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AAnniimmaall SScciieenncceeDDeeppaarrttmmeenntt RReeppoorrtt ••
22000077
Arkansas
A R K A N S A S A G R I C U L T U R A L E X P E R I M E N T S T
A T I O NDivision of Agriculture University of Arkansas
SystemDecember 2007 Research Series 553
Zelpha B. JohnsonD. Wayne Kellogg
Editors
AAnniimmaall SScciieenncceeDDeeppaarrttmmeenntt RReeppoorrtt ••
22000077
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Technical editing, layout, and cover design by Camilla Crone
This publication is available on the Internet at:
http://arkansasagnews.uark.edu/408.htm
Arkansas Agricultural Experiment Station, University of Arkansas
Division of Agriculture, Fayetteville. Milo J. Shult, Vice
President forAgriculture. Mark J. Cochran, AAES Director and
Associate Vice President for Agriculture–Research. TS675QX6.52.The
University of Arkansas Division of Agriculture follows a
nondiscriminatory policy in programs and employment.ISSN:1051-3140
CODEN:AKAMA6
Cover photo by Peggy Greb, USDA/ARS Image Gallery
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ARKANSAS ANIMAL SCIENCE DEPARTMENT REPORT 2007
Edited by
Zelpha B. JohnsonProfessor
and
D. Wayne KelloggProfessor
Department of Animal ScienceUniversity of Arkansas
University of Arkansas Division of AgricultureArkansas
Agricultural Experiment Station
Fayetteville, Arkansas 72701
DisclaimerNo findings, conclusions, or reports regarding any
product or any process that is contained in any article published
in this report
should imply endorsement or non-endorsement of any such product
or process.
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INTRODUCTION
It is hard to believe that this is the 10th edition of Arkansas
Animal Science. We owe a great debt to Drs. Zelpha Johnson and
WayneKellogg who devote valuable time to making this a quality
publication. They have edited this publication since 1999; a year
after Dr. StaceyGunter designed the format and edited the first
edition in 1998.
We believe that Arkansas Animal Science is an essential
publication for our program. While peer-reviewed journals are the
ultimategoal for publication of quality research, the time-lines
for publication and the frequent necessity to combine several
trials limit the utili-ty of journals for early dissemination of
results. Stakeholders, other researchers, extension faculty, and
industry professionals need resultsas quickly as the data are
analyzed statistically and prepared in a professional publication
such as Arkansas Animal Science. The capacityto present this
publication in both hard copy and electronic format on our website
further increases its impact.
The research described in this report was conducted at the four
main experiment stations used by the Department of Animal
Science,including the Arkansas Research and Extension Center at
Fayetteville, the Southwest Research and Extension Center at Hope,
theSoutheast Research and Extension Center at Monticello, and the
Livestock and Forestry Branch Station at Batesville. Other
valuableresearch and extension work was conducted at numerous
private farms across the state. In the modern world of animal
science, the tra-ditional lines between research and extension
programs are increasingly disappearing. This should be apparent as
one looks at the author-ship of the articles in this
publication.
Readers are invited to view all programs of the Department of
Animal Science at the departmental website at
animalscience.uark.eduand the Livestock and Forestry Branch Station
website at www.Batesvillestation.org.
Finally, we want to thank the many supporters of our teaching,
research, and extension programs. Whether providing grants
forresearch and extension, funds for scholarships, supporting
educational and extension programs, donating facilities or horses
and livestock,these friends are essential to maintaining a quality
animal science program. We thank each and every one of you on
behalf of our faculty,staff, students, and stakeholders. We hope
you find the research, extension, and educational programs reported
herein to be timely, use-ful, and making a contribution to the
field of animal science.
Sincerely,
Keith LusbyDepartment Head
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INTERPRETING STATISTICS
Scientists use statistics as a tool to determine which
differencesamong treatments are real (and therefore biologically
meaningful)and which differences are probably due to random
occurrence(chance) or some other factors not related to the
treatment.
Most data will be presented as means or averages of a
specificgroup (usually the treatment). Statements of probability
that treat-ment means differ will be found in most papers in this
publication,in tables as well as in the text. These will look like
(P < 0.05); (P <0.01); or (P < 0.001) and mean that the
probability (P) that any twotreatment means differ entirely due to
chance is less than 5, 1, or0.1%, respectively. Using the example
of P < 0.05, there is less thana 5% chance that two treatment
averages are really the same.Statistical differences among means
are often indicated in tables byuse of superscript letters.
Treatments with any letter in common arenot different, while
treatments with no letters in common are.Another way to report
means is as mean ± standard error (e.g. 9.1± 1.2). The standard
error of the mean (designated SE or SEM) is ameasure of the amount
of variation present in the data—the largerthe SE, the more
variation. If the difference between two means isless than two
times the SE, then the treatments are usually not sta-tistically
different from one another. Other authors may report anLSD (least
significant difference) value. When the differencebetween any two
means is greater than or equal to the LSD value,then they are
statistically different from one another. Another esti-mate of the
amount of variation in a data set that may be used isthe
coefficient of variation (CV), which is the standard errorexpressed
as a percentage of the mean. Orthogonal contrasts maybe used when
the interest is in reporting differences between spe-cific
combinations of treatments or to determine the type ofresponse to
the treatment (i.e. linear, quadratic, cubic, etc.).
Some experiments may report a correlation coefficient (r),which
is a measure of the degree of association between two vari-ables.
Values can range from –1 to +1. A strong positive correlation
(close to +1) between two variables indicates that if one
variablehas a high value then the other variable is likely to have
a high valuealso. Similarly, low values of one variable tend to be
associated withlow values of the other variable. In contrast, a
strong negative cor-relation coefficient (close to –1) indicates
that high values of onevariable tend to be associated with low
values of the other variable.A correlation coefficient close to
zero indicates that there is notmuch association between values of
the two variables (i.e. the vari-ables are independent).
Correlation is merely a measure of associa-tion between two
variables and does not imply cause and effect.
Other experiments may use similar procedures known asregression
analysis to determine treatment differences. The regres-sion
coefficient (usually denoted as b) indicates the amount ofchange in
a variable Y for each one unit increase in a variable X. Inits
simplest form (i.e. linear regression), the regression coefficient
issimply the slope of a straight line. A regression equation can
beused to predict the value of the dependent variable Y (e.g.
perform-ance) given a value of the independent variable X (e.g.
treatment).A more complicated procedure, known as multiple
regression, canbe used to derive an equation that uses several
independent vari-ables to predict a single dependent variable.
Associated statistics arer2, the simple coefficient of
determination, and R2, the multiplecoefficient of determination.
These statistics indicate the propor-tion of the variation in the
dependent variable that can be account-ed for by the independent
variables. Some authors may report thesquare root of the Mean
Square for Error (RMSE) as an estimate ofthe standard deviation of
the dependent variable.
Genetic studies may report estimates of heritability (h2)
orgenetic correlation (rg). Heritability estimates refer to that
portion
of the phenotypic variance in a population that is due to
heredity.A genetic correlation is a measure of whether or not the
same genesare affecting two traits and may vary from –1 to +1.
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LIST OF COMMON ABBREVIATIONS
Abbreviation Term
Physical Units
cal Calorie
cc cubic centimeter
cm centimeteroC Degrees CelsiusoF Degrees Fahrenheit
ft Foot or feet
g Grams(s)
gal Gallon(s)
in Inch(es)
IU International unit(s)
kcal Kilocalories(s)
kg Kilograms(s)
lb Pound(s)
L Liter(s)
m Meter(s)
mg Milligram(s)
Meq Milliequivalent(s)
Mcg Microgram(s)
mm Millimeter(s)
ng Nanogram(s)
oz ounce
ppb Parts per billion
ppm Parts per million
Units of Time
d Days(s)
h Hour(s)
min Minute(s)
mo Month(s)
s Second(s)
wk Week(s)
yr Year(s)
Others
ADF Acid detergent fiber
ADFI Average daily feed intake
ADG Average daily gain
avg Average
BCS Body condition score
BW Body weight
CP Crude protein
CV Coefficient of variation
cwt 100 pounds
DM Dry matter
DNA Deoxyribonucleic acid
EPD Expected progeny difference
F/G Feed:gain ratio
FSH Follicle stimulating hormone
LH Lutenizing hormone
N Nitrogen
NDF Neutral detergent fiber
NS Not significant
r Correlation coefficient
r2 Simple coefficient of
determination
R2 Multiple coefficient of
determination
SD Standard deviation
SE Standard error
SEM Standard error of the mean
TDN Total digestible nutrients
wt Weight
COMMON ABBREVIATIONS
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A Comparison of Weaning Ratio in Five Breeds of CattleZ.B.
Johnson, A.H. Brown, Jr., and S.T.
Dewey..................................................................................................................................................10
Relationship of Lactate Dehydrogenase Activity with Body
Measurements of Angus x Charolais Cows and CalvesM.L. Looper, T.P.
Neidecker, C.W. Wall, S.T. Reiter, R. Flores, A.H. Brown, Jr., Z.B.
Johnson, and C.F. Rosenkrans, Jr.
..............................13
Supplemental Trace Minerals (Zn, Cu, Mn, And Co) as Availa®4 or
Inorganic Sources for Shipping-Stressed CattleM.R. Pass, E.B.
Kegley, and C.K. Larson
............................................................................................................................................................16
Arkansas Steer Feedout Program 2005-2006B. Barham, S. Gadberry,
J. Richeson, and S. Cline
............................................................................................................................................22
Regression of Feed Intake on Selected Environmental Factors for
Beef Bulls During Post-Weaning Feedlot Performance Tests
G.T. Tabler, Jr., A.H. Brown, Jr., E.E. Gbur, Jr., I.L. Berry,
Z.B. Johnson D.W. Kellogg, and K.C.
Thompson................................................25
Effects of Selected Weather Factors on Feed Intake of Angus,
Polled Hereford, and Simmental Beef Bulls During Feedlot
Performance Tests
G.T. Tabler, Jr., A.H. Brown, Jr., E.E. Gbur, Jr., I.L. Berry,
Z.B. Johnson, D.W. Kellogg, and K.C. Thompson
..............................................29
Influence of Sanitizing Feedlot Pens on Microbial Populations
and Cattle Performance M.S. Lee, J.K. Apple, J.S. Yancey, J.T.
Sawyer, M.M. Brashears, and TP. Stephens
............................................................................................34
Influence of Reproductive Tract Score on Pregnancy in Angus
HeifersJ.G. Powell, A.H. Brown, T.A. Yazwinski, R.A. Rorie, Z.B.
Johnson, J.L. Reynolds
..........................................................................................39
Reproductive Performance, Blood Urea Nitrogen, and Blood Glucose
Concentration in Beef Heifers Grazing Annual Ryegrass in the Spring
and Supplemented at Different Intervals Prior to Timed AI
D.L. Kreider, K.P. Coffey, J.D. Caldwell, W.A. Whitworth, T.G.
