QUALITY ANALYSIS OF CONTAINERIZED ILLINOIS SOYBEAN …of soybean or soybean meal quality impacts. Bulk Shipments o This would allow a comparison of the quality impacts of containerized

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Prepared for:

ILLINOIS SOYBEAN ASSOCIATION

Prepared by:

&

Illinois Crop Improvement Assocation

January 2013

QUALITY ANALYSIS OF

CONTAINERIZED ILLINOIS

SOYBEAN SHIPMENTS

Quality Analysis of Containerized Illinois Soybean Shipments January 2013

© informa economics, inc. Page ii

This copyrighted material is intended for the use of clients of Informa Economics, Inc., only and may not be reproduced or electronically transmitted to other companies or individuals, whole or in part, without the prior written permission of Informa Economics, Inc. The information contained herein is believed to be reliable and the views expressed within this document reflect judgments at this time and are subject to change without notice. Informa Economics, Inc., does not guarantee that the information contained herein is accurate or complete and it should not be relied upon as such.


© informa economics, inc. Page iii

TABLE OF CONTENTS

I. EXECUTIVE SUMMARY ...................................................................................... 5

II. INTRODUCTION .................................................................................................. 9

III. BACKGROUND OF CONTAINERIZED SOYBEAN AND SOYBEAN PRODUCT SHIPMENTS ...................................................................................................... 10

IV. DATA COLLECTION TECHNIQUES AND PARTNER TRAINING.................... 12

A. PROCESS CRITERIA............................................................................................... 12 B. EQUIPMENT SELECTED .......................................................................................... 12 C. TRAINING ............................................................................................................. 15

D. DATA ................................................................................................................... 16

V. QUALITY TESTED SHIPMENTS ....................................................................... 18

VI. ANALYTICAL METHODOLOGY ....................................................................... 22

A. OFFICIAL U.S. GRADE ........................................................................................... 22

B. PHYSICAL FACTORS .............................................................................................. 23 C. COMPOSITION FACTORS ........................................................................................ 23

D. ANALYTICAL SERVICES PROVIDERS ........................................................................ 26

VII. QUALITY RESULTS .......................................................................................... 27

A. U.S. GRADE FACTORS .......................................................................................... 27

B. PHYSICAL FACTORS .............................................................................................. 27 C. COMPOSITION ....................................................................................................... 28

D. SOYMILK AND TOFU TEST RESULTS ........................................................................ 29 E. GERMINATION ....................................................................................................... 30

F. AMBIENT CONDITIONS INSIDE THE CONTAINERS DURING TRANSIT ............................. 30

VIII. ECONOMIC IMPLICATIONS TO ILLINOIS SOYBEAN FARMERS .................. 33

IX. FUTURE ANALYSIS .......................................................................................... 36

X. SUMMARY ......................................................................................................... 37

XI. APPENDICES .................................................................................................... 39


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LIST OF TABLES

Table 1: Containerized Soybean Shipment Destinations and Type of Loading ............ 21

LIST OF FIGURES

Figure 1: TrakLok Device (in ready to lock position) ...................................................... 5

Figure 2: Duration of Quality Tested Shipments ............................................................. 6

Figure 3: Illinois Container Export Inspections of Grain................................................ 10

Figure 4: U.S. Containerized Exports of Grain and Soybeans (Prior to 2004/2005) ..... 11

Figure 5: State Market Share of Containerized Grain and Soybean Export Inspections .............................................................................................................. 11

Figure 6: Example of the TrakLok Device .................................................................... 13

Figure 7: Three Data Loggers Ready for Use .............................................................. 14

Figure 8: TrakLok within Cardboard Box ...................................................................... 14

Figure 9: Destination Sample & Rigging ....................................................................... 14

Figure 10: Anchor Line Latch ....................................................................................... 15

Figure 11: TrakLok (Latched but not Locked) ............................................................... 15

Figure 12: Research Team and Collaborating Members from Private Industry ............ 16

Figure 13: Container Ship Load Planning Side View .................................................... 17

Figure 14: Container Ship Load Planning Cross Sectional View .................................. 17

Figure 15: Observed Shipping Container Routes to Export Position ............................ 18

Figure 16: Container Moving to Container Ship via Yard Hostler ................................. 19

Figure 17: Containers being Loaded on Container Ship ............................................... 19

Figure 18: Duration of Shipments Measured in Days ................................................... 21

Figure 19: Temperature Observations within Shipping Containers .............................. 31

Figure 20: Relative Humidity Observations within Shipping Containers ....................... 32

Quality Analysis of Containerized Illinois Soybean Shipments

© informa economics, inc. Page 5

I. Executive Summary

This study was funded by the Illinois Soybean Check-off and utilizes technology to monitor the factors that affect soybean quality during transit from Illinois to destinations in Eastern and Southeast Asia. The majority of containerized U.S. soybeans, about 66%, are shipped from Illinois. Containerization of commodities is primarily used as a backhaul for the container unit or to maintain higher levels of quality. Although it is believed that Illinois soybeans maintain higher quality levels when in a container versus shipping bulk, there has not been a published analysis of quality changes or methods to monitor soybean quality within the container. This report attempts to do both. The research team also put an emphasis on testing conditions inside the container as it was enroute. A standardized sampling methodology was developed to monitor the changes in quality within shipping containers. Criteria used to select the devices used to monitor the soybeans enroute include: testing integrity, route tracking, data collection, ability to capture specific variables, and ease of use. Several devices were chosen to accomplish the goals of the project and meet the above criteria. Also, customized shipping materials and handling instructions were developed and used for the project. The off-the-shelf devices used in the project include: data loggers to monitor temperature and humidity and TrakLok devices that maintained controlled access to the container and reported GPS locations (see Figure 1).

Figure 1: TrakLok Device (in ready to lock position)



The analysis and findings in this report are based on 8 shipments that included 17 observations from data logging devices (See Appendix F). However, there were 7 additional partial observations from containerized soybeans in which destination samples were never recovered. In one case the sample was not taken. Although, in later shipments, (in an effort to increase sample size) data loggers were deployed without the security of a TrakLok device. These loggers and their respective samples were not recovered at the destination. It is unclear whether they were removed prior to final destination or not, but this does raise an issue of who is opening each container and what are the associated risks. A summary of the time from origination sampling to destination sampling is shown in Figure 2.

Figure 2: Duration of Quality Tested Shipments

Quality was measured by evaluating a variety of variables. Twenty variables were tested and include: grade factors, physical characteristics and composition. A full description of the variables is found in the methodology section of the report. Several important takeaways were discovered during the project that could impact farmer economic returns. The takeaways include:

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Foreign Matter (Detailed in Section VII, page 27) o The foreign matter was expected to stay the same from the origination

sample to the destination sample. The vast majority of the containers remained latched and locked during the entire transit so there was not an opportunity for foreign material to either be added or removed. However, the origin and destination samples showed different levels for foreign material both better and worse depending on the shipment. The logical indication for the change in foreign material is sampling error. It is also possible that the load shifted and caused foreign material to settle in the same area rather than being evenly distributed. If this area was sampled then foreign material levels dramatically increased and if this area was not sampled foreign material levels nearly disappeared.

o The change in foreign material during sampling could have both positive

and adverse impacts on grower economics, but either way (adverse or positive) it is assumed that accuracy and correct sampling will prove to have the best results over time. Any positive change in the sampling will likely not lead to additional revenue, but an adverse change could result in a re-negotiation or, even worse, a rejected load.

Protein Solubility (Detailed in Section VII, pages 29)

o The initial Protein Dispersibility Index (PDI) and Nitrogen Solubility Index (NSI) tests consistently showed lower results for the destination than for the origin samples, especially for the bulk shipments. As such, sampling methods may account for at least part of the change. Results from the additional shipments that were shipped in August of 2012 further reconfirmed the lower ratings at destination. Although, the data set is still relatively small in count, this may impact importers who need higher ratings from the PDI and NSI test for quality soymilk and tofu production.

Germination changes during transit (Detailed in Section VII, page 30) o Although germination is not typically required for the buyer’s end use, it is

commonly used as a type of litmus test to check for quality. The germination did deteriorate and was consistently less for each shipment. Despite the loss in germination, the actual quality variables performed well and suggest that germination is not a good litmus test for quality when using containerized shipping. Of course, if the shipment was for seed or a food use such as sprouting, then the quality would in fact be affected to some degree. Even then, containerized shipping may be the best means available to meet the needs of the customer.

o Additional research would be required to determine exactly why germination deteriorates in the container. It is sufficient to say that if a buyer uses germination to test for quality, the seller may want to educate the buyer as to the fact that the traditional relationships between germination and quality do not always hold true with containerization.



Quality is maintained (Detailed in Section VII, U.S. Grade Factors page 27)

o Perhaps the most important finding and the main focus of the project is that in all the shipments that returned a sample for lab testing, the overall quality was maintained during containerized shipment.

Shipping times vary by shipment (See Figure 18, page 21) o The shortest shipment lasted only 24 days, whereas the longest

completed shipment required 70 days to complete. By completed, it is meant that the container was un-latched and the destination sample was taken. It may have taken several more days to reach the final customer. The methodology section of the report discusses the proper levels of soybean drying for storage. Understanding the possible routing and duration of shipments would assist growers and shippers in sending soybeans with a moisture content that will properly handle the time enroute to the customer.

The project provided some valuable documentation and insights for containerized soybean shipments, but also made the research team more aware of future analysis to better document the results. Some examples of potential future analysis include:

Studying soybean meal o With a limited number of observations available to the research team, the

project narrowed its focus to soybeans that were either bagged product or bulk. However, none of the observations were for soybean meal, which is also shipped via container to export markets.

