.13 and 0.10, respectively), DBH was significant for all

stands (Table 3-5). In this analysis, except for two stands, stand was confounded by

collection day. This occurred because during the 2013 tapping season at the Alachua 1

and Alachua 2 stands, the collection day for treatments were around 70 days while

others were around 85 days. The number collection days was significant in 2013 for the

Alachua 1 stand but not the Alachua 2 stand (p-values <0.0001 and 0.582, respectively)

(Table 3-5). Crown volume was significant at the 2013 Alachua 2, 2013 Union 1, 2014

Union 2, and 2015 Bradford 1 stands (p-values <0.0001, 0.01, <0.0001, and 0.01,

respectively) (Table 3-5).

When comparing oleoresin yield by chemical treatment, site and tree size (DBH)

had the most significant effect (Table 3-6). For all chemical treatments, DBH

significantly affected the yield of oleoresin (p-values all <0.0001) (Table 3-6). Only for

the iron sulfate combined with methyl jasmonate chemical treatment was site not

significant (p-value 0.11) (Table 3-6). In the control, methyl jasmonate with in-tree

injection, and ethephon treatments, number of collection days had a significant effect on

yield (p-values al <0.0001) (Table 3-6). Finally, crown volume was only a significant

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effect in the control and ethephon treatments (p-value 0.001 and 0.04, respectively)

(Table 3-6).

Because the length of the tapping season for certain stands varied widely,

oleoresin yield normalized to the number of collection days was analyzed. Chemical

treatment and DBH were once again the most significant effects (Table 3-7). Chemical

treatment was highly significant among all collection days apart from 88 days and 90

days (p-values all <0.0001) (Table 3-7). In this analysis, except for 72 days, stand was

confounded with collection days. DBH was highly significant across all collection days,

except for 72, 73, 88, 90, 147 days (p-values 0.05, 0.69, 0.63, 0.05, and 0.10,

respectively) (Table 3-7). Crown volume was only significant at collection days 69, 72,

73, and 130 (p-values 0.01, <0.0001, 0.004, and <0.0001, respectively) (Table 3-7).

Stand Age

Comparison of oleoresin yield across stand ages during the three tapping

seasons indicated an increase in overall tree yield with increasing age (Table 3-8;

Figure 3-3). Oleoresin yield also depended on the number of collection days. The

oleoresin yield per collection day was estimated and compared across all ages. The

yield per day decreased with age, apart from two age groups that had significantly lower

yield (15 years and 22 years) (Table 3-9). Furthermore, the oleoresin yield per day was

analyzed by tapping season. In 2013 and 2015, the oleoresin yield per day for trees

aged 14/22 and 16/23, respectively, were not significantly different from one another

(Table 3-10). In contrast to years 2013 and 2015, the average oleoresin yield per day

during the 2014 tapping season was lower (Table 3-10).

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Collection Days

The number of days oleoresin was collected strongly impacted the final yield

(Table 3-8). Maximum oleoresin yields were not achieved at 60 or 90 days as total yield

was significantly higher after more than 110 or more days.

Chemical Stimulants

Chemical stimulants were very effective at increasing the flow of oleoresin in

slash pines. Trees treated with chemical stimulants had a significantly greater oleoresin

yield compared to those treated with the control solution (Table 3-11; Figure 3-4; Figure

3-5). The trees treated with methyl jasmonate alone or combined with ethephon or iron

sulfate, yielded significantly more oleoresin (approximately 200 g more per tree)

compared to those treated with ethephon alone (Table 3-11; Figure 3-4).

Across sites of varying ages and tapping seasons, methyl jasmonate was

consistently the most effective chemical stimulant. The methyl jasmonate treatment

alone generally resulted in significantly higher oleoresin yields compared to the

combined methyl jasmonate and ethephon or iron sulfate treatments, except for a few

sites (Tables A1-A15). At the Alachua 3 site tapped in 2014, the iron sulfate mixed with

methyl jasmonate chemical stimulant treatment produced a significantly greater

oleoresin yield compared to methyl jasmonate alone (approximately 902 g versus 642 g

per tree) (Tables A1-A15). At the 2014 Alachua 3 site, the methyl jasmonate treated

trees produced less oleoresin compared to the ethephon treatment (642 g versus 758 g

per tree), though not significantly different (Tables A1-A15). During the 2015 tapping

season, the methyl jasmonate treatment combined with ethephon produced significantly

more oleoresin compared to the methyl jasmonate alone (959 g versus 490 g) (Tables

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A1-A15). In 2015, the methyl jasmonate treatment did not produce significantly more

oleoresin compared to the ethephon treatment, however, it was significantly more

effective than the control treatment (Tables A1-A15).

During the 2015 tapping season, methyl jasmonate did not perform well at

stimulating oleoresin yield in the Alachua 4 site. Also, during the 2014 tapping season,

methyl jasmonate was not an effective chemical stimulant at the Union 1 site. In the

Alachua 4 and Union 1 sites, the methyl jasmonate treatment yielded the least amount

of oleoresin (383 g and 643 g, respectively) compared to all treatments, including the

control (Tables A1-A15). In these situations, there may have been some level of human

error in the field and the chemical stimulant may not have been properly applied.

Effects of in-tree injection. During the 2014 and 2015 tapping seasons, trees

were injected with chemical stimulants a second time using an in-tree injector to test for

the effect on resin production. In 2014 the injections took place a month after drilling the

boreholes, while in 2015 the injections occurred two weeks prior to drilling the

boreholes. The in-tree injection method did not significantly increase oleoresin

production (Tables B1-B12). In many cases, the in-tree injection was detrimental to

production and trees treated with this treatment produced less overall oleoresin than

those that were not injected (Tables B1-B12). The Union 1 site during the 2014 tapping

season benefitted from the in-tree injection with the ethephon and methyl jasmonate

combined with iron sulfate injection treatments producing significantly more oleoresin

compared to all other treatments (Tables B1-B12).

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Tree Size

Tree size had a positive impact on total resin yields per tree. The relationship

between DBH (cm) and total oleoresin yield (kg) was modeled using a nonlinear

regression (Figure 3-6). This nonlinear regression model explained 38.8% of the

variation of oleoresin yield with tree size (r2 = 0.388) (Figure 3-6). The equation for the

nonlinear regression model is as followed:

Y = 1.120 × (1 - 2.119 × e-0.085 D)

where Y equals the estimated yield per tree and D is the DBH (cm) of the tapped tree.

Stand Management

The effects of thinning and pine straw raking as stand management techniques

on oleoresin yields were also evaluated. In both the 2014 and 2015 tapping seasons,

the stand managed for pine straw, in addition to timber, had significantly greater resin

yield compared to comparable stands only managed for timber (Figure 3-7). The total

oleoresin yield per tree was analyzed by chemical stimulant in relation to pine straw

management. The ethephon stimulant promoted yield in stands managed for pine straw

raking and was not significantly different from the control treatment in the stands not

managed for pine straw (Figure 3-8A). The methyl jasmonate and methyl jasmonate

combination treatments all increased oleoresin yield at both pine straw and non-pine

straw sites; increasing the average yield by about 200 to 300 g per tree (Figure 3-8A).

Surprisingly, for this study, thinning was not found to have a positive effect on the

overall yield of oleoresin across tapping sites. In the 2013 tapping season, unthinned

and thinned sites were not significantly different (Figure 3-7). During both the 2014 and

2015 tapping seasons, thinned sites yielded significantly less oleoresin compared to

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unthinned sites (Figure 3-7). The only chemical stimulant that showed a difference in

effectiveness between thinned and not thinned sites was the methyl jasmonate and iron

sulfate combination treatment, which was more effective in thinned sites (Figure 3-8B).

Tapping Area

The tapping intensity for each tree was calculated based on the tree basal area

and the area of the sector tapped. The linear relationship between the tapping intensity

and total tree oleoresin yield (kg) was modeled and has a slope of –0.0163 [Yield =

1.164 – 0.0163 x (Tapping Intensity), r2 = 0.388; p-value = <0.0001] (Figure 3-9).

The tapping sector area was estimated for each tree as described in the methods

section and the total oleoresin yield in relation to tapping area was analyzed. The

overall yield by sector area decreased as the tapping intensity increased (Figure 3-10).

The linear relationship between the tapping intensity and yield per sector area (g/cm2)

modeled has a slope of –0.152 [Yield = 14.306 – 0.152(Tapping Intensity), r2 = 0.222; p-

value = <0.0001] (Figure 3-10).

The tapping borehole area was estimated for each tree based on the predicted

hole of 10.16 cm in depth and 2.54 cm in diameter. The oleoresin yield in relation to the

area of the borehole by tapping intensity was analyzed. Similar to sector area

calculations, the overall yield by hole area decreased as the tapping intensity increased

(Figure 3-11). The relationship between the tapping intensity and yield per hole area

(g/cm2) was modeled as a linear function and has a slope of –0.631 [Yield = 45.120 –

0.631 x (Tapping Intensity), r2 = 0.388, p-value = <0.0001] (Figure 3-11). Overall,

oleoresin yield per borehole area and per sector area is inversely related to tapping

intensities.

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Discussion

Assessing the effects of chemical inducers, tree morphology and site

characteristics on the yield of oleoresin in slash pine is important to evaluate the

potential for the reinvigoration of the oleoresin tapping industry in the southern U.S. The

borehole tapping method used in this study has been used in other studies within the

U.S. (Hodges, 1995; Hodges, 2000), and has also been used in India (Lekha, 2002).

Compared with previous reports, this study collected oleoresin from younger trees (from

11 to 23 years), which would allow oleoresin to be collected prior to typical final stand

harvest for timber products in North Florida.

Oleoresin yield using the short-term tapping method (Knebel et al., 2008) and the

Chinese tapping method, described in Chapter 2 (Wang et al., 2006) was positively

correlated with stand age. In this study although we observed a general increase in

oleoresin yield with tree age, when accounting for the number of collection days, stand

age was not a significant variable with oleoresin yield (Table 3-3). One explanation for

age not being significant is that the tapped trees were in a narrow age range (15-23

years) and based on cambial age changes in chemical and mechanical wood properties

of loblolly pine all trees are making mature wood. Thus, tree size rather than age is

correlated with yield.

Tree size, more specifically DBH was positively correlated with oleoresin yield,

where the overall trend was increased oleoresin yield in larger diameter trees. The trees

in the larger diameter classes yielded about twice the quantity of oleoresin compared to

trees in smaller diameter classes. These results are similar to those reported for older

trees by Hodges (1995), Tadesse et al. (2001), and Hadiyane et al. (2015).

118

In North Florida with the borehole tapping system, chemical stimulants were the

most effective method for increasing oleoresin yields in slash pine trees. Across all

sites, all ages, and all tapping years, methyl jasmonate was consistently the most

effective chemical stimulant, increasing yields on average by 0.3 kg per tree. It has

been reported that methyl jasmonate induces new traumatic resin canal formation and

increases wood terpene content (Franceschi et al., 2002; Hudgins et al., 2003; Martin et

al., 2003; Hudgins et al., 2004). Methyl jasmonate has also been found to increase

monoterpene levels in the stem (Huber et al., 2005) which, in turn, reduces viscosity

and crystallization rate allowing oleoresin to continue flowing (Hodges, 1995). The

yields at all other sites during the three tapping years showed that methyl jasmonate

increased oleoresin yields greater than the other chemical stimulants tested; therefore,

we believe that the lack of effect at the 2014 Union 1 and Alachua 3 sites and 2015

Alachua 4 and Bradford 1 sites (Table 3-2), is likely due to human error in the

application of the chemical. The results show that to sustainably collect oleoresin from

pine trees in a commercial operation, it is crucial to apply stimulant to the trees after

wounding.

The additional in-tree injection treatment was done to provide more chemical

stimulant, both before or after tapping, with the hypothesis that this would promote

oleoresin yields. In-tree injection did not significantly affect yield of oleoresin. In some

cases, this added treatment was detrimental to yields. The in-tree injection may have a

negative effect on oleoresin yields because creating an extra wound site, no matter how

small, may draw oleoresin production away from the collection site. To stimulate an

119

increase of oleoresin flow from an already tapped collection site, it may be more useful

to either increase the size of the wounding site by re-drilling a slightly larger hole or re-

applying the chemical stimulant as tested by Lekha (2002). This, however, would be

very time-consuming and may not be cost-effective in the long run, especially in the

U.S. where the cost of labor is high.

Stands managed for pine straw raking had significantly greater oleoresin yields

compared to stands managed solely for timber. We also found that the stands managed

for pine straw raking showed a significant positive effect of ethephon as a stimulant.

These greater yields may be a result of the more intensive management of understory

competition and/or the more intensive fertilizer application. Knebel et al. (2008)

observed two to four times greater oleoresin flow of young Pinus taeda in North

Carolina, U.S. from trees that were fertilized compared to unfertilized. However, other

studies did not find a positive impact on oleoresin yields due to fertilization (Lombardero

et al., 2000; Wei et al., 2004; Klepzig et al., 2005). Moreover, the lack of nutrient

availability due to overcrowding in a stand can negatively impact the yield of oleoresin

(Lorio, 1986). Thus, the higher yields of oleoresin observed in the pine straw raking site

may be due to the decrease in understory competition from more active management.

This also supports the idea that managing stands in the Southern U.S. for both timber

and non-timber products by collecting pine straw and oleoresin in live trees prior to

harvesting timber could lead to greater value for landowners (Susaeta et al., 2014). The

soil nutrient levels were not tested at any of our sites, so we cannot determine whether

soil nutrient deficiencies had a negative impact on oleoresin yields.

120

With the bark streak method, Mason (1971) found a negative effect of stand

density on the yield of oleoresin. Overall stand productivity is improved by managing the

stand density using various silvicultural techniques such as thinning (Reineke, 1933;

Mason, 1971; Jokela, 2004; Wallin et al., 2004; Zhang et al., 2006). We hypothesized

that trees with larger crown volume should produce more oleoresin. Decreasing stand

density reduces competition among trees and promotes growth by increasing tree

crown size and leaf area. We measured crown volume and found that in the overall

analysis it was significantly correlated with oleoresin yield (Table 3-3). However, crown

volume was only significant at three of the 15 stands and only in one year at two of the

sites which were tapped for multiple years (Table 3-5). Our results did not show a

positive effect of thinning on the overall yield of oleoresin. One explanation for no effect

is that thinned and unthinned stands at different locations we compared and the DBH of

the trees tapped within each stand were similar. We did not calculate the stand density

at each site; future studies evaluating the impacts of stand density on oleoresin yield

would be valuable.

Total tree oleoresin yield in a collection season was higher for trees tapped at

lower intensities. Furthermore, sector area and hole area yields decreased as the

tapping intensity increased. Hodges (1995) also reported similar results with the

negative impact of increased tapping intensities on oleoresin yields per unit tree basal

area. This suggests that it would be more beneficial to select larger diameter trees for

tapping slash pine for oleoresin.

While oleoresin yields from trees using the borehole tapping method vary

considerably, it is possible to predict potential yields from a stand. DBH was the

121

strongest predictor variable for oleoresin yields across all sites, stands, chemical

inducers, and number of collection days. Chemical treatment also had a significant

impact on yields and was the most effective method of increasing production within a

stand. In the full general linear model analysis, a positive significant effect of chemical

treatment, collection days, DBH, and crown volume on oleoresin yields were observed.

This shows that to increase production in slash pine trees chemical stimulants should

be applied to the wounding site, the collection season should last for as long as

possible, and trees with larger stem diameters and crowns are favorable.

Summary and Conclusions

The objectives of this study were to test the effects of chemical stimulants, tree

size, stand age, and stand management on the yield of oleoresin in slash pine trees.

Our results suggest a general positive effect of DBH on the yield of oleoresin. Methyl

jasmonate, whether alone or applied with another stimulant, was the most effective at

stimulating and increasing the yields of oleoresin within a tree. Our results showed that

yields averaged 1.0 to 1.5 kg of oleoresin per tree from young slash pine stands aged

between 11 and 22 years using the standard borehole tapping method and applying

methyl jasmonate as a stimulant. The number of days between oleoresin tapping and

final collection has a significant effect on the final season yields and thus it is

recommended to allow oleoresin flow for at least 120 days. Future studies could

evaluate the impact of soil nutrient availability on oleoresin yields in North Florida. The

soils in southern U.S. tend to be nutrient poor and thus require fertilization, so there may

be some inherent limitations to oleoresin production due to lack of site resources.

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Table 3-1. Summary of treatments for oleoresin tapping during the 2013 to 2015 field study.

Age Pine Straw Thinning Inducers Inducer Application Total #

11 N N Control MeJ Eth M+E Whole Tree Base 320 15 Y N Control MeJ Eth M+E Whole Tree Base 320 15 N Y Control MeJ Eth M+E Whole Tree Base 320 15 N N Control MeJ Eth M+E Whole Tree Base 320 22 N Y Control MeJ Eth M+E Whole Tree Base 320 22 N N Control MeJ Eth M+E Whole Tree Base 320

123

Table 3-2. Summary of sites selected for oleoresin tapping during the 2013 to 2015 field study.

Fall 2013

Stand Age Thinning Management Site

Site Index Soil Series

Mean DBH (cm)

Mean Height (m)

14 Not Thinned No Pine Straw Union 1 76 Mascotte Sand 18.6 17.2

16 Thinned No Pine Straw Alachua 1 76 Newnan/Wauchula/Ponoma Sand 19.9 17.8

22 Thinned No Pine Straw Alachua 2 63 Newnan Sand 21.6 18.1

Summer 2014



Mean DBH (cm)

Mean Height (m)

11 Not Thinned No Pine Straw Bradford 1 70 Sapello Sand 17.3 12.2


15 Not Thinned Pine Straw Union 2 NA Mascotte Sand 19.6 17.0

15 Thinned No Pine Straw Alachua 3 84 Ponoma Sand 21.3 17.7

22 Not Thinned No Pine Straw Alachua 4 90 Newnan Sand 20.6 17.0


Summer 2015



Mean DBH (cm)

Mean Height (m)

12 Not Thinned No Pine Straw Bradford 1 70 Sapello Sand 17.4 12.9


16 Not Thinned Pine Straw Union 2 NA Mascotte Sand 19.5 18.0


23 Not Thinned No Pine Straw Alachua 4 90 Newnan Sand 22.1 18.8


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Table 3-3. Summary of main and interactive effects on oleoresin yield in sites using the standard borehole tapping method between 2013 to 2015 based on a general linear model with covariates.

Effect DF Den DF p-value

Treatment 9 32.8 <0.001**

Collection 1 236.9 <0.001**

DBH 1 4232.3 <0.001**

Age 1 10.0 0.850

Crown 1 3791.9 0.020*

Treatment:Collection 9 156.1 <0.001**

Treatment:DBH 9 4136.3 0.049*

Treatment:Age 9 39.8 0.100

Treatment:Crown 9 3664.7 0.009**

Collection:DBH 1 3854.5 0.940

Collection:Age 1 2139.9 0.320

Collection:Crown 1 3792.3 0.140

DBH:Age 1 3061.1 0.800

DBH:Crown 1 2410.6 <0.001**

Age:Crown 1 2960.9 0.420

Treatment:Collection:DBH 9 3425.0 <0.001**

Treatment:DBH:Crown 9 3384.4 0.020*

Note: P-values with * superscripts are significant based on a test with p-value <0.05, while p-values with ** superscripts are significant based on a test with p-value <0.01.

125

Table 3-4. Summary of main effects F-statistic and p-values on oleoresin yield by site using the standard borehole tapping method between 2013 to 2015 based on a general linear model without covariates.