Montgomery, R. Rorie, R.W. McNew,W. Coblentz, and R.K. Ogden
..........................................................................................................................................................................41
Effect of Bovine Somatotropin Treatment on AI Pregnancy Rate in
Dairy HeifersR.W. Rorie and T.D. Lester
..................................................................................................................................................................................45
Effects of Penicillamine, Hypotaurine and Epinephrine (PHE) on
Post-Thaw Bovine Sperm Parameters, as Measured by Computer-Assisted
Sperm Analysis
C.N. Person, T.D. Lester, M.D. Person, and R.W. Rorie
....................................................................................................................................47
Computer-Assisted Analysis of Sperm Parameters after Selection
of Motile Sperm by Either Percoll Gradient,Filtration, or Swim-up
Procedures
C.N. Person, T.D. Lester, M.D. Person, and R.W. Rorie
....................................................................................................................................51
Effects of Milk Antimicrobial Proteins on Incidence of Mastitis
in Dairy CattleM.D. Person, C.N. Person, T.D. Lester, and R.W.
Rorie
....................................................................................................................................54
DairyMetrics for Arkansas Herds in May, 2007J.A. Pennington
....................................................................................................................................................................................................56
Glycerol as a Supplemental Energy Source for Meat GoatsK.R.
Hampy, DW. Kellogg, K.P. Coffey, E.B, Kegley, J.D. Caldwell, M.S.
Lee, MS. Akins, J.L. Reynolds,
J.C. Moore, and K.D. Southern
........................................................................................................................................................................63
In Vitro DM Digestibility of Crabgrass, Bermudagrass, and Wheat
Forages Supplemented with Four Levels of Glycerol1
K.R. Hampy, D.W. Kellogg, K.P. Coffey, and K. Anschutz
................................................................................................................................65
Cow and Calf Performance While Grazing Tall Fescue Pastures with
Either the Wild-Type Toxic Endophyte or a Non-Toxic Novel
Endophyte
K.P. Coffey, W.K. Coblentz, J.D. Caldwell, C.P. West, R.K.
Ogden, T. Hess, D.S. Hubbell, III, M.S. Akins,and C.F. Rosenkrans,
Jr.
....................................................................................................................................................................................67
Growth Performance and Immune Function of Fall-Born Beef Calves
Weaned from Endophyte-Infected Tall Fescue Pastures on Different
Dates in the Spring
J.D. Caldwell, K.P. Coffey, W.K. Coblentz, R. K. Ogden, J. A.
Jennings, D.S. Hubbell, III, D.L. Kreider, and C.F. Rosenkrans, Jr.
..............70
TABLE OF CONTENTS
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Nutritive Value of Fall-Grown Cereal-Grain Forages over TimeM.S.
Akins, E.B. Kegley, J.L. Gunsaulis, W.K. Coblentz, K.S. Lusby, R.K.
Ogden, J.D. Caldwell,
R.K. Bacon, and K.P. Coffey
..............................................................................................................................................................................73
Effect of Surface Decontamination Using Antimicrobial Agents on
Microbiological Quality of Beef SteaksF.W. Pohlman, P.N.
Dias-Morse, C.W. Rowe, and S.R. De Silva
......................................................................................................................78
Effect of Salt, Trisodium Phosphate, Synthetic Antioxidants, and
Conjugated Linoleic Acid on Sensory and Quality Characteristics of
Beef Striploins
C.W. Rowe, F.W. Pohlman, A.H. Brown, Jr., and Z.B. Johnson
........................................................................................................................81
Effect of Salt, Trisodium Phosphate, Synthetic Antioxidants, and
Conjugated Linoleic Acid on Instrumental Color Characteristics and
Physical Characteristics of Beef Striploins of Different Quality
Grades
C.W. Rowe, F.W. Pohlman, A.H. Brown, Jr., and Z.B. Johnson
........................................................................................................................84
Color Stability of Dark-cutting Beef Enhanced with Lactic
AcidJ.T. Sawyer, J.K. Apple, Z.B. Johnson, R.T. Baublits, and
J.W.S. Yancey
............................................................................................................87
The Impact of Acidic Marination Concentration and Sodium
Chloride on Sensory and Instrumental Color Characteristics of
Dark-cutting Beef
J.T. Sawyer, J.K. Apple, and Z.B. Johnson
..........................................................................................................................................................92
Impact of Stressing a Pen Mate on Physiological Responses of
Growing PigsJ.B. Koonce, E.B. Kegley, D.L. Galloway, Sr., and J.K.
Apple..............................................................................................................................96
Effect of Weaning Age on Nursery Pig Growth PerformanceB.E.
Bass, C.L. Bradley, J.W. Frank, and C.V. Maxwell
....................................................................................................................................100
Effect of Feeding Alfalfa on Nursery Pig Growth PerformanceC.L.
Martin, J.W. Frank, Z.B. Johnson, G.M. Weiss, and C.V.
Maxwell..........................................................................................................103
Characterization of Claw Lesions Associated with Lameness in the
University of Arkansas Sow HerdC.L. Bradley, J.W. Frank, C.V.
Maxwell, Z.B. Johnson, J.G. Powell, S.R. Van Amstel, and T.L. Ward
..........................................................106
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Introduction
The ratio of calf weight to cow weight at calf weaning(WnRatio)
is utilized in some performance testing programs as ameasure of
gross biological or economic efficiency in cow-calf pro-duction.
Generally, cows that have a high ratio (> 0.50) are
moreefficient and profitable than cows that have a low ratio (<
0.50). AsWnRatio goes down, calf break-even cost goes up. Kress et
al.(2001) reported that calf weight at weaning divided by cow
weightat weaning was an accurate indicator of cow-calf biological
effi-ciency. However, Dinkel and Brown (1978) and MacNeil
(2005)showed that the WnRatio had little advantage over calf
weaningweight alone in estimating efficiency in cow-calf
production.Despite differences in the aforementioned reports, there
exists aneed for further evaluation of this ratio, because of
interest in usingthe ratio as a selection trait and because of the
need to improve effi-ciency of cow-calf production. Thus, the
objectives of this studywere to estimate genetic parameters for
calf weaning weight, cowweight at calf weaning, and WnRatio, and to
compare ratios amongsamples of five breeds of beef cattle managed
on Ozark nativerange.
Experimental Procedures
Data for this study came from purebred beef cattle popula-tions
reared on the University of Arkansas Experiment StationFarm near
Savoy. Five breeds were represented: Angus (years 1965through
1995), Hereford (years 1965 through 1998); Charolais(years 1970
through 1988), Red Poll (years 1978 through 1995), andChianina
(years 1985 through 1995). Description of the establish-ment and
management of these herds was given by Johnson et al.(1990). Calves
were born in the Spring and birth weights (Brwt)
recorded within 24 h of birth. Both cow and calf weights
wererecorded when calves were weaned in the Fall (usually
October).Calf weights were adjusted to 205 d of age by linear
regression.Weaning ratio was calculated as calf weight at 205 d of
age (Wt205)divided by cow weight (CowWt) at weaning of her
calf.
Heritabilities for each of these four traits (Brwt, Wt205,CowWt,
and WnRatio) for each breed (except Chianina where thesmall sample
size prevented estimation of genetic parameters) wereestimated
using the MTDFREML program of Boldman et al.(1993) and Boldman and
Van Vleck (1991). Multiple-trait analyseswere conducted with Brwt
included in each analysis because thistrait was available for all
records. The model included fixed effectsfor year and sex. Age of
dam (at birth of the calf) was included as acovariate for Brwt,
Wt205, and WnRatio. For CowWt, this covari-ate would be interpreted
as age of the cow at the birth of her calf.Both direct and maternal
heritabilities were obtained for all traitsexcept CowWt, where
maternal effects were not included in themodel. Approximate
standard errors were obtained from a singletrait analysis of each
trait. Breed differences for each trait wereexamined using PROC
MIXED of SAS (SAS Inst., Inc., Cary, N.C.).The model included
breed, year, sex, and breed by sex interaction asfixed effects. Age
of dam was a covariate, and sire within breed wasa random effect
used to test for breed differences. Mean separationwas accomplished
using the PDIFF option of LSMEANS in PROCMIXED.
Results and Discussion
Number of observations for each trait and breed, along withmean,
standard deviation, minimum and maximum values, is givenin Table 1.
Most of the observations were from Angus and Herefordbreeds, with
fewer Charolais and Red Poll, and only a few Chianina.
Estimates of heritabilities for direct and maternal effects
for
Story in Brief
The objectives of this study were to estimate genetic parameters
for calf weaning weight (Wt205), cow weight at calf weaning(CowWt),
and ratio of calf weight to cow weight at calf weaning (WnRatio),
and to compare ratios among samples of five breedsof beef cattle.
Data for this study came from purebred beef cattle populations
reared on the University of Arkansas ExperimentStation Farm and
included Angus, Hereford, Charolais , Red Poll, and Chianina.
Heritabilities for each trait for each breed (exceptChianina which
did not have enough numbers) were estimated. Multiple-trait
analyses were conducted with birth weight includ-ed in each
analysis because this trait was available for all records. Year of
birth and sex of calf were included as fixed effects and ageof dam
was a covariate. Heritability estimates for direct effects of Wt205
were 0.38, 0.21, 0.30 and 0.10 for Angus, Hereford,Charolais, and
Red Poll, respectively. Heritability estimates for maternal effects
for Wt205 were 0.19, 0.25, 0.23, and 0.44 for Angus,Hereford,
Charolais, and Red Poll, respectively. Estimates of heritability
for direct effects for CowWt were similar for Angus,Hereford, and
Charolais (0.62 and 0.63) and somewhat higher for Red Poll (0.89).
For WnRatio, heritabilities for direct effects werelow, ranging
from an estimate of zero for Red Poll to 0.15 for Angus; whereas,
heritabilities for maternal effects were higher, rang-ing from 0.39
for Charolais to 0.70 for Red Poll. The Chianina breed did not
differ (P > 0.05) from the Hereford breed for WnRatio;however,
all other breeds differed (P < 0.05) from each other for this
trait.
A Comparison of Weaning Ratio in Five Breeds of Cattle
Z.B. Johnson, A.H. Brown, Jr., and S.T. Dewey1
1 All authors are associated with the Department of Animal
Science, Fayetteville.