Additional markets

o Of the 8 total shipments sent out, 4 went to Japan, 3 went to Taiwan, and 1 went to Indonesia through Taiwan and Hong Kong. Testing shipments for other destinations, such as Europe, would allow further documentation of soybean or soybean meal quality impacts.

Bulk Shipments o This would allow a comparison of the quality impacts of containerized and

non-containerized export shipments.

Tofu and Soymilk o Examining in further detail the effect, if any, on tofu and soymilk

production, from containerized soybean shipments. If there is an effect, the additional research can assist in determining the shipping months and routes that offer the least impact to quality. Developing best practices for shipping months and routes will, as a consequence, provide an opportunity to provide greater value to the customers.



II. Introduction

During 2010, the most recent year with full data, there were more than 86,000 containers loaded with 72.9 million bushels of soybeans that were inspected for the export market (USDA-FGIS inspection data). More than one-third of those containers were destined for Indonesia, greater than one-quarter to Taiwan, and another quarter to China, Thailand and Vietnam combined. The majority of containerized U.S. soybeans, about 66%, are shipped from Illinois. Containerization of commodities is primarily used, from the container carrier’s perspective, as a backhaul for the container unit or to maintain higher levels of quality. Although it is believed that Illinois soybeans maintain higher quality levels when in a container versus shipping bulk, there has not been a definitive published analysis of the quality changes through monitoring quality conditions within the container. This report attempts to do both. Origin and destination samples were taken from containerized soybean shipments that originated in Illinois. Shipments, hereon referred to as “test shipments”, were monitored using GPS controlled access devices which ensured the container doors stayed latched during transit. This ensured that the temperature and humidity devices placed in each shipment would not be influenced by factors external to the container. This study was funded by the Illinois Soybean Check-off and utilizes technology to monitor the factors that affect quality during transit from Illinois to destinations in Eastern and Southeast Asia. This study currently provides findings that suggest that quality is maintained during transit when containerization is used.



III. Background of Containerized Soybean and Soybean Product Shipments

The chart in Figure 3 depicts the recent trend of containerizing grain and soybeans for export. Crop years prior to 2004/2005 have little recorded USDA EGIS data for containerized soybeans that originated in Illinois. Crop year 2010/2011 on the other hand had over 110 million bushels of wheat, soybeans, and corn containerized for export.

Figure 3: Illinois Container Export Inspections of Grain

Source: EGIS

Total containerized exports of grain and soybeans in the U.S. were 160.7 million bushels for the 2010/2011 crop year. Similar to Illinois, containerized exports of grain have been growing over the last decade. Prior to the 2004/2005 crop year, containerization of grain and soybeans existed, but at a much smaller level in terms of total volume. The chart in Figure 4 shows U.S. totals prior to 2004/2005. Illinois is currently a major hub for containerized grain and soybean exports. This is an important competitive advantage because it places Illinois farmers closer to the initiation point for export focused unit trains. The chart in Figure 5 shows Illinois’ average market share (2008-2010) for grain and soybean containerization.

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Figure 4: U.S. Containerized Exports of Grain and Soybeans (Prior to 2004/2005)

Source: EGIS

Figure 5: State Market Share of Containerized Grain and Soybean Export Inspections

Source: EGIS

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All OtherStates26.7%



IV. Data Collection Techniques and Partner Training

A. Process Criteria

Testing for containerized soybean quality changes can be conducted using standard methods at origination and destination. However the research team also put an emphasis on testing conditions inside the container as it was enroute. Criteria used to select the devices used to monitor the soybeans enroute were as follows:

Testing Integrity: It was important on initial shipments to be able to control access to the soybean container and obtain notification if the container was open, for how long, and when it was closed again.

Route Tracking: It was assumed that different routes to destinations across the Pacific Ocean would cause the container and soybeans to experience differing climatic conditions. For example, a route across the Southern U.S. enroute to California might impact soybean quality different than a route across the central U.S.

Data Collection: Data collection should be conducted at regular intervals, with

shorter intervals leading to a more complete data set of the climate changes within the container.

Enroute Variables: Temperature and relative humidity will be tested. If it is possible to test for physical impacts and light, these would be helpful as well.

Ease of Use: Collaborators will be the ones primarily loading and unloading all devices and samples so ease of use is critical.

B. Equipment Selected

Several devices were chosen to accomplish the goals of the project and meet the above criteria. Also, customized rigging and packaging was developed to harness the equipment enroute and to ensure all items were properly shipped back. Detailed instructions were created for the various steps, which have been attached to this report in the appendices. These devices include:

TrakLok The TrakLok is a device that serves as a lock for shipping containers, as well as a security monitor that detects impacts to the shipping container. The lock reports to a web-based portal every two hours or in an event (such as code entry, or



physical impact) and reports global position, speed, and status. Three TrakLok units were activated for the project, and there was an attempt to have one TrakLok present with each group of shipments. This device allowed the research team to track the time and path that the soybeans took from Illinois to export position. In some cases, the device was also able to report enroute while on board a container ship. One of the TrakLok devices used can be viewed in Figure 6.

Figure 6: Example of the TrakLok Device

Data Logger The data logger is the device that housed the sensors used for relative humidity and temperature and also stored the data for download after the shipment was completed. The logger was suspended near the top of the shipping container. In an attempt to gather additional data points, additional data loggers were deployed when multiple shipping containers were sent out together. Examples of the data loggers are shown in Figure 7.



Figure 7: Three Data Loggers Ready for Use

Custom Rigging, Packaging, and

Testing Kits

Rigging was developed to secure the instruments and return shipping material in the shipping container. Rigging was designed for ease of use and to ensure that the instruments would be in position to operate as designed. The picture in Figure 8 shows the return box and packing that was prepared for shipping the TrakLok device. The picture in Figure 9 shows the rigging, data logger and other equipment being placed into the return shipping cardboard box.

Figure 8: TrakLok within Cardboard Box

Figure 9: Destination Sample & Rigging



C. Training

A training workshop was conducted at Illinois Crop Improvement Association’s office in Champaign, Illinois. Companies shipping goods that assisted in the project as well as a representative from Illinois Soybean Association were in attendance to be trained with respect to the TrakLok device and the standard procedures that were developed. A nearby standard shipping container, used to store equipment, was used for training. The picture in Figure 10 shows the end of the anchor line that latches onto the standard shipping container. The data logger was attached to this line as well as a mesh bag with the samples and return packages for use at destination. The line was important so that a consistent sampling technique was used for the temperature and relative humidity measures. The anchor line also prevented destination supplies from becoming lost in the bulk soybeans. The picture in Figure 11 shows the TrakLok. The TrakLok is latched on the container door. When the door is closed, the TrakLok is locked to secure the shipment.

Figure 10: Anchor Line Latch

Figure 11: TrakLok (Latched but not Locked)

An intermediate meeting was held in Champaign Illinois where the cooperating shippers, foreign buyers, buyer’s agent, Illinois Crop Improvement, Illinois Soybean Association, and Informa Economics were able to review the project, initial results and learn about the groups’ perceptions about containerized soybeans. Also discussed was the effectiveness of the technology deployed for the project, as well as the ease of sampling and returning of equipment and samples. It was made clear that containerized soybeans are preferred for specific high-end food uses, because quality is believed to be maintained from origin to destination. Final results have confirmed this



belief, but have also raised discussion with potential effects to tofu and soymilk production, which is discussed in the results section of this report. The photo in Figure 12 shows members of the project group at Illinois Crop Improvement’s offices in Champaign.

Figure 12: Research Team and Collaborating Members from Private Industry

D. Data

In addition to temperature and relative humidity data, as much additional information as possible was uncovered about each shipment. Knowing additional facts like the route, time in transit, stowage on the ship, date it was shipped, and weather during shipment were important variables to consider while explaining differences in shipment results. The diagram in Figure 13 and Figure 14 show the side and cross sectional views of a container ship. It was believed that different container placements on the ship (i.e. near the engine, above deck, below deck, etc.) could affect the impact on soybean quality. In order to keep the center of gravity as low as possible, containers of soybeans were generally placed under the deck and near the bottom. The only exceptions to this were for short hauls from Japan to ports across the South China Sea. Although stowage



information was not always readily available for these movements, the fact that the containers were able to emit GPS signals via the TrakLok suggest that the containers were above deck.

Figure 13: Container Ship Load Planning Side View

The container ships that carried test shipments had container capacities of 6,000 to 10,000 twenty foot equivalent units (TEU). The data in the results section of the report indicates that there was a significant change in temperature within the container after the hatches were locked down and the container was under the deck. The diagrams in Figure 13 and Figure 14 show the possible stowage locations for containers aboard a container ship.

Figure 14: Container Ship Load Planning Cross Sectional View



V. Quality Tested Shipments

Eight shipments of one to five containers were sent in 2012. All shipping containers were sent to destinations across the Pacific Ocean. The first five shipments were all routed to southern California where they were loaded onto container vessels. One shipment that was loaded on a vessel in southern California sailed north to Oakland and then Tacoma before departing across the ocean. The last three traveled by rail across the Northern Plains to reach Tacoma, Washington. The map in Figure 15 shows the shipping routes that were used for the shipments to reach a U.S. export position. The photos in Figure 16 and Figure 17 show a shipment being transported and then loaded onto the container ship.

Figure 15: Observed Shipping Container Routes to Export Position

Of the eight shipments sent, differing routing, as well as idle time, caused varying shipping durations for each shipment. The duration of the shipments are shown in Figure 18. The chart is organized by shipment and show the duration of each segment. The segments are defined as follows.

Outbound to Trans-Pacific Destinations



Figure 16: Container Moving to Container Ship via Yard Hostler

Figure 17: Containers being Loaded on Container Ship



Time to Export Position o This segment represents the time used to move the container from its

origination to a port where it can be exported. This includes truck movements to intermodal yards and rail time from the intermodal yard to a port.