Site Chemical Treatment DBH Age Collection Days Crown Volume

Alachua 1 75.26 (<0.001**) 44.84 (<0.001**) NA 14.08 (<0.001**) 0.40 (0.530)

Alachua 2 61.70 (<0.001**) 26.94 (0.127) NA 0.54 (0.582) 12.15 (<0.001**)

Alachua 3 18.68 (<0.001**) 73.15 (<0.001**) 0.64 (0.42) NA 0.28 (0.600)

Alachua 4 4.71 (<0.001**) 57.25 (<0.001**) 300.60 (<0.001**) NA 0.56 (0.460)

Alachua 5 36.45 (<0.001**) 112.20 (<0.001**) 256.90 (<0.001**) NA 0.00 (0.100)

Union 1 18.60 (<0.001**) 121.40 (<0.001**) 18.86 (0.070) 52.44 (<0.001**) 5.81 (0.020*)

Union 2 22.74 (<0.001**) 57.72 (<0.001**) 89.69 (<0.001**) NA 15.12 (<0.001**)

Bradford 1 25.02 (<0.001**) 13.34 (<0.001**) 103.00 (<0.001**) NA 4.33 (0.040*)


126

Table 3-5. Summary of main effects F-statistic and p-values on oleoresin yield by stand using the standard borehole tapping method between 2013 to 2015 based on a general linear model without covariates.

Stand Chemical Treatment DBH Collection Days Crown Volume

2013 Alachua 1 75.26 (<0.001**) 44.84 (<0.001**) 14.08 (<0.001**) 0.40 (0.530)

2013 Alachua 2 61.70 (<0.001**) 26.94 (0.130) 0.54 (0.582) 12.15 (<0.001**)

2013 Union 1 122.70 (<0.001**) 31.40 (0.040*) NA 6.72 (0.010*)

2014 Alachua 3 16.72 (<0.001**) 47.52 (<0.001**) NA 0.08 (0.780)

2014 Alachua 4 4.26 (<0.001**) 58.39 (<0.001**) NA 0.66 (0.420)

2014 Alachua 5 14.35 (<0.001**) 76.19 (<0.001**) NA 3.40 (0.070)

2014 Union 1 5.38 (<0.001**) 23.76 (0.030*) NA 2.46 (0.120)

2014 Union 2 18.25 (<0.001**) 38.42 (0.007**) NA 11.18 (<0.001**)

2014 Bradford 1 38.79 (<0.001**) 2.95 (0.100) NA 0.17 (0.680)

2015 Alachua 3 28.24 (<0.001**) 51.33 (<0.001**) NA 0.02 (0.890)

2015 Alachua 4 11.78 (<0.001**) 104.90 (<0.001**) NA 0.61 (0.440)

2015 Alachua 5 50.63 (<0.001**) 67.93 (<0.001**) NA 3.29 (0.070)

2015 Union 1 8.22 (<0.001**) 102.20 (<0.001**) NA 1.25 (0.260)

2015 Union 2 15.86 (<0.001**) 25.35 (0.001**) NA 2.26 (0.130)

2015 Bradford 1 33.48 (<0.001**) 28.50 (<0.001**) NA 6.08 (0.010*)


127

Table 3-6. Summary of main effects F-statistic and p-values on oleoresin yield by chemical treatment using the standard borehole tapping method between 2013 to 2015 based on a general linear model without covariates.

Treatment Site DBH Collection Days Crown Volume

Control 11.22 (<0.001**) 102.40 (<0.001**) 88.10 (<0.001**) 10.19 (0.001**)

Control/Whole 14.71 (<0.001**) 67.17 (<0.001**) 1.69 (0.180) 0.25 (0.610)

MeJa 16.46 (<0.001**) 45.05 (<0.001**) 0.88 (0.420) 2.61 (0.110)

MeJa/Whole 15.92 (<0.001**) 25.67 (0.001**) 82.86 (<0.001**) 2.14 (0.140)

Ethephon 22.32 (<0.001**) 91.23 (<0.001**) 100.90 (<0.001**) 4.23 (0.040*)

Ethephon/Whole 14.81 (<0.001**) 52.62 (<0.001**) 0.24 (0.610) 1.20 (0.270)

MeJaEthephon 6.02 (<0.001**) 79.10 (<0.001**) 1.56 (0.190) 2.31 (0.130)

MeJaEthephon/Whole 4.03 (<0.001**) 44.10 (<0.001**) NA 1.49 (0.220)

FeSMeJa 10.60 (0.002**) 26.66 (<0.001**) NA 0.05 (0.830)

FeSMeJa/Whole 3.32 (0.110) 30.03 (<0.001**) NA 1.06 (0.300)


128

Table 3-7. Summary of main effects F-statistic and p-values on oleoresin yields by collection days drilled using the standard borehole tapping method between 2013 to 2015 based on a general linear model without covariates.

Collection Days Treatment DBH Stand Crown Volume

57 8.22 (<0.001**) 102.20 (<0.001**) NA 1.25 (0.260)

63 15.86 (<0.001**) 25.35 (0.001**) NA 2.26 (0.130)

68 50.63 (<0.001**) 67.93 (<0.001**) NA 3.29 (0.070)

69 33.48 (<0.001**) 28.50 (<0.001**) NA 6.08 (0.010*)

71 28.24 (<0.001**) 51.33 (<0.001**) NA 0.02 (0.890)

72 52.79 (<0.001**) 43.35 (0.050) 4.59 (0.030*) 18.81 (<0.001**)

73 215.40 (<0.001**) 15.74 (0.690) NA 8.22 (0.004**)

76 11.78 (<0.001**) 104.90 (<0.001**) NA 0.61 (0.440)

85 31.52 (<0.001**) 27.98 (<0.001**) NA 0.01 (0.920)

86 3.73 (<0.008**) 23.39 (<0.001**) NA 1.81 (0.180)

88 0.00 (0.440) 0.85 (0.630) NA 3.47 (0.080)

90 1.12 (0.350) 3.03 (0.050) NA 0.97 (0.330)

128 5.38 (<0.001**) 23.76 (0.030*) NA 2.46 (0.120)

130 18.25 (<0.001**) 38.42 (0.007**) NA 11.18 (<0.001**)

133 16.72 (<0.001**) 47.52 (<0.001**) NA 0.08 (0.780)

140 4.26 (<0.001**) 58.39 (<0.001**) NA 0.66 (0.420)

147 38.79 (<0.001**) 2.95 (0.100) NA 0.17 (0.680)


129

Table 3-8. Summary of oleoresin yields by stand age from tapping slash pine using the borehole tapping method. Trees were tapped between summer and early fall of 2013-2015.

Note: The means with different letter superscripts were significantly different based on Tukey’s HSD test (p-value <0.05).

Stand Age (years)

Number of Trees Tapped

Mean Collection Days

Mean DBH (cm)

Mean Tree Yield (kg)

SE Tree Yield (kg)

CV (%)

11 320 147 17.26 0.691b 0.021 55.03

12 304 69 17.40 0.528c 0.023 76.96

14 318 73 18.63 0.660b 0.018 47.54

15 949 130 20.02 0.792a 0.014 54.63

16 1247 69 20.02 0.647b 0.011 59.62

22 909 113 21.49 0.811a 0.015 55.80

23 624 72 21.13 0.699b 0.019 69.30

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Table 3-9. Summary of oleoresin yields per collection day by age from tapping slash pine trees using the borehole tapping method. The trees were tapped between summer and early fall 2013-2015.

Age (years) Mean Yield Per Day (g/day) SE (g/day) CV (%)

11 4.699d 0.14 55.03

12 7.657b 0.34 76.96

14 9.108a 0.24 47.48

15 6.084c 0.11 54.80

16 9.509a 0.16 59.63

22 7.492b 0.15 61.35

23 9.863a 0.29 72.70

Note: The ages with different letter superscripts were significantly different from Tukey’s HSD test (p-value < 0.05)

131

Table 3-10. Summary of oleoresin yields per collection day by age from tapping slash pine trees using the borehole tapping method. The trees were tapped between summer and early fall 2013-2015.

Tapping Year Age (years) Mean Yield (g) SE (g) CV (%)

2013 14 9.108a 0.24 47.48 2013 16 8.009b 0.27 59.00 2013 22 8.957ab 0.34 66.84

2014 11 4.699c 0.15 55.03 2014 15 6.084b 0.11 54.80 2014 22 6.711a 0.14 50.69

2015 12 7.657b 0.34 79.96 2015 16 10.01a 0.19 58.64 2015 23 9.863a 0.29 72.70

Note: The ages with different significance level letters within a tapping season were significantly different based on Tukey’s HSD test (p-value < 0.05)

132

Table 3-11. Summary of oleoresin yields by chemical treatment from tapping slash pine using the borehole tapping method. Trees were tapped between summer and early fall of 2013-2015. Chemical stimulants tested include ethephon, Methyl jasmonate (MeJa), iron sulfate mixed with methyl jasmonate (FeSMeJa), and Methyl jasmonate mixed with ethephon (MeJaEthephon).

Chemical Treatment Number of Trees Tapped Mean Yield (kg) SE (kg) CV (%)

Control (no chemical) 1153 0.493d 0.0083 56.86

Ethephon 1173 0.611c 0.0099 55.46

FeSMeJa 467 0.860ab 0.0188 47.30

MeJa 1182 0.896a 0.0148 56.66

MejaEthephon 697 0.830b 0.0158 50.19


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Figure 3-1. Calculations for the cross-sectional tapping area and individual hole area

model for the trees with DBH greater than 10.16 cm. c is the center of the tree, r is the radius calculated using the predicted stump diameter, bd represents the borehole depth, and bw represents the borehole width. The tapping area is the triangle c-y-x

134

Figure 3-2. Calculations for the cross-sectional tapping area and individual hole area model for the trees with DBH less than 10.16 cm. c is the center of the tree, r is the radius calculated using the predicted stump diameter, bd represents the borehole depth, bw represents the borehole width, and the shaded area is the tapping area.

135

Figure 3-3. Age effect on oleoresin yield (kg) with standard errors when tapping slash

pine trees in North Florida during the 2013 to 2015 field seasons.

0

0.2

0.4

0.6

0.8

1

2013 2014 2015

To

tal Y

ield

(kg

)

Tapping Year

11/12 Years 14/15 Years 16 Years 22/23 Years

a

a

aaab

b

c

c

136

Figure 3-4. Chemical effect on oleoresin yield (kg) with standard errors when tapping

slash pine trees in North Florida during the 2013 to 2015 field seasons. The means with different letter superscripts were significantly different based on Tukey’s HSD test (p-value <0.05).

137

Figure 3-5. Chemical effects of oleoresin yield (g) per day with standard errors when

tapping slash pine trees in North Florida during the 2013 to 2015 field seasons. The means with different letter superscripts were significantly different based on Tukey’s HSD test (p-value <0.05).

138

Figure 3-6. Nonlinear regression displaying the actual relationship between average

oleoresin yield (kg) in slash pine and DBH in cm for all trees tapped in the 2013 to 2015 tapping season.

139

Figure 3-7. Effect of pine straw management and thinning on oleoresin yield (kg) with

standard errors when tapping slash pine trees in North Florida during the 2013 to 2015 field seasons. The means with different letter superscripts were significantly different based on Tukey’s HSD test (p-value <0.05).

140

A

B

Figure 3-8. Chemical effect on oleoresin yield (kg) when tapping slash pine trees in

North Florida during the 2013 to 2015 field seasons under different management scenarios. A) Effect of managing stands for pine straw raking, B) Effect of thinning.

141

Figure 3-9. Bivariate fit of total tree yield of oleoresin (kg) in slash pine by tapping

intensity. The r2 for the linear relationship between tapping intensity and average total tree yield is 0.388 (p-value <0.0001).

142

Figure 3-10. Bivariate fit of sector area yield of oleoresin in slash pine by tapping

intensity. The r2 for the linear relationship between tapping intensity and average yield per sector area is 0.22 (p-value <0.0001).

143

Figure 3-11. Bivariate fit of hole area yield of oleoresin in slash pine by tapping

intensity. The r2 for the linear relationship between tapping intensity and average yield per hole area is 0.39 (p-value <0.0001).

144

CHAPTER 4 CHEMICAL STIMULANT DOSAGE AND CARRIER SOLVENTS IN THE BOREHOLE

METHOD TO INCREASE OLEORESIN YIELD IN SLASH PINE

Introduction

With the desire for increased energy security and to mitigate global warming, the

U.S. demand for alternatives to petroleum based fuel is high. Using woody biomass as

biofuel feedstocks can help increase the value of timber land in the southern U.S.

Chapter 2 reviewed global and U.S. demand for pine terpenes and the established

market for pine chemicals. Terpene extraction from slash pine trees can help meet the

market demands for biofuel, jet fuel, and strengthen energy security, providing an

alternative to petroleum (Barranx et al., 2002). Currently, in the U.S. the pulping

processes extract hemicelluloses from conifers which can be fermented to produce

cellulosic ethanol (Nesbit et al., 2011). In their study, Nesbit et al. (2011) concluded that

the most profitable scenario for non-industrial forest landowners in the southern U.S.

was the production of traditional timber products with the collection of harvest residues

to produce biofuels. While this form of ethanol production is not yet cost-competitive

with traditional corn-based ethanol, it will become more competitive as the technology

develops and improves (Nesbit et al. 2011). However, the technique of removing

biomass residues on site can lead to diminishing growth yields overtime due to the

removal of soil nutrients (Eisenbies et al., 2009; Nesbit et al. 2011). The nutrients in the

soil can be replaced by increasing fertilization rates from 45% to 60% in certain sites

(Eisenbies et al., 2009). On the other hand, with the oleoresin tapping technique

considered in this study, pine terpenes can be extracted directly from live trees without

the removal of residual biomass. This technique also allows for traditional timber

harvest in conjunction with oleoresin collection.

145

Oleoresin is currently collected from live trees in various countries using primarily

a method of tapping involving the removal of streak of bark. Most resin is collected in

countries with low cost labor and use methods where laborers visit the tree multiple

times during a tapping season. These methods are not economically feasible in the U.S.

due to high labor cost, even though the southern U.S. has extensive planted and natural

slash pine forests available. The borehole tapping method is the most attractive

oleoresin production method for use in the U.S. (Hodges, 1995; Hodges 2000).

However, to commercialize production of oleoresin in the U.S. and be competitive global

producers, it is crucial to increase the yield of oleoresin per individual tree.

Terpene production in conifers has been found to increase significantly with the

application of chemical stimulants. Martin et al. (2003) studied the effects of spraying

methyl jasmonate on the terpene formation in needles of Norway spruce (Picea abies

Karst.) saplings. Without wounding the saplings, Martin et al. (2003) observed a 2-fold

increase in terpene accumulation and a 5-fold increase in terpene emission from the

foliage. Past studies have determined that the increase in terpene production in the

stem after the application of methyl jasmonate was due to the formation of new

traumatic axial resin canals (Franceschi et al., 2002; Martin et al., 2003; Hudgins et al.,

2004). However, limited research has explored the dynamic between chemical dosage

of methyl jasmonate and oleoresin yields in slash pine (Pinus elliottii Engelm. Var.

elliottii) trees.

The primary goal of this research is to develop optimal and sustainable methods

for increasing oleoresin yields from live slash pine trees in the southern U.S. In Chapter

3 the yield of oleoresin was compared with various chemical stimulants, stand

146

management techniques, and stand age, and assessed relationships between yield and

various tree phenotypic characteristics. Here, chemical concentrations and stimulant

solvents were investigated to identify methods to improve oleoresin yield per individual

tree. Because methyl jasmonate was the most effective chemical at stimulating

oleoresin yield and production in slash pine (Chapter 3), we focused on this chemical.

Therefore, the objectives of this study are: 1) to determine which concentration of

methyl jasmonate and, 2) to identify which carrier solvent is most effective to increase

oleoresin yield.

Methods

Study Areas

The same thinned slash pine stand in Alachua county described in Chapter 3

(Alachua 3) was used for the dosage carrier solvent experiments. This site was 15

years old in 2014 and 17 years old in 2016, is located just outside of Gainesville, Florida

(29°46’N latitude and 82°18’W longitude) at an elevation 51 meters from average sea

level. This stand was managed using conventional silvicultural practices including

bedding, weed control, and fertilizer treatments. Trees with prominent physical signs

and symptoms of diseases such as fusiform rust (Cronartium fusiforme Hedgcock &

Hunt ex Cummins), pitch canker (Fusarium circinatum Nirenberg & O’Donnell), bark

beetles, and pitch moth were not selected.

The study site had a humid subtropical climate with hot wet summers and mild

dry winters, and the topography was primarily flat with a 1-2% slope. The soils in the

study sites ranged from poorly drained to moderately well drained. The understory

vegetation was primarily sparse. Understory vegetation included saw palmetto (Serenoa

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repens (B.) Small.), blackberries (Rubus L. spp.), bluestems (Andropogon spp.),

gallberry (Ilex glabra (L.)), and greenbriers (Smilax L. spp.), among others.

Borehole Tapping

The borehole tapping method, more thoroughly described in Chapter 3, was used

to tap living slash pine trees for oleoresin collection. This method involves drilling two

boreholes 2.54 cm in diameter 10.16 inches into the stem at a slight upwards angle at

the base of the tree using a gas-powered drill. Once the boreholes were drilled, each

hole received 2 ml of a chemical treatment using a handheld compression sprayer. The

chemical treatments were assigned randomly to the trees in the experiment prior to

visiting the field site and each treatment had a sample size of 40 trees. Following the

chemical application, a fitting was inserted into the borehole using a mallet to seal it

securely and a collection bag was attached and secured using a cable tie. Additional

details describing the borehole tapping technique are presented in Chapter 3.

Chemical Stimulants

2015 tapping season

During the 2015 tapping season, a methyl jasmonate dose response experiments

was conducted. Methyl jasmonate at 7 concentrations, 0 mM (control), 25 mM, 50 mM,

100 mM, 200 mM, 400 mM, and 600 mM in DI water and Tween 20 was applied. In

2015 a methyl jasmonate and ethephon dose response experiment tested methyl

jasmonate and ethephon at 9 concentration combinations: 50 mM methyl jasmonate

with 1%, 5% and 10% ethephon; 100 mM methyl jasmonate with 1%, 5% and 10%

ethephon, and 400 mM methyl jasmonate with 1%, 5% and 10% ethephon. During the

2015 tapping season, 90% ethanol compared to DI water and Tween 20 as the carrier

solvent for methyl jasmonate was tested.

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2016 tapping season

In 2016 another dose response experiment was implemented that tested methyl

jasmonate at 5 concentrations, 0 mM (control), 100 mM, 200 mM, 400 mM, and 600 mM

diluted with 90% ethanol.

Data Collection

Diameter at breast height (DBH), tree height and crown volume were measured

in the carrier solvent experiment. For the 2015 methyl jasmonate dose response test, all

the collection bags were weighed every 4 days for the first 40 days prior to final

collection. At the end of the tapping season, all bags were weighed using a digital scale.

Additional details explaining data collection techniques used are presented in Chapter

3.


The chemical inducer treatments for each all dose response experimental tests

were randomized prior to visiting the field with each treatment was assigned to 40 trees.

A one-way analysis of variance (ANOVA) was used to compare the mean oleoresin

yield across treatments for all tests using the JMP software from SAS (SAS Institute,

2016). Tukey’s studentized range (HSD) test was used to test for significant differences

among means at an α level of 0.05.

During the 2015 methyl jasmonate dose response experiment, the mass of the

oleoresin collection bags was recorded every 4 days for 40 days and once more at day

95. To examine the cumulative flow of oleoresin during a tapping season, a nonlinear

regression model was fitted for each chemical stimulant using the JMP software from

SAS (SAS Institute, 2016). The predicted cumulative flow of oleoresin over time during

a 95-day tapping season was estimated using the regression model and graphed.

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Lastly, to examine the overall cumulative flow of oleoresin for all 2015 methyl jasmonate

dose response treatments, a nonlinear regression model was fitted.