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Arkansas Animal Science Department Report 2007
11
each trait and breed are given in Table 2. Estimates of
heritabilityfor Brwt were obtained from each of the three analyses
and rangedfrom 0.55 to 0.59 in Angus, from 0.31 to 0.36 in
Hereford, from0.52 to 0.63 in Charolais, and from 0.33 to 0.40 in
Red Poll fordirect effects. Estimates of heritability of maternal
effects for Brwtranged from 0.12 to 0.16 in Angus, from 0.16 to
0.21 in Hereford,from 0.08 to 0.16 in Charolais, and all estimates
were 0.05 in RedPoll. Standard errors in Red Poll were larger than
the estimateimplying that none of these estimates were different
from zero.MacNeil (2005) reported heritability estimates of direct
effects of0.46 ± 0.04, 0.48 ± 0.03, 0.76 ± 0.02, and 0.20 ± 0.03
for birthweight, 200-day weight, cow weight, and weaning ratio,
respective-ly, in a composite population of beef cattle developed
by USDA-ARS at Fort Keogh Livestock and Range Research Laboratory
inMontana. He also reported heritability estimates of maternal
effectsof 0.10 ± 0.02, 0.13 ± 0.02, and 0.58 ± 0.05 for birth
weight, 200-day weight, and weaning ratio, respectively.
Heritability estimates for direct effects for Wt205 were
0.38,0.21, 0.30, and 0.10 for Angus, Hereford, Charolais, and Red
Poll,respectively. Heritability estimates for maternal effects for
Wt205were 0.19, 0.25, 0.23, and 0.44 for Angus, Hereford,
Charolais, andRed Poll, respectively. These estimates are slightly
lower for directeffects and slightly higher for maternal effects
than those reportedby MacNeil (2005) (0.48 ± 0.03 for direct
effects and 0.13 ± 0.02 formaternal effects).
Estimates of heritability for direct effects for CowWt were
sim-ilar for Angus, Hereford, and Charolais (0.62 and 0.63), and
some-what higher for Red Poll (0.89).These estimates are comparable
tothe 0.76 ± 0.02 reported by MacNeil (2005) for this trait.
ForWnRatio, heritabilities for direct effects were low ranging from
anestimate of zero for Red Poll to 0.15 for Angus, and would not
bedifferent from zero for any breed except Angus. These estimates
arelower than the 0.20 ± 0.03 reported by MacNeil (2005). The
directeffect is the dam’s genes on her performance in producing
weaningweight and any direct effect of the calf genes on its
performance toweaning. Although estimates of the coefficient of
heritability forthe direct component of WnRatio in this study were
low, this traitis so important economically that it deserves to be
selected fordespite low heritability.
Milk production and mothering ability comprise the
maternalcomponents of weaning weight. These components are
determinedby the mother’s genes as well as by her environment. The
dam’sgenes for these traits do not affect offspring’s growth rate
directly,but they do affect the environment provided for the calf
by thedam. They also relate to the dam’s ability to protect her
calf.Heritabilities for maternal effects for WnRatio were higher
than fordirect effects, ranging from 0.39 for Charolais to 0.70 for
Red Poll.MacNeil (2005) also reported higher estimates for maternal
effects(0.58 ± 0.05). Because of the high estimates of heritability
for thematernal component, the WnRatio could be used in selection
toimprove both biological and economic efficiency in
cow-calfproduction.
Management systems emphasize the best combination of bio-logical
and economic efficiency. Although the two types of efficien-cy are
interrelated, they are different. Biological efficiency is
theamount of beef produced relative to the amount of feed
consumed.Economic efficiency is the dollars returned for each
dollar spent.
The number of calves weaned and the weight of each calf
atweaning are the two most important factors in cow-calf
produc-tion. The weaning weight is important because it represents
thepounds of production per cow per year. This trait depends on
themilk production of the cow, and to a lesser extent, on the
ability ofthe calf to grow. The numerator of the WnRatio measures
outputof the cow-calf unit and the denominator indicates input
througha commonly accepted relationship of cow weight and
nutrientrequirements. For the cow, these requirements are affected
by hersize and by the demand for milk production by her calf. A cow
ofintermediate size will more likely have a higher WnRatio than
alarge cow, all else being equal. Most of the time as cow size
increases,the WnRatio declines. Davis et al. (1983) found cow
weight to becorrelated to efficiency, with smaller cows being more
efficient inproduction of weaning weight of calf. The extent to
which this ratiorepresents gross efficiency and economic efficiency
is only esti-mated.
Least-squares means for breed are presented in Table 3. Aswould
be expected Brwt was lowest (P < 0.05) in the Angus breedand
highest in Chianina (P < 0.05). Weight at 205 d of age
rangedfrom a low of approximately 383 lb for Angus and Hereford
breeds(which did not differ, P > 0.05) to a high of 469 lb for
Charolais,with Red Poll being intermediate. Charolais calves did
not differ(P > 0.05) from Chianina calves for this trait.
Chianina cowsweighed the most, followed by Charolais, and Hereford.
Angus andRed Poll cows were the lightest and did not differ from
each other(P > 0.05). The Chianina breed did not differ (P >
0.05) from theHereford breed for WnRatio; however, all other breeds
were differ-ent from each other (P < 0.05). Breed differences
for WnRatio pri-marily reflect differences in cow size and milk
production amongthe breed groups compared.
Literature Cited
Boldman, K.G., et al. 1993. A manual for use of MTDFREML-A setof
programs to obtain estimates of variances and covariances.ARS,
USDA, Washington, D.C.
Boldman, K.G., and L.D. Van Vleck. 1991. J. Dairy Sci.
74:4337-4343.
Davis, M.E., et al. 1983. J. Anim. Sci. 57:852-866.Dinkel, C.A.,
and M.A. Brown. 1978. J. Anim. Sci. 46:614-617.Johnson, Z.B., et
al. 1990. Ark. Agric. Exp. Station Bulletin 923.Kress, D.D. 2001.
Calf weight/cow weight ratio of weaning as a pre-
dictor of beef cow efficiency. Proceedings, Western
Section,ASAS. Vol. 52.
MacNeil, M.D. 2005. J. Anim. Sci. 83:794-802.
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AAES Research Series 553
Table 1. Descriptive statistics for each purebred
population.Traita N Mean SD Minimum Maximum
Angus Birth wt, lb 3,872 62.88 11.19 27.00 118.00 Wt205, lb
3,341 387.49 53.66 162.00 605.00 CowWt, lb 2,907 913.92 125.91
554.00 1575.00 WnRatio 2,611 0.43 0.06 0.18 0.73
HerefordBirth wt, lb 2,445 69.46 10.97 29.00 104.00 Wt205, lb
2,106 384.33 57.12 184.00 573.00 CowWt, lb 1,964 999.64 124.10
645.00 1548.00 WnRatio 1,767 0.39 0.06 0.19 0.60
Charolais
Birth wt, lb 575 91.34 15.44 38.00 152.00 Wt205, lb 489 473.92
81.67 193.00 692.00 CowWt, lb 376 1220.29 164.35 800.00 1660.00
WnRatio 316 0.40 0.06 0.20 0.63
Red Poll Birth wt, lb 349 78.50 11.10 50.00 105.00 Wt205, lb 301
430.01 64.88 245.00 620.00 CowWt, lb 246 971.56 135.06 700.00
1472.00 WnRatio 217 0.45 0.06 0.29 0.63
Chianina Birth wt, lb 98 106.39 12.17 80.00 138.00 Wt205, lb 73
473.66 77.57 318.00 708.00 CowWt, lb 94 1318.03 146.37 1010.00
1711.00 WnRatio 71 0.36 0.06 0.23 0.50 aBirth and 205-d weight
(Wt205) of calf, cow weight (CowWt) at weaning of her calf and the
ratio of calf weight at 205 d of age to cow weight at weaning
(WnRatio).
Table 2. Estimates of direct and maternal heritability
coefficients (± approximate standard error) for each breed.
Heritability (h2) Traita Angus Hereford Charolais Red Poll
Analyses with Brwt and Wt205
Direct Brwt 0.59 ± 0.04 0.36 ± 0.05 0.63 ± 0.12 0.37 ± 0.19
Maternal Brwt 0.12 ± 0.02 0.16 ± 0.03 0.08 ± 0.06 0.05 ± 0.10
Direct Wt205 0.38 ± 0.05 0.21 ± 0.05 0.30 ± 0.13 0.10 ± 0.12
Maternal Wt205 0.19 ± 0.03 0.25 ± 0.03 0.23 ± 0.07 0.44 ± 0.08
Analyses with Brwt and CowWtDirect Brwt 0.55 ± 0.04 0.34 ± 0.05
0.52 ± 0.12 0.33 ± 0.19 Maternal Brwt 0.14 ± 0.02 0.17 ± 0.03 0.08
± 0.06 0.05 ± 0.10 Direct CowWt 0.62 ± 0.03 0.62 ± 0.04 0.63 ± 0.10
0.89 ± 0.09
Analyses with Brwt and WnRatio Direct Brwt 0.59 ± 0.04 0.31 ±
0.05 0.52 ± 0.12 0.40 ± 0.12 Maternal Brwt 0.16 ± 0.02 0.21 ± 0.03
0.16 ± 0.06 0.05 ± 0.10 Direct WnRatio 0.15 ± 0.04 0.03 ± 0.03 0.09
± 0.13 0.00 ± 0.12 Maternal WnRatio 0.46 ± 0.03 0.56 ± 0.03 0.39 ±
0.09 0.70 ± 0.08 aBirth (Brwt) and 205-d weight (Wt205) of calf,
cow weight (CowWt) at weaning of her calf and the ratio of calf
weight at 205 d of age to cow weight at weaning (WnRatio).
Table 3. Least-squares means (± SE) by breed for weight of calf
at birth and 205 days of age, cow weight at weaning and weaning
ratio.
Traita
Breed Birth wt, lb Wt205, lb CowWt, lb WnRatio Angus 63.6 ± 0.7
f 384.5 ± 3.3 d 918 ± 6 e 0.427 ± 0.003 c
Hereford 70.5 ± 0.7 e 383.3 ± 3.6 d 1,012 ± 6 d 0.383 ± 0.003
e
Charolais 87.2 ± 1.1 c 468.9 ± 5.7 b 1,196 ± 12 c 0.407 ± 0.006
d
Red Poll 74.6 ± 1.9 d 420.9 ± 9.3 c 932 ± 18 e 0.469 ± 0.008
b
Chianina 98.9 ± 2.9 b 456.1 ± 14.2 bc 1,250 ± 23 b 0.375 ± 0.011
eaBirth wt and 205-d weight (Wt205) of calf, cow weight (CowWt) at
weaning of her calf and the ratio of calf weight at 205 d of age to
cow weight at weaning of her calf (WnRatio). b,c,d,,e,f Within a
column, least-squares means without a common superscript differ (P
< 0.05).
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13
Introduction
Measurement of maternal body condition and (or) bloodmetabolites
late in gestation may help predict subsequent calf per-formance.