Time at Preliminary Export Position

o Once containers reached a U.S. port for export and were loaded on a vessel, they often sailed to other U.S. ports before heading across the Pacific Ocean. This segment represents the idle time for the container once it arrived at a preliminary U.S. export port.

Time at Sea/Other Ports to Final Export Position

o After arriving at the preliminary U.S. port. Time spent idle at the port and aboard the container ship as the ship continued to load cargo at other U.S. and Canadian ports.

Time at Final Export Position

o This segment represents the idle time the container spent at the last U.S. or Canadian port and was not moving. For all shipments, except Shipment 5 and Shipment 6, this was the only U.S. port visited prior to departure. All shipments were held either on the pier or while aboard the ship for 0.5 to 13 days before departing across the Pacific Ocean.

Time at Sea to Preliminary Destination

o Shipment 5 was sent to Taiwan, then to Hong Kong, and finally to its final port position in Indonesia. This segment represents the time from the U.S. export position to the initial overseas port. In the case of Shipment 5, this segment represents the time it took to go from the U.S. to Japan.

Idle time at the Preliminary Destination

o This represents the time that the container was not moving at the preliminary destination.

Time at Sea/Other Ports to Final Destination

o For Shipment 5, this represents the time from leaving Taiwan to arriving in Indonesia. For all other shipments, this is the time from North America to arrival at final destination.

Idle time at Final Destination

o This segment represents the duration that the container spent idle at the destination port prior to being unlocked and sampled for quality.

Transit time for Destination Samples to Return

o Although not tracked throughout the project, later samples proved that destination samples are not always returned in the same amount of time.



The average times for key segments were: Time to Export Position 6 days Time at Export Position 8 days Time from Export Position to Final Destination 19 days Idle Time at Destination Port 27 days

Figure 18: Duration of Shipments Measured in Days

Distance to final destination explains a portion of the duration for Shipment 5. The shipments had varying destinations and soybean types, which are shown in Table 1.

Table 1: Containerized Soybean Shipment Destinations and Type of Loading

Shipment Destination Type of Loading

1 Taiwan Bulk Soybeans

2 Japan Cleaned and Bagged



5 Indonesia, via Hong Kong, via Taiwan Bulk Soybeans


7 Japan Cleaned and Bulk Bagged (tote)


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VI. Analytical Methodology

The determination of differences between the soybeans loaded into the shipping container and those received at the destination depend on using appropriate analytical methods to measure various quality factors. These factors typically depend on physical differences between the samples, changes in composition during transit, and interactions of physical and chemical characteristics that affect processing. These effects may be altered product yields, enhanced or reduced product quality and/or altered process efficiency, to the positive or negative. The following analytical procedures were utilized to determine any differences between the origin and destination samples.

A. Official U.S. Grade

The official U.S. grade for soybeans is based on the evaluation of a number of factors. Official grade is the basis for trade, so any variation in soybeans from origin to destination could result in lower prices to shippers and ultimately lower prices to Illinois soybean farmers. There are thresholds for each factor that vary by grade. The final grade assigned to a sample is the lowest grade received for any of the individual factors. Examples of these factors include damage, foreign material, and splits. The grade factors and allowable tolerances are shown in Appendix E. Low amounts of damage are desired, particularly in food uses. Damaged soybeans are materially unsound and more susceptible to further degradation of quality than are undamaged soybeans. Damage from sources such as fungi, insects, and sprouting can potentially occur during transit of containerized shipments if proper handling conditions are not used. Damage is evaluated by visual inspection. Foreign material (FM) in soybeans is defined as all matter in a sample that passes through an 8/64” round-hole sieve and all matter other than soybeans remaining in the sieved sample after sieving according to procedures prescribed in FGIS instructions. Foreign material is not expected to change during containerized transit, unless some action results in the breaking of soybeans into particles that are able to pass through the sieve. Non-soybean material should not change significantly between origin and destination. Foreign material is evaluated by screening, visual inspection, and weighing. Splits are defined as soybeans with more than one-fourth of the bean removed and that are not damaged. Splits are commonly caused by repeated handling of the soybeans which results in injury and partial or complete removal of the seed coat from a soybean. This, in turn, allows the cotyledons to break apart. Because of the reduced handling involved in containerized shipments, the amount of splits in the origin and destination samples is anticipated to be relatively unchanged. Splits are evaluated by screening, visual inspection, and weighing.



B. Physical Factors

Test Weight Test weight is the weight in pounds of the soybeans in one Winchester bushel (2,150.42 cubic inches), obtained using an approved device. Higher test weight generally indicates sound, fully developed soybeans. Seed Count Seed count is a measure of soybean seed size. Seed size is affected by genetics and by environmental conditions (e.g. rainfalls during pod fill). Some soybean processors have strong preferences for particular seed sizes. For instance tofu manufacturers often prefer very large beans. Natto (fermented product) beans are very small. The test is performed by randomly selecting 100 representative intact seeds. The seeds are weighed, calculated, and reported as seeds per pound. Values may range from 1200-4600 seeds per lbs., though results of 2400-3200 are more typically seen. Differences between origin and destination samples were not anticipated.

C. Composition Factors

Moisture Moisture content is a critical factor for the long-term storability of soybeans. Soybeans should be dried in the field or artificially to 13% moisture for storage up to 6 months, 12% for storage up to one year, and 11% for over one year. Over-drying of soybeans wastes energy, money, and time. Over-drying soybeans will also lead to an increase in splits as the seed coat may be weakened. Soybeans will reach equilibrium moisture content (EMC) based on the ambient temperature and relative humidity of the air to which they are exposed; soybeans will lose or absorb moisture during transit based on the ambient conditions. EMC will be higher in air at higher relative humidity at a given temperature than at a lower relative humidity and the same temperature. EMC will be higher at a lower temperature and given relative humidity than at a higher temperature and the same relative humidity. Higher moisture levels can, in turn, lead to increased microbial and fungal activity and subsequent increases in damage. Sugars There are three primary sugars discussed with regard to soybean quality – sucrose, raffinose, and stachyose. High levels of sucrose (“table” sugar) are often desired to mask the beany flavor in soy foods. The oligosaccharides raffinose and stachyose are not digested in the upper digestive system and are fermented in the intestine. The gases produced in fermentation can cause the discomfort and flatulence associated with some foods from soybeans. As such, efforts have been made to reduce the levels of these sugars in soybeans. Sugars were measured using High Performance Liquid Chromatography (HPLC) methods.



Oil Soybeans are foremost an oil crop; the quantity of oil per unit is of utmost importance to many buyers of quality soybeans. Low quantities of oil will lead to reduced oil yield and processing inefficiency. From a mass balance standpoint, the quantity of oil in the beans should not change during storage or transit. However, the quality of the oil, and thus the value to a processor, may be affected. Crude oil content was determined using AOCS Am 5-04. Fatty Acid Profile Soybean oil is made up of a number of fatty acids, the specific amounts of which determine the characteristics of the oil for various uses. While any material change in fatty acid composition seems unlikely, if changes occur (either in storage or transit) it can have a large effect on the end use. Fatty Acids were determined using AOAC Official Method 969.33; 963.22. Free Fatty Acids (FFA’s) During storage, especially with high levels of splits or other damage (especially at relatively high temperatures and moisture contents), fatty acids can be pulled, or “hydrolyzed” from the triglyceride form (three fatty acids attached to a glycerol backbone) and become “free” fatty acids. FFA’s can be measured and used to predict processing losses and associated costs from the reduction in quality. Free fatty acids are measured by titration of the oil with sodium hydroxide as in AOAC Official Method 940.28. Crude Protein (Nitrogen x 6.25) Protein, calculated from the measured nitrogen content of the soybeans, is critical to a processor’s bottom line and is the starting point for the development of most feed rations. From a mass balance standpoint, the quantity of nitrogen in the beans should not change during storage or transit. However, the quality of the protein, and thus the value to a processor, may be affected. Crude protein was determined by combustion using AOCS Ba 4e-93. Amino Acid Profile The amino acid profile provides a more detailed look at protein composition. The relative amounts of the various amino acids, the building blocks of proteins, tell a great deal about the protein quality. Of most common concern are the levels of certain “essential” amino acids, particularly certain limiting amino acids – lysine, methionine, cysteine, threonine, and tryptophan. The amino acid profile is determined using AOAC Official Method 982.30E (a,b,c). Nitrogen Solubility Index (NSI) The nitrogen solubility index is a measure of protein quality from the standpoint of remaining soluble or un-denatured. Denaturation of protein is most prevalent in heat-processed soy products, but can be used as a measure of quality of whole soybeans as well. High solubility is very important to manufacturers of soymilk and tofu, as their job is



to extract as much protein from the soybean as possible. Exposure to high heat during transit may affect protein quality to an extent measurable by the NSI. For this test, a sample of soybeans is ground, mixed in a specific ratio with water, and stirred at a set speed (120 rpm) in a constant-temperature (30°C) water bath for a specific time (2 hours) according to AOCS Ba 11-65. The nitrogen content of the ground soybeans and extract are determined using the combustion method. The NSI value is the quotient of the water-soluble nitrogen content in the extract divided by the nitrogen content of the original bean. Protein Dispersibility Index (PDI) The Protein Dispersibility Index, or PDI, is another measure of the solubility of soybean protein in water. The difference between the NSI and PDI procedures is in the time and speed of extraction. For the PDI, a sample of soybeans is ground, mixed in a specific ratio with water, and blended at a set speed (7500 rpm) for a specific time (10 minutes) according to AOCS Ba 10a-05. The nitrogen content of the ground soybeans and of the extract is determined using the combustion method. The PDI value is the quotient of the water-soluble nitrogen content in the extract divided by the nitrogen content of the original bean. Soymilk and Tofu Process Test The Tofu and Soymilk Process Test (Evans et al., 19971) gives soybean processors information on the yield and quality of the products expected from a particular variety or sample of beans. Data is collected from the raw soybeans, the soymilk made from those beans, and the silken (non-pressed) tofu product made from that soymilk. The whole soybeans are evaluated for oil content, protein content, and seed count. A sample of the beans are ground into a powder and blended with hot water. The resulting slurry is steam-cooked and put through a juice extractor. Insoluble solids (okara) are removed by filtration through a series of cloths, and the soymilk is refrigerated overnight. The total volumetric yield is determined after the sample has warmed back to room temperature. The solids content of the soymilk is also measured using the Air Oven Method and reported. A portion of the soymilk is mixed with a coagulant and cooked in a hot water bath to make the tofu product. Glucono-delta-lactone (GDL) is the standard coagulant. The finished tofu is weighed to measure product yield and the moisture content is determined using the Air Oven Method. The color of the soymilk and tofu are measured using the Hunter Lab color scale: L measure of lightness (0 = black to 100 = white)

a measure of greenness (larger negative number) to redness (higher positive value)

b measure of blueness (larger negative number) to yellowness (higher positive value)

1 Evans, D. E., C. Tsukamoto, and N. C. Nielsen. 1997. A Small Scale Method for the Production of

Soymilk and Silken Tofu. Crop Sci. 37:1463-1471.