Results

During the 2015 tapping season, a dose response experiment with various

ethephon doses (1%, 5%, and 10%) and methyl jasmonate concentrations (50 mM, 100

mM, and 400 mM) was implemented. Results showed that methyl jasmonate was more

effective at stimulating oleoresin yields when combined with lower levels of ethephon,

except at 100 mM concentration, methyl jasmonate where there were no significant

differences between yields (Figure 4-1). Overall, the average oleoresin yields increased

as the concentrations of methyl jasmonate increased (Figure 4-1). The 50 mM with 1%

ethephon, 100 mM with 1, 5, and 10% ethephon, and the 400 mM with 10% ethephon

treatments did not yield significantly different quantities of oleoresin (Figure 4-1). The

400 mM 1% and 5% yielded significantly more oleoresin than all the other treatments,

but were not different from one another (Figure 4-1).

As expected, in the 2015 methyl jasmonate dose response test, oleoresin yields

increased with methyl jasmonate concentration (Figure 4-2). The final oleoresin yield of

the 600 mM methyl jasmonate treatment was close to double the yield (2.3 kg) of 100

mM methyl jasmonate treatment (1.3 kg) (Figure 4-2), which is the standard dose for

experiments described earlier in Chapter 3 (Figure 4-2). The 25 mM methyl jasmonate

treatment was not effective and did not yield significantly more oleoresin compared to

the control treatment (Figure 4-2). The 400 mM and 600 mM methyl jasmonate

treatments were not significantly different; however, the 200 mM treatment yielded

significantly less oleoresin compared to the 600 mM treatment (Figure 4-2).

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During this study, the weight of the collection bags was measured every 4 days

for the initial 40 days and once more at day 95. These data were used to calculate the

cumulative flow rate of oleoresin overtime by chemical stimulant. The data was then

modeled using a nonlinear function for each chemical stimulant (Figure 4-3). The

equations for the nonlinear regression models are listed in Figure 4-3. The nonlinear

regression models explained between 97.0% and 99.4% of the variation of oleoresin

yield with concentration of methyl jasmonate (control r2 = 0.99; 25 mM r2 = 0.99; 50 mM

r2 = 0.99; 100 mM r2 = 0.97; 200 mM r2 = 0.98; 400 mM r2 = 0.97; 600 mM r2 = 0.98)

(Figure 4-3). The cumulative oleoresin flow rate from the control and treatments with 25

mM, 50 mM, and 100 mM methyl jasmonate concentrations slowed at about day 60,

yielding between 70 grams and 216 grams during the last 35 days of collection (control

= 70 grams, 25 mM = 149 grams, 50 mM = 140 grams, and 100 mM = 216 grams)

(Figure 4-2; Figure 4-3). The chemical treatments with 200 mM, 400 mM, and 600 mM

methyl jasmonate concentrations did not appear to have reached their full oleoresin

production capacity at the time of collection, which suggests the tapping season should

be greater than 95 days (Figure 4-3).

The data for all chemical treatments in the 2015 methyl jasmonate dose

response experiment were used to calculate and plot the cumulative flow of oleoresin

and oleoresin flow rate over time since the day of tapping (Figure 4-4). The following

nonlinear regression model was obtained:

Y = 1673.058 × (1 - 0.959 × e-0.017 D)

where Y is the oleoresin yield (kg) and D corresponds to the collection day. These data

were plotted as the percent of full season oleoresin yield and the percent to reach full

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season yield, in this case, the full season yield was based on the 95-day season (Figure

4-4). Based on these calculations, about 50 % of the oleoresin yield was collected by

day 30 (Figure 4-4).

Because the previously described methyl jasmonate dose response experiment

did not apparently saturate the response, we conducted a second test in 2015 were we

compared DI water and Tween 20 and 90% ethanol as a carrier solvent. These results

show that methyl jasmonate was significantly more effective when diluted with 90%

ethanol as opposed to the combination of DI water and Tween 20 (Table 4-2; Figure 4-

5). The trees treated with the alcohol dilution averaged 1.5 kg, while the trees treated

with the DI water and Tween 20 dilution averaged 0.94 kg of oleoresin (Table 4-2;

Figure 4-5). Furthermore, the main effects of tree height and crown volume were not

significant (Table 4-2).

During the 2016 tapping season, a methyl jasmonate dose response test diluted

in ethanol instead of DI water and Tween 20 was conducted. Similar to the 2015 methyl

jasmonate dose response test, we observed a positive effect of increasing chemical

concentration on oleoresin yield (Figure 4-6). Trees that received a methyl jasmonate

dose of 400 mM yielded close to double the yield of oleoresin (3.0 kg) compared to

trees treated with 100 mM (1.65 kg) (Figure 4-6). The 100 mM and 200 mM methyl

jasmonate treatments were not significantly different to one another (Figure 4-6). The

400 mM and 600 mM methyl jasmonate treatments were not significantly different to

one another; however, the 400 mM treatment yielded more oleoresin (Figure 4-6).

Discussion

The methyl jasmonate and ethephon dose response experiment show a potential

negative interaction with the combination of the two chemical stimulants, particularly

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10% ethephon. This negative effect of ethephon when combined with methyl jasmonate

was also observed with many of the other experiments discussed in Chapters 3 and 4

where the methyl jasmonate treatment yielded more oleoresin compared to the methyl

jasmonate and ethephon combination treatments. Since methyl jasmonate performed

well or significantly better when applied alone and ethephon at 1% and 5% did not

stimulate oleoresin yield when combined with methyl jasmonate, we conclude that

methyl jasmonate is best used alone to stimulate oleoresin flow. This will also lower the

cost of tapping as there will be no need to purchase ethephon.

Compared with the DI water and Tween 20, the alcohol and methyl jasmonate

solution increased oleoresin yield. In the field, it appeared that methyl jasmonate

dissolved more easily in ethanol compared to DI water and Tween 20. The solutions

with 100, 200, 400, and 600 mM of methyl jasmonate in DI water had to be mixed

throughout the day, while the solutions with all dosages of methyl jasmonate in ethanol

did not. This is likely due to increased solubility of the methyl jasmonate in the ethanol

compared with the Tween 20/water. Franceschi et al. (2001) and Martin et al. (2003)

solubilized methyl jasmonate at concentrations of 100 mM and lower with Tween 20,

however, they did not test higher dosages of methyl jasmonate. Ethanol was used to

dissolve methyl jasmonate at low concentrations in a study by Mizukami et al. (1993).

Further, methyl jasmonate is freely soluble in 95% ethanol at estimated volumes of 1 to

10 ml of solvent to dissolve 1 g of solute (Bio-World, 2017), while it is very slightly

soluble in water at estimated volumes of 1000 ml of solvent to dissolve 0.34 gram of

solute (Sigma-Aldrich, 2017).

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Interestingly, the dose response curve with similar concentrations of methyl

jasmonate did not saturate with the Tween 20/water (Figure 4-2) whereas it did saturate

with the ethanol solvent, suggesting a more uniform response with ethanol (Figure 4-6).

It is also possible that ethanol carries the methyl jasmonate better into the wood itself to

stimulate production of new resin canals, and/or slow oleoresin crystallization at the

wound site.

Since ethanol was observed to be a better carrier of methyl jasmonate in 2015,

we used a solution of ethanol to apply methyl jasmonate to trees in our 2016 methyl

jasmonate dose response treatment. In this study, DBH was the only main tree effect

that significantly predicted oleoresin yields. This suggests larger trees tend to be more

productive and thus have the potential to produce more oleoresin. This result is also

consistent with findings from other oleoresin tapping trials discussed in Chapter 2.

The results from the 2015 and 2016 methyl jasmonate dose response

experiments showed increasing the concentration of methyl jasmonate increased

oleoresin production. In the 2016 dose response test, the 400 mM and 600 mM methyl

jasmonate yielded the same oleoresin amount per tree showing that the response was

saturated around 400 mM. Therefore, an additional experiment optimizing the dosage

between 200 and 400 mM of methyl jasmonate using the borehole tapping method in a

commercial operation would be beneficial. The 2016 experiment highlighted the

potential of collecting an average of 3 kg of oleoresin in young live slash pine trees in

the southeast U.S., using methyl jasmonate diluted in 90% ethanol as a stimulant.

Based on this study, the optimal treatment for oleoresin collection is drilling two 10.16

cm boreholes at the base of the tree and applying 2 ml of 400 mM methyl jasmonate

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diluted in 90% ethanol. Although Coppen (1995) suggested that to be economically

viable, oleoresin yields per tree should be at least 2 kg. Cost sensitivity analyses

suggest that the borehole method in the southeast U.S. can be cost effective at yields of

2.5 to 3.0 kg per tree.

Our kinetic data show the importance of the first couple weeks after tapping,

when fifty percent of the final oleoresin mass was collected within the first month. Lekha

(2002) increased the yield of oleoresin per tree by re-drilling a slightly larger borehole

every month. If we wanted to increase the yield of oleoresin per tree, along with

increasing methyl jasmonate concentrations, it may be beneficial to re-drill and re-apply

chemical stimulants monthly or at least once after the first month of tapping. However,

this may not be cost-effective due to the high labor cost in the U.S.

We conducted a cost analysis based on the yield results from the 2016 ethanol-

methyl jasmonate results. For commercial production chemical, labor and equipment

costs would have to be considered when determining the optimal tapping treatment

(Hodges and Ferguson, 2011; Table 4-3). The labor and equipment cost would be the

same for all chemical stimulant treatments. Based on average productivity rates of 26.7

trees per hour from our study and a labor cost of $8.50 per hour per person, the total

cost of labor and equipment for an oleoresin tapping operation would be $1.648 per tree

(Table 4-3). Average oleoresin yield of trees treated with 100 mM of methyl jasmonate

was 1.65 kg. The estimated cost per tree of 100 mM methyl jasmonate is $0.28, which

would make for a total cost of $1.70 per kg of oleoresin (Table 4-3). Average oleoresin

yield of trees treated with 400 mM of methyl jasmonate was 3.00 kg. The estimated cost

per tree for 400 mM methyl jasmonate is $1.11, and the total cost per kg of oleoresin is

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$1.21 (Table 4-3). Finally, the estimated cost per tree of 600 mM methyl jasmonate is

$1.66, and the total cost per kg of oleoresin is $1.55 based on average tree yield of 2.7

kg (Table 4-3). Because of the significant increase in oleoresin yield with increasing

methyl jasmonate dosage, the most cost-effective chemical stimulant is 400 mM of

methyl jasmonate diluted in 90% ethanol.


This study was designed to test the effects of various concentrations of methyl

jasmonate and ethephon on the yield of oleoresin. The goal was to determine the

optimal and most effective dose. Our results suggest the application of methyl

jasmonate alone increased oleoresin production in younger slash pine trees in the

southern U.S. Ethanol was a more efficient carrier solvent of methyl jasmonate

compared with a combination of Tween 20 and DI water at concentrations above 100

mM. The optimal chemical stimulant treatment for maximizing oleoresin yields in slash

pine is 400 mM of methyl jasmonate diluted in 90% ethanol. Furthermore, since it

appears that the trees, based on time series data, had not reached their full oleoresin

yield potential at 90-100 days, particularly with the higher doses of methyl jasmonate it

is beneficial to allow for 140 days for a full collection season. With 400 mM methyl

jasmonate giving an average oleoresin yields of 3.0 kg per tree in 16-year-old slash pine

stands in North Florida we estimate that oleoresin can be collected at a cost of $1.21

per kg.

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Table 4-1. Summary of oleoresin tapping dosage and carrier solvent experiments in 2014-2016.

Year

Site Location Experiment Stand Age (Years)

Number Chemical Inducers

Number Trees

Number Boreholes Per Tree

2014 Gainesville, FL Methyl Jasmonate Dose Response

15 10 400 2


15 7 280 2


16 7 280 2

2015 Gainesville, FL Methyl Jasmonate and Ethephon Dose

Response

16 9 360 2

2015 Gainesville, FL Alcohol 16 2 80 2 2016 Gainesville, FL Methyl Jasmonate Dose

Response 17 6 240 2

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Table 4-2. Effects of methyl jasmonate carrier solvent, DBH, height and crown volume on oleoresin yield (kg) when tapping slash pine trees in 2015 using the standard borehole tapping method.

Chemical Treatment DBH(cm) Tree Height (m) Crown Volume (m3) Oleoresin Yield (kg)

Average SE Average SE Average SE Average SE Alcohol 22.845a 0.54 20.115a 0.22 47.891a 4.17 1.507a 0.12 Tween 21.873a 0.52 19.594a 0.24 44.064a 3.66 0.936b 0.11


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Table 4-3. Estimated cost per tree of borehole tapping method to collect oleoresin. Calculated costs are based on productivity rates of tapping 26.7 trees per hour and applying 400 mM of methyl jasmonate diluted in 90% ethanol. Adapted from Hodges and Ferguson (2011).

Cost Category / Item Quantity per tree

Units Unit Price Cost per

Tree

Supplies

Spouts: 2.54 x 12.7 cm PVC pipe, or custom molded PE 2 Ea. $0.150 $0.300 Collection bags, Nylon/PE laminate, 6x20 in. 2 Ea. $0.090 $0.180 Cable ties for bag closure 2 Ea. $0.010 $0.020 Methyl jasmonate – 400 mM 2 Dose $0.553 $1.105 Distilled water 2 Dose $0.001 $0.002 Ethanol 2 Dose $0.141 $0.281 Diesel fuel for drill machine and utility vehicle 0.050 Gal. $3.00 $0.150 Gasoline and oil for power drill 0.004 Gal. $4.50 $0.019

Subtotal supplies $2.205

Labor

Borehole Treatment/Installation (3-man crew, average productivity rate)

0.163 Hr. $8.50 $1.388

Oleoresin harvesting (3-man crew, average productivity) 0.017 Hr. $8.50 $0.143 Subtotal labor $1.530

Equipment Quantity

per crew

Unit Price Total Cost Cost per

Tree*

Off-road utility vehicle (Kubota RTV900XT) 1 $10,000 $10,000 $0.040

Power drill (Sthil BT45) 2 $450 $900 $0.004 Drill bits: 2.54 cm 3 $25 $75 $0.000 Chemical sprayer 2 $100 $200 $0.001 Small tools: mallet, machete, pliers, measuring cup 4 $50 $200 $0.001

Rubber gloves (for chemical mixing and resin handling) 100 $3 $300 $0.001

Note: Equipment costs depreciated over useful life of 250,000 trees; does not include transportation equipment. The cost of 1 kg of methyl jasmonate from Bedoukian Research is $3080. The cost per tree of 100 mM methyl jasmonate is $0.276; the cost per tree of 600 mM methyl jasmonate is $1.658

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Table 4-3. Continued.

Equipment Quantity

per crew

Unit Price Total Cost Cost per

Tree*

Fuel can: 2 gal. 2 $15 $30 $0.000 Fuel cans: 15 gal.

Buckets: 5 gal. 10 $5 $50 $0.000 Barrels: 55 gal. capacity 50 $30 $1,500 $0.006

Subtotal equipment $11,755 $0.054

Total All Costs $3.642

Predicted average yield per tree at 100 days (Kg) 3.000 Total Cost Per Kg Resin $1.214

Note: Equipment costs depreciated over useful life of 250,000 trees; does not include highway transportation equipment. The cost of 1 kg of methyl jasmonate from Bedoukian Research is $3080. The cost per tree of 100 mM methyl jasmonate is $0.276; the cost per tree of 600 mM methyl jasmonate is $1.658

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Figure 4-1. Chemical dose effects on oleoresin yield (kg) with standard errors when

tapping slash pine trees in 2015 using the standard tapping method. The different doses are methyl jasmonate concentrations (50 mM, 100 mM, and 400 mM) and ethephon percentages (1%, 5%, and 10%). The means within a methyl jasmonate concentration with a different letter superscripts were significantly different based on Tukey’s HSD test (p-value <0.05).

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

50 mM 100 mM 400 mM

Ole

ore

sin

Yie

ld (

kg

)

Methyl Jasmonate Concentration

1% 5% 10%

ab

c

bc

a

ab

abab

ab

a

Ethephon Concentration

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tapping slash pine trees in 2015 using the standard tapping method. The different doses are methyl jasmonate concentrations in DI water and Tween 20. The means with different letter superscripts were significantly different based on Tukey’s HSD test (p-value <0.05).

162

Figure 4-3. Cumulative flow rate of oleoresin (g) since day of tapping treatment by

chemical treatment at the 2015 dose response test. The following equations correspond to the oleoresin flow rate when trees are stimulated by the different methyl jasmonate doses: control: y = 652.107 * (1 – 0.891 e-0.027D ); 25 mM: y = 1004.612 * (1 – 0.928 e-0.019D ); 50 mM: y = 1097.538 * (1 – 0.991 e-0.023D ); 100 mM: y = 1502.460 * (1 – 0.913 e-0.019D ); 200 mM: y = 2509.604 * (1 – 0.944 e-0.012D ); 400 mM: y = 2723.893 * (1 – 0.948 e-0.012D ); 600 mM: y = 5508.152 * (1 – 0.961 e-0.005D ). Where y corresponds to oleoresin yield (g) and D corresponds to number of days since treatment.

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Figure 4-4. Cumulative flow of oleoresin (g) and resin flow rate over time since day of

tapping treatment in Gainesville at the 2015 methyl jasmonate dose response test.

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Figure 4-5. Effect of carrier solvent on oleoresin yield (kg) for 100 mM methyl

jasmonate when tapping slash pine trees in North Florida using the standard borehole drilling method. The means with different letter superscripts were significantly different based on Tukey’s HSD test (p-value <0.05).

165


tapping slash pine trees in 2016 using the standard tapping method. The different doses are methyl jasmonate concentrations diluted in 90% ethanol. The means with different letter superscripts were significantly different based on Tukey’s HSD test (p-value <0.05).

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CHAPTER 5 GENETIC EFFECTS ON OLEORESIN FLOW OF SLASH PINE CLONES

Introduction

The individual tree variation in slash pine (Pinus elliottii Engelm. Var. elliottii)

oleoresin composition is high and suggests that many components are under genetic

control (Squillace and Fisher, 1966). In Chapter 2, the variation of oleoresin flow and

yield among conifer species were discussed. The flow rate of oleoresin is influenced by

environmental and biological factors. Resin duct size, number, and length, oleoresin

viscosity, crystallization rate, and exudation pressure can all affect the rate of flow of

resin and potential yield (USDA Forest Service, 1971a; Hodges, 1995). These resin and

tree properties are not only different among conifer species, but can be controlled by

genetics within species (Schopmeyer et al., 1954; USDA Forest Service, 1971a; USDA

Forest Service, 1971b; Hodges, 1995; Sukarno et al., 2015). The duration of oleoresin

flow also varies within and among species and in the southeast U.S.; oleoresin in slash

pine trees flows for months, while oleoresin flow in loblolly pine tends to slow

dramatically after 2 days (Hodges et al., 1977).

There is a great potential of increasing productivity in an oleoresin tapping

operation through breeding programs due to the high broad-sense heritability of growth

traits that have a direct influence on yield as well as the heritability of oleoresin flow and

yield (Schopmeyer et al., 1954; Franklin et al., 1970; USDA Forest Service, 1971a;

USDA Forest Service, 1971b; Westbrook et al., 2013; Sukarno et al., 2015). Increasing

the productivity of southeastern pine species through intensive forest management and

selective breeding is crucial to ensure global timber and non-timber forest products

demands are met.

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The first objective of this study was to evaluate the correlation between short

term with long term oleoresin yield of slash pine trees by using the CCLONES 2 site

established by the University of Florida’s FBRC. A strong genetic correlation between

short term and long-term oleoresin yields would allow us to screen trees more cost

effectively for making selections. The second objective of this study was to estimate

heritability of the oleoresin flow traits among various families to determine the level of

genetic control of this trait.