Body condition score (BCS) of cows can be assessed withthe nine
point BCS system with 1 being thin and 9 being fat(Wagner et al.,
1988). Ultrasonography is a good estimator of sub-cutaneous fat
thickness in grazing cattle (Aiken et al., 2004), andrecently,
several research groups (Miller et al., 2004; Schröder
andStaufenbiel, 2006) have suggested ultrasonography may
alleviatesome of the subjectivity of BCS.
Relationships between various prepartum metabolic hor-mones in
cows and subsequent calf birth weights have been inves-tigated;
however, the relationship between maternal lactate dehy-drogenase
(LDH) activity and calf performance has not been exam-ined. Lactate
dehydrogenase is the last enzyme of the glycolyticpathway, and
catalyzes the reversible conversion of pyruvate to lac-tate.
Reduced LDH activity has been associated with increased car-cass
quality in steers (Flores et al., 2005) and increased
reproductiveperformance of heifers (Looper et al., 2002).
Objectives were toexamine 1) relationships between LDH activity and
body measure-ments of grazing beef cows, and 2) the association
between mater-nal LDH activity in late gestation and subsequent
calf birth weight(BRW), hip height (CALFHH) at weaning, and
adjusted weaningweight (205-day WW).
Experimental Procedures
Eighty-eight Angus and Charolais cows (age = 5.1 ± 2.6 yr)and
their Angus-sired calves (n = 86) from a private farm inCrawford
County, Ark., were used. Cattle grazed endophyte-infect-ed tall
fescue pastures during the cooler months and commonbermudagrass
pastures during the warmer months. At 60 daysbefore calving (mean
calving date = January 29), BW, BCS, and cowhip height (COWHH) were
recorded, and longissimus muscle area(LMA), intramuscular fat
percentage (IMF), and rib fat (RF) weremeasured via ultrasonography
using an Aloka SSD-500V with a3.5-MHz linear array transducer.
Cross-sections of the LMA werescanned between the 12th and 13th
ribs, and RF at 3-quarters thewidth of the LMA. Blood samples were
collected into vacutainers(Becton Dickinson, Franklin Lakes, N.J.),
allowed to clot for 24 h at40°F, and centrifuged (1500 x g for 25
min). Serum samples werestored at 0°F until analysis.
Lactate dehydrogenase activity was measured via a colorimet-ric
assay. Enzyme activity is expressed in IU/L. Concentrations ofLDH
activity were ranked into three categories by using the
meanconcentration ± 1 SD. The 3 categories with associated
concentra-tions of LDH activity are shown in Table 1.
Calves were spring-born, and birth weight and sex of calf
wererecorded. Calves remained with dams until weaning, and
CALFHHand weight were recorded at weaning. Eleven calves were
early-weaned (June 19) while the remaining 75 calves were weaned
onAugust 31. Weaning weight was adjusted to a standard
205-dayweaning weight.
1 Names are necessary to report factually on available data;
however, the USDA does not guarantee orwarrant the standard of the
product, and the use of the name by the USDA implies no approval of
theproduct to the exclusion of others that also may be
suitable.
2 USDA-ARS, Dale Bumpers Small Farms Research Center,
Booneville, Ark.3 Neidecker Farms, Van Buren, Ark.4 University of
Arkansas Cooperative Extension Service, Van Buren, Ark.5 Department
of Animal Science, University of Arkansas, Fayetteville, Ark.
Story in Brief
Objectives were to examine 1) relationships between lactate
dehydrogenase (LDH) activity and body measurements of beefcows, and
2) the association between maternal LDH activity in late gestation
and subsequent calf birth weight (BRW), hip height(CALFHH) at
weaning, and adjusted weaning weight (205-day WW). At 60 days
before calving, BW, body condition score (BCS),and cow hip height
(COWHH) were recorded, and longissimus muscle area (LMA),
intramuscular fat percentage (IMF), and ribfat (RF) were measured
via ultrasonography from Angus x Charolais cows (n = 88). A blood
serum sample was collected from eachcow and concentrations of LDH
activity were determined and ranked (mean ± 1 SD) into 3
categories. Cows with low reverse LDHactivity had calves with
increased (P < 0.05) CALFHH and 205-day WW compared with cows
with high LDH activity. Cow LMAwas correlated (P < 0.05) with
BW, BCS, and COWHH, and 205-day WW of calves. The canonical
correlation between cow for-ward and reverse LDH activity, and
205-day WW and CALFHH of calves tended to be significant (r = 0.30;
P = 0.08). Further, thecanonical correlation between cow traits
including LMA, IMF, and RF, and calf traits of 205-day WW and
CALFHH was signifi-cant (P = 0.02). Cow LMA and reverse LDH
activity were correlated (P < 0.01) to 205-d WW and CALFHH (r =
0.38). Decreasedreverse LDH activity in prepartum cows was
associated with taller and heavier calves at weaning; increased
weaning weights willenhance profitability of Arkansas cow-calf
operations.
Relationship of Lactate Dehydrogenase Activity with Body
Measurements ofAngus x Charolais Cows and Calves1
M.L. Looper2, T.P. Neidecker3, C.W. Wall4, S.T. Reiter5, R.
Flores5, A.H. Brown, Jr.5, Z.B. Johnson5, and C.F. Rosenkrans,
Jr.5
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14
AAES Research Series 553
Statistical analyses. The effect of cow age on LDH forward
andreverse activity was analyzed by ANOVA using the MIXED
proce-dure of SAS (SAS Inst. Inc., Cary, N.C.). The effects of
prepartumLDH forward and reverse activity category (low, medium, or
high)on BRW, CALFHH, and 205-day WW also were analyzed byANOVA
using the MIXED procedure of SAS. Chi-square analysiswas used to
determine the effect of prepartum LDH forward andreverse activity
category (low, medium, or high) on gender of calf.Relationships
among prepartum cow traits (BW, BCS, COWHH,LMA, IMF, and RF), and
between prepartum cow traits and subse-quent calf traits (BRW,
CALFHH, and 205-day WW) were exam-ined by Pearson and canonical
correlations. Objective of canonicalcorrelation analysis was to
find a linear combination of one groupof variables (cow traits)
that had a maximal correlation with a lin-ear combination of a
second group of variables (calf traits). Theanalysis continues
until the number of pairs of canonical variablesequals the number
of variables in the smaller group. Three separatecanonical analyses
were examined in this experiment. The firstcanonical correlation
analysis (Analysis 1) compared cow LDH for-ward and reverse
activity (Set 1) with 205-day WW and CALFHHof calves (Set 2). The
second canonical correlation analysis(Analysis 2) compared the cow
traits of LMA, IMF, and RF (Set 1)with the set of calf traits that
included 205-day WW and CALFHH(Set 2). The third canonical
correlation analysis (Analysis 3) was acombination of LDH activity
and ultrasound measurement withcow reverse LDH activity and LMA
(Set 1) with 205-d WW andCALFHH of calves (Set 2).
Results and Discussion
Relationships among cow measurements. Age of cow did
notinfluence prepartum forward (P = 0.19) or reverse (P = 0.46)
LDHactivity. Mean concentrations of forward and reverse LDH
activitywere 748 ± 48 IU/mL and 227 ± 26 IU/mL, respectively. Sire
breedof the cow did not influence (P = 0.82) forward LDH
activity(mean = 747± 18 IU/mL); however, Angus-sired cows tended (P
=0.07; 242 ± 7 IU/mL) to have greater prepartum reverse LDH
activ-ity than Charolais-sired cows (219 ± 11 IU/mL). Prepartum
LDHactivity (forward or reverse) was not correlated (P > 0.10)
with anycow measurements with the exception of cow BCS and
forwardLDH activity (r = 0.21; P = 0.09).
Longissimus muscle area (r = 0.39; P < 0.05) and RF (r =
0.26;P < 0.05) measured with ultrasound were moderately
correlated tovisual BCS. Others (Miller et al., 2004; Schröder and
Staufenbiel,2006) have suggested that ultrasound provides a more
precise esti-mate of body condition than visual BCS.
Relationships between cow prepartum LDH activity and
calfmeasurements. Distribution of calf gender was similar (P >
0.10)among the 3 categories of prepartum LDH activity (forward
orreverse). Cows with low reverse LDH activity had calves
withincreased 205-day WW (P = 0.03; Fig. 1) and CALFHH (P =
0.001;Fig. 2) compared with cows with high LDH activity. Reverse
LDHactivity was inversely correlated with CALFHH (r = -0.28; P =
0.01)and 205-day WW (r = -0.21; P = 0.05) of calves. Forward
LDHactivity tended (P = 0.11) to be negatively correlated (r =
-0.18)with CALFHH. Similarly, reduced LDH activity in steers
(Flores etal., 2005) and heifers (Looper et al., 2002) was
associated withincreased animal performance.
Cow LMA was correlated (P < 0.05) with BW (r = 0.37), BCS(r =
0.39), and COWHH (r = 0.25) in cows, and with 205-day WWof calves
(r = 0.28; P = 0.01). First canonical correlation (Analysis1)
between cow forward and reverse LDH activity, and CALFHHand 205-day
WW tended to be significant (r = 0.30; P = 0.08; datanot shown).
Further, the canonical correlation between the set ofcow traits
including LMA, IMF, and RF (Analysis 2) was correlated(r = 0.36; P
= 0.02; data not shown) with the set of calf traits thatincluded
205-day WW and CALFHH. Of all 3 canonical correlationanalyses, a
linear combination of cow LMA and reverse LDH activ-ity (Analysis
3) had the highest (P < 0.01) canonical correlationwith a linear
combination of calf 205-day WW and CALFHH (r =0.38; Table 2). Our
data suggest that a combination of both ultra-sonography
measurements as well as LDH activity in cows may bea better
predictor of calf measurements (hip height and adjustedweaning
weight) at weaning than ultrasound or LDH activityalone.
Development of a ‘chute-side’ LDH activity test (enzyme-linked
assay) is warranted if threshold concentrations of LDHactivity are
substantiated with future research studies using largernumbers of
cattle. Ideally, producers would collect a minimalamount of blood
from the cow (i.e., skin prick of ear), place bloodin the LDH test
cartridge, and wait a short amount of time (i.e., 2-3 minutes) for
a positive/negative result. It is estimated that such achute-side
test would cost producers $10-15/test. Beef producersare likely to
utilize any test that will allow them to make manage-ment decisions
about weaned calves much earlier in the productioncycle; however,
economic analyses of a chute-side LDH activity testare needed.
Implications
Decreased reverse LDH activity in prepartum cows was associ-ated
with taller and heavier calves at weaning. Use of prepartummaternal
LDH activity may help in selection of superior calves ear-lier in
the production cycle enhancing profitability of cow-calfoperations
in Arkansas.