The protein content of the soymilk and tofu are measured using the combustion method. Any observed differences in the samples between the origin and destination would likely be seen by a full-scale processor in the destination country. Germination The ability of the soybean seed to produce a normal seedling, or germinate, may not seem like an important factor to a processor who does not intend for the soybeans to grow. However, “The ability of soybeans to germinate and vigorously grow is an important quality trait [not only] for seed production but often for food and commercial use as well. When quality of a seed declines, germination is one of the first attributes that is lost.” (Johnson, et al, 2008)2 Germination potential can be reduced greatly by mechanical damage during handling, frost and insect damage, exposure to extreme temperatures, and disease and/or fungal infection. The standard “warm” germination, a test that evaluates seedling potential under ideal conditions, was utilized to measure seed viability. The procedure (AOSA. 20113) uses four replicates of 100 seeds planted on moistened creped cellulose paper. The seeds are maintained at 25°C (77°F) for seven days. After that time the seedlings are evaluated as normal, abnormal, or dead. The germination percentage is reported as the number of normal seedlings divided by the total number of seeds tested (subject to specific rules).

D. Analytical Services Providers

Illinois Crop Improvement Association, Identity Preserved Grain Laboratory, Champaign, IL (Project Testing Coordinator) – Seed Count, Crude Protein, Oil, Nitrogen Solubility Index, Protein Dispersibility Index, Soymilk and Tofu Process Test

Illinois Crop Improvement Association, Seed Laboratory, Champaign, IL – Warm Germination

Champaign-Danville Grain Inspection, Urbana, IL – Damage, Foreign Material, Splits, Test Weight, Moisture

University of Missouri Agricultural Experiment Station Chemical Laboratories, Columbia, MO – Amino Acid Profile, Fatty Acid Profile, Free Fatty Acids

Minnesota Valley Testing Laboratories, New Ulm, MN – Sugar Profile

2 Johnson, L. A, P. J. White and R. Galloway. 2008. Soybeans: Chemistry Processing and Utilization.

AOCS Press. Urbana, IL 3 AOSA. 2011. Rules for Testing Seeds. Association of Official Seed Analysts.



VII. Quality Results

Section VI explained the factors used to measure quality and the analysis used for the project. This section presents the results of the analysis for the project. The data from origin and destination used in the analysis to obtain the results in this section can be viewed in Appendix F.

A. U.S. Grade Factors

None of the samples at origin or destination showed heat damage. Differences in total damage at the destination compared to the origin ranged from 0.3% higher to 0.4% lower. All samples were at or below levels of 0.4% total damage, easily meeting the criteria for U.S. No. 1 for the factor. The range of differences is likely attributable to inherent statistical error and/or uncertainty of measurement in sampling and the test methodology. All but one of the samples met the requirements for foreign material to receive the U.S. No. 2 grade. In fact, only one of the samples that met U.S No. 2 would not have been eligible to receive a grade of U.S. No. 1. The amount of foreign material in the samples was typically lower in the destination samples than in the origin samples, especially for the bulk-loaded containers. Sampling error is likely the explanation here. The origin sample for the bulk samples were drawn as the container was being loaded by a trained grain sampler who also collected the official sample for grading. The destination sample was requested to be representative, but based on the nature of unloading for each specific container may have been simply “dipped” from the surface. The sampling may have inadvertently or intentionally omitted the foreign material. The bagged samples showed negligible increase in FM at the destination. This could be the result of FM settling on the top or the bottom of the load and not being accounted for. It also brings up an interesting discussion with regard to educating clients about correct sampling techniques as incorrect techniques could grossly over or under-estimate the FM and the quality of the shipment. Splits for bulk shipments ranged from 1.7% higher at the destination to 7.1% lower at the destination. Again the nature of sampling at the destination must be questioned. Are the splits stratifying in the bulk shipments? The destination samples for bagged shipments showed little to no increase in splits, but levels at origin (0.0-0.2%) were much less than at origin for the bulk shipments (3.1-15.4%). Again, almost all samples, origin and destination, met the factor’s criteria for U.S. No. 1.

B. Physical Factors

The test weight showed no real trend of difference between the origin and destination samples. The test weight of the destination samples ranged from 3.5 lbs./bu. less than the origin, to 0.8 lbs./bu. more than the origin. The bulk shipments showed the greatest differences, where the cleaned and bagged samples were within 0.1 lbs./bu. between



origin and destination consistently. Again, as with splits, this may be due to sampling procedures used at the destination. The seed counts showed no strong trend between the origin and destination samples. Most of the seed counts were within 5% difference between destination and origin samples. A couple of samples, both from the typically more consistent bagged shipments showed over 8% more soybeans per pound at the destination than at the origin, though the reason is not clear.

C. Composition

Temperature/Moisture As expected with changing temperature and relative humidity conditions, the moisture levels in the soybeans varied between the origin and destination samples. The moisture content of the destination samples ranged from 1.6 percentage points higher than the origin to 3.9 percentage points lower than the origin. In most cases, bulk or bagged, the destination sample was somewhat drier than the origin sample. The greatest differences were seen in the bulk bag (totes) shipments to Japan from August to October, where the moisture levels dropped three percentage points on average. The crude oil and crude protein levels were not expected to change significantly from the origin to destination. The early shipments showed a slight trend for higher oil and lower protein, but later shipments showed slight change in the opposite direction. As such, no specific conclusions could be made regarding any difference in protein or oil levels between the origin and destination samples. Sugars The concentrations of the sugars sucrose, raffinose and stachyose were not expected to vary to any large degree from origin to destination. Sucrose values ranged from 4.2% to 7.2%. Few samples showed a difference in sucrose level between origin and destination of more than 0.4 percentage points and showing no clear trend of change. Raffinose and stachyose performed similarly. Raffinose ranged from 0.33 to 0.91% of dry seed weight with a difference between destination and origin of 0.10 percentage points or less. Stachyose ranged from 3.52 to 4.5.57% with a typical difference of less than 0.3 percentage points between origin and destination. Fatty Acid/Amino Acids As anticipated, no trends were observed with regard to the fatty acid and amino acid profiles between the origin and destination samples. Any differences were within the range of uncertainty of sampling and of the analytical method. On the other hand, increases in free fatty acids during transit seemed possible. The results showed generally no change in the FFA’s between the origin and destination, with some destination samples showing distinctly lower FFA results than the origin. In practicality, FFA’s should never go down; it is a quality factor that can only get worse. As such, the results indicate the issues were likely with sampling methods.



Nitrogen Solubility Index The nitrogen solubility Index (NSI) showed distinct differences between the origin and destination samples. On average, the scores of the destination samples were 5.4 points lower than the origin samples. More pronounced are the differences between the bagged and bulk shipments. The bagged samples only decreased by about 3 points. The bulk samples decreased by an average of 8 percentage points. The group that went to Indonesia (longer trip, warmer conditions) decreased by over 10 points on average. Protein Dispersibility Index The same trend was visible in the PDI test results, but not to the same degree. On average the PDI of the destination samples were 2.7 points lower than the respective origin samples. However, in similar fashion to the NSI, the samples from bagged shipments only fell by 1.6 points on average, where the bulk samples dropped an average of 4.1 points. While there appears to be detectable differences between the origin and destination samples for protein solubility, the real effect of these numbers is hard to quantify. Differences of 5.4 and 2.7 percentage points on a 100 point scale may not have a large effect to the processor. This information is difficult to determine or quantify from the scope of this study.

D. Soymilk and Tofu Test Results

Reduced protein solubility should be evident from the soymilk and tofu test. There appears to be some delineation between the shipments completed before June 30 and those completed between July and October, though that separation is not complete. The solids content of the soymilk showed overall relatively low variability between the origin and destination samples (0.08 percentage points), but the soymilk yield went from virtually no change to a difference of 0.44 ml per gram of dry soybean, approximately an 8 to 10% drop. At the same time, the protein in the soymilk went from almost no change to being approximately 5% (2.08% db for a range of 41-50% db protein). The tofu yield also went down 5 to 10% during the later shipments compared to negligible change in the early shipments. However, there does not appear to be a strong correlation between the NSI and PDI tests and the soymilk yields. For instance, the greatest decrease in PDI and NSI occurred in the containers that went to Indonesia, part of the early shipments. The soymilk and tofu results from Indonesia do not reflect this, though, as they show relatively small changes. The color of the soymilk and tofu showed no abnormal variation between the origin and destination samples.