Methods

Study Area

The slash pine CCLONES 2 (Comparing Clonal Lines On Experimental Sites)

stand used for this study was established by the University of Florida’s FBRC in

December 2002 (FBRC, 2002). This study was located in a low rust hazard property

owned and managed by Rayonier Inc. in northeast Gainesville, Florida (29°43’45.7” N,

82°17’46.0” W). The study was established by the FBRC, Rayonier Inc., and Boise

Corp. to better understand clonal biology and to “characterize elite genotypes of slash

pine and to understand their growth dynamics, ecophysiology, nutrition, pest resistance

and wood quality across a range of planting sites and management intensities as both

cuttings (clones from FS families) and seedlings (FS families)” (FBRC, 2002).

The study area was prepared with chopping, raking and bedding between April

and May 2002. In September 2002, the site was treated with 48 ounces Chopper and

five quarts Conquer and in November 2002, a second bed was established in the study

area. The site was then planted with test, border and filler trees in December 2002. The

study area was divided into eight replicate plots; four intensively managed plots

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(replicates 5, 6, 7, and 8) and four non-intensively managed plots (replicates 1, 2, 3, 4).

In November 2002, the intensive treatments received an additional herbicide treatment

of 20% Garlon with 80% JLB Oil applied by hand on palmetto stems. In April 2003, the

whole study area was treated with three ounces Oust per acre in 20 gallons of water via

broadcast application using a tractor to control herbaceous weeds. Between September

and October 2003, the whole study area received 200 lbs per acre of diammonium

phosphate (DAP) via helicopter and 50 per acre DAP via four-wheeler.

The study area has a humid subtropical climate with hot wet summers and mild

dry winters, and the topography was flat with a slope between 0 and 2%. The study was

established on a poorly drained site and the dominant soil series was Wauchula. The

Wauchula series is a Spodosol and is classified as a sandy over loamy, siliceous,

active, hyperthermic Ultic Alaquods (USDA Natural Resources Conservation Service

1993b). The understory vegetation included saw palmetto (Serenoa repens (B.) Small.),

blackberries (Rubus L. spp.), bluestems (Andropogon spp.), gallberry (Ilex glabra (L.)),

greenbriers (Smilax L. spp.), lopsided Indiangrass (Sorghastrum nutans (L.) Nash) and

a variety of other native grasses.

Study Design and Genetic Material

The CCLONES 2 study consisted of genotypes from 22 elite parents of slash

pine clones from the same FS families and seedlings from FS families. The genetic

materials for this study were provided by Rayonier Inc. and Boise Corp. (FBRC, 2002).

Five of the elite parents were CFGRP families; while 17 of the elite parents were from

WGFTIP selections (Western Gulf Tree Improvement Program) (FBRC, 2002). The

study was planted using an incomplete block plot design with 60 incomplete blocks in

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each replicate plot. The 22 elite parents were used to create 19 FS families (FBRC,

2002). In total, 672 clones and 48 seedlings were planted in each replicate plot. Each

replicate plot contains 20 beds with 36 trees in each, for a total of 720 trees per

replicate. The study area was planted at a density of 725 seedlings per acre with each

replicate plot being about 1 acre. The non-intensive and intensive treatments were

separated by a ten-row buffer. Within each intensity treatment there were no border

rows. Each treatment had a total of 40 beds and 72 trees in each, split into four

replicates. For this dissertation research, only four replicate plots, two from each

intensity treatments (i.e., replicates 1, 3, 5, and 7) were selected. Figure 5-1 outlines the

planting layout for the study. Table 5-1 summarizes the number of trees selected for

tapping in each family and replicate plot.

Oleoresin Collection

The trees in the CCLONES 2 site were tapped using a short-term oleoresin

collection method described in Strom et al. (2002) and Roberds et al. (2003). This

method involved making a 1.27 cm in diameter circular wound using an arch punch,

facilitated removal of the bark and phloem at breast height. Immediately after wounding,

plastic taps with a 15-ml collection tube were placed over the wound site and mounted

with a screw. Oleoresin flowed into the tubes for roughly 24 hours after tapping and was

weighed within one week of collection. The empty tubes, with individual barcodes, were

weighed prior to tapping to get the final oleoresin mass.

The trees in the CCLONES 2 site were also tapped using the borehole tapping

method discussed in Chapter 3. Each tree was tapped with one borehole and treated

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with 100 mM methyl jasmonate stimulant diluted in 90% ethanol as discussed in

Chapter 4.


The diameter at breast height (DBH) in cm and oleoresin yield (g) data from the

CCLONES 2 study were analyzed in R 3.1.1 and ASReml-R v.3 (R Development Core

Team, 2016; Gilmour et al., 2015). To assess the bivariate effects of DBH on short- and

long-term oleoresin yield, a linear regression model was fitted using the JMP software

from SAS (SAS Institute, 2016). The least squares mean was calculated using lsmeans

R package based on a general linear mixed model with replicate and family as fixed

effects. Outliers more than two standard deviations from the mean were omitted in the

analysis. Broad-sense heritabilities of individual phenotypic traits were calculated based

on the following clonal model with the constructed pedigree and without covariates:

Yij = µ + Ri + Ri:IBj + ped(Cloneid) + Familyid + ide(Cloneid) + eij

where Yij corresponds to the phenotypic trait in the ith replicate (i = 1, 3, 5, or 7) and ith

replicate by jth incomplete block (j = 1 to 60), Ri corresponds to the fixed replicate effect,

Ri:IBj corresponds to the random incomplete block within replicate effect, ped(Cloneid)

corresponds to the random additive effect, ide(Cloneid) corresponds to the random non-

additive effects of a given clone, and ej corresponds to the random residual effect.

There is a pedigree associated with the term ped(Cloneid) that was used to assign a

numerator relationship matrix.

To assess the individual and interactive effects of DBH and short-term oleoresin

yield on long-term oleoresin yield, a general linear mixed model was fitted using R 3.1.1


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and ASReml-R v.3 (R Development Core Team, 2016; Gilmour et al., 2015). The

following clonal model with the constructed pedigree and covariates was used:

Yij = µ + Ri + TM + D + D:TM + Ri:IBj + ped(Cloneid) + Familyid + ide(Cloneid) + eij

where Yij corresponds to the phenotypic trait in the ith replicate (I = 1, 3, 5, or 7) and ith

replicate by jth incomplete block (j = 1 to 60), TM corresponds to the fixed short-term

oleoresin yield effect, D corresponds to the fixed DBH effect, D:TM corresponds to the

fixed interaction effect of DBH and short-term oleoresin yield. All other terms were

previously defined.

The type A genetic correlation between short-term and long-term yield was

analyzed using R 3.1.1 and ASReml-R v.3 (R Development Core Team, 2016; Gilmour

et al., 2015). The following equation to calculate genetic correlation was used:

Correlation(TM,BM)=Cov(TM,BM)

√Var(TM)×Var(BM)

Where TM corresponds to short-term yield, BM corresponds to long-term yield,

Cov(TM,BM) corresponds to the covariance between short- and long-term yield,

Var(TM) corresponds to the variance component of short-term yield, and Var(BM)

corresponds to the variance component of long-term yield.

Results

DBH had a very strong positive influence on total oleoresin yields for long-term

but not short-term oleoresin collection. The oleoresin was collected long-term for four

months by drilling a single borehole into the base of the tree and was collected short-

term for 24 hours by wounding the bark at breast height. The relationship between DBH

(cm) and total long-term oleoresin yield (g) was modeled using a linear regression



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(Figure 5-3). This linear regression model explained 78.5% of the variation of oleoresin

yield with tree size (r2 = 0.7846 and p-value <0.0001) (Figure 5-3). The equation for the

linear regression model is as followed:

Y = 137.30 + (50.12 × D)

where Y equals the estimated yield per tree (g) and D is the DBH (cm) of the tapped

tree.

The relationship between DBH (cm) and total long-term oleoresin yield (g) by

Family ID was also modeled using a linear regression (Figure 5-4). This linear

regression model explained 37.8% of the variation of oleoresin yield with tree size (r2 =

0.3873 and p-value = 0.0147) (Figure 5-4). The equation for the linear regression model

is as followed:

Y = 198.61 + (29.00 × D)

where Y equals the estimated yield per tree (g) and D is the DBH (cm) of the tapped

tree.

In contrast, no relationship was observed between tree size and short-term

oleoresin yield (r2 = 0.0023 and p-value = 0.7503) (Figure 5-5).

Table 5-2 summarizes the least squares means for DBH (cm), short-term yield

(g), and long-term oleoresin yield (g) for all replicate plots. While the clones in family

504 were larger than all the other families (average DBH 17.2 cm), the trees had some

of the lowest oleoresin short-term yields (0.60 g) and not significantly different from

long-term yield (Table 5-2; Table 5-3; Figure 5-2). Family 534 had the smallest trees

(DBH 13.18) and the lowest long-term yield with a mean about 540 g of oleoresin (Table

5-2; Table 5-3; Figure 5-2). Family 521, had average DBH and short-term yields, but the

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highest long-term oleoresin yield (782.3 g) (Table 5-2; Table 5-3; Figure 5-2). Family

539 had the highest short-term oleoresin yields (1.7 g) and had on average larger DBH

(Table 5-2; Table 5-3; Figure 5-2). Short-term oleoresin yields were the same for

families 502 and 532; these families had the lowest yields (0.4 g and 0.5 g, respectively)

(Table 5-2; Table 5-3; Figure 5-2).

The estimated broad-sense heritabilities for all three traits, based on a clonal

model with fixed replicate effect and random incomplete block within replicate and

individual additive and non-additive clonal effects are presented in Table 5-4. Broad-

sense heritability estimates ranged from moderate to low (Table 5-4). DBH had the

highest heritability estimate (H2 = 0.321) (Table 5-4). The broad-sense heritability

estimates for short-term and long-term oleoresin yield were low (H2 = 0.161 and H2 =

0.190, respectively) (Table 5-4).

The individual and interactive effects of DBH and short-term oleoresin yield on

long-term yield were fitted using a general linear clonal model. The model showed only

significant main effects of replicate plot and DBH (p-values 0.002 and <0.0001,

respectively) (Table 5-5). Short-term yield (Tube Mass) was not a significant predictor

as a main effect (p-value = 0.619); however, it had a positive significant interaction with

DBH (p-value = 0.041) (Table 5-5). The broad-sense heritability estimate of long-term

oleoresin yield with DBH, short-term yield, and the interaction as covariates was

moderately low (H2 = 0.194) (Table 5-4).

The relationship between short- and long-term oleoresin yield (g) was modeled

using a linear regression (Figure 5-6). This linear regression model did not explain the

variation of long-term oleoresin yield with short-term yield (r2 = 0.001 and p-value =

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0.4177) (Figure 5-6). In contrast, the Type-A genetic correlation between short- and

long-term yield was analyzed based on the Family ID and accounting for incomplete

block effects. This analysis observes the phenotypic correlation among two traits and

can be used to examine the biological relationship between traits and make selections

for breeding. The Type-A genetic correlation between short- and long-term yield was

0.718 (Table 5-6).

Discussion

Planted loblolly and slash pine grown in the Coastal Plain typically take around

20-25 years to reach rotation age and, as a result, progeny tests are used by tree

breeders to make inferences and select better performing families at a younger age

(Squillace and Gansel, 1974). Ten-year-old slash pine progeny tests can be used to

make growth and productivity predictions at the age of 25 (Squillace and Gansel, 1974).

Understanding the genetic architecture of short- and long-term oleoresin yields

and tree size on long-term oleoresin yield will allow us to increase productivity of

tapping operations and overall profitability of slash pine stands. As observed in the

studies discussed in Chapters 2 and 3, DBH is correlated positively with long-term

oleoresin yield. Hodges (1995), Tadesse et al. (2001), and Hadiyane et al. (2015), all

found similar positive correlations between DBH and oleoresin yields. In the size

considered from the CCLONES 2 study, the linear regression model showed a very

strong correlation between DBH and long-term oleoresin yield (r2 = 0.7846). This

suggests that slash pine families selected for larger stem size on average can increase

the potential oleoresin yield of a plantation. Tree size was not correlated with short-term

175

oleoresin yield. This was not surprising as oleoresin was collected from a small surface

wound for only 24-hours.

According to Tadesse (2001), the best method to increase oleoresin yields is by

selecting and breeding high yielding trees. McReynolds and Gansel (1985) found that a

high gum yielding slash pine progeny test established in 1946 yielded 30% more

oleoresin compared to non-high gum stands. In our study, there were families that

outperformed others based on DBH, short-term oleoresin yields and long-term oleoresin

yields. However, in certain cases, like family 504, the families with larger trees had less

short-term oleoresin yield. In terms of long-term oleoresin yield, one family (521) had

significantly higher yield, which would make the high yielding clones within this family

good selections.

The broad-sense heritability of DBH in the CCLONES 2 site was moderately

strong at H2 = 0.32. However, the broad-sense heritability estimates for short- and long-

term oleoresin yield in the CCLONES 2 site were moderately low. These results are not

comparable to those obtained in other studies which calculated broad-sense heritability

estimates between 67 and 90% (Mergen et al., 1955; Squillace and Doman, 1959;

Squillace and Bengtson, 1961; Squillace, 1965). This is likely due to the small number

of families studied here. Nevertheless, these heritability estimates are still high enough

to be able to make selections and achieve attractive genetic gains. However, heritability

estimates for short-term oleoresin flow in slash pine were comparable to the short-term

oleoresin flow reported by Westbrook et al. (2013) in loblolly pine tapped in North

Florida, U.S. using the same method. Westbrook et al. (2013) recorded within site

broad-sense heritability estimates of 0.25 to 0.38, compared to our estimates of 0.16.

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DBH was again the best phenotypic predictor of long-term oleoresin yield.

Because there was no phenotypic correlation between short- and long-term yield, short-

term yield alone is not a good predictor of long-term yield. However, there was a strong

positive genetic correlation (0.718) between short- and long-term yields. This positive

association suggests the potential of selecting high yielding trees based on short-term

oleoresin flow studies for breeding. Selection of trees with higher short-term oleoresin

yields will lead to genetic gain for both short- and long-term oleoresin yields.

Planting high yielding clones and families would increase the profitability of slash

pine stands and would allow the U.S. to be more competitive in the global pine chemical

industry. Future research should focus on examining the age to age correlation of short-

and long-term oleoresin yield. A strong correlation between short-term oleoresin flow in

young trees aged 5 to 6 and long-term oleoresin yield in trees aged 15 to 20 would

allow us to confidently make early selections of high yielding trees.


This study was designed to examine the genetic effects on oleoresin yield. The

goals of this study were to evaluate the correlations between DBH and short-term

oleoresin yield on long-term oleoresin yields and the heritability estimates of these traits

in a slash pine clonal site. Phenotypically, short-term yield was not correlated to long-

term yields. The strong positive genetic correlation between short- and long-term yield

support the approach that genetic tests screened with short-term yields can be used to

select high yielding trees. One family tested had significantly higher long-term yields.

This family would be a great candidate for a breeding program aimed at increase

oleoresin productivity in slash pine.

177

Table 5-1. Summary of genotypes selected in each replicate of the CCLONES 2 study.

Family ID Replicate 1 Replicate 3 Replicate 5 Replicate 7

501 13 14 14 14 502 13 10 15 15 504 14 15 14 14 505 15 14 15 14 521 16 15 15 15 529 13 14 14 15 530 14 13 14 14 531 15 15 14 14 532 10 11 15 11 533 14 14 14 14 534 10 10 14 15 535 12 13 15 15 537 15 12 14 15 538 13 15 14 15 539 14 15 13 15 540 14 15 11 13 Total 216 215 225 229

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Table 5-2. Least square means with standard errors for phenotypic traits measured at the CCLONES 2 study.

Family ID DBH (cm) Short-Term Oleoresin Yield (g)

Long-Term Oleoresin Yield (g)

501 16.579 (0.275) 1.002 (0.156) 643.760 (41.486) 502 16.585 (0.285) 0.382 (0.160) 626.718 (42.291) 504 17.169 (0.268) 0.603 (0.156) 645.623 (40.752) 505 15.249 (0.272) 1.141 (0.152) 722.132 (40.399) 521 15.535 (0.272) 0.892 (0.152) 782.266 (39.393) 529 16.772 (0.275) 1.090 (0.152) 735.904 (41.116) 530 15.749 (0.282) 1.308 (0.159) 649.500 (41.486) 531 15.752 (0.272) 0.799 (0.156) 676.961 (40.399) 532 14.488 (0.296) 0.462 (0.167) 608.080 (44.908) 533 16.819 (0.272) 1.111 (0.156) 658.482 (41.113) 534 13.166 (0.298) 0.761 (0.167) 538.959 (43.993) 535 15.341 (0.282) 0.826 (0.160) 638.262 (41.496) 537 15.948 (0.279) 0.859 (0.157) 659.035 (41.123) 538 15.295 (0.272) 1.377 (0.157) 642.213 (40.755) 539 16.756 (0.270) 1.663 (0.152) 745.471 (40.755) 540 15.129 (0.282) 0.966 (0.157) 639.986 (42.276)

Note: short-term oleoresin was collected in a 24-hour period and long-term oleoresin was collected over four months.

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Table 5-3. Tukey significance group letters of the least square means for phenotypic traits measured at the CCLONES 2 study (alpha < 0.05) recorded in Table 5-2.

Family ID DBH (cm) Short-Term Oleoresin Yield (g)

Long-Term Oleoresin Yield (g)

501 ABC ABCD AB 502 ABCD D AB 504 A CD AB 505 DEF ABCD AB 521 BCDEF BCD A 529 AB ABCD AB 530 BCDEF ABC AB 531 BCDEF BCD AB 532 FG D AB 533 AB ABCD AB 534 G BCD B 535 CDEF BCD AB 537 ABCDE BCD AB 538 CDEF AB AB 539 AB A AB 540 EF ABCD AB

Note: The different Tukey group letters were significantly different based on Tukey’s HSD test (p-value <0.05). Short-term oleoresin was collected in a 24-hour period and long-term oleoresin was collected over four months.

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Table 5-4. Broad sense heritability estimates calculated for phenotypic traits measured at the CCLONES 2 study.

Phenotypic Trait Broad Sense Heritability Standard Error

DBH 0.321 0.064

Short Term Oleoresin Yield 0.161 0.050

Long Term Oleoresin Yield 0.190 0.048

Long Term Oleoresin Yield with Covariates 0.194 0.049


181

Table 5-5. Summary of main and interactive effects on long-term oleoresin yields at the CCLONES 2 site using the borehole tapping method in 2016 based on a general linear clonal model.

Effect DF Den DF F-statistic p-value

Replicate 3 175.7 5.45 0.002**

Tube Mass 1 832.8 0.04 0.619

DBH 1 698.9 125.40 <0.000**

DBH:Tube Mass 1 820.6 4.17 0.041

Note: P-values with ** superscripts are significant based on a test with p-value <0.01. Tube mass represents short-term 24-hour oleoresin yield.

182

Table 5-6. Summary of variance components of genetic correlation between short-term and long-term oleoresin yield in the CCLONES 2 site.

Trait Variance Component Standard Error

Short-Term Oleoresin Yield 0.053 0.03

Long-Term Oleoresin Yield 1413.780 1068.89

Short- and Long-Term Oleoresin Yield 6.227 4.04


183

Figure 5-1. Layout of the University of Florida’s CCLONES 2.

184

A

B Figure 5-2. Least square means with standard errors for oleoresin traits measured at

the CCLONES 2 study. A) Average short-term oleoresin yield. B) Average long-term oleoresin yield.