Acknowledgment
The technical assistance of Larry Huddleston, Brent Woolley,and
Sam Tabler, USDA-ARS, Booneville, Ark., is
gratefullyacknowledged.
Literature Cited
Aiken, G. E., et al. 2004. Prof. Anim. Sci. 20:246.Flores, R.,
et al. 2005. Proc. West. Sec. Am. Soc. Anim. Sci. 56:240.Looper, M.
L., et al. 2002. Prof. Anim. Sci. 18:120.Miller, L. R., et al.
2004. Proc. West. Sec. Am. Soc. Anim. Sci. 55:163.Schröder, U. J.,
and R. Staufenbiel. 2006. J. Dairy Sci. 89:1.Wagner, J. J., et al.
1988. J. Anim. Sci. 66:603.
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Arkansas Animal Science Department Report 2007
15
Table 1. Concentrations of maternal lactate dehydrogenase (LDH)
activity (forward and reverse) ranked (mean ± 1 SD) into one of
three categories.
Category n LDH activity (IU/mL) LDH forward Low 9 592 ± 66
Medium 66 741 ± 56 High 13 920 ± 41
LDH reverse Low 17 164 ± 13 Medium 56 231 ± 27 High 15 327 ±
21
Table 2. Canonical correlations of prepartum cow traits (Set 1)
with subsequent calf performance traits (Set 2) (Analysis 3).
Set 1 (cow traits)a V1 V2
LMA 0.67 0.74 LDHr -0.66 0.76
Set 2 (calf traits) W1 W2205-day WW 0.97 0.23 CALFHH 0.73
-0.68
Canonical correlation 0.38* 0.18
*P < 0.01
aLMA is longissimus muscle area; LDHr is lactate dehydrogenase
reverse activity; 205-day WW is 205-d weaning weight of
calves; and CALFHH is hip height of calves at weaning.
0
100
200
300
400
500
600
700
Low LDHr Medium LDHr High LDHr
205-
dW
W,l
bin
aa
b
05
101520253035404550
Low LDHr Medium LDHr High LDHr
Hip
heig
ht,i
nche
sin
a bb
Fig. 1. Influence of maternal reverse lactate dehydrogenase
(LDHr) activity on 205-day weaning weight (205-d WW) of Angus-sired
calves (a,bP = 0.03).
Fig. 2. Influence of maternal reverse lactate dehydrogenase
(LDHr) activity on hip height at weaning of Angus-sired calves
(a,bP = 0.001).
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16
Introduction
Morbidity in receiving cattle is a costly economic problem
thatmay, in part, be addressed by nutritional intervention.
Previousresearch indicates that not only are there medication costs
associat-ed with morbid cattle, but that these cattle usually grow
slowerthroughout the feedlot phase, are less efficient in
converting feed togain, and their carcasses grade lower after
slaughter. Thus, improv-ing health and growth during the receiving
period is of interest.Trace minerals are some of the nutrients that
impact immune func-tion; therefore, the objective of this study was
to compare twosources of zinc, copper, manganese, and cobalt in
backgroundingdiets for cattle.
Experimental Procedures
Two hundred and eighty-eight male calves (77 steers and
211bulls) initially averaging 527 lb were obtained from sale barns
insouth-central Arkansas or eastern Oklahoma and shipped to
theUniversity of Arkansas Beef Cattle Facility at Savoy. Calves
arrivedin 3 sets with arrival dates of January 10 (n = 96), January
31 (n =98), and March 8, 2006 (n = 94). Upon arrival, calves were
ear-tagged with an individual identification number, weighed, and
keptin a common pen with access to hay and water overnight. The
fol-lowing morning, calves were given viral (BoviShield Gold 5,
Pfizer,New York, N.Y.) and clostridial (Covexin 8,
Schering-Plough,Branchburg, N.J.) vaccinations, and were dewormed
(Cydectin,Fort Dodge, Madison, N.J.). Bulls were castrated by
banding(California Bander, Inosol Co. LLC, El Centro, Calif.), and
hornedanimals had their horns tipped. All calves were branded
andweighed.
Within each set of calves, calves were allocated randomly
with-in 4 weight blocks (using the arrival weight) to pen (2
pens/weightblock; 11 to 13 calves/pen). Pens within block were
randomlyassigned to treatment. Calves were housed on 1.1-acre grass
pad-docks. All calves were fed grain supplements (Tables 1, 2, and
3)that served as the carrier of each of the 2 treatments.
Treatmentsconsisted of supplemental zinc (360 mg/d), copper (125
mg/d),manganese (200 mg/d), and cobalt (12 mg/d) from inorganic
ororganic (Availa-4, Zinpro Corp. Eden Prairie, Minn.)
sources.Calves were offered 2 lb supplement on the first day. There
were 2supplements (one/dietary treatment) formulated for feeding at
the2 lb/d rate. When the majority of the calves in each pen were
con-suming the supplement, the pen was switched to supplements
withthe appropriate mineral treatment that were formulated for
feedingat the 3 lb/d rate (d 7, Set 1; d 6, Set 2; d 5, Set 3), and
then the 4lb/d rate (d 14, Set 1; d 9, Sets 2 and 3), with the
calves receivingthese supplements for the remainder of the 42-d
trial. Calves had adlibitum access to bermudagrass hay (10.1% CP,
DM basis). Samplesof supplements and the hay were analyzed for DM,
CP by totalcombustion, and trace minerals by inductively coupled
plasmaspectroscopy (ICP) after wet ashing (Table 3). Booster
vaccinationswere given on d 14.
Calves were observed daily for signs of morbidity beginningthe
day after processing. Calves were scored by one of the pencheckers
and given a clinical illness score of 1 to 5 (Table 4). Calveswith
a score > 1 were brought to the chute and a rectal
temperaturewas taken. If the rectal temperature was ≥ 104°F, the
calf was treat-ed according to a preplanned antibiotic regimen
(Table 5). Recordswere kept of all antibiotics given. Sick animals
were returned totheir home pen for convalescence.
Weights were taken initially and prior to supplement feedingon d
7, 14, 28, 41, and 42. Average daily gain was calculated, based
1 Department of Animal Science, Fayetteville2 Zinpro Corp., Eden
Prairie, Minn.
Story in Brief
Male beef calves (n = 288, avg BW 527 lb) were obtained from
sale barns. Within each set (n = 3), calves were allocated
ran-domly within 4 weight blocks to pen (2 pens/ block; 11 to 13
calves/pen). Pens within block were randomly assigned to
treatment.During the 42-d backgrounding period, calves were on
1.1-acre paddocks, had ad libitum access to bermudagrass hay, and
werefed corn-soybean meal supplements that served as the carrier
for treatments. Treatments consisted of supplemental zinc
(360mg/d), copper (125 mg/d), manganese (200 mg/d), and cobalt (12
mg/d) from inorganic (zinc sulfate, manganese sulfate,
coppersulfate, and cobalt carbonate) or organic (zinc amino acid
complex, manganese amino acid complex, copper amino acid
complex,and cobalt glucoheptonate; Availa®4, Zinpro Corp., Eden
Prairie, Minn.) sources. Calves supplemented with organic trace
miner-al sources had a greater final weight (598 vs. 588 lb for
organic and inorganic, respectively; P = 0.04) and ADG (1.7 vs. 1.5
lb/d fororganic and inorganic, respectively; P = 0.04) than calves
supplemented with trace minerals from inorganic
sources.Supplementation with organic trace minerals tended (P =
0.09) to reduce the percentage of calves that received a second
antibiot-ic treatment. When calves that had initial antibodies to
infectious bovine rhinotracheitis virus (IBRV) were removed, there
was aneffect of dietary treatment (P = 0.03) in the naïve calves.
Calves supplemented with inorganic trace minerals had a greater
anti-body response to IBRV vaccination. Organic trace mineral
supplementation improved growth performance of shipping
stressedcalves compared to those fed equivalent levels of inorganic
sources.
Supplemental Trace Minerals (Zn, Cu, Mn, And Co) as Availa®4 or
Inorganic Sources for Shipping-Stressed Cattle
M.R. Pass1, E.B. Kegley1, and C.K. Larson2
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Arkansas Animal Science Department Report 2007
17
on averages of initial and final weights that were taken on
consecu-tive days; and any feed refusals were noted. Calves were
bled on d 0,14, and 41. Plasma from d 0 and 41 was analyzed for
zinc and cop-per by ICP. Serum from d 0, 14, and 41 was analyzed
for antibodytiters for infectious bovine rhinotracheitis virus
(IBRV), parain-fluenza virus 3 (PI3), bovine respiratory syncytial
virus (BRSV), andbovine viral diarrhea (BVD) at the Oklahoma Animal
DiseaseDiagnostic Laboratory (Oklahoma State University,
Stillwater, Okla.).
Growth performance, medication costs and number of
treat-ments/calf were analyzed using MIXED procedures of SAS
(SASInstitute, Inc., Cary, N.C.) as a randomized complete block
design.The model included treatment as a fixed effect, and set of
calves,and BW block as random effects. Plasma trace mineral
concentra-tions and antibody titer responses were analyzed using a
repeatedstatement and the covariance structure SP (POW); the
subject ofthe repeated statement was pen within set of calves. The
modelincluded set, block, treatment, day, and the day by treatment
inter-action. Pen was used as the experimental unit for these
analyses.Morbidity data (whether calves were treated one, two, or
threetimes with antibiotics) were analyzed using Chi-square
analyseswith calf as the experimental unit. The LIFETEST procedure
wasalso used to compare when calves received their first, second,
third,or last antibiotic treatment; with calf as the experimental
unit.
Results and Discussion
Calves supplemented during the receiving period with organ-ic
sources of trace minerals had a 10 lb greater final weight (P
=0.04) and 0.24 lb greater ADG than calves supplemented with
thesame levels of trace minerals from inorganic sources (Table
6).
Sixty three percent of these sale barn calves were treated
forbovine respiratory disease, and there was no effect (P = 0.46)
ofsupplemental trace mineral source on the percentage of calves
thathad to be treated with an initial antibiotic (Table 7).
However, sup-plementation with organic trace minerals tended (P =
0.09) toreduce the percentage of calves that received a second
antibiotic forbovine respiratory disease. Numerically, 5 calves
that were supple-mented with inorganic trace minerals were deemed
“chronics” ver-sus 2 calves that were supplemented with organic
trace minerals.Cattle considered “chronics” were those that did not
show improve-ment after receiving the 3 antibiotic treatments.
Supplemental tracemineral source did not affect (P ≥ 0.67) the
average number ofantibiotic treatments or the medication costs
(Table 7). The day ofthe study that the first or third antibiotic
treatment was given wasnot impacted by supplemental trace mineral
source (Table 8 andFig. 1). However, calves supplemented with
organic trace mineralstended (P = 0.08) to receive the second
treatment 1 d later thancalves supplemented with inorganic trace
minerals.