E. Germination

The change in germination potential was the most consistent difference between the origin and destination samples from the containers. While the individual differences ranged from the destination sample being one percentage point higher to 11 percentage points lower than the origin, all but one destination sample was lower than the corresponding origin sample. The average difference was 4.7 percentage points, a number that overall is not significant for most uses, but does show a fairly consistent change between loading and unloading of the container.

F. Ambient Conditions inside the Containers during Transit

The shipping container, when properly closed, should provide watertight, nearly airtight protection to the contents. The interior is not climate controlled, though. As external conditions, primarily air temperature and exposure to direct sunlight, change, and the interior conditions will try to come to equilibrium. In a closed system, humid air (that is, air containing an amount of moisture) that increases in temperature will have a lower relative humidity than it did at its original temperature. As the air in the closed system is cooled, it cannot hold as much water and the relative humidity increases. As the temperature of the system reaches saturation, or the “dew point”, the relative humidity reaches 100% and liquid water begins to condense from the air. But the closed system of a container of soybeans has an additional factor. As the temperature and humidity of the air next to the soybeans change, the soybeans exposed to that air will try to come to the equilibrium moisture content (EMC) for that temperature and relative humidity. The data loggers for each container measured temperature and relative humidity of the air inside the containers. Figure 19 shows a representative graph of temperature for two containers loaded 5 days apart and sailing one week apart. The first section shows wide swings in temperature; this is the change between the daily highs and low, coupled with the effect of direct sunlight. During the middle of the day, the temperature rises, cooling as night falls. The extent of heating and cooling depends on the outside temperature and sun exposure as the containers sit at the intermodal yards, are railed to port and when idle at the port for loading. As such, a container shipped through the U.S. southwestern desert to Long Beach in July experiences much different conditions than one shipped across the northern tier states in February. Upon loading and sailing, the temperatures in the containers begin to descend slowly as the ships pass through the ocean water. As each ship nears land, the temperature in the containers generally began to rise slowly until the hold is opened and the container is offloaded. At that time, the external weather conditions take over again, showing the dramatic daily rise and fall in temperature. Often, when the container is opened, samples pulled, and the data loggers removed, the fluctuations stabilize – the materials are inside a climate-controlled facility. Upon return shipping, more wide swings were typical. The narrowest temperature fluctuation during a shipment was 45.9 degrees



Fahrenheit (50.6 degrees-96.4 degrees) and the largest temperature fluctuation during a shipment was 88.5 degrees Fahrenheit (30.6 degrees – 119.1 degrees). A greater number of samples would be required to make definite statements about the impact of temperature swings, but the results from this study suggest that quality was maintained in each of the extreme temperature shipments.

Figure 19: Temperature Observations within Shipping Containers

Relative humidity followed much the same way, only in the opposite direction as temperature (Figure 20). One primary concern raised was the increase in relative humidity during the ocean faring portion of the trip. As described earlier, if the relative humidity reaches 100%, condensation can occur on the surface of the beans or bags. This could potentially lead to mold growth and other damage. Though reaching levels higher than 90% at times, none of the shipments in this study reached the dew point. There were varying ranges in humidity, depending on the shipment. The largest fluctuation was 66.6% (32.8%-99.4%) and the narrowest fluctuation was 33.4% (34.9%-68.3%). Similar to the results of the temperature analysis, quality was maintained in each shipment. A summary of all of the data collected is included in Appendix F or this report. Also, supplemental temperature and humidity figures are provided in Appendix G.

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VIII. Economic Implications to Illinois Soybean Farmers

The economic implications of containerization of soybeans include:

The ability to market to smaller clients o Rather than shipping entire bulk loaded ships (upwards of 17,000 in a

single hold to 60,000 metric tons within an entire vessel) to customers abroad, shipments can be sold in container sized units (26 metric tons per container), which allows smaller customers to buy directly from U.S. shippers.

Potential for Quicker Shipping Times o Unlike bulk soybean shipments, containers are shipped on vessels

carrying all types of goods. This means containers can rely on non-commodities to complete a load and depart, where bulk ships are dependent on loading larger volumes of commodities prior to departing.

Farmers Benefit from Nearby Access to Intermodal Yards

o Bulk soybeans can be sent in covered hopper cars from country and shuttle rail elevators. There is still a benefit for soybean farmers whose operations and production are near container loading facilities. At those locations, there will be less transportation expenses to take the product to market.

Quality Preservation o This report, and the remainder of this section, focuses on the quality

aspects of containerized soybeans. Initial test shipments indicate that quality is maintained during transit. Quality preservation allows soybean shippers to market to higher end users with less rejected loads. The ability to market higher quality soybeans allows for the potential to secure higher prices. It also creates confidence on the receiver’s side that the product will meet grade and quality for the subject’s end use.

Several important takeaways were discovered during the project that could impact farmer economic returns. These takeaways include:

Foreign Matter o The foreign matter was expected to stay the same from the origination

sample to the destination sample. The vast majority of the containers remained latched and locked during the entire transit so there was not an opportunity for either foreign material to be added or removed. However, the origin and destination samples showed different levels for foreign material both better and worse depending on the shipment. The logical indication for the change in foreign material is sampling error. It is also possible that the load shifted and caused foreign material to settle in the same area rather than being evenly distributed. If this area was sampled,



then foreign material levels dramatically increased and if this area was not sampled, foreign material levels nearly disappeared.

o The change in foreign material during sampling could have both positive

and adverse impacts on grower economics.

Positive impacts: If the foreign material settled to the bottom of the load, then the quality will not be downgraded and the load will likely not be rejected. In fact many of the destination samples were U.S. No. 2 soybeans that could have qualified as U.S. No. 1 soybeans. Some buyers may think they are getting a higher quality product than what was paid for.

Adverse impacts: If the sample is taken after the soybeans are mostly unloaded, the destination sample may record high foreign material levels from material that settled to the bottom. This could also be true if certain foreign material settles at the top. Also, if a client runs soybeans that sampled as U.S. No. 1 at destination, but were really U.S. No. 2, this could give a buyer a false sense of security. Furthermore, if the differences show up in the quality of the processed product, the buyer may change their taste and preferences for U.S. soybeans based on the incorrect perception of how the soybeans should have performed.

o Either way (adverse or positive) it is assumed that accuracy and correct

sampling will prove to have the best results over time. Any positive change in the sampling will likely not lead to additional revenue, but an adverse change could result in a re-negotiation or even worse, a rejected load.

Protein solubility

o The PDI and NSI tests consistently showed lower results for the destination than for the origin samples, especially for the bulk shipments. As such, sampling methods may account for at least part of the change.

o The NSI and PDI results do not necessarily confirm changes in soymilk

and tofu production or quality. Addition observations would be needed to test the specific implications.

Germination changes during transit

o Although germination is not typically required for the buyer’s end use, it is commonly used as a type of litmus test to check for quality. The germination did deteriorate to some degree and was consistently less for each shipment. Despite the loss in germination, the actual quality variables performed well and suggest that germination is not a good litmus



test for quality when using containerized shipping. Of course, if the shipment was seed, then the quality would in fact be affected.

o Additional research would be required to determine exactly why germination is deteriorating in the container, but it is sufficient to say that if a buyer uses germination to test for quality, the seller may want to educate the buyer that the traditional relationships between germination and quality do not always hold true with containerization.

Quality is maintained

o Not surprisingly, the cleaned and bagged shipments generally resulted in fewer observed differences in quality characteristics. Being a more consistent product (mostly whole beans, foreign material removed, movement during transit limited), more consistent results than from bulk shipments are a logical conclusion. The primary question left is if the differences observed with the bulk shipments are due to shipping conditions or product inconsistency and sampling issues.

o Perhaps the most important finding and the main focus of the project is that in all shipments that returned for lab testing, the quality was maintained very well during containerized shipment, even for bulk shipments. Although, the a change in quality may exist in terms of protein, the consequences for soymilk and tofu production appear to be limited.



IX. Future Analysis

The analysis and finding in this report are from 8 shipments that recovered 17 complete data observations. The shipments analyzed were a mix of bagged product, cleaned and bagged product, and bulk soybeans. However, none of the observations were for soybean meal, which is also shipped via container to export markets. Additional, shipments that were for meal shipments would allow the research team to better understand how well quality is maintained in soybean meal. Of the 8 total shipments sent out, 4 went to Japan, 4 went to Taiwan, and 1 went to Indonesia through Taiwan and Hong Kong. Two main routes were used to cross the U.S. and ships leaving the U.S. used a similar path to reach the destination countries. Future analysis as to the quality impacts from shipping bulk soybeans, bagged soybeans, and soybean meal to additional locations, such as Europe would provide additional observations as to how quality is impacted. The sample size was too small to offer a solid explanation of the changes to PDI and NSI. These two measures are important aspects of the production of tofu and soymilk. Future analysis could examine in further detail the effect, if any, on tofu and soymilk production. If there is an effect on tofu or soymilk, additional research can assist in determining the shipping months and routes that offer the least impact to quality. The study team has 13 data logging devices now instead of the original 3 that were used. It was made apparent after the first shipments took a longer than foreseeable time to return that more devices were needed to obtain a suitable number of samples. The increase in devices mean that even at current device levels, nearly twice as many samples could be obtained in a year’s time frame. Additional devices could be obtained if more observations are needed to do more in depth statistical analysis of the results. Additional analysis would likely increase the reliability of the study’s findings. Another area of research is to conduct similar analysis on soybean shipments moving in bulk vessel. This could take a similar course of process, sampling prior to soybeans being loaded in a barge or covered hopper rail car, sampled upon unloading into an export elevator, sampled as being loaded into a dry bulk ocean ship, monitored during transit and sampled at final destination. Such research will provide comprehensive and comparative analysis among the key modes used to export soybeans and soybean meal to global market positions.