185

Figure 5-3. Bivariate fit of total long-term tree yield of oleoresin (g) in slash pine by DBH

(cm). The r2 for the linear relationship between DBH and average total tree yield is 0.785 (p-value <0.0001).

186

Figure 5-4. Bivariate fit of total long-term clonal mean oleoresin yield (g) in slash pine

by DBH (cm). The r2 for the linear relationship between DBH and average total tree yield is 0.378 (p-value 0.0147).

187

Figure 5-5. Bivariate fit of short-term tree yield of oleoresin (g) in slash pine by DBH

(cm). The r2 for the linear relationship between DBH and average short-term tree yield is 0.002 (p-value 0.7503).

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Figure 5-6. Bivariate fit of short-term and long-term oleoresin yield (g). The r2 for the linear relationship between short-term tree yield and average long-term yield is 0.001 (p-value 0.4177).

189

CHAPTER 6 CONCLUSION

To maximize the value of forest plantations in the southeast U.S., the primary

focus of this research was to understand the effects of chemical and physical inducers,

and environmental and genetic effects on the flow and yield of oleoresin from slash pine

trees. The specific objectives of this research were: (1) to maximize collection and

recovery of oleoresin and increase terpene synthesis in slash pine for renewable

chemicals and biofuel production by testing different chemical stimulants, tapping

intensity, stand ages, and stand management practices, (2) to determine the optimal

methyl jasmonate dosage and carrier solvent that gives the greatest oleoresin yields in

the southeast U.S., and (3) to determine the genotypic and phenotypic correlations

between 24-hour resin flow with multi-month resin collection for genetic improvement in

oleoresin yields.

The borehole tapping method to collect oleoresin has numerous benefits

compared to other methods used around the world. This method only requires laborers

to visit the tree two times during a collection season, it yields better quality oleoresin

with less impurities and greater amounts of monoterpenes, reducing crystallization, and

this method allows landowners to maintain their stands for timber production without

damage to merchantable wood (Hodges, 1995).

In Chapter 3, the effects of stand management, tree characteristics, age, and

chemical stimulants on the yield of oleoresin in slash pine trees in North Florida were

examined. Overall, oleoresin yields increased with tree age; however, this increase was

positively correlated with tree size because age was not significant. Larger trees are

more productive and thus have a greater potential for producing oleoresin. Tapping

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intensity was negatively correlated to oleoresin yield, which further supports tapping of

larger trees is preferred. Crown volume was not nearly as strong a predictor of oleoresin

yield compared to DBH. Hodges (1995) also concluded that canopy was not as good of

a predictor and inferred that oleoresin flow capacity from the borehole tapping method is

fixed.

Pine straw management had a significantly positive impact on oleoresin yields.

Active management, increased fertilization treatments, and reduced understory

competition all potentially play a role in increasing oleoresin yields observed in trees

tapped on a site managed for pine straw raking. Numerous questions on the effects of

soil nutrient availability on oleoresin productivity remain unanswered. Knebel et al.

(2008) observed an increase in oleoresin production in loblolly pines with fertilization.

Understanding how the soil nutrient limitations impact production in slash pine trees will

help frame silvicultural management regimes for plantations established to collect

oleoresin.

Across all sites and all ages, chemical stimulant was the most significant

predictor of oleoresin yields. Methyl jasmonate was the best inducer of oleoresin yields

tested in slash pine trees. The optimal tapping season length with the borehole tapping

method is a minimum of 120 days, with tapping occurring in the late spring/early

summer. In summary, when tapping young slash pine trees, aged 15 to 22, in the

southeastern U.S. using the borehole method, it is possible to collect on average 1 to

1.5 kg of oleoresin per tree.

In Chapter 4, the optimal and most sustainable treatment for increasing oleoresin

yields in slash pine trees was examined. As observed in Chapter 3, the application of

191

chemical stimulants was the most effective inducer of oleoresin yields. The dilution of

chemical inducers in ethanol as opposed to DI water and Tween 20 was beneficial. The

alcohol may allow methyl jasmonate to better penetrate the xylem, reduce the

crystallization rate within the borehole and help maintain the flow of the oleoresin. The

dose response experiments showed the benefit of increasing methyl jasmonate

concentration on oleoresin yield. The optimal concentration of methyl jasmonate to

induce oleoresin flow was 400 mM. With this increase in concentration it is possible to

collect close to 3.0 kg of oleoresin in 15-year-old slash pine trees, which would make

the operation economically viable.

Several variations of the borehole tapping method were tested, including six and

eight boreholes and smaller boreholes within larger ones (Appendix C). However, it was

found that the best tapping method is an automated system with three boreholes drilled

at the base of the tree all connecting to one collection borehole.

The automated method is less labor intensive and allows for a much larger

oleoresin collection operation. The average productivity for the manual drilling method

using the gas-powered drill to drill two boreholes was 26.7 trees per hour. On the other

hand, average productivity using the automated tapping method, which drills three

connected boreholes was significantly higher at 61 trees per hour. Further, the

estimated total cost per kg of oleoresin using the automated drilling technique is $1.29,

compared to $3.00 for the manual drilling method. Further, the most cost-effective

chemical stimulant treatment was the 400 mM methyl jasmonate diluted in 90% ethanol

which costs an estimated $1.21 per kg of oleoresin using the manual drilling technique.

These costs could be further reduced by tapping trees using the automated drilling

192

technique as opposed to manually. For commercial production, the most cost-effective

treatment in the southern U.S. is tapping slash pine stands using an automated drilling

machine and applying 400 mM of methyl jasmonate diluted in 90% ethanol.

Chapter 5 also examined the correlations between DBH and short-term oleoresin

yield on long-term production as well as the effects of genetics on short- and long-term

oleoresin flow. To do this, a slash pine clonal site (CCLONES 2) was tapped for short-

term flow and long-term yield using the borehole tapping method. DBH was found to

have a very strong positive correlation to long-term yield but was not correlated to short-

term yield. There was no significant bivariate phenotypic correlation between short-term

yield and long-term oleoresin yield; however, there was a strong positive genetic

correlation between the two phenotypic traits. The interaction between DBH and short-

term yield was a significant predictor of long-term yield. Comparing the average long-

term oleoresin yield between different slash pine families allows us to make selections

for higher gum oleoresin yielding families. In this study one family (521) had significantly

higher yields. Unlike other studies that found broad-sense heritability estimates of

oleoresin between 67 and 90%, this study calculated moderate to low broad-sense

heritabilities of 0.16 for short-term yield, 0.19 for long-term yield, and 0.194 of long-term

yield with covariates (Mergen et al., 1955; Squillace and Doman, 1959; Squillace and

Bengtson, 1961; Squillace, 1965). Nevertheless, it is still possible to make important

genetic gains from selections.

In conclusion, there is potential to reinvigorate oleoresin tapping and collection in

the U.S. Increasing overall productivity of southern pine stands, primarily slash pine,

through intensive management and selective breeding programs, will allow forest

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landowners to increase their stand’s potential oleoresin productivity. Larger diameters

have a positive correlation to oleoresin yields. Slash pine trees should be stimulated

with a chemical inducer, preferably methyl jasmonate diluted in ethanol, to maximize

oleoresin yields.

The effect of soil nutrient availability on oleoresin yield in the southeast U.S.

remain unanswered. Understanding these impacts is important to maximize the

potential oleoresin productivity of a stand to reinvigorate the industry in the U.S. To

establish a commercial operation, it is imperative to identify areas for improvement in

the collection and processing method. Establishing a system to more efficiently collect,

process, and sort through the collection bags will allow for more trees to be sampled

and will decrease cost of labor.

Future studies should investigate the short- and long-term oleoresin flow and

yield in pseudo backcross loblolly and slash pine hybrids. Loblolly pines tend to be more

productive in terms of growth while slash pine is more productive in terms of oleoresin

flow. Since the pseudo backcross hybrids were found to be more growth efficient, they

may also have more productive oleoresin yields. Unfortunately, in this study the pseudo

backcross hybrid site sampled in Appendix 5 fell victim to a wildfire and we were unable

to sample short-term oleoresin flow.

While Squillace and Gansel (1974) found it possible to make growth and

productivity predictions for 25-year-old trees using 10-year-old progeny tests, questions

remain on the age-to-age correlation of oleoresin yield. Understanding age-age

correlations for short-term oleoresin yield in 5-year-old progeny tests to long-term yield

in 15 to 20-year-old stands will be important when making selections. Since the rotation

194

age for slash pine in the southeast U.S. is 20 to 25 years, finding a strong positive age

to age correlation for these oleoresin traits will allow tree breeders to make selections

for high yielding trees at a younger age, accelerating the rates of genetic gain. This will

then allow breeders to make second a third cycle selections to further improve the

oleoresin production in slash pine trees and establish plantations for collection and

timber.

195

APPENDIX A COMPARING OLEORESIN YIELD BY CHEMICAL TREATMENT FOR INDIVIDUAL

SITES DURING THE 2013 TO 2015 TAPPING SEASONS

Table A-1. Summary of oleoresin yields by chemical treatment in Union 1 site during the 2013 tapping season. Stand age is 14 years old.

Chemical Treatment Mean Yield (g) Tukey Group

Control 447.25 B

Ethephon 431.25 B

MeJa 844.49 A

MejaEthephon 923.50 A

Table A-2. Summary of oleoresin yields by chemical treatment in Alachua 1 site during

the 2013 tapping season. Stand age is 16 years old.


Control 392.47 B Ethephon 484.69 B

MeJa 903.46 A





Control 394.01 C

Ethephon 507.53 C

MeJa 1059.01 A

MejaEthephon 762.05 B

Table A-4. Summary of oleoresin yields by chemical treatment in Bradford 1 site during



Control 431.77 C

Ethephon 522.35 C

MeJa 1104.25 A

MejaFeS 703.25 B




Control 495.70 C

Ethephon 757.70 B

MeJa 641.77 B

MejaFeS 902.25 A

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Table A-6. Summary of oleoresin yields by chemical treatment in Union 1 site during



Control 755.44 AB

Ethephon 843.25 A

MeJa 643.25 B

MejaFeS 779.62 AB


the 2014 tapping season. Stand age is 15 years old. This stand was managed for pine straw raking.


Control 605.44 C

Ethephon 919.25 B

MeJa 1347.25 A

MejaFeS 805.44 B




Control 772.06 C

Ethephon 1020.58 AB

MeJa 1089.45 A

MejaFeS 890.42 BC




Control 598.48 B

Ethephon 679.62 B

MeJa 915.50 A

MejaFeS 1079.75 A

Table A-10. Summary of oleoresin yields by chemical treatment in Bradford 1 site

during the 2015 tapping season. Stand age is 12 years old.


Control 289.13 C

Ethephon 411.04 BC

MeJa 490.07 B


197

Table A-11. Summary of oleoresin yields by chemical treatment in Alachua 3 site during the 2015 tapping season. Stand age is 16 years old.


Control 481.71 C

Ethephon 377.89 C

MeJa 1029.74 A





Control 460.00 B

Ethephon 468.08 B

MeJa 668.61 A



the 2015 tapping season. Stand age is 16 years old. This stand was managed for pine straw raking.


Control 363.08 C

Ethephon 671.75 B

MeJa 852.00 A

MejaEthephon 788.13 AB

Table A-14. Summary of oleoresin yields by chemical treatment in Alachua 4 site



Control 513.56 B

Ethephon 563.92 AB

MeJa 383.09 C


Table A-15. Summary of oleoresin yields by chemical treatment in Alachua 5 site



Control 451.92 C

Ethephon 548.70 C

MeJa 1471.77 A


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APPENDIX B

COMPARING OLEORESIN YIELD BY CHEMICAL TREATMENT AND IN TREE INJECTION FOR INDIVIDUAL SITES DURING THE 2014 AND 2015 TAPPING

SEASONS

Table B-1. Summary of oleoresin yields by chemical treatment and in tree injection in Bradford 1 site during the 2014 tapping season. Stand age is 11 years old.


Control 452.00 D

Control/Injection 411.03 D

Ethephon 517.75 CD

Ethephon/Injection 526.83 BCD

MeJa 1075.25 A

Meja/Injection 1133.25 A

MejaFeS 717.50 B

MejaFeS/Injection 689.00 BC

Table B-2. Summary of oleoresin yields by chemical treatment and in tree injection in

Alachua 3 site during the 2014 tapping season. Stand age is 15 years old.


Control 500.75 D


Ethephon 771.88 B

Ethephon/Injection 741.94 BC

MeJa 716.41 BC

Meja/Injection 569.00 CD

MejaFeS 1026.92 A

MejaFeS/Injection 783.66 B


Union 1 site during the 2014 tapping season. Stand age is 15 years old.


Control 841.03 ABC

Control/Injection 672.00 BC

Ethephon 721.75 BC

Ethephon/Injection 964.75 A

MeJa 623.25 C

Meja/Injection 663.25 BC

MejaFeS 673.85 BC

MejaFeS/Injection 885.38 ABC

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Table B-4. Summary of oleoresin yields by chemical treatment and in tree injection in Union 2 site during the 2014 tapping season. Stand age is 15 years old. This stand was managed for pine straw raking.


Control 646.75 C

Control/Injection 563.08 C

Ethephon 845.75 BC

Ethephon/Injection 992.75 B

MeJa 1338.75 A


MejaFeS 839.52 BC

MejaFeS/Injection 766.76 BC




Control 775.94 B

Control/Injection 768.06 B

Ethephon 1064.71 AB

Ethephon/Injection 977.71 AB

MeJa 1143.61 A

Meja/Injection 1036.76 AB

MejaFeS 941.94 AB

MejaFeS/Injection 837.43 AB




Control 657.44 DE

Control/Injection 541.00 E

Ethephon 648.25 DE

Ethephon/Injection 711.79 CDE

MeJa 977.25 ABC

Meja/Injection 853.75 BCD

MejaFeS 1169.74 A

MejaFeS/Injection 992.00 AB

200

Table B-7. Summary of oleoresin yields by chemical treatment and in tree injection in Bradford 1 site during the 2015 tapping season. Stand age is 12 years old.


Control 282.50 D


Ethephon 415.13 CD

Ethephon/Injection 406.84 CD

MeJa 541.62 C



MejaEthephon/Injection 800.61 B

Table B-8. Summary of oleoresin yields by chemical treatment and in tree injection in Alachua 3 site during the 2015 tapping season. Stand age is 16 years old.


Control 474.36 CD

Control/Injection 489.46 CD

Ethephon 378.16 D

Ethephon/Injection 377.63 D

MeJa 1075.90 A



MejaEthephon/Injection 680.00 BC


Union 1 site during the 2015 tapping season. Stand age is 16 years old.


Control 484.05 BCD


Ethephon 456.92 D

Ethephon/Injection 479.23 CD

MeJa 704.75 A

Meja/Injection 631.54 ABCD


MejaEthephon/Injection 664.47 ABC

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Table B-10. Summary of oleoresin yields by chemical treatment and in tree injection in Union 2 site during the 2015 tapping season. Stand age is 16 years old. This stand was managed for pine straw raking.


Control 355.79 C


Ethephon 699.50 AB

Ethephon/Injection 644.00 B

MeJa 842.75 AB

Meja/Injection 861.25 AB


MejaEthephon/Injection 698.00 AB




Control 489.44 BCD

Control/Injection 537.03 ABC

Ethephon 612.31 AB

Ethephon/Injection 516.75 BCD

MeJa 355.37 D



MejaEthephon/Injection 632.31 AB




Control 462.75 C


Ethephon 518.42 C

Ethephon/Injection 578.21 C

MeJa 1564.75 A



MejaEthephon/Injection 949.00 B

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APPENDIX C SLASH PINE OLEORESIN TAPPING OPTIMIZATION TRIALS

Methods

Study Areas

Planted slash pine (Pinus elliottii Engelm. Var. elliottii) stands between the ages

of 15 and 26 were selected from privately owned and managed companies in Alachua

and Union counties. Rayonier and Roberts Land & Timber Investment Corp. provided

the stands selected for this research. Throughout these experimental studies, four

stands were selected. All stands were managed using similar conventional silvicultural

practices including bedding, weed control, and fertilizer treatments. The criteria used to

select stands for tapping included: not easily accessed by the public, sufficient number

of trees available to tap, appropriate age, and appropriate thinning regime. Trees with

signs and symptoms of diseases such as fusiform rust (Cronartium fusiforme), pitch

canker (Fusarium circinatum), bark beetles, and pitch moth were not selected. Trees

with a diameter less than 12.7 cm, dead trees, and those damaged were not selected

for tapping.

Trees in these experimental studies were tapped from 2014 to 2015. The same

thinned 15-year-old slash pine stand in Alachua county was used for most of the

optimization experiments. This slash pine experimental site is located just outside of


from average sea level. An additional thinned 15-year-old slash pine stand in Alachua

County was selected for the 2014 six boreholes and six borehole match experimental

study. This site is also located just outside of Gainesville, Florida (29°43’N latitude and

82°17’W longitude) at an elevation 48 meters from average sea level.

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We compared the yield of oleoresin from a site identified as planted with high

gum trees to a non-high gum stand. These two 26-year-old stands were in Union

county. The 26-year-old non-high gum experimental site is in Lake Butler, Florida

(30°03’N latitude and 82°22’W longitude) at an elevation 41 meters from average sea

level. The stand that did not have the high gum selection was also managed for cattle

grazing, was planted at a lower density, and contained very little understory competition.

The stand with the high gum selection contained more woody and non-woody

understory vegetation.

The climate at all study sites was humid subtropical with hot wet summers and

mild dry winters, and the topography was primarily flat with a 1-2% slope. The soils in

the study sites ranged from poorly drained to moderately well drained. The understory

vegetation varied throughout the different sites. The 26-year-old high gum stand had a

thick understory, while the 26-year-old non-high gum stand had a clear understory. The

two sites in Gainesville, Florida had a mild understory. Understory vegetation included

saw palmetto (Serenoa repens (B.) Small.), blackberries (Rubus L. spp.), bluestems

(Andropogon spp.), gallberry (Ilex glabra (L.)), and greenbriers (Smilax L. spp.).

Borehole Tapping

An automated tapping system was used for one test at the 15-year-old slash pine

experimental site located just outside of Gainesville, Florida. A drilling rig mounted on a

tractor was designed to drill three interconnected boreholes. The two outer holes were

2.54 cm in diameter and were drilled at a slight downward angle towards the central

hole, which was 3.81 cm in diameter and drilled at a slight upward angle (Figure 4-1).

The two-outer hole were sealed with a plastic fitting and the central hole was fitted with

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a 3.175 cm PVC Lasco male adapter fitting and collection bag. This allowed the

oleoresin from the two outer holes to drain into and flow out of the main collection

borehole. The collection bags were left in the field for about 90 days until weighed.

Four additional borehole tapping designs that altered the intensity or volume of

wood tapped were investigated using the manual drilling (Figure C-1, Table C-1). The

big-small design followed the 2-borehole tapping design apart from being drilled only

5.08 cm deep; inside the main tapping hole, a 0.9525 cm drill bit was used to drill a

15.24 cm deep hole. The opposing side design used an identical method to our

standard two-holes but instead of parallel holes on the same side of the tree, the holes

were placed on opposite sides of the tree. The three-borehole design had one central

hole that was 3.81 cm in diameter and two inner holes drilled on each side of the central

hole was also tested with the control treatment only having the central hole. The fourth

design involved drilling 6 or 8 holes that were each 5.08 cm deep and placed around the

tree at two levels (6 borehole test and 8 borehole test). The upper level was 10 cm

higher than the lower one which was near the base of the tree as our standard design.

The holes were also placed at an equal distance from each other. In these experiments,

the chemical stimulant was applied as described in Chapter 3 and a collection bag was

attached.