Antibody response to vaccination was compared in all calves,and
was also compared in the subpopulation of calves that did nothave
detectable antibodies to the virus of interest on d 0
(naïvecalves). The size of this subpopulation varied by virus
(BRSV, n =166; BVD, n = 207; IBR, n = 262; and PI3, n = 95). There
was aneffect (P < 0.001) of sampling day in all models; calves
did produceantibodies in response to vaccination. There was no
effect (P ≥0.12) of dietary treatment or a dietary treatment by
sampling dayinteraction on BRSV, BVD, or PI3. A dietary treatment
by samplingday interaction for IBRV was detected when all calves
were consid-ered (P = 0.05); calves supplemented with inorganic
trace mineralshad greater antibody titers to IBRV on d 14 (P =
0.09) and d 41 (P= 0.07) than calves supplemented with organic
trace minerals.When calves that initially had antibodies to IBRV
were removed,there was a main effect of treatment (P = 0.03) and a
tendency fora treatment by sampling day interaction (P = 0.06).
Calves supple-mented with inorganic trace minerals had a greater
antibodyresponse to IBRV vaccination on d 14 (P = 0.02) and 41 (P =
0.01)than those supplemented with organic trace minerals.
There was no effect (P ≥ 0.24) of supplemental trace
mineralsource on the plasma concentrations of zinc or copper (Table
9).Plasma zinc concentrations were increased (P = 0.02) on d 41
com-pared to d 0.
Implications
Supplementation with organic sources of trace mineralsimproved
growth performance of shipping stressed cattle for theinitial 42 d
as compared to equivalent levels of inorganic sources ofzinc,
copper, manganese, and cobalt.
Acknowledgments
The authors wish to express their appreciation to ZinproCorp.,
Eden Prairie, Minn., for funding this project. P. Hornsby, G.Carte,
and S. Behrends are greatly appreciated for their assistancewith
this research and care of the cattle.
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18
AAES Research Series 553
aVitamin ADE premix contains 4,000,000 IU vitamin A, 800,000 IU
vitamin D, and 500 IU vitamin E/lb. bVitamin E premix contains
20,000 IU/lb. cTo provide 160 mg monensin/d when supplement fed at
4 lb/d.
Table 1. Ingredient composition of grain supplements. Fed at 2
lb/d Fed at 3 lb/d Fed at 4 lb/d
Ingredient Inorganic Organic Inorganic Organic Inorganic Organic
Corn-cracked, % 56.3 56.3 68.9 68.9 75 75 Soybean meal, % 34 34
23.2 23.2 18 18 Molasses, % 2 2 2 2 2 2 Fat, yellow grease, % 1 1 1
1 1 1 Dicalcium phosphate, % 0.9 0.9 0.4 0.4 0.18 0.18 Limestone, %
2.4 2.4 2 2 1.8 1.8 Salt, white, % 2 2 1.5 1.5 1 1 Availa-4, g/ton
- 6,982 - 4,667 - 3,500 Zinc sulfate (35.5% Zn), g/ton 1011 - 676 -
507 - Manganese sulfate (32% Mn), g/ton 623.5 - 416.7 - 312.5 -
Copper sulfate (25.2% Cu), g/ton 494.7 - 330.7 - 248 - Cobalt
carbonate (46% Co), g/ton 25.9 - 17.4 - 13 - Sodium selenite (0.99%
Se), g/ton 100.8 100.8 67.3 67.3 50.5 50.5
Vitamin ADE premixa, % 0.2 0.2 0.14 0.14 0.1 0.1 Vitamin E
premix b, % 0.1 0.1 0.07 0.07 0.05 0.05 Rumensin mixc, % 0.8 0.8
0.54 0.54 0.4 0.4
Table 2. Calculated nutrient composition of supplements, DM
basis. Fed at 2 lb/d Fed at 3 lb/d Fed at 4 lb/d
Nutrient Unit Inorganic Organic Inorganic Organic Inorganic
Organic CP % 24.2 24.2 19.4 19.4 17.1 17.1 NEm Mcal/100 lb 95.8
95.8 97.9 97.9 99.2 99.2 NEg Mcal/100 lb 63.8 63.8 64.7 64.7 65.4
65.4 Ca % 1.4 1.4 1.1 1.1 0.9 0.9 P % 0.6 0.6 0.45 0.45 0.39 0.39
Zn mg/d 360 360 360 361 360 360 Mn mg/d 200 200 200 200 200 200 Cu
mg/d 125 125 125 125 125 125 Co mg/d 12 12 12 12 12 12 Se mg/d 1 1
1 1 1 1
Table 3. Analyzed nutrient composition of supplements, DM basis.
Fed at 2 lb/d Fed at 3 lb/d Fed at 4 lb/d
Nutrient Unit Inorganic Organic Inorganic Organic Inorganic
Organic DM % 93.6 94.1 90.6 91.7 91.0 91.0 CP % 23.1 23.1 18.5 18.1
16.6 17.5 Zn mg/kg 410. 438. 312. 303. 243. 259. Mn mg/kg 271. 272.
224. 182. 114. 152. Cu mg/kg 152. 166. 119. 115. 92. 93. Co mg/kg
13.2 13. 9.6 8.6 6.5 6.9
-
Arkansas Animal Science Department Report 2007
19
Table 4. Clinical illness scores for calvesa.
Score Description Appearance
1 Normal No abnormal signs noted
2 Slightly ill Mild depression, gaunt, +/- ocular/nasal
discharge
3 Moderately ill Ocular/nasal discharge, gaunt, lags behind
other animals in the group, coughing, labored breathing, moderate
depression, +/- rough hair coat, weight loss
4 Severely ill Severe depression, labored breathing, purulent
ocular/nasal discharge, not responsive to human approach
5 Moribund Near death aModified from clinical assessment score
criteria provided by Dr. Dianne Hellwig, DVM.
Table 5. Treatment schedule for calves treated for BRD.
Therapy 1: Nuflor (Schering-Plough Animal Health, Branchburg,
NJ), 6 mL/100 lb BW, subcutaneous in neck x Check in 48 h. If
clinical illness score > time 0 score or 2 and rectal
temperature is 104ºF,
then consider the treatment a failure and go to Therapy 2,
otherwise consider the treatment a success.
Therapy 2: Baytril (Bayer, Shawnee, KS), 5 mL/100 lb BW
subcutaneous in neck x Check in 48 h. If clinical illness score
> time 0 score or 2 and rectal temperature is 104ºF,
then go to Therapy 3 (treatment failure) otherwise consider the
treatment a success.x Also for animals that recovered from Therapy
1 and relapsed at a later date.
Therapy 3: Excede (Pfizer, New York, NY), 1.5 mL/100 lb BW
subcutaneous in back of ear x Check on fourth day. If clinical
illness score > time 0 score or 2 and rectal temperature is
104ºF, then this is a treatment failure and the calf is
identified as a “chronic”, otherwise consider the treatment a
success.
x Also for animals that recovered from therapy 2 and relapsed at
a later date.
If bovine respiratory disease symptoms occur > 21 d after
administering the previous therapy, then considered a new episode
andbegin again with Therapy 1.
-
20
AAES Research Series 553
A B
C
Fig. 1. Curves generated with the LIFETEST procedure of SAS for
day the calves received their first (A); second (B), P = 0.08; and
third (C) antibiotic treatments.
-
Arkansas Animal Science Department Report 2007
21
012345678
0 14 28 42
Time, d
BV
D,l
ogof
Ab
titer
0
1
2
3
4
5
6
0 14 28 42
Time, d
BR
SV
,log
Ab
titer
InorganicOrganicNaïve -- InorganicNaïve -- Organic
012345678
0 14 28 42
Time, d
PI3
,log
Ab
tite r
-0.50
0.51
1.52
2.53
3.5
0 14 28 42
Time, d
IBR
,log
Ab
titer
A B
C D
Fig. 2. Response to vaccination with modified live vaccine for
respiratory viruses, (A) antibodies to bovine respi-ratory
syncytial virus (BRSV); (B) antibodies to bovine viral diarrhea
(BVD); (C) antibodies to infectious bovinerhinotracheitis virus
(IBRV), all calves in model – treatment x day interaction P = 0.05,
naïve calves in model –
treatment P = 0.03 and treatment x day interaction P= 0.06; and
(D) antibodies to parainfluenza type 3 (PI3).
-
Introduction
The University of Arkansas Cooperative Extension ServiceSteer
Feedout Program provides cow-calf producers the opportuni-ty to
acquire information about post-weaning performance andcarcass
characteristics of their calves. It also points out factors
thatinfluence value beyond the weaned calf phase of beef
production.The program is not a contest to compare breeds or
breeders or topromote retained ownership. The Feedout Program
creates anopportunity for producers to determine how their calf
crop fits theneeds of the beef industry. The program also provides
the informa-tion needed to determine if changes in genetics and/or
manage-ment factors are warranted for producers to be competitive
in beefproduction.
Experimental Procedures
On November 10, 2005, 139 steer calves from 16 Arkansas
pro-ducers representing 11 counties were placed on feed at
WheelerBrothers Feedyard in Watonga, Oklahoma. Producers
wererequired to administer 5-way modified live vaccinations to
allcalves and were encouraged to precondition the calves for a
mini-mum of 30 days prior to shipment. Calves were weighed
andprocessed on November 11, 2005. Processing included weight
col-lection, deworming, implanting with a growth implant, and
eartagging with a feedlot lot tag. All calves were placed in one
pen.Management factors such as processing, medical treatments
andrations were the same as the other cattle in the feedyard. This
wasthe first year that electronic ear tags (EID) were used in the
pro-gram. The EID tags helped the feedyard and Extension
personnelmanage individual animal medicine costs and weights. The
feed-yard manager and Extension personnel selected animals for each
ofthe 3 harvest groups when they reached the weight and
conditionregarded as acceptable for the industry and market
conditions.Cattle were sold on a carcass basis with premiums and
discounts forvarious quality grades, yield grades and carcass
weights. Feed, pro-cessing and medicine costs were financed by the
feedyard. Allexpenses were deducted from the carcass income, and
proceedswere sent to the owners. Of the 139 steers that started on
feed in thefall, one died (0.99% death loss). One calf suffered
from severe
bloat, and was sold to a local packing plant where its carcass
wascondemned. These 2 calves were not included in the
statisticalanalyses; therefore, 137 steers were used in the
analyses.
Carcasses were placed in 2 groups according to industry
stan-dards for carcass merit. Carcass groups were 1) fit industry
stan-dards (at least USDA Choice, Yield Grade < 3.5, and hot
carcassweight between 550 and 950 lb) or 2) did not fit industry
standards.The main effect of carcass group and the interaction with
depend-ent variables carcass value, average daily gain (ADG), and
netreturn were determined using PROC GLM of SAS ( SAS Inst.