X. Summary

Eight shipments containing a total of 24 observations were deployed to study the quality changes in containerized soybeans from Illinois to destinations across the Pacific Ocean. The process to set up and complete the project included:

Identifying suitable technology

Identifying shippers and buyers willing to cooperate with on the project

Training the research team, shippers and buyers of the procedures to use the

selected technology and soybean sampling supplies

Regular check-ins with cooperating shippers and buyers to provide support and

obtain feedback

Monitoring of shipments and GPS tracking and controlled access container locks

Analysis of quality changes using origin and destination samples

The result of the project was two-fold. It created standardized methods for analyzing the quality impacts of containerized soybeans (directions created for shippers and buyers are included in the appendices in Section XI). The study also provided initial results that indicate that quality is maintained while using containers for shipping. Additional key quality takeaways included:

Foreign matter testing can change as a result of product shifting in the

container and because of sampling techniques. Buyer education with regard to the results of foreign material sampling is an important step toward ensuring that the perception of soybean quality within a shipment is based on reality.

Protein solubility was tested for using the PDI and NSI tests, which consistently showed lower results for the destination than for the origin samples, especially for the bulk shipments. As such, sampling methods may account for at least part of the change. Results from the pending shipments will hopefully provide more insight into these observations, as additional data is needed to understand the economic implications.

Germination was reduced to a small degree during container transit. This is important because germination is sometimes used as a test for quality, but would provide unfair results, because the overall quality of the shipments was maintained despite the drop in germination. Again, buyer education could assist in less confusion over true quality concerns. Shippers of seed may also need to consider the implications of containerization and if the changes in germination are below their shipping tolerances.



Other key takeaway includes:

Shipping times vary by shipment. The shortest shipment lasted only 24 days, whereas the longest completed shipment required 70 days. By completed, it is meant that the container was un-latched and the destination sample was taken. It may have taken several more days to reach the final customer. The methodology section of the report discusses the proper levels of soybean drying for storage. Understanding the possible routing and duration of shipments would assist growers and shippers in sending soybeans with a moisture content that could withstand the time enroute to the customer.



XI. Appendices

Appendix A: Origination Sampling Procedures Appendix B: Origination Sampling Procedures (Logger Only) Appendix C: Destination Sampling Procedures (With TrakLok) Appendix D: Destination Sampling Procedures (No TrakLok) Appendix E: U.S. Official Soybean Grade Table and Definitions Appendix F: Data Results Appendix G: Supplementary Temperature and Humidity Figures

Appendix A: Origination Sampling Procedures

(Continue to Side 2) SIDE 1

1. Please read through these procedures. If any questions, contact John McKinney at Illinois Crop Improvement Association (IL Crop, phone: 217-359-4053, mobile: 217-840-2164, or email: [email protected]).

2. Open Sampling Kit and find included items (Inside white plastic bag, do not discard): a. Plastic Sample Bag b. Sample Label c. Paper Bag d. Packing Tape e. Return Shipping Box – pre-addressed to IL Crop

3. Obtain a representative sample of the soybeans in the container. This is best done by taking smaller subsamples over the course of loading, gently mixing the subsamples, and dividing a sample from that of at least 5.0 pounds (2,270 grams) and up to 5.5 pounds (2,500 grams) and place in the Plastic Sample Bag (2.a) as shown in Exhibit 1. Alternatively, a request may be made to the official inspection and grading office to forward their sample to IL Crop. If the official inspection and grading office produces a sample for IL Crop, proceed to Step 9.

Exhibit 1: Soybean Sample

Send Origination Sample to: John McKinney Illinois Crop Improvement Association 3105 Research Road Champaign, IL 61822 Phone: 217.359.4053

4. Squeeze excess air from the bag and seal it using the zip-lock closures. 5. Complete the information on the Sample Label (2.b) and attach to the Plastic Sample Bag. 6. Place the Plastic Sample Bag in the Paper Bag (2.c). Fold the opening of the Paper Bag and roll it

under several times, then use the provided Packing Tape (2.d) to securely seal the Paper Bag closed. Additional tape may be used to reinforce the seams of the bag.

7. Place the bagged sample into the enclosed Return Shipping Box (2.e) and seal the Return Box. 8. Complete the origination questionnaire and place in the return box with the sample. 9. Mail the return box with the sample inside if USPS, if FedEx call for pickup (phone 1.800.463.3339). 10. Contact John McKinney to notify that the shipment is en route to IL Crop. If using the official

inspection and grading sample, please also provide the name and location of the grading office used.

11. The DESTINATION SAMPLING KIT will remain in the Destination Cardboard Box with the destination instructions.

Bag will weigh approximately 5.0 pounds

(2,270 grams)

Page 40

mailto:[email protected]

Appendix A: Origination Sampling Procedures

SIDE 2

12. The anchor line is to be attached to the “Lashing Rings” or “Hooks” inside the shipping container near the ceiling by the doors (See Exhibit 2 reference I and III).

Exhibit 2: Anchor Line used to Secure Plastic Bag and Data Logger Inside Shipping Container

13. The Destination Cardboard Box, with its contents, is to be placed in the enclosed Plastic Bag (see Exhibit 2 reference II) and lashed using the Carabiner to the Anchor Line. The destination directions are to be secured by the carabiner that is holding the plastic bag. The Plastic Bag can rest on the soybeans behind the “grain door” if necessary.

14. The Data Logger is to be lashed to the anchor line using the other Carabiner. 15. Notify John McKinney at IL Crop when the container is shipped (see Step 1 for contact

information). 16. Thank you for your assistance following these procedures.

Data Logger will be placed inside small mesh bag

and attach here

Plastic Bag will contain the Destination Cardboard Box with the Destination Sampling Kit and Instructions

“Lashing Ring” or “Hooks” inside

the container

I II

III IV

Destination Directions hang via Plastic Bag

or carabiner

Anchor Line

Page 41

Appendix B: Origination Sampling Procedures (Data Logger Only)


1. Please read through these procedures. If any questions, contact John McKinney at Illinois Crop Improvement Association (IL Crop, phone: 217-359-4053, mobile: 217-840-2164, or email: [email protected]).

2. Open Sampling Kit and find included items (Inside white plastic bag, do not discard): a. Plastic Sample Bag b. Sample Label c. Paper Bag d. Packing Tape e. Return Shipping Box – pre-addressed to IL Crop

3. Obtain a representative sample of the soybeans in the container. This is best done by taking smaller subsamples over the course of loading, gently mixing the subsamples, and dividing a sample from that of at least 5.0 pounds (2,270 grams) and up to 5.5 pounds (2,500 grams) and place in the Plastic Sample Bag (2.a) as shown in Exhibit 1. Alternatively, a request may be made to the official inspection and grading office to forward their sample to IL Crop. If the official inspection and grading office produces a sample for IL Crop, proceed to Step 9.


Send Origination Sample to: John McKinney Illinois Crop Improvement Association 3105 Research Road Champaign, IL 61822 Phone: 217.359.4053

4. Squeeze excess air from the bag and seal it using the zip-lock closures. 5. Complete the information on the Sample Label (2.b) and attach to the Plastic Sample Bag. 6. Place the Plastic Sample Bag in the Paper Bag (2.c). Fold the opening of the Paper Bag and roll it

under several times, then use the provided Packing Tape (2.d) to securely seal the Paper Bag closed. Additional tape may be used to reinforce the seams of the bag.

7. Place the bagged sample into the enclosed Return Shipping Box (2.e) and seal the Return Box. 8. Complete the origination questionnaire and place in the return box with the sample. 9. Mail the return box with the sample inside if USPS, if FedEx call for pickup (phone 1.800.463.3339). 10. Contact John McKinney to notify that the shipment is en route to IL Crop. If using the official

inspection and grading sample, please also provide the name and location of the grading office used.

11. The DESTINATION SAMPLING KIT will remain in the Destination Cardboard Box with the destination instructions.


(2,270 grams)

Page 42


Appendix B: Origination Sampling Procedures (Data Logger Only)

SIDE 2

12. The anchor line is to be attached to the “Lashing Rings” or “Hooks” inside the shipping container near the ceiling by the doors (See Exhibit 2 reference I and III).

Exhibit 2: Anchor Line used to Secure Plastic Bag and Data Logger Inside Shipping Container

13. The Destination Cardboard Box, with its contents, is to be placed in the enclosed Plastic Bag (see Exhibit 2 reference II) and lashed using the Carabiner to the Anchor Line. The destination directions are to be secured by the carabiner that is holding the plastic bag. The Plastic Bag can rest on the soybeans behind the “grain door” if necessary.

14. The Data Logger is to be lashed to the anchor line using the other Carabiner. 15. Notify John McKinney at IL Crop when the container is shipped (see Step 1 for contact

information). 16. Thank you for your assistance following these procedures.

Data Logger will be placed inside small mesh bag

and attach here

Plastic Bag will contain the Destination Cardboard Box with the Destination Sampling Kit and Instructions

“Lashing Ring” or “Hooks” inside

the container

I II

III IV

Destination Directions hang via Plastic Bag

or carabiner

Anchor Line

Page 43

Appendix C: Destination Sampling Procedures (With TrakLok)


1. Please read through these procedures. If any questions, contact John McKinney at Illinois Crop Improvement Association (IL Crop, [email protected] or phone: 217-359-4053).