Chemical Stimulants

2014 tapping season

For the automated drilling test, 2 ml of methyl jasmonate and a combination of

methyl jasmonate with ethephon were applied to all three connected boreholes. For the

high gum versus non-high gum test, for each site, the 2 ml of chemical stimulants,

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methyl jasmonate, ethephon, methyl jasmonate combined with ethephon, and a control

treatment were applied, and the standard two-parallel borehole technique drilled 10.16

cm deep was used. For the opposing side test a different chemical stimulant, paraquat,

was tested and applied to the boreholes along with the methyl jasmonate chemical used

previously. As discussed in Chapter 2, paraquat (C12H14N2C +2; 1,1’-Dimethyl-4,4’-

bipyridinium dichloride) is a photosynthesis inhibiting herbicide which induces the

formation of lightwood and in turn stimulates production of oleoresin (Stubbs et al. 1984

and Silverman et al. 2005). In addition to the new stimulant, a new application method

was also tested. For a subset of the trees, the stimulant was applied by spraying into

the borehole, while for others, the stimulant was applied in the form of a paste. Lanolin

was used as the carrier for the chemical stimulants in the pastes. There were five

chemical treatments and one control treatment for this test. The chemical treatments

are as followed: methyl jasmonate, paraquat, methyl jasmonate paste, methyl

jasmonate and paraquat, methyl jasmonate and paraquat paste.

For the test with 8 boreholes per tree, methyl jasmonate and ethephon were

used as chemical stimulants, and there was also a control treatment. For the test with 6

boreholes per tree, methyl jasmonate was the only chemical stimulant tested; forty trees

were drilled with 6 holes while forty were drilled with 2 boreholes 10.16 cm in depth. The

6 and 8 boreholes test received 1 mL of stimulant per borehole, while the 2 boreholes

test received 2 mL per borehole.

2015 tapping season

In 2015 the triple borehole test had one main and two inner side holes, methyl

jasmonate was the only chemical stimulant tested and each hole was sprayed with

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approximately 2 ml of stimulant. For the big-small test, methyl jasmonate, ethephon,

methyl jasmonate combined with ethephon, and a control treatment were applied. In

2015 an experiment with 8 boreholes per tree, tested methyl jasmonate, ethephon,

methyl jasmonate combined with ethephon and a control treatment were applied at 1

mL dose per borehole.

Data Collection

The same data collection methods discussed in Chapter 3 were used for the

experiments in Appendix C. In addition, for the 2014 8 borehole test, all the collection

bags were weighed every 7 days for the first 32 days prior to final collection.


The chemical inducer treatments for each experimental test were randomized

prior to visiting the field and each treatment was assigned to 40 trees. A one-way

analysis of variance (ANOVA) was used to compare the mean oleoresin yield across

treatments (chemical and borehole number) using the JMP software from SAS (SAS

Institute, 2016). Tukey’s studentized range (HSD) test was used to test for significant

differences among means at an alpha level of 0.05.

To assess the individual and interactive effects of site, chemical inducers, DBH,

height, and crown volume on oleoresin yield, a general linear model was fitted for each

experiment using R 3.1.1 and ASReml-R v.3 (R Development Core Team, 2016;

Gilmour et al., 2015). The models differed among experiments depending on significant

and measured variables and were fitted with covariates. The general model fitted was:

Y = µ + C + D + H + CV + Interactive Effects + e


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where, µ is the overall mean; C is the fixed effect of chemical inducer; D is the fixed

effect of DBH; H is the fixed effect of height; CV is the fixed effect of crown volume;

fixed interaction effects; and e is the random error.

The General Linear Model (GLM) approach was used to analyze the main and

interactive effects as well as perform analysis of variance for the 26-year old high gum

and non-high gum trees tapped. The following model was fitted:

Y = µ + C + D + S + S:C + S:D + C:D + S:C:D + e

where, µ is the overall mean; C is the fixed effect of chemical inducer; D is the fixed

effect of DBH; S is the fixed effect of site; S:C is the fixed interactive effect of site and

chemical; S:D is the fixed interactive effect of site and DBH; C:D is the fixed interactive

effect of chemical and DBH; S:C:D is the fixed interactive effect of site, chemical, and

DBH; and e is the random error.

For the big-small test, the General Linear Model (GLM) approach was used to

analyze the main effects and their interactions using a 2.54 cm drill bit to bore a 5.08 cm

deep hole and a 0.9525 cm drill bit to drill a 15.24 cm deep hole and those taped using

the standard method. The following model was fitted:

Y = µ + T + C + D + H + CV + T:C + T:D + T:CV + T:H + C:D + C:CV + C:H

+ D:CV + D:H + H:CV + e

where, µ is the overall mean; T is the fixed effect of tapping method; C is the fixed effect

of chemical inducer; D is the fixed effect of DBH; H is the fixed effect of tree height; CV

is the fixed effect of crown volume; T:C is the fixed interactive effect of tapping method

and chemical inducer; T:D is the fixed interactive effect of tapping method and DBH;

T:CV is the fixed interactive effect of tapping method and crown volume; T:H is the fixed

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interactive effect of tapping method and tree height; C:D is the fixed interactive effect of

chemical and DBH; C:CV is the fixed interactive effect of chemical and crown volume;

C:H is the fixed interactive effect of chemical and tree height; D:CV is the fixed

interactive effect of DBH and crown volume; D:H is the fixed interactive effect of DBH

and tree height; H:CV is the fixed interactive effect of tree height and crown volume; and

e is the random error.

The oleoresin yields per unit area tapped in the six and eight borehole

experiments were calculated from the cross-sectional area of the individual borehole as

well as the estimated sector-shaped tapping area of the tree stem. The cross-sectional

area of the borehole was estimated as a polygon with sides a-b-c-d (Figure C-2). The

tapping area was considered as the area in which there was access to resin canals from

the borehole tapped. The projected area was estimated from the extremities of the

borehole and the center of the tapped tree (Figure C-2). As in Chapter 3, the areas were

estimated using trigonometric formulas for the area of a triangle and the predicted

stump diameter was calculated using the taper equation developed by Bailey (1994) for

slash pine trees. To estimate the outer bark stump diameter in cm for slash pine trees

the equation used was:

Db = D (137.16

hb

)

β

Where Db is the stump diameter, D is the DBH calculated at breast height (1.3716

meters or 137.16 cm), hb is the height of the stump which is equal to the height of

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borehole (assumed to be 15.24 cm for all tapped trees), and β is the constant parameter

for slash pine trees (0.094138) based on a fitted equation (Bailey, 1994).

The following are the formulas used to calculate the angles to determine the area

in cm2 of the projected triangle (c-x-y) or tapping area in in the six and eight boreholes

experiment (Figure C-2):

<β = sin-1 bw/2

r-bd

<α = <β × 2

Tapped Sector Area cm2 = α

360 × r2× π

Where r is the radius calculated from the estimated stump diameter, bd is the depth of

the borehole (5.08 cm for all tapped trees) and bw is the width of the borehole (2.54 cm

for all tapped trees). For the six borehole experiment, tapped sector area was multiplied

by six to calculate the total tree tapped area and for the eight borehole experiment it

was multiplied by eight. The tapping intensity for the trees tapped with two boreholes in

the six borehole experiment was calculated using the tapping area modeled in Chapter

3 for trees greater than 10.16 cm in diameter (Figure 3-1).

The following formulas were used to calculate the tapping intensity (Figure C-2):

Tree Basal Area cm2 = (0.00007854 × d2) × 10000

Tree Tapping Intensity (%) = Tapped Sector Area

Tree Basal Area× 10000

During the 2014 8 borehole experiment, the mass of the oleoresin collection bags

was recorded at day 7, 16, 24, 30, and 99. To examine the cumulative flow of oleoresin

during a tapping season, a nonlinear regression model was fitted for each chemical

stimulant using the JMP software from SAS (SAS Institute, 2016). Furthermore, the

210

predicted cumulative flow of oleoresin over time during a 99-day tapping season was

estimated using the regression model and graphed.

Results

High Gum Yielding Slash Pine

The main effect of chemical treatment and DBH were significant. Comparison of

oleoresin yield between trees reported to be high gum and non-high gum matched in

age were on the threshold of being significantly different (p-value 0.051) (Table C-2;

Table C-3), although the non-high gum yielded more oleoresin. Chemical stimulant was

the most effective (p-value <0.000) at predicting the yield of oleoresin (Table C-3). DBH

was also a significant predictor of oleoresin yield in these stands (p-value 0.003) (Table

C-3). The site by chemical treatment interaction was the only significant interaction (p-

value 0.025) (Table C-3).

Across both sites, the trees treated with methyl jasmonate, whether alone or

combined with ethephon, yielded significantly more compared to those treated with

ethephon or no chemical stimulant (Table C-2). Methyl jasmonate was more effective

alone at stimulating oleoresin yield at both sites, yielding at least 0.24 kg more

compared to the combination treatment, though not significantly different (Table C-2). At

both sites, control and ethephon treatments were not significantly different (Table C-2).

The control (C) and ethephon (E) treatments performed better in the high gum stand (C:

1.258 kg vs. 1.027 kg; E: 1.262 kg vs. 1.188 kg) (Table C-2). The methyl jasmonate (M)

and methyl jasmonate combined with ethephon (ME) treatments performed better at the

non-high gum site (M: 2.405 kg vs. 2.087 kg; ME: 2.124 kg vs. 1.847 kg) (Table C-2).

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Big-Small

The methyl jasmonate treatments significantly increased oleoresin yield, almost

double, compared to control and ethephon treatments (Table C-4). The trees treated

with the methyl jasmonate stimulant yielded about 0.22 kg more oleoresin compared to

the methyl jasmonate and ethephon combination treatment (Table C-4). In this

experiment, ethephon was not an effective stimulant and did not yield significantly more

oleoresin than the control treatment (Table C-4). There were no significant differences

among the DBH, height, and crown volume of the trees tapped between the different

chemical treatments (Table C-4).

A comparative test was also established at the same site to measure the yield of

oleoresin with the control, ethephon, methyl jasmonate, and methyl jasmonate

combined with ethephon treatments using the standard borehole tapping method. With

the standard borehole method, control and ethephon stimulants gave the same yield

(Figure C-3). The control treatment yielded 0.47 kg with the standard borehole method

and 0.54 kg with the big-small method (Figure C-3). The ethephon treatment yielded

0.39 kg with the standard borehole method and 0.55 kg with the big-small method

(Figure C-3). Further, methyl jasmonate treatment yielded about the same as the

methyl jasmonate and ethephon combination; with methyl jasmonate yielding 1.08 kg

using the standard tapping method, 1.30 kg using the big-small tapping method, and the

combination treatment yielding 0.86 kg and 1.08 kg, respectively, for the standard and

big-small methods of tapping (Figure C-3). The methyl jasmonate and ethephon

combination treatment yielded significantly less oleoresin compared to the methyl

jasmonate treatments, though it was more effective of a stimulant compared to

212

ethephon alone (Figure C-3). Using the big-small method, methyl jasmonate yielded

significantly more oleoresin compared to all other treatments (Figure C-3). Overall, the

big-small tapping method was more effective across all chemical treatments compared

to the standard method (Figure C-3).

The main effects of tapping method, chemical treatment, DBH, and height were

strongly significant (p-value <0.000, <0.000, <0.000 and 0.041, respectively) (Table C-

5). No interactive effects were significant (Table C-5).

Triple Borehole Test

The triple borehole method, using one main exit hole and two smaller inner

holes, was a significantly more effective tapping technique when compared to the single

borehole method (Table C-6). The trees tapped using the triple borehole method yielded

on average 1.341 kg of oleoresin, while the trees tapped using the single borehole

method yielded 0.758 kg of oleoresin (Table C-6).

Opposing Side

The trees treated with methyl jasmonate alone or combined with paraquat,

diluted in a lanolin paste or diluted in DI water and Tween 20, yielded significantly more

compared to those treated with paraquat or no chemical stimulant (Table C-7). Methyl

jasmonate, applied as a paste and as a liquid, was also more effective alone at

stimulating oleoresin yield, yielding at least 0.113 kg more compared to the other

chemical treatments (Table C-7). The methyl jasmonate and paraquat combination

stimulant, applied as a paste and as a liquid, yielded the same as the control treatment

and the paraquat stimulant (Table C-7). There were no significant differences found in

oleoresin yield between chemical stimulants applied as a paste compared to those

213

applied as a liquid. The 15-year-old trees treated with methyl jasmonate using the

opposing site method yielded on average 0.757 kg, while the 14 and 16-year-old trees

treated with methyl jasmonate using the standard method yielded on average 0.894 and

0.903 kg, respectively (Table C-7; Table A-1; Table A-2). Furthermore, oleoresin was

collected for 96 days using the opposing side method and 73 and 85 days using the

standard method.

Automated Drilling

When tapped using the automated drilling technique which introduces three

interconnected holes, methyl jasmonate combined with ethephon (ME) was significantly

more effective at stimulating oleoresin yield compared to methyl jasmonate (M) alone

(Table C-8; Figure C-4). These results differ from those for many of the other manually

drilled tapping techniques tested and discussed, as methyl jasmonate tended to be

more effective as a chemical stimulant when applied alone. In the automated trial, the

ME treatment yielded around 0.4 kg more oleoresin (Figure C-4). When conducting the

field experiment, the automated drilling machine malfunctioned and some trees were

only tapped with two boreholes instead of three (the central hole and the left hole).

However, this only affected the ME treatments. The number of boreholes, whether 2 or

3, did not have a significant effect on the yield of oleoresin for the ME treatment, with

the 3 boreholes yielding only about 0.02 kg more oleoresin (Table C-8). The positive

effect of combining ethephon with methyl jasmonate as a stimulant is highlighted by the

fact that the trees drilled with 2 boreholes yielded significantly more oleoresin than the

trees drilled with 3 boreholes and stimulated by methyl jasmonate only (Table C-8).

214

Multi-Borehole Tests

We tested two methods which consisted of drilling 6 and 8 boreholes around the

base of the stem, with three or four at two different heights. In 2014, 40 trees at one site

were drilled with 6 boreholes and 40 were drilled with two boreholes; all trees were

stimulated with methyl jasmonate. Overall, the trees tapped with 6 boreholes yielded

significantly more oleoresin compared to those tapped with only 2 boreholes (2

boreholes: 0.946 kg; 6 boreholes: 1.526 kg) (Table C-9). However, when considering

the yield per borehole, the two-borehole treatment had a significantly higher, almost

double, yield compared to the 6-hole treatment (0.473 kg vs. 0.254 kg) (Table C-9).

In 2014, a similar experiment was tested at the same stand in which trees were

drilled with 8 boreholes at the base of the stem and 3 chemical stimulants were tested.

When tapped using this drilling technique, methyl jasmonate was significantly more

effective at stimulating oleoresin yields compared to the control and ethephon

treatments (Table C-10). The ethephon treatment was not an effective stimulant as it did

not result in significantly higher yields compared to the control treatment (Table C-10).

The bags in this experiment were weighed at days 7, 16, 24, 30 and once again at the

end of the tapping season on day 99. This information was used to plot the predicted

cumulative resin yields throughout the growing season. A nonlinear regression was

used to model the average yield per day with the different chemical stimulants and the

8-borehole tapping method (Figure C-5). The non-linear equations for the obtained

prediction model are shown in Figure C-5. All three regression models were effective at

explaining the observed variations (control and ethephon r2 = 0.98; methyl jasmonate r2

= 0.99) (Figure C-5). The treatments did not appear to have reached their full oleoresin

215

capacity at the time of collection, which suggests tapping season should be more than

100 days when 8 holes are used (Figure C-5).

In 2015, another 8-borehole test was established where trees were stimulated

with 4 different chemical treatments. Methyl jasmonate was significantly more effective

at stimulating the flow and yield of oleoresin compared to the control, ethephon, and

methyl jasmonate combined with ethephon treatments (Table C-11). The methyl

jasmonate treatments yielded close to double the quantity of oleoresin compared to the

control and ethephon treatments (Table C-11). The trees treated with the methyl

jasmonate stimulant yielded on average 0.70 kg more oleoresin compared to the methyl

jasmonate and ethephon combination treatments (Table C-11). In this experiment,

ethephon and the methyl jasmonate/ethephon combination treatment were not effective

stimulants and did not yield significantly more oleoresin compared to the control

treatment (Table C-11). There were no significant differences among the DBH, height,

and crown volume of the trees tapped between the different chemical treatments (Table

C-11).

Tapping Intensity

The tapping intensity for tree treated with methyl jasmonate and tapped using the

2, 6 and 8 borehole methods was calculated based on the tree basal area and the area

of the sector tapped. The linear relationship between the tapping intensity and total tree

oleoresin yield (kg) for the six and eight boreholes was modeled and has a slope of –

0.0304 [Yield = 2.767 – 0.0304(Tapping Intensity), r2 = 0.148; p-value = 0.0022] (Figure

C-6). The overall oleoresin yield decreased as the tapping intensity increased (Figure C-

6). As expected, the tapping intensity of the trees tapped with eight boreholes was

216

significantly higher than the trees tapped with six boreholes (Table C-12). Furthermore,

the tapping intensity of trees tapped with two boreholes was significantly less than trees

tapped with six and eight boreholes (Table C-12). The oleoresin yields between the six

and eight boreholes were the same (1.53 kg and 1.71 kg, respectively), and were

significantly higher than yields from the two-borehole method (0.95 kg) (Table C-12).

Since the oleoresin yield for the two borehole tapping method clustered

separately, the oleoresin yield by tapping intensity was modeled only for the six and

eight borehole methods. As observed in Chapter 3 and in Hodges (1995), the oleoresin

yield was higher as tapping intensity increased. However, with the trees tapped with two

boreholes, the yields per tapping area were not as high as the trees tapped with multiple

boreholes, even with the lower tapping intensities.

Table C-13 summarizes the average total tree oleoresin yield from each

optimization experiment

Discussion

The stand recorded to have high gum yielding slash pine trees did not on

average yield more oleoresin compared to the non-high gum match site. When

comparing the chemical stimulants at two sites, the control and ethephon treatments

yielded more oleoresin in the high gum site, while methyl jasmonate and methyl

jasmonate and ethephon combination treatments yielded more in the non-high gum site.

The results may be due to various other factors that were not tested in this study, such

as water availability, stand density management, soil resources, understory competition

and fertilization. As discussed in Chapter 2, these factors influence the production of

oleoresin in conifers. Furthermore, the sites were managed very differently. The non-

217

high gum match site is managed by a landowner that also raises cattle on the property,

leases the area for pine straw collection and actively maintains a clear understory.

However, the high gum site is not being actively managed for understory competition.

The management of understory competition may lead to overall increases in tree

productivity and growth due to the increase availability of nutrients and water. This in

turn may have a positive effect on the tree’s ability to produce more oleoresin when

wounded and treated with a chemical stimulant. Age also had a positive significant

effect on the yield of oleoresin since the average yields of resin from the 26-year-old

sites were higher than the average yields of resin from all the other 15-year-old tests.

The opposing sides experiment tested the effects of another type of stimulant

(paraquat) and a different application method (a lanolin paste) as used in other studies

(Rodrigues et al., 2008; Rodrigues and Fett-Neto, 2009; Rodrigues et al., 2011). The

lanolin paste stimulants, which were slightly more time consuming to apply, did not yield

significantly different yields of oleoresin. This suggests it would be more efficient to

continue using a liquid stimulant when tapping pine trees for oleoresin using the

borehole tapping method. The methyl jasmonate was once again more effective at

stimulating the production of oleoresin. When comparing the oleoresin yields using this

tapping method to the yields obtained drilling two parallel holes, this method is not

effective.