Inc.,Cary, N.C.). Least-squares means were calculated with the
PDIFFoption and reported.
Calves were sorted into categories based upon their
feedlotreturn (income minus feedlot direct expenses). Data from
calves inthe top 25% and bottom 25% were sorted out for further
analysis.Factors affecting feedlot return for the top 25% and the
bottom25% were determined using the Stepwise method of PROC REG
ofSAS. Independent variables included initial (arrival) weight;
per-centage Brahman, English, and Continental breeding; ADG;
YieldGrade; Quality Grade; feed cost per pound of gain; hot
carcassweight; days on feed; medicine cost; ribeye area; ribeye
area per 100lb of hot carcass weight; and dressing percentage. The
breeding per-centages were provided by the producer upon
delivery.
Results and Discussion
The financial summary is reported in Table 1. Average
grossincome per head was $1,029.17 (range = $504 to $1,315). The
feed-lot return averaged $686.76; whereas, the calculated
returns,accounting for the initial value of the calf at arrival,
averaged$32.99 (range = $-188 to $259).
The sick pull rate was high with 80 calves (56%) treated
forsickness. Still, this is a dramatic improvement over last year's
80%pull rate. The pull rate was high for cattle that were all
listed asbeing preconditioned. The average medicine cost for the
entire penwas $13.39 per head, $30 less than last year's average.
The healthstatus of cattle in the feedyard usually has a major
impact on per-formance and profit. Healthy steers had numerically
higher feedlotnet returns ($703) than steers that became sick
($674) but this dif-ference was not statistically significant. No
differences were noted
22
1 Animal Science Section, Cooperative Extension Service, Little
Rock.
Story in Brief
The objective of the Arkansas Steer Feedout Program is to
provide cow-calf producers information about the
post-weaningfeedlot performance and carcass characteristics of
their calves. For the 2005-2006 feedout, quality grade, initial
weight, hot carcassweight, yield grade and medicine costs were all
factors that affected (P < 0.05) the feedlot return over
specified costs. Cow calf pro-ducers who participated in the
program can use the information to evaluate how their cattle
breeding programs fit the needs ofthe beef cattle industry.
Arkansas Steer Feedout Program2005-2006
B. Barham, S. Gadberry, J. Richeson, and S. Cline1
-
between healthy and sick steers for ADG, hot carcass weight,
feedcost per pound of gain, total cost per pound of gain, dressing
per-centage, yield grade, ribeye area, and ribeye area per cwt. of
carcassweight (P > 0.10). Previous feedout data indicate that
health status(healthy vs. sick) negatively impacts feedlot and
carcass perform-ance. Given past health issues that cattle in the
program have faced,Arkansas producers need to implement a sound
health manage-ment plan. Arkansas producers should consult with
their veterinar-ian on designing a vaccination program for their
herd. By imple-menting a sound vaccination program at the ranch of
origin, pre-dictability and consistency of calves increases along
with productvalue, and calves have the opportunity to express their
geneticpotential.
The performance of the steers in the top 25% and bottom 25%for
feedlot return are shown in Table 2. The average steer
arrivalweight and final weight were 609 pounds (range = 373 to 889
lb)and 1,284 pounds (1,057 to 1,528 lb), respectively. Average
dailygain was 3.47 pounds and ranged from 2.17 to 4.67 pounds.
Theaverage number of days on feed was 194 days, and the average
totalcost of gain was $0.47. Overall, 40 percent of the steers
gradedChoice, which is lower than the national average (56.8%).
Onehead graded Prime, and 10 head received a premium for
CertifiedAngus Beef or Angus Pride Choice. Carcass standards for
the beefcattle industry are Choice quality grade, yield grade of
less than 4,and hot carcass weight between 550 and 950 pounds.
Thirty-fivepercent of the steers fit these industry standards. The
steers thatmet the industry standards averaged $171 per head more
thanthose that did not fit the industry standards (P < 0.001).
They hadhigher carcass values because they graded Choice, and they
werenot discounted for yield grades greater than 4.0 or for
carcassesoutside the weight range. Of the steers that were in the
top 25%based on feedlot net return, 94% met the industry standards,
andfor those in the bottom 25% based on feedlot net return, 100%
didnot meet the industry standards.
Listed below are the significant (P < 0.01) factors that
affectedfeedlot net return over specified costs for steers in the
2005-2006program. Specified costs include feed, freight, insurance,
process-ing, medicine, Beef Check-off dues, and interest. Factors
are listedin descending order of importance.
Quality Grade - Cattle that graded Prime, Choice, Select, andNo
Roll had feedlot net returns of $835, $782, $621 and $543 perhead,
respectively. All feedlot net returns based on quality
gradesdiffered (P < 0.001) from each other. Marbling is the
primary factorthat affects a calf 's ability to grade Choice. Three
main factors thataffect marbling are: (1) the genetic ability to
marble; (2) the matu-rity or the physiological age, not the
chronological age; and (3)ration. Some cattle breeds report
marbling EPD's in their sire sum-maries. Carcass traits such as
marbling are highly heritable; there-fore, selecting high marbling
EPD bulls can be effective for improv-ing the marbling ability of
their calves. Breed can also influence acalf 's ability to grade
Choice. Calves with a high percentage ofEnglish breeding usually
have an increased ability to grade Choice.
Physiological age influences frame score. Large-frame cattlemust
be older (chronologically) to reach the same physiological ageto
express marbling as compared to smaller-frame cattle. Steers
should be medium to large frame, and extremes at both ends of
thescale (small and extremely large) should be avoided.
Initial Weight - The relationship between initial weight
andfeedlot net return was negative indicating that as initial
weightincreased feedlot net return decreased. This relationship is
slightlymisleading though. The main reason initial weight was
present as asignificant factor was due to the market at the time of
harvest. Thefirst group of steers harvested received the lowest
carcass price ofthe 3 harvest groups. This first harvest group of
steers was largelymade up of the calves with heavier initial
weight. Generally, theheavier the calf upon entrance to the
feedyard the fewer days theytake to reach harvest weight.
Nonetheless, in this year’s program,heavier calves were at a
disadvantage due to the market. It is notrecommended to change the
type and size of calf entering the feed-lot based upon this
finding.
Hot Carcass Weight - The relationship between hot carcassweight
and feedlot net return was positive; therefore as hot carcassweight
increased, so did feedlot net return. The more carcasspounds sold,
the greater the gross income and feedlot net return.Table 3 shows
the relationship between hot carcass weight, totalcost of gain,
average daily gain, feedlot net return, and calculatedreturn.
Factors that affect hot carcass weight include frame size,
mus-cle thickness, and backfat. Muscle thickness is a major factor
thatrelates to carcass weight. Thickness, depth and fullness of
quarter,and width (without excessive fat) of back, loin, and rump
are indi-cations of muscling.
Yield Grade - As yield grade increased from 1 to 5, feedlot
netreturn changed very little ($630, $657, $714, $712, $742 per
headfor yield grades 1, 2, 3, 4 and 5, respectively). There were no
differ-ences (P > 0.05) between feedlot net returns for Yield
Grades 1 and5, although there appeared to be a trend that the
higher yield gradeshowed an increase in feedlot net return.
Backfat, ribeye area, hotcarcass weight and percentage of kidney,
pelvic and heart fat are thefactors that determine yield grade. As
yield grade (1 to 5) increases,the amount of fat increases in
relation to the amount of lean mak-ing a lower numerical yield
grade more desirable.
Medicine Cost - Healthy calves outperformed sick calves. Agood
preconditioning vaccination program will not guarantee ahealthy
feedyard calf, but it is the best management tool available.Healthy
calves had a higher feedlot net return ($703 vs. $674 perhead) than
calves that were treated for illness. A higher percentageof healthy
steers graded Choice than did the sick calves.
Implications
Both high and low feedlot returns are affected by calf
health(medicine costs), feedlot performance factors, and carcass
charac-teristics. Value based or grid marketing is increasing in
use and var-ious forms of value based marketing are spreading to
all levels ofthe industry. A producer’s goal should be to produce a
product thatmeets the demands of all segments of the beef industry
and beefconsumers – those who do this will be more competitive in
the everchanging marketplace.
Arkansas Animal Science Department Report 2007
23
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Table 1. Financial results summary, 2005-2006 Arkansas Steer
Feedout Program. Item Average per head ($)a Range ($) Gross income
1,029.17 504 to 1,315 Expenses Feed 275.18 213 to 336 Freight,
interest, etc. 61.43 57 to 87 Medicine 13.39 0 to 63.31Total
feedlot expenses 342.41 273 to 427 Feedlot net return 686.76 484 to
912 Calf initial valueb 653.77 442 to 889 Calculated return 32.99
-188 to 259 a 137 head b An Arkansas Livestock Market News Reporter
placed an arrival value on each calf bases upon arrival weight and
frame and muscle scores.
24
AAES Research Series 553
Table 2. Performance summary of the bottom 25%, top 25% and
average steers based on feedlot net return. Item Bottom 25% Top 25%
Average Number of steers Gross Income per head ($) Carcass value
per lb ($) Initial value per head ($) Medicine per head ($) Feed
cost per head ($) Total expense per head ($) Feedlot net return per
head($) Calculated return per head ($) Days on feed Feed cost per
lb of gain ($) Total cost per lb of gain ($) Arrival weight (lb)
Muscle scoreFrame score Percent large Percent medium Final weight
(lb) Average daily gain (lb) Hot carcass weight (lb) Carcass value
($/lb) Dressing percentage Ribeye area (sq in) Backfat (in) REA per
100 lb carcass weight Quality grade Percent Prime Percent Choice
Percent Select Percent No roll Yield grade
35890a
1.17a
592a
17.39c
261 a
331 a
559a
-32 a
198 0.38 0.47
543a
1.8
35% 65%
1,256a
3.36a
762a
1.17a
63.1%a
13.6 0.41c
1.77a
0%a
0%a
92%a
8%a
2.32
35 1,184b
1.36b
702b
12.17d
286b
353b
831b
128b
196 0.37 0.47
651b
1.6
42% 58%
1,390b
3.49b
867b
1.36b
65.2%b
13.8 0.58d
1.59b
3%b
91%b
6%b
0%b
2.7
137 1,029
1.25 653
13.00 272 339 686
30.59 194
0.38 0.47
609 1.7
35% 65%
1,284 3.47
825 1.24
64.3% 13.6
0.52 1.65
0.7% 40% 57%
2.2% 2.61
a,b Values within rows with unlike superscripts differ (P <
0.0001). c,d Values within rows with unlike superscripts differ (P
< 0.001).
Table 3. Summary of hot carcass weight, total cost of gain,
average daily gain, feedlot net return and calculated return.