2. Remove the Destination Sampling Kit from the Cardboard box inside the Mesh Bag, which is inside a large plastic bag and find included items: a. Plastic Sample Bag b. Sample Label c. Paper Bag d. Packing Tape e. Return Shipping Box – preaddressed to IL Crop f. Shipping Paperwork inside Inner Flap of the Large Cardboard Box (Commercial Invoice and

Aphis Letter and attachable pouch for the outside of the container) 3. Obtain a representative sample of the soybeans in the container. This is best done by taking

smaller subsamples over the course of unloading, gently mixing the subsamples, and dividing a sample from that of at least 5.0 pounds (2,270 grams) and up to 5.5 pounds (2,500 grams) and place in the Plastic Sample Bag (2.a) as shown in Exhibit 1.


4. Squeeze excess air from the Plastic Sample Bag and seal it using the zip-lock closures. 5. Complete the information on the Sample Label (2.b) and attach to the Plastic Sample Bag. 6. Place the Plastic Sample Bag in the Paper Bag (2.c). Fold the opening of the Paper Bag and roll

it under several times, then use the provided Packing Tape (2.d) to securely seal the Paper Bag closed. Additional Packing Tape may be used to reinforce the seams of the bag.

7. Place the TrakLok, Soybean Sample, Anchor Line, Mesh Bag, Data Logger and 3/8” hand drill into the Cardboard Box (See Exhibit 2 and Exhibit 3).

8. Ensure the shipping paperwork (2.f) is in the inner flap pouch of the Large Cardboard Box and then seal the box with the Packing Tape.

9. Please complete the shipping label on the FedEx Cardboard Box and then contact FedEx to schedule pickup (See www.fedex.com for assistance).

10. Contact John McKinney by email at [email protected] to notify that the shipment is en route to IL Crop.


(2,270 grams)

Page 44


http://www.fedex.com/


Appendix C: Destination Sampling Procedures (With TrakLok)

SIDE 2

Exhibit 2: Select Contents of the Soybean Container

Exhibit 3: Packing Illustration

Data Logger

detaches here

Mesh Bag is inside a Plastic Bag and will contain Cardboard Box, Destination Sampling Kit and Instructions

Remove Anchor Line and place in the

Mesh Bag

“Shipping Documents” to remain in the inner flap of the Cardboard Box and the duplicate copies in the outer pouch

III IV

I II

Box containing Anchor Line, Mesh Bags, and Data Logger

Page 45

Appendix D: Destination Sampling Procedures (No TrakLok)


1. Please read through these procedures. If any questions arise, contact John McKinney at Illinois

Crop Improvement Association (IL Crop, [email protected] or phone: 217-359-4053). 2. Remove the Destination Sampling Kit and the Cardboard box inside the Plastic Bag and find

included items: a. Plastic Sample Bag b. Sample Label c. Paper Bag d. Packing Tape e. FedEx Shipping Box – preaddressed to IL Crop f. Shipping Paperwork – Commercial Invoice and APHIS Letter (Two copies of each)

3. Obtain a representative sample of the soybeans in the container. This is best done by taking smaller subsamples over the course of unloading, gently mixing the subsamples, and dividing a sample from that of at least 5.0 pounds (2,270 grams) and up to 5.5 pounds (2,500 grams) and place in the Plastic Sample Bag (2.a) as shown in Exhibit 1.


4. Squeeze excess air from the Plastic Sample Bag and seal it using the zip-lock closures. 5. Complete the information on the Sample Label (2.b) and attach to the Plastic Sample Bag. 6. Place the Plastic Sample Bag in the Paper Bag (2.c). Fold the opening of the Paper Bag and roll

it under several times, then use the provided Packing Tape (2.d) to securely seal the Paper Bag closed. Additional Packing Tape may be used to reinforce the seams of the bag.

7. Place the Soybean Sample, Anchor Line, and Data Logger into the Cardboard Box (See Exhibit 2 and Exhibit 3). Dispose of the large plastic bag that was attached to the Carabiner.

8. Ensure the “Shipping Paperwork” (2.f) is in the Cardboard Box and then seal the box with the Packing Tape.

9. Please complete the shipping label on the FedEx Cardboard Box and then contact FedEx to schedule pickup (See www.fedex.com for assistance).

10. Contact John McKinney by email at [email protected] to notify that the shipment is en route to IL Crop.


(2,270 grams)

Page 46


http://www.fedex.com/


Appendix D: Destination Sampling Procedures (No TrakLok)

SIDE 2

Exhibit 2: Select Contents of the Soybean Container

Exhibit 3: Packing Illustration

Data Logger

detaches here

Plastic Bag will contain Cardboard Box, Destination Sampling Kit and Instructions

Remove Anchor Line and place in the Cardboard Box for

return shipping

Envelope containing “Shipping Documents” is to be inside the return FedEx box in an inside pouch and outside in a pouch.

III

I II

Page 47

Appendix E: U.S. Official Soybean Grade Table and Definitions

Official U.S. Soybean Grades (FGIS)

Maximum Limits of -

Grade Damaged Kernels

Heat (part of total)

(percent)

Total (percent)

Foreign Material (percent)

Splits

(percent)

Soybeans of

other colors 1/

(percent)

U.S. No. 1 0.2 2.0 1.0 10.0 1.0

U.S. No. 2 0.5 3.0 2.0 20.0 2.0

U.S. No. 3 1.0 5.0 3.0 30.0 5.0

U.S. No. 4 3.0 8.0 5.0 40.0 10.0

U.S. Sample Grade:

U.S. Sample Grade is soybeans that: a) Do not meet the requirements for grades U.S. No.1, 2, 3, or 4; or

b) Contains 4 or more stones which have an aggregate weight in excess of 0.1 percent of the sample

weight, 1 or more pieces of glass, 3 or more crotalaria seeds (Crotalaria spp.), 2 or more castor beans

(Ricinus communis L.), 4 or more particles of an unknown foreign substance(s) or a commonly

recognized harmful or toxic substance(s), 10 or more rodent pellets, bird droppings, or an equivalent

quantity of other animal filth in 1,000 grams of soybeans, or

c) Contain 11 or more animal filth, castor beans, crotalaria seeds, glass, stones, or unknown foreign

substance(s) in any combination, or

d) Have a musty, sour, or commercially objectionable foreign odor (except garlic odor); or

e) Are heating or otherwise of distinctly low quality.

1/ Disregard for Mixed Soybeans

Definitions (FGIS, 2007)

Classes: There are two classes of soybeans: Yellow soybeans and Mixed soybeans.

o Yellow soybeans Soybeans that have yellow or green seed coats and which in cross

section, are yellow or have a yellow tinge, and may include not more than 10.0 percent of soybeans of other colors.

o Mixed soybeans Soybeans that do not meet the requirements of the class Yellow soybeans.

Damaged kernels:

Soybeans and pieces of soybeans that are badly ground-damaged, badly weather-damaged, diseased, frost-damaged, germ-damaged, heat-damaged, insect bored, mold-damaged, sprout-damaged, stinkbug-stung, or otherwise materially damaged. Stinkbug-stung kernels are considered damaged kernels at the rate of one fourth of the actual percentage of the stung kernels.

Foreign material:

All matter that passes through an 8/64” round-hole sieve and all matter other than soybeans remaining in the sieved sample after sieving according to procedures prescribed in FGIS instructions.

Heat-damaged kernels: Soybeans and pieces of soybeans that are materially discolored and damaged by heat.

Page 48

Appendix E: U.S. Official Soybean Grade Table and Definitions

Purple mottled or stained: Soybeans that are discolored by the growth of a fungus; or by dirt; or by a dirt like substance(s) including nontoxic inoculants; or by other nontoxic substances.

Sieve:

8/64” round-hole sieve. A metal sieve 0.032 inch thick perforated with round holes 0.125 (8/64) inch in diameter.

Soybeans of other colors:

Soybeans that have green, black, brown, or bicolored seed coats. Soybeans that have green seed coats will also be green in cross section. Bicolored soybeans will have seed coats of two colors, one of which is brown or black, and the brown or black color covers 50 percent of the seed coats. The hilum of a soybean is not considered a part of the seed coat for this determination.

Splits:

Soybeans with more than one-fourth of the bean removed and that are not damaged.

Page 49

Appendix F: Data Results

Sample Identification ICIA Proximate Results ICIA Seed Lab Results CDGI Grade Factor Results