When a small hole was drilled deeper into the wood in the big-small method,

methyl jasmonate stimulation nearly doubled oleoresin yield compared to trees treated

with ethephon and yielded more oleoresin compared to the methyl jasmonate and

ethephon combination treatment. This once again suggests that methyl jasmonate is a

218

more effective chemical stimulant for increasing oleoresin production in younger slash

pine trees in the southeast U.S. Across all chemical treatments, the big-small tapping

method produced significantly more oleoresin compared to the standard borehole

method. This suggests that having a small diameter hole drilled further into the stem

allows for better access of stimulant deeper in the xylem and potentially increases the

number of radial resin canals and terpene synthesis thus increasing the potential yield

of oleoresin.

Drilling two boreholes inside of the single exit hole (triple borehole method) was

significantly more effective than drilling simply a single borehole. This may be due to the

access of more resin canals from tapping extra boreholes combined with better

stimulation. The method of drilling 3 holes within a single exit hole does not take much

more time and does not use more supplies and thus is almost as cost effective.

Establishing an automated drilling equipment to tap pine trees for oleoresin

should create a more efficient method for commercial operation. Though there were

some technical issues when tapping a stand using the automated tractor operated

drilling rig, a lot more trees are tapped in a shorter time increasing labor efficiency.

Since the automated system drills the three boreholes into the tree, it decreases the

labor intensiveness of the operation and reduces the fatigue of labor workers because

they do not have to manually drill each borehole. In this study, the methyl jasmonate

and ethephon combination treatment yielded significantly more oleoresin than the

methyl jasmonate treatment. It is unclear why the combination was significantly better,

when methyl jasmonate alone was better in all the other manually drilled experiments.

219

Tapping slash pine trees with numerous (six and eight) but shallower boreholes

did not result in oleoresin yields convincingly high enough to justify using this more time-

consuming tapping method. When comparing the yields of the standard borehole

tapping method that was stimulated by methyl jasmonate diluted in 90% ethanol and

collected after 97 days with the yields of the 8-borehole tapping method that was

stimulated by methyl jasmonate diluted with Tween 20 and DI water and collected after

103 days, we see that the yields are not that much higher for the multi borehole test. In

that case, the chemical stimulant has a greater effect on the yield of oleoresin. With the

standard borehole tapping method, we manually drilled two holes into about 300 trees

per day, but with the 8-borehole method only about 80 trees per day. Thus, tapping

more trees per stand per season with similar number of hours would yield more

oleoresin compared to the 8-borehole method because we would be able to tap more

trees within a season. Using an automated system with the 8-borehole method would

also be more complicated as it would be more difficult for a tractor operated system to

navigate around each tree in the pine plantation. When considering the yield per

borehole, the two-borehole treatment had almost double the oleoresin yield compared

to the 6-hole treatment. This makes sense since each borehole in the 2-borehole

treatment were drilled at double the depth of the 6-borehole treatment. Tapping more

than two boreholes in a tree can be beneficial and lead to increase oleoresin yield per

tree, however, it is important to consider the cost effectiveness of these tapping

methods.

The nonlinear regressions from the 2014 8-borehole tapping treatment showed

the importance of the first 30 days of tapping as about 75% of the potential oleoresin

220

yield was collected during that time. This regression also made the case for a more

extended tapping season as the full oleoresin capacity did not appear to have been

reached at 100 days.

Table C-14 shows a cost-comparison of the automated drilling method and the

manual drilling method. Based on the oleoresin yields obtained from the methyl

jasmonate and ethephon combination treatment in the Alachua 3 site manual drilling

method (Chapter 3) and the Alachua 3 site automated drilling experiment, the most

cost-effective tapping method is the automated technique. Average oleoresin yield of

trees treated with 100 mM of methyl jasmonate combined with ethephon tapped with the

manual drilling technique was 0.86 kg (Table B-8). The estimated cost per tree of 100

mM methyl jasmonate and ethephon is $0.328, which would make for a total cost of

$3.00 per kg of oleoresin (Table C-14). Average oleoresin yield of trees treated with 100

mM of methyl jasmonate combined with ethephon and tapped with the automated

drilling technique was 1.48 kg (Figure C-4). The estimated cost per tree for the

automated technique of 100 mM methyl jasmonate and ethephon is $0.493, which

would make for a total cost of $1.29 per kg of oleoresin (Table C-14).

221

Table C-1. Summary of oleoresin tapping optimization experiments for slash pine in 2014-2016.

Year

Site Location Soil Series Site Index

Experiment Stand Age

(Years)

Number Chemical Inducers

Number Trees

Number Boreholes

2014 Gainesville, FL Ponoma Sand 84 Automated Drilling 15 2 542 3 2014 Worthington

Springs, FL NA NA High Gum 26 4 160 2

2014 Lake Butler, FL Sapello Sand NA Non-High Gum 26 4 160 2 2014 Gainesville, FL Ponoma Sand 84 Opposing Side 15 6 240 2 2014 Gainesville, FL Ponoma Sand 84 2014 8 Borehole 15 3 120 8 2014 Gainesville, FL Ponoma Sand 84 2014 6 Borehole 15 1 80 6 2014 Gainesville, FL Ponoma Sand 84 2014 6 Borehole Match 15 1 40 2 2015 Gainesville, FL Ponoma Sand 84 Multiple Borehole 16 1 87 3 2015 Gainesville, FL Ponoma Sand 84 Big-Small 16 4 160 2 2015 Gainesville, FL Ponoma Sand 84 2015 8 Borehole 16 4 160 8

222

Table C-2. Chemical treatment and improved genetic effects on average oleoresin yield per tree (kg) from slash pine trees using the standard borehole tapping method in 2014.

Chemical Treatment Genetically Improved Not Genetically Improved (High Gum)

Control (no chemical) 1.258b 1.027b

Ethephon 1.262b 1.188b

Methyl Jasmonate 2.087a 2.405a

Methyl Jasmonate/Ethephon 1.847a 2.124a


223

Table C-3. Summary of main and interactive effect on oleoresin yields in high gum and non-high gum site based on a general linear model.


Chemical 3 296 41.87 <0.000**

DBH 1 296 6.43 0.003*

Site 1 296 3.61 0.051

Site:Treatment 3 296 2.35 0.025*

Site:DBH 1 296 0.62 0.346

Treatment:DBH 3 296 1.18 0.319

Site:Treatment:DBH 3 296 0.34 0.795


224

Table C-4. DBH, height, crown volume, and effect of chemical stimulant on oleoresin yield (kg) when tapping slash pine trees in 2015 using the big-small borehole tapping method.

Chemical Treatment DBH(cm) Tree Height (m) Crown Volume (m3) Oleoresin Yield (kg)

Average SE Average SE Average SE Average SE Control (no chemcial) 22.66a 0.26 20.32a 0.21 47.77a 3.60 0.530b 0.05

Ethephon 22.44 a 0.21 20.02a 0.20 47.48a 3.40 0.550b 0.04 MeJa 22.52 a 0.23 19.99a 0.22 49.12a 4.06 1.303a 0.08

MeJaE 22.59a 0.27 20.01a 0.23 45.35a 3.43 1.084a 0.08

Note: The means with different letter superscripts were significantly different based on Tukey’s HSD test (p-value <0.05). The notations MeJa and MeJaE, respectively represent the chemical treatments methyl jasmonate and methyl jasmonate combined with ethephon.

225

Table C-5. Summary of main and interactive effect on oleoresin yields in site drilled using the big-small borehole tapping method based on a general linear model.


Treatment 1 285 18.94 <0.000**

Chemical 3 285 82.56 <0.000**

DBH 1 285 30.59 <0.000**

Height 1 285 4.83 0.041*

Crown Volume 1 285 13.67 0.65

Treatment:DBH 1 285 7.90 0.07

Treatment:Chemical 3 285 1.54 0.15

Treatment:Crown Volume 1 285 0.37 0.36

Treatment:Height 1 285 0.23 0.84

Chemical:DBH 3 285 1.96 0.11

Chemical:Crown Volume 3 285 0.41 0.58

Chemical:Height 3 285 1.57 0.18

DBH:Crown Volume 1 285 0.01 0.59

DBH:Height 1 285 0.39 0.89

Height:Crown Volume 1 285 0.80 0.37


226

Table C-6. Effects of tapping treatment, DBH, height and crown volume on oleoresin yield (kg) when tapping slash pine trees in 2015 using the triple borehole (two inner holes) tapping method and stimulated by methyl jasmonate.

Treatment DBH(cm) Tree Height (m) Crown Volume (m3) Oleoresin Yield (kg)

Average SE Average SE Average SE Average SE One Borehole 23.95a 0.46 19.98a 0.22 59.99a 3.97 0.758b 0.05

Triple Borehole 24.19a 0.35 20.00a 0.22 68.96a 5.17 1.341a 0.07


227

Table C-7. Effects of chemical stimulant and DBH on oleoresin yield (kg) when tapping slash pine trees in 2014 using the opposing side borehole tapping method. The following were the chemical stimulants: control, methyl jasmonate (MeJa). methyl jasmonate and paraquat (MeJaP), methyl jasmonate and paraquat paste (MeJaPPs), methyl jasmonate paste (MeJaPs), and paraquat.

Chemical Treatment DBH(cm) Oleoresin Yield (kg)

Average SE Average SE Control (no chemical) 21.667a 0.56 0.527b 0.04

MeJa 21.642a 0.61 0.757a 0.06 MeJaP 21.156a 0.51 0.641ab 0.05

MeJaPPs 20.770a 0.48 0.621ab 0.05 MeJaPs 21.899a 0.45 0.754a 0.05 Paraquat 20.723a 0.45 0.519b 0.04


228

Table C-8. Effects of chemical stimulant and number of boreholes on oleoresin yield (kg) when tapping slash pine trees in 2014 using the automated borehole tapping method.

Holes

2 3

Chemical Treatment Average SE Average SE MeJa NA NA 1.061b 0.03

MeJaE 1.475a 0.05 1.493a 0.04


229

Table C-9. Effects of chemical stimulant and DBH on total oleoresin yield (kg) and oleoresin yield per borehole (kg) when tapping slash pine trees in 2014 using the 6 borehole and standard borehole tapping method.

Treatment DBH(cm) Oleoresin Yield (kg) Oleoresin Yield per Borehole (kg)

Average SE Average SE Average SE Two Boreholes 20.619a 0.36 0.946b 0.10 0.473a 0.02 Six Boreholes 19.958a 0.25 1.526a 0.07 0.254b 0.02


230

Table C-10. Effects of chemical stimulant on oleoresin yield (kg) when tapping slash pine trees in 2014 using the 8-borehole tapping method.

Chemical Treatment Oleoresin Yield (kg)

Average SE Control (no chemical) 0.770b 0.06

Ethephon 0.808b 0.06 Methyl Jasmonate 1.071a 0.06


231

Table C-11. Effects of chemical stimulant, DBH, height and crown volume on oleoresin yield (kg) when tapping slash pine trees in 2015 using the 8-borehole tapping method.

Treatment DBH(cm) Tree Height (m) Crown Volume (m3) Oleoresin Yield (kg)

Average SE Average SE Average SE Average SE Control (no chemcial) 21.520a 0.43 19.318a 0.23 42.981a 4.20 0.906b 0.09

Ethephon 22.332a 0.43 19.503a 0.23 48.653a 4.26 0.848b 0.09 MeJa 21.980a 0.43 19.929a 0.23 44.598a 4.20 1.708a 0.09

MeJaE 21.283a 0.43 19.670a 0.23 41.079a 4.20 1.005b 0.09


232

Table C-12. Effects of number of boreholes on tapping intensity and oleoresin yield (kg) when tapping slash pine trees using the 6 and 8 borehole taping method.

Number of Boreholes Tapping Intensity Oleoresin Yield (kg)

Average SE Average SE

Two 11.066c 0.32 0.945b 0.07

Six 35.052b 0.72 1.526a 0.08

Eight 40.152a 1.26 1.708a 0.13

Note: The means with different letter superscripts were significantly different based on Tukey’s HSD test (p-value <0.05). Tapping intensity is calculated based on the cross-sectional area tapped at the base of the tree. The model for the 6-borehole method is shown in Figure C-2 and the model for the 2-borehole method is shown in Figure 3-1.

233

Table C-13. Summary of optimization treatments, number of boreholes, collection days, chemical inducers and oleoresin yields.

Experiment Stand Age

Number of Boreholes

Collection Days

Chemical Mean Oleoresin

Yield (kg)

Automated Drilling

15 3 155 MeJa 1.061

15 3 155 MeJaE 1.493

15 2 155 MeJaE 1.475

High Gum

26 2 176 Control 1.258

26 2 176 Ethephon 1.262

26 2 176 MeJa 2.087

26 2 176 MeJaE 1.847

Non-High Gum

26 2 176 Control 1.027

26 2 176 Ethephon 1.188

26 2 176 MeJa 2.405

26 2 176 MeJaE 2.124

Opposing Side

15 2 96 Control 0.527

15 2 96 MeJa 0.757

15 2 96 MeJaP 0.641

15 2 96 MeJaPPs 0.621

15 2 96 MeJaPs 0.754

15 2 96 Paraquat 0.519

2014 8 Borehole

15 8 99 Control 0.77

15 8 99 Ethephon 0.808

15 8 99 MeJa 1.071

2014 6 Borehole

15 6 167 MeJa 1.129

15 6 169 MeJa 1.944

15 6 172 MeJa 1.723

15 6 174 MeJa 1.848

2014 6 Boreholes Match

15 2 178 MeJa 0.946

3 Hole Test 16 1 120 MeJa 0.758

16 3 120 MeJa 1.341

Big-Small

16 2 94 Control 0.529

16 2 94 Ethephon 0.55

16 2 94 MeJa 1.303

16 2 94 MeJaE 1.084

2015 8 Borehole

16 8 103 Control 0.906

16 8 103 Ethephon 0.848

16 8 103 MeJa 1.708

16 8 103 MeJaE 1.005

Alcohol 16 2 97 Alcohol 1.507

16 2 97 Tween 0.936

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Table C-14. Estimated cost per tree of borehole tapping method to collect oleoresin. Calculated costs are based on

productivity rates of tapping 26.7 trees per hour for the manual drilling and 61 trees per hour for the automated drilling. Adapted from Hodges and Ferguson (2011).

Manual Drilling Automated Drilling

Cost Category / Item Quantity per tree

Units Unit Price

Cost per Tree

Quantity per tree

Units Unit Price Cost per

Tree

Supplies

Spouts: 1 x 5 in. PVC pipe, or custom molded PE

2 Ea. $0.150 $0.300 1 Ea. $0.150 $0.150

Collection bags, Nylon/PE laminate, 6x20 in.

2 Ea. $0.090 $0.180 1 Ea. $0.090 $0.090

Cable ties for bag closure 2 Ea. $0.010 $0.020 1 Ea. $0.010 $0.010 Plugs for machine-drilled boreholes 2 Ea. $0.037 $0.073 Ethephon, 55% active ingredient 2 Dose $0.026 $0.052 3 Dose $0.026 $0.079 Methyl jasmonate – 100 mM 2 Dose $0.138 $0.276 3 Dose $0.138 $0.414 Distilled water 2 Dose $0.001 $0.002 3 Dose $0.001 $0.002 Diesel fuel for drill machine and utility vehicle

0.050 Gal. $3.00 $0.150 0.075 Gal. $3.50 $0.263

Gasoline and oil for power drill 0.004 Gal. $4.50 $0.019

Subtotal supplies $1.00 $1.081

Labor

Borehole Treatment/Installation (3-man crew, average productivity rate)

0.163 Hr. $8.50 $1.388 0.050 Hr. $8.50 $0.422

Oleoresin harvesting (3-man crew, average productivity)

0.017 Hr. $8.50 $0.143 0.017 Hr. $8.50 $0.143

Subtotal labor $1.530 $0.565

Note: Equipment costs depreciated over useful life of 250,000 trees; does not include highway transportation equipment. The cost of 1 kg of methyl jasmonate from Bedoukian Research is $3080.

235

Table C-14. Continued. Manual Drilling Automated Drilling

Equipment Quantity

per crew

Unit Price

Total Cost

Cost per Tree

Quantity per

crew

Unit Price

Total Cost Cost per

Tree

Off-road utility vehicle (Kubota RTV900XT)

1 $10,000 $10,000 $0.040 1 $10,000 $10,000 $0.040

Automated drilling machine and prime mover (Volvo L20F)

0 1 $55,000 $55,000 $0.220

Power drill (Sthil BT45) 2 $450 $900 $0.004 0

Drill bits: 2.54 cm 3 $25 $75 $0.000 6 $25 $150 $0.001 Chemical sprayer 2 $100 $200 $0.001 2 $100 $200 $0.001 Small tools: mallet, machete, pliers, measuring cup

4 $50 $200 $0.001 4 $50 $200 $0.001

Rubber gloves (for chemical mixing and resin handling)

100 $3 $300 $0.001 100 $3 $300 $0.001

Fuel can: 2 gal. 2 $15 $30 $0.000 0

Fuel cans: 15 gal. 2 $40 $80 $0.000 Buckets: 5 gal. 10 $5 $50 $0.000 10 $5 $50 $0.000 Barrels: 55 gal. capacity 50 $30 $1,500 $0.006 50 $30 $1,500 $0.006

Subtotal equipment $11,755 $0.054 $65,980 $0.271

Total All Costs $2.584 $1.917

Predicted average yield per tree at 100 days (Kg)

0.86 1.48

Total Cost Per Kg Resin $3.004 $1.295

Note: Equipment costs depreciated over useful life of 250,000 trees; does not include transportation equipment. The cost of 1 kg of methyl jasmonate from Bedoukian Research is $3080.

236

Figure C-1. Diagrams of borehole tapping designs. A) Standard boreholes drilled

manually with a gas-powered drill. B) Standard boreholes drilled manually on opposite sides of the tree. C) Boreholes drilled using a tractor mounted automated system, (d) borehole drilled manually with two shallower wide holes and two longer holes drilled with a 0.9525 cm drill bit. E) Six boreholes drilled manually in two levels, the black-marked holes drilled at the base and the grey-marked holes drilled 10.16 cm higher. F) Eight boreholes drilled manually in two levels, the black-marked holes drilled at the base and the grey-marked holes drilled 10.16 cm higher. G) Three borehole system drilled manually with one central borehole and two interior boreholes. All boreholes were drilled using a 2.54 cm drill bit; apart from the longer borehole in D which was drilled using a 0.9525 cm drill bit, the central borehole in the automated system (B) which was drilled with a 3.175 cm bit and the boreholes in the triple borehole experiment (G) which had a counterbore drilled with a 3.175 cm bit and a 2.54 cm drill bit.

237

Figure C-2. Calculations for the cross-sectional tapping area and individual hole area

model for the trees tapped using the 8-borehole method. c is the center of the tree, r is the radius calculated using the predicted stump diameter, bd represents the borehole depth, and bw represents the borehole width. The tapping area is the triangle c-y-x. This diagram is also used to calculate tapping area intensity using the 6-borehole method.

238

Figure C-3. Chemical effects on oleoresin yield (kg) with standard errors when tapping

slash pine trees in 2015 using the standard method and the big-small tapping method. The means with different letter superscripts were significantly different based on Tukey’s HSD test (p-value <0.05).

239

Figure C-4. Chemical effects on oleoresin yield (kg) with standard errors when tapping

slash pine trees in North Florida in 2014 using the automated drilling technique. The means with different letter superscripts were significantly different based on Tukey’s HSD test (p-value <0.05).

240

Figure C-5. Predicted cumulative flow of oleoresin (g) by chemical treatment since day

of tapping treatment at the 2014 8 borehole test. The following equations correspond to the oleoresin flow when trees are stimulated by the different treatments: control: y = 802.529 * (1 – 0.911 e-0.032D; r2 = 0.98); ethephon: y = 836.953 * (1 – 0.922 e-0.033D; r2 = 0.98); methyl jasmonate: y = 1108.968 * (1 – 0.991 e-0.035D; r2 = 0.99). Where y corresponds to oleoresin yield (g) and D corresponds to number of days since treatment.