Hot carcass weight (lb)
Total cost of gain ($)
ADG(lb)
Feedlot net return per head ($)
Calculated return per head ($)
600-699 0.52 2.5 545 -33 700-799 0.46 3.3 617 23800-899 0.47 3.5
703 30900-999 0.47 3.8 798 74
-
Introduction
Weather has a strong impact on feed intake of beef
cattle.Understanding effects of environmental variables is of
economicimportance because weight gain is dependent on feed
intake.However, skin thickness, hair coat, rumen volume, rate of
diges-tion, and metabolic efficiency differ among breeds (Kidwell
andMcCormick, 1956; Dean et al., 1976), and could affect
behavioralresponses among animals to environmental conditions.
Conditionsto which cattle are unacclimatized can upset normal feed
intakeand adversely affect performance. Duration of adverse
conditionsseems important, and because effects caused by
environmentalconditions are variable, feed intake in a variable
environment is dif-ficult to predict (NRC, 1987). Thermal stress
can markedly alterenergetic efficiency of ruminants as evidenced by
effects of coldstress on energy utilization by beef cattle (Delfino
and Mathison,1991). Other adverse environmental conditions (wind,
precipita-tion, humidity, etc.) can accentuate effects of thermal
stress.Performance and mortality of fed cattle are heavily
influenced byweather conditions cattle are exposed to during
feeding periods.Seasonal weather patterns contribute to seasonal
intake patternsand performance of cattle. Therefore, our objective
was to identifyand quantify impacts of selected environmental
variables on feedintake of beef bulls during feedlot performance
tests.
Experimental Procedures
Feed intake data originated from bulls (n = 1,874) evaluated
in52 individual 140-d University of Arkansas Cooperative Bull
Testsat Fayetteville, Hope, and Monticello. On arrival at test
stations,bulls were weighed, identified by tattoo or brand and
ear-taggedwith a test identification number. Bulls were sorted into
groups of10 according to weight, and the groups randomly assigned
to exer-
cise lots. Bulls in each of the groups remained together
throughoutthe test. Individual animals within groups were assigned
to a feed-ing stall prior to the official test. Bulls were given a
preliminary 21-d period prior to the 140-d feeding trial to lessen
weaning stressand become adjusted to the new surroundings, feeding
proceduresand diet. Each bull was provided with approximately 93
ft2 underroof for shade and protection from inclement weather and
approx-imately 159 ft2 in an exercise lot. Lots were paved and each
con-tained 10 adjacent individual feeding stalls.
Diet, Feeding and Weighing Procedures. Each bull was allowed 2h
of eating time in the early morning (0800 to 1000) and 2 h in
lateafternoon (1500 to 1700). Individual intake was measured
byweighing feed and orts each day. A total mixed ration
preparedcommercially from the same formula was fed each year at
eachlocation. As formulated, the diet contained 0.8 Mcal NEm, 0.5
Mcal
NEg and 12% CP per lb DM. When not in feeding stalls, bulls
had
access to fresh water and commercial mineral mixture
containingcalcium, phosphorus and trace-mineralized salt. Weights
weretaken at the beginning of each test and at 28-d intervals. All
weightswere partially shrunk because calves were weighed
immediatelybefore the morning feeding and had not been allowed
access towater since the evening feeding of the previous day.
Photoperiod and Weather Data. Photoperiod information
wasobtained from sunrise/sunset tables (U.S. Naval
Observatory,Washington, D.C.). Weather data for the period Jan.
1977 to Dec.1990 were obtained from the National Climatic Data
Center(Asheville, N.C.). Nine environmental variables and 3
productterms were in the initial data set but this number was
carefullyreduced to 6 environmental variables in the final
analysis. Weathervariables used in the final analysis included:
maximum tempera-ture, day length, rainfall, relative humidity,
barometric pressure,and wind speed. The arithmetic mean intake and
mean environ-mental variables by location of test and period of
test are present-ed in Table 1.
1 Department of Animal Science, Fayetteville2 Agricultural
Statistics Lab, Fayetteville3 Department of Biological and
Agricultural Engineering, Fayetteville
Story in Brief
Weather data were analyzed to identify and quantify effects on
feed intake of performance-tested beef bulls. Feed intake
dataoriginated from bulls (n = 1,874) in University of Arkansas
Cooperative Bull Tests at Fayetteville, Hope, and Monticello during
52trials. Bulls were given a 21-d adjustment period then
individually full-fed a total mixed ration twice daily in the same
stall for 140d. Photoperiod and climate data were obtained from
U.S. Naval Observatory (Washington, D.C.) and National Climatic
DataCenter (Asheville, N.C.), respectively. Data were pooled,
divided into five 28-d periods with each period analyzed separately
usingall animals over all tests. Principal component (PC) analysis
was used to reduce number of independent variables in the
regressionand overcome collinearity associated with numerous
weather variables. Feed intake was influenced by 5 PC representing
6 climatevariables (maximum temperature, day length, rainfall,
relative humidity, barometric pressure and wind speed) throughout
thestudy. Coefficients for environmental factors ranged from
positive to negative during various study periods. No single
environ-mental variable had a consistent effect throughout all 5
periods. Results indicated numerous environmental variables
influencefeed intake and that effects of individual variables may
vary as feeding period progresses, making consistently accurate
predictionsdifficult.
Regression of Feed Intake on Selected Environmental Factors for
Beef Bulls During Post-Weaning Feedlot Performance Tests
G.T. Tabler, Jr.1, A.H. Brown, Jr.1, E.E. Gbur, Jr.2, I.L.
Berry3, Z.B. Johnson1 D.W. Kellogg1, and K.C. Thompson2
25
-
26
AAES Research Series 553
Statistical Analysis. Feed intake data from 52 feedlot
perform-ance tests at three Arkansas locations over 13 yr were
pooled anddivided into five 28-d periods beginning with the start
of each test,with each period analyzed separately, using all
animals over all tests.Because each location used different start
dates, the 28-d periodswere different calendar dates corresponding
to the weigh dates ofanimals. Average starting test dates were Nov
19 at Fayetteville, Nov5 at Monticello, and at Hope, Feb 3 (Hope 1)
and Aug 18 (Hope 2).Statistical analyses were performed using SAS
Version 8.2 (SASInstitute, Inc., Cary, N.C.).
Distribution of bulls by breed and location of test is
presentedin Table 2. Because weather variables tended to be highly
collinear,regression of feed intake on them would be problematic.
To avoidthese issues, principal components (PCs) were calculated
from thestandardized original variables. Each PC is a linear
combination ofthe original set of independent variables. There are
as many PC asthere are original variables. As a group, they account
for all of thevariation in the original variables and are mutually
independent.Because some PC will explain only a small percentage of
the varia-tion, these PC can be eliminated from the analysis
without signifi-cant loss of information, thereby reducing the
dimensionality ofthe problem. As a result, 5 PC remained after
initial elimination.Each PC was interpreted by considering only
those variables whosecoefficients were sufficiently large in
magnitude relative to thelargest absolute value of all coefficients
in that PC. All interpretedcoefficients (eigenvectors) had a
magnitude of at least 0.35. Sixweather variables were dominant
influences based on eigenvectorsof the linear equation for each
PC.
Principal component 1 (Table 3) was associated with maxi-mum
temperature and day length in all 5 feeding periods and
wassignificant (P < 0.001) in periods 2 through 5. For PC 2,
significant(P ≤ 0.002) in periods 1, 4, and 5, rainfall was
prominent in periods1, 2, and 4 while relative humidity appeared in
periods 1, 2, 3, and5, with barometric pressure also prominent in
period 3. Principalcomponent 3 was significant (P = 0.002) in
period 3 and associat-ed with rainfall and relative humidity.
Principal component 4 wassignificant (P < 0.001) in periods 1, 4
and 5 and associated withrainfall, and additionally in period 5,
relative humidity. The fifthPC was significant (P ≤ 0.012) and
associated with wind speed inperiods 2 and 3. Finally, using the
PLS procedure of SAS, feedintake was regressed on the initial set
of 6 environmental variables(maximum temperature, day length,
rainfall, relative humidity,barometric pressure, and wind speed)
not eliminated by PC analy-sis. These regression coefficients are
reported and discussed.
Results and Discussion
Coefficients of regression from PROC PLS for the effects
ofmaximum temperature, day length, rainfall, relative
humidity,barometric pressure, and wind speed on feed intake of
individual-ly fed beef bulls in feedlot performance tests are
presented in Table4. None of the 6 selected weather variables had a
consistently posi-tive or negative effect on feed intake across all
5 periods. The coef-ficients of regression for maximum temperature
on feed intake inperiods 1 through 5 were -5.86, -8.11, -23.13,
24.49, and -5.55,respectively. The negative coefficients indicate
that as temperatureincreased in periods 1, 2, 3, and 5, feed intake
decreased. In con-trast, a positive coefficient in period 4
indicates that, as temperatureincreased, feed intake also increased
during this period.
Regression coefficients for the effects of day length on
feedintake were -0.80, 52.15, 3.71, -26.55, and -2.61 in periods
1through 5, respectively. Negative coefficients in periods 1, 4,
and 5indicate that feed intake decreased as day length increased in
theseperiods; while in periods 2 and 3, positive coefficients
indicate feedintake increased as day length increased.
Coefficients of regression for the effects of rainfall on
feedintake were -8.14, 0.77, -3.02, -0.98, and -1.26 for periods 1
through5, respectively. Similar to maximum temperature, rainfall
displayednegative coefficients in 4 of 5 periods. Negative
coefficients indicatethat feed intake decreased as rainfall
increased in periods 1, 3, 4,and 5. In contrast, a positive
coefficient in period 2 indicates feedintake increased as rainfall
increased.
Relative humidity and barometric pressure each displayedpositive
coefficients in 4 of 5 periods and a negative coefficient in
1period. Regression coefficients for the effects of relative
humidityon feed intake were 13.57, 162.95, -9.39, 150.28, and 3.42
for peri-ods 1 through 5, respectively. Positive coefficients in
periods 1, 2, 4,and 5 indicate that, as relative humidity
increased, feed intakeincreased. In contrast, during period 3, a
negative coefficient indi-cates that feed intake decreased as
relative humidity increased.
Coefficients of regression for the effects of barometric
pressureon feed intake in periods 1 through 5 were: -2.73, 19.20,
4.20, 34.98,and 31.49, respectively. Similar to relative humidity,
positive coeffi-cients in four periods (periods 2 through 5)
indicate feed intakeincreased as barometric pressure increased.
However, during peri-od 1, feed intake decreased as barometric
pressure increased as evi-denced by a negative coefficient.
Regression coefficients for the effects of wind speed on
feedintake were 8.30, 4.27, 0.62, -0.69, and -2.43 for periods 1
through5, respec