0

200

400

600

800

1000

1200

0 20 40 60 80 100 120

Ole

ore

sin

Yie

ld (

g)

Day Since Treatment

Control Ethephon Methyl Jasmonate

241

Figure C-6. Bivariate fit of total tree oleoresin yield (kg) in slash pine by tapping

intensity using the 6 and 8 borehole methods. The r2 for the linear relationship between tapping intensity and average total tree yield is 0.148 (p-value 0.0022).

242

APPENDIX D PSEUDO BACKCROSS HYBRID STUDY

Introduction

The two primary conifer species planted in the southeast United States for timber

production and pulpwood are slash pine (Pinus elliottii Engelm. Var. elliottii) and loblolly

pine (Pinus taeda L.). The two species have some distinct phenotypic and growth

differences. Forestry companies tend to prefer planting loblolly pine, which accounts for

120,000 km2 of land, as it usually responds better to nutrition management and

intensive silvicultural treatments yielding greater total volume at earlier ages (Xiao et al.,

2003). During early developmental stages, loblolly pine is more productive compared to

slash pine (Xiao et al., 2003). While loblolly pine outperforms slash pine, slash pine

grows better on very poorly drained sites (Borders and Harrison, 1989). Compared to

slash pine, loblolly allocates more biomass to crown production, and thus tends to have

more primary and secondary branching and larger crown widths (Xiao et al., 2003). As a

result, compared to slash pine, loblolly pine tends to have a higher leaf area and poorer

stem form caused by the higher number of branches (Xiao et al., 2003; Muñoz Del Valle

et al., 2011). The allocation of biomass to crown development in loblolly pine promotes

increased tree size (Xiao et al., 2003). Furthermore, slash pine is less resistant to

fusiform rust (Cronartium quercuum), a fungal disease that can be fatal to pine trees,

but is more resistant to wind damage (Muñoz Del Valle et al., 2011).

Methods

Study Area

In January 2013, the CFGRP and FBRC established the pseudo backcross

hybrid study. This study is located at the Murphree Well Field protection area in

243

northeast Gainesville, Florida (29°44’50.0” N, 82°19’44.5”W). The study area is owned

and managed by the Weyerhaeuser Company (formerly Plum Creek Timber Company),

and was established to evaluate the performance of progeny and identify beneficial

backcross hybrids for tree improvement programs.

In September 2012, the site was raked and double bedded, and prior to planting

the site received a broadcast application of 48 ounces of Chopper. The site was then

planted in January 2013, and following a 6-week survival check, dead trees were

replaced with replants in March 2013. Following planting, release herbicide treatment of

13 ounces of Oustar were applied using broadcast application in May 2013 and hand

application of 100 gallons of roundup with 6 ounces per gallon in June 2014. The site

was fertilized using a hand broadcast at five feet around each tree between late May

and early June 2014. Replicate 1 received a low treatment of 200# per acre DAP and

replicate 2 received a high treatment of 500# per acre 10-10-10 with micronutrients.

Finally, the site received a herbicide treatment of 48 ounces garlon and 64 ounces

glyphosate per acre.

The study location has a humid subtropical climate with hot wet summers and

mild dry winters, and the topography was flat with a slope between 0 and 2%. The study

was established on a somewhat poorly drained site and the dominant soil series was

Newnan. The Newnan series is a Spodosol and is classified as a sandy, siliceous,

hyperthermic Oxyaquic (USDA Natural Resources Conservation Service, 1993a). The

understory vegetation included saw palmetto (Serenoa repens (B.) Small.), blackberries

(Rubus L. spp.), bluestems (Andropogon spp.), gallberry (Ilex glabra (L.)), greenbriers

244

(Smilax L. spp.), lopsided Indiangrass (Sorghastrum nutans (L.) Nash) and a variety of

other native grasses.

Study Design and Genetic Material

The backcross hybrid study consisted of slash pine and loblolly pine hybrid

backcrosses and parent material. This study consisted of one open pollinated slash pine

parent (E63xMix), one open pollinated loblolly pine (LobxOP) and one loblolly elite

family (Filler) (Table D-1; Figure D-1). Furthermore, three pseudo-backcrosses between

an elite P. elliottii x an elite P. taeda F1 hybrid (2904), with two P. elliottii and one P.

taeda family were planted (Table D-1; Figure D-1). The following are the three pseudo-

backcross hybrid species: [(2904 x 22056) (FS loblolly); (2904 x E63) (FS slash); and

(2904 x open pollinated) (half-sib slash)] (Table D-1; Figure D-1). There was a total of

3420 trees planted; 1710 in each replicate (Table D-1; Figure D-1). Half of the trees in

this study were managed with high intensity fertilization (replicate 2), while the other half

were managed with operational fertilization (replicate 1). The two replicate plots were

separated with three border rows.

The genetic materials for this study were provided by Plum Creek and the

CFGRP and the seeds were germinated and grown at the ArborGen nursery in

containers. Plum Creek supplied the OP loblolly seeds while the CFGRP supplied the

OP slash pine seeds from a mix of two full sib families (E63xE93 and E63xE82). A

Latinized row-column design with single-tree plots spaced at 2.13ˣ3.66 m, as described

by Muñoz Del Valle et al. (2011), was used to plant the trial. Each replicate contained

95 plots; replicate 1 was planted along 11 rows while replicated 2 was planted along 10

rows. Figure D-2 outlines the planting layout for the study.

245

Phenotypic Measurement

The backcross site has been measured annually for mortality, disease and

height. Between November 2015 and March 2016, age 3 status (mortality and disease),

stem form (ramicorn and forking), height (m), DBH (cm), and crown width (m) along and

across planting beds were measured for the entire stand. For this study, a ramicorn

branch was defined as a branch that was obviously bigger than other branches on the

tree and that was growing at less than 45-degree angle from the main stem. A fork was

defined as the main stem split into two stems of similar or equal size. Heights of the tree

was measured from the base to the tip of the primary bud using a telescoping pole.

DBH was measured using a diameter tape and the crown width along and across the

planting bed was measured using a standard tape measure. The number of primary

branches and secondary branches at two nodes (3 and 5 from the base of the tree)

were counted for all pseudo-backcross trees and for a sample of the parents. If the tree

had a dead top or had severe needle dieback, the branch characteristics were not

measured. Furthermore, only trees with a height of at least 1.829 meter were measured

for their branch characteristics. A code system was used to measure status of the tree

and considered if the tree was healthy, had fusiform rust galls on the branch or stem,

dead top from rust or unknown causes, and mortality from rust and unknown causes

(Figure D-3).


The DBH, height, crown and branch data from the pseudo backcross hybrid

study were analyzed in R 3.1.1 and ASReml-R v.3 (R Development Core Team, 2016;

Gilmour et al., 2015). The data were analyzed for normality and the residual plots were


246

examined. The data were analyzed using a general linear mixed model with replicate,

family, and replicate by block as fixed effects. The least squares mean was calculated

using lsmeans R package based on a general linear mixed model. Narrow-sense

heritabilities of individual phenotypic traits were calculated based on the following

individual model with the constructed pedigree:

Yij = µ + Ri + Ri:Bj + ped(I) + eij

where Yij corresponded to the phenotypic trait in the ith replicate (I = 1 or 2) and ith

replicate by jth block (j = 1 to 95), Ri corresponded to the fixed replicate effect, Ri:Bj

corresponded to the fixed replicate by block effect, ped(I) corresponded to the random

individual pedigree effect, and ej corresponded to the random residual effect.

Results

All phenotypic traits were statistically significant with a p-value ≤ 0.01, for

differences among families. Furthermore, all phenotypic traits apart from primary and

secondary branches at nodes 3 and 5 were statistically different with a p-value of 0.01

when comparing high versus operational fertilization (Table D-2). Pure slash pine had

the largest diameters by year 3, though not significantly different to the pseudo

backcross loblolly (SLLL) and the second pseudo backcross slash (SSSL) (Table D-2).

For crown traits, the pure slash pine family was unexpectedly significantly larger than all

other families measured (Table D-2; Table D-3). The pseudo backcross loblolly pine

individuals were significantly taller than the other families and had more primary

branches (Table D-2; Table D-3).

The pure loblolly family had more primary branches at node 3 and significantly

more primary branches at node 5 compared to all other families (Table D-2; Table D-3).

247

As expected, the pure loblolly family and the pseudo backcross loblolly family had

significantly more secondary branches compared to all other families at both nodes 3

and 5 (Table D-2; Table D-3). The pure slash pine trees had on average 9.3 secondary

branches at node 3 and 5.9 secondary branches at node 5, while the pure loblolly pine

trees had on average 27.7 and 28.7 secondary branches at nodes 3 and 5, respectively,

which is between 3 and 5 times more branches (Table D-2). On average, the number of

secondary branches in the pseudo backcross individuals was somewhere in between

the number of secondary branches from the slash and loblolly individuals (Table D-2).

The pseudo backcross slash pine trees had significantly less secondary branching

compared to the pseudo backcross loblolly trees (Table D-2). The number of secondary

branches at nodes 3 and 5 were the same in pure loblolly and the pseudo backcross

loblolly trees (Table D-3).

The pseudo backcross loblolly family was more susceptible to fusiform rust,

accounting for about 56% of total rust occurrence in the study (Table D-4). 9.0% of the

trees in the pseudo backcross family has either branch or stem galls. Overall mortality in

this study at the end of the growing season was 4.5 % (Table D-4), excluding the

mortality from the slash pseudo backcross. Stem form of the pseudo backcross loblolly

was poorer compared to the other families, with more forking and ramicorn branching

(Table D-5).

The estimated narrow-sense heritabilities for all measured traits, based on an

individual pedigree model with fixed replicate and replicate by block effect and random

individual pedigree effects are presented in Table D-6. Estimates of narrow-sense

heritability for the various phenotypic traits measured were relatively low and ranged

248

from 0.046 to 0.195. The number of primary branches and secondary branches at node

5 had the highest heritability estimate (h2 = 0.195) (Table D-6). The heritability estimates

for DBH and primary branches at node 3 were low (h2 = 0.046 and h2 = 0.059,

respectively) (Table D-6). The heritability estimates for the other traits were slightly

higher (height h2 = 0.094, crown h2 = 0.102, primary branch h2 = 0.194, secondary

branch node 3 h2 = 0.133, primary branch node 5 h2 = 0.100, secondary branch node 5

h2 = 0.195) (Table D-6).

Discussion

At the FBRC and CFGRP’s backcross hybrid stand, several full-sib families were

compared for various growth traits. The pure slash pine trees in this study had wider

stem diameters. Compared to loblolly pine trees, slash pine allocates more dry matter to

stem wood and stem bark (Colbert et al. 1990). Surprisingly, the average crown size in

the pure slash pine trees was significantly larger than all the other families. Although it is

well documented that loblolly pine tends to have larger crowns than slash pine (Xiao et

al., 2003), it may not be the case for very young trees. Loblolly and pseudo backcross

loblolly trees were found to have on average more primary and secondary branches. In

their study, Colbert et al. (1990) reported a greater dry matter partitioning to crown

foliage and branches in loblolly pine compared to slash pine. These inter-whorl

branches allow loblolly pine to more efficiently intercept light and reduces self-shading

at higher leaf areas, which would make them more productive at higher densities

(Colbert et al. 1990). However, at lower planting densities with lower leaf areas, slash

pine is more productive than loblolly pine (Colbert et al. 1990). The loblolly pine pseudo

249

backcross showed signs of hybrid vigor as it had more primary branches and was taller

than all other families, including the pure slash and pure loblolly.

Muñoz Del Valle et al. (2011) and Lopez-Upton et al. (1999), reported that

loblolly pine tends to be less susceptible to fusiform rust compared to slash pine,

although certain families in both species are more resistant. However, in our study,

overall rust occurrence was low, but the pseudo backcross loblolly family had 9.0% of

trees infected with a branch or stem rust gall. This may be due to the higher rate of

these seedlings having nurse rust prior to planting. The narrow-sense heritability

estimates for most of the growth traits at age 3 were relatively low as reported in many

other studies (Lopez-Upton et al., 1999; Li et al., 2007). The heritability estimates for the

number of primary branches and the number of secondary branches at node 5 were the

highest.

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Table D-1. Summary of genotypes planted in each replicate of the CFGRP pseudo backcross hybrid study.

Family # Individuals Replicate 1 # Individuals Replicate 2 Total # Individuals

2904 x 22056 615 604 1219

2904 x OP 99 99 198

Filler 135 150 285

2904 x E63 407 381 788

E63 x Mix 246 254 500

Lob x OP 208 222 430

Grand Total 1710 1710 3420

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Table D-2. Least square means with standard errors for phenotypic traits measured at the pseudo-backcross hybrid study. Pure slash and loblolly pine families are SSSS and LLLL, respectively, and backcross hybrids with slash and loblolly are (SSSL 1 and 2, and SLLL, respectively.

Year 3 Measurements

SSSS SSSL (1, 2) SLLL LLLL

Height (m)

3.31 (0.04) 3.18 (0.06) 3.58 (0.02) 3.35 (0.04)

3.45 (0.03) DBH (cm)

5.72 (0.08) 5.20 (0.12) 5.63 (0.05) 5.41 (0.08)

5.64 (0.07) Crown (m)

2.08 (0.02) 1.85 (0.03) 1.98 (0.01) 1.92 (0.02)

1.98 (0.02) Primary Branch 27.48 (0.47) 35.72 (0.76) 39.17 (0.29) 36.58 (1.09)

33.82 (0.39) Primary Branch Node 3

2.64 (0.08) 3.16 (0.13) 2.97 (0.05) 3.20 (0.18)

2.77 (0.07) Secondary Branch Node 3

9.28 (0.93) 23.71 (1.50) 29.22 (0.58) 27.74 (2.14)

14.74 (0.77) Primary Branch Node 5

2.89 (0.08) 3.18 (0.13) 3.46 (0.05) 3.84 (0.18)

3.46 (0.07) Secondary Branch Node 5

5.85 (0.87) 17.39 (1.40) 25.00 (0.54) 28.67 (1.99)

10.13 (0.72)

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Table D-3. Tukey significance group letters of the least square means for phenotypic traits (alpha < 0.05) recorded in Table D-2. Pure slash and loblolly pine families were measured (SSSS and LLLL, respectively), as well as backcross hybrids with slash and loblolly (SSSL and SLLL, respectively).

Year 3 Measurements

SSSS SSSL 1 SSSL 2 SLLL LLLL

Height (m) BC C B A BC

DBH (cm) A B A A AB

Crown (m) A C B B BC

Primary Branch C B B A B

Primary Branch Node 3 C A BC AB AB

Secondary Branch Node 3 D B C A AB

Primary Branch Node 5 C BC AB AB A Secondary Branch Node 5 D B C A A

Note: The different Tukey group letters were significantly different based on Tukey’s HSD test (p-value <0.05).

253

Table D-4. Disease and mortality observed at the end of the 3rd growing season in the two replicate treatments of the pseudo-backcross hybrid. Pure slash and loblolly pine families were measured (SSSS and LLLL, respectively), as well as backcross hybrids with slash and loblolly (SSSL and SLLL, respectively). Replicate 1 represents the operational fertilization treatment, while replicate 2 represents the higher intensity fertilization. The top line in each family represents disease at mortality in both replicate plots.

Disease and Mortality Status by Environment

Family Rust Rust Mortality Pitch Moth Mortality

SLLL 8.97% 0.06% 1.73% 0.47%

Replicate 1 4.06% 0.06% 0.94% 0.18%

Replicate 2 4.91% 0% 0.79% 0.29%

SSSL1 1.17% 0% 0.32% 0.21%

Replicate 1 0.56% 0% 0.12% 0.12%

Replicate 2 0.61% 0% 0.20% 0.09%

SSSL2 2.96% 0.03% 1.72% 2.08%

Replicate 1 1.67% 0.03% 0.73% 0.99%

Replicate 2 1.29% 0% 0.99% 1.08%

SSSS 2.46% 0.18% 1.17% 0.44%

Replicate 1 1.11% 0.12% 0.56% 0.18%

Replicate 2 1.35% 0.06% 0.61% 0.26%

LLLL 0.56% 0% 0.42% 0.20%

Replicate 1 0.15% 0% 0.23% 0.00%

Replicate 2 0.41% 0% 0.18% 0.20%

Study Means 16.12% 0.27% 5.36% 3.39%

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Table D-5. Percentage of trees with stem form issues at the end of the 3rd growing season in the pseudo-backcross hybrid study. Pure slash and loblolly pine families were measured (SSSS and LLLL, respectively), as well as backcross hybrids with slash and loblolly (SSSL and SLLL, respectively). Replicate 1 represents the operational fertilization treatment, while replicate 2 represents the higher intensity fertilization. The top line in each family represents stem form in both replicate plots.

Stem Form by Environment

Family None Forking Ramicorn Branching Both

SLLL 11.38% 5.55% 15.69% 5.74%

Replicate 1 6.12% 2.81% 7.97% 2.52%

Replicate 2 5.26% 2.74% 7.72% 3.22%

SSSL1 2.63% 0.84% 2.30% 0.42%

Replicate 1 1.44% 0.48% 1.02% 0.16%

Replicate 2 1.18% 0.35% 1.28% 0.26%

SSSL2 13.01% 3.12% 5.96% 0.86%

Replicate 1 6.12% 1.53% 3.70% 0.57%

Replicate 2 6.89% 1.59% 2.26% 0.29%

SSSS 9.57% 1.44% 4.08% 0.26%

Replicate 1 4.88% 0.67% 1.88% 0.13%

Replicate 2 4.69% 0.77% 2.20% 0.13%

LLLL 5.59% 1.59% 5.45% 0.86%

Replicate 1 2.78% 0.89% 2.55% 0.41%

Replicate 2 2.81% 0.70% 2.90% 0.45%

Study Means 42.18% 12.54% 33.48% 8.14%

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Table D-6. Narrow sense heritability estimates calculated for phenotypic traits measured at the end of the 3rd growing season in the pseudo-backcross hybrid study.

Year 3 Measurements

Phenotypic Trait Narrow Sense Heritability Standard Error

Height 0.094 0.058

DBH 0.046 0.043

Crown 0.102 0.065

Primary Branch 0.194 0.071

Primary Branch Node 3 0.059 0.055

Secondary Branch Node 3 0.133 0.050

Primary Branch Node 5 0.100 0.063

Secondary Branch Node 5 0.195 0.070

256

Figure D-1. Pedigree of the genotypes planted in the pseudo backcross hybrid study using a Latinized row-column design.

257

Figure D-2. Layout of the pseudo backcross hybrid study using a Latinized row-column design.

258

Figure D-3. Codes used for the pseudo backcross hybrid study. Part A shows the tree status codes and part B shows the stem form codes.

259

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BIOGRAPHICAL SKETCH

Marie Jennifer Lauture was born in Port-au-Prince, Haiti in 1992, and moved to

Miami, Florida at age 5. In 2009, after graduating high school, she moved to Gainesville,

Florida to pursue an undergraduate degree at the University of Florida. As an

undergraduate student, Jennifer began working with Dr. Gary Peter and his graduate

students as a field and laboratory technician. In 2013, Jennifer received her Bachelor of

Science degree in Wildlife Ecology and Conservation. In 2013, she joined the School of

Forest Resources and Conservation at the University of Florida to pursue her graduate

study under the supervision of Dr. Gary Peter. She received her PhD from the

University of Florida in the winter of 2017.

REINVIGORATING OLEORESIN COLLECTION IN THE SOUTHEAST … · reinvigorating oleoresin collection in the southeast usa: evaluation of chemical inducers, stand management, tree characteristics,

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