Sample

ID

Sample

Type

Date Shipped

or Received*

Country

Delivered

to

NIR

Moisture

NIR

Crude

Fiber

DB

Wet

Chemistry

Crude

Protein

DB

Wet

Chemistry

Crude Oil

DB Germ%

Dead

Seeds %

Pod &

Stem

Blight

Test

Weight Moisture

Total

Damage

Foreign

Material Splits

Heat

Damage

Soybeans

of Other

Colors

112063 Origin 02/15/12 Taiwan 9.3 5.4 40.7 20.5 93 7 0.00 56.8 9.5 0.1 0.9 3.1 0.0 0.1

112064 Dest. 04/18/12 Taiwan 9.2 5.4 41.2 20.5 90 10 0.25 57.4 9.3 0.0 0.3 1.5 0.0 0.0

112065 Origin 03/01/12 Japan 8.8 5.6 39.5 23.2 88 12 0.00 57.2 9.2 0.0 0.0 0.0 0.0 0.0

112066 Dest. 04/13/12 Japan 10.1 5.5 39.1 22.9 86 14 0.00 57.2 10.8 0.0 0.1 0.0 0.0 0.0

112067 Origin 03/06/12 Japan 8.4 5.5 43.1 20.6 84 16 0.00 57.7 8.7 0.0 0.0 0.1 0.0 0.1

112068 Dest. 04/20/12 Japan 8.6 5.5 42.4 20.5 73 27 0.25 57.6 8.8 0.1 0.0 0.1 0.0 0.0

112160 Origin 05/10/12 Indonesia 10.0 5.6 39.2 19.6 92 8 0.00 57.4 10.3 0.0 0.7 5.6 0.0 0.0

120193 Dest. 6/27/2012 Indonesia 9.2 5.6 38.5 19.1 89 11 0.00 57.5 9.5 0.3 0.4 3.9 0.0 0.0


120192 Dest. 6/27/2012 Indonesia 10.4 5.6 39.1 19.6 87 13 0.50 57.0 10.8 0.3 0.5 9.9 0.0 0.0


120189 Dest. 6/27/2012 Indonesia 9.8 5.5 39.9 20.3 90 10 0.25 57.6 10.0 0.4 0.2 4.2 0.0 0.0


120191 Dest. 6/27/2012 Indonesia 9.4 5.5 38.7 19.6 78 22 0.00 54.3 9.4 0.0 0.8 3.1 0.0 0.0


120190 Dest. 6/27/2012 Indonesia 10.1 5.6 39.6 20.6 86 14 0.50 57.8 10.5 0.3 0.2 10.0 0.0 0.0

112172 Origin 05/22/12 Japan 10.9 5.2 41.7 21.1 83 17 0.00 57.3 11.4 0.0 0.0 0.2 0.0 0.0

120097 Dest. 07/05/12 Japan 10.4 5.3 39.7 21.3 82 18 0.00 57.3 10.8 0.0 0.0 0.1 0.0 0.0

112173 Origin 05/23/12 Japan 10.8 5.3 42.1 21.3 84 12 0.00 57.3 11.2 0.2 0.0 0.2 0.0 0.0

120088 Dest. 07/05/12 Japan 10.6 5.2 40.5 21.9 82 18 0.00 57.3 11.1 0.0 0.0 0.2 0.0 0.0

112174 Origin 05/25/12 Japan 10.2 5.6 40.9 22.2 89 11 0.25 56.4 10.8 0.0 0.1 0.1 0.0 0.3

120089 Dest. 07/05/12 Japan 10.4 5.6 39.2 23.3 84 16 1.00 56.3 10.9 0.0 0.0 0.4 0.0 0.0

120148 Origin 07/16/12 Taiwan 9.7 5.5 38.7 20.9 92 8 0.50 56.6 9.7 0.7 0.5 7.5 0.3 0.0

122140 Dest. 8/28/2012 Taiwan 9.1 5.6 38.8 21.0 87 4 0.00 56.2 9.3 0.1 0.7 4.8 0.0 0.0

120606 Origin 8/7/2012 Japan 11.3 5.5 39.5 21.8 92 2 0.25 58.1 11.8 0.0 0.2 0.5 0.0 0.0

122142 Dest. 10/15/2012 Japan 7.6 5.7 40.3 21.5 81 7 0.00 56.6 7.9 0.2 0.0 0.5 0.0 0.0

120607 Origin 8/8/2012 Japan 10.2 5.4 40.1 21.1 89 2 0.00 56.2 10.4 0.0 0.1 0.8 0.0 0.0

122143 Dest. 10/15/2012 Japan 7.2 5.9 40.3 21.1 79 8 0.00 56.7 7.6 0.0 0.1 0.6 0.0 0.0

120608 Origin 8/8/2012 Japan 10.3 5.4 40.1 20.5 94 2 0.00 56.1 10.4 0.3 0.0 0.5 0.0 0.0

122144 Dest. 10/15/2012 Japan 7.4 5.8 40.2 20.8 86 8 0.00 56.8 7.7 0.0 0.0 0.9 0.0 0.0

120609 Origin 8/7/2012 Japan 10.2 5.5 40.2 20.3 94 2 0.50 56.4 10.3 0.3 0.2 1.0 0.0 0.0

122145 Dest. 10/15/2012 Japan 7.3 5.8 40.4 20.8 85 11 0.25 56.8 7.6 0.1 0.0 0.7 0.0 0.0

120613 Origin 8/8/2012 Taiwan 10.7 5.6 39.1 20.6 86 0 0.25 56.4 11.2 0.1 0.9 15.4 0.0 0.0

122141 Dest. 9/18/2012 Taiwan 8.2 5.8 39.1 21.1 85 6 0.00 55.4 10.5 0.3 0.5 9.9 0.0 0.0

*some dates approximate based on shipping records

Page 50


Sample

ID

Sample

Type

Date Shipped

or Received*

Country

Delivered

to NSI PDI

Seed

Count

Sds/lb

Soymilk

% Solids

Soymil

k Yield

(ml/gD

S)

Soymil

k

Protein

DB

Tofu

Moistur

e %

Tofu

Yield

Kg/kg/D

S

Tofu

Protein

DB L a b L a b

112063 Origin 02/15/12 Taiwan 69.7 86.4 2955 10.03 5.31 45.97 89.83 5.53 46.61 76.08 0.16 10.47 77.37 0.98 11.07

112064 Dest. 04/18/12 Taiwan 69.0 88.3 2936 10.22 5.13 46.29 89.48 5.35 45.27 76.44 0.2 10.45 77.76 1.1 10.7

112065 Origin 03/01/12 Japan 69.7 89.5 2835 10.38 5.39 44.78 89.42 5.62 44.42 76.59 0.05 10.66 78.11 0.92 11.18

112066 Dest. 04/13/12 Japan 69.8 88.0 3086 10.28 5.48 44.46 89.67 5.73 45.58 76.5 -0.07 10.87 77.26 0.79 11.53

112067 Origin 03/06/12 Japan 71.6 87.3 2585 10.60 5.23 48.32 89.37 5.46 50.24 77.77 -0.02 12.32 78.1 0.92 12.45

112068 Dest. 04/20/12 Japan 67.9 88.0 2541 10.23 5.16 48.28 89.28 5.36 46.74 77.62 -0.01 12.1 77.93 0.94 12.27

112160 Origin 05/10/12 Indonesia 89.2 91.6 3139 10.11 4.78 43.83 89.29 5.00 43.79 76.63 -0.14 10.92 77.54 0.57 11.37

120193 Dest. 6/27/2012 Indonesia 68.6 80.8 3065 10.31 5.24 46.54 89.49 5.44 45.11 76.97 -0.27 11.04 77.7 0.69 10.94


120192 Dest. 6/27/2012 Indonesia 77.7 88.4 3044 10.36 5.19 44.70 89.27 5.43 44.26 76.71 0.11 10.92 77.41 0.7 11.08


120189 Dest. 6/27/2012 Indonesia 70.0 85.3 2945 10.31 4.83 44.63 88.88 5.05 43.62 76.91 -0.09 11.14 77.22 0.91 11.02


120191 Dest. 6/27/2012 Indonesia 70.4 86.8 2741 10.23 4.96 44.49 89.38 5.18 45.94 77.01 -0.19 10.7 77.88 0.31 10.92


120190 Dest. 6/27/2012 Indonesia 71.4 85.5 2994 10.14 4.96 43.59 89.66 5.13 44.50 76.48 -0.02 11.03 77.88 0.53 11.24

112172 Origin 05/22/12 Japan 78.8 89.9 2757 9.42 5.16 49.76 89.22 5.41 44.25 76.56 0.04 10.97 76.65 1.2 11.19

120097 Dest. 07/05/12 Japan 69.4 88.3 3065 10.23 5.03 46.53 89.30 5.25 47.48 76.13 0.12 10.9 77.22 1.47 10.65

112173 Origin 05/23/12 Japan 77.4 89.4 2716 9.88 5.44 49.61 88.34 5.66 42.87 76.06 0.04 11.29 76.72 1.18 11.43

120088 Dest. 07/05/12 Japan 81.7 90.7 2791 10.39 5.38 46.97 89.02 5.65 45.44 75.9 0.04 11.1 77.38 1.29 10.8

112174 Origin 05/25/12 Japan 80.4 89.7 3240 9.52 5.02 46.84 89.37 5.20 43.65 76.23 0.21 11.5 76.9 1.2 11.56

120089 Dest. 07/05/12 Japan 83.5 90.0 3299 10.05 5.03 44.97 89.42 5.27 46.68 75.8 0.27 11.61 76.86 1.35 11.42

120148 Origin 07/16/12 Taiwan 73.4 88.5 2844 10.26 5.16 44.06 88.85 5.33 42.78 77.5 -0.46 10.71 77.44 0.46 10.85

122140 Dest. 8/28/2012 Taiwan 73.8 83.8 2741 10.03 4.52 43.27 89.27 4.72 42.02 76.33 -0.17 10.98 76.49 0.7 11.05

120606 Origin 8/7/2012 Japan 74.7 86.4 2926 9.95 5.30 44.34 89.12 5.58 42.81 74.35 0.47 11.41 75.82 1.11 11.52

122142 Dest. 10/15/2012 Japan 74.5 81.9 3004 9.76 4.55 42.52 90.09 4.79 42.70 74.31 0.87 11.05 75.58 1.55 11.14

120607 Origin 8/8/2012 Japan 72.8 86.2 3014 10.04 5.18 45.13 89.43 5.40 46.34 74.39 0.46 11.36 75.63 1.23 11.29

122143 Dest. 10/15/2012 Japan 66.9 85.9 3086 9.72 4.76 43.31 89.80 5.01 45.37 74.88 0.82 11.06 76.16 1.67 11.18

120608 Origin 8/8/2012 Japan 71.6 89.7 3096 9.46 4.68 46.61 89.83 4.87 41.58 74.21 0.56 11.18 75.44 1.52 11.18

122144 Dest. 10/15/2012 Japan 64.4 83.8 3128 9.60 4.43 43.55 89.78 4.70 43.34 74.3 0.81 11.12 75.2 1.63 11.22

120609 Origin 8/7/2012 Japan 77.9 87.1 3150 10.04 4.95 44.21 89.56 5.15 45.10 74.25 0.44 11.47 75.03 1.69 11.16

122145 Dest. 10/15/2012 Japan 68.4 84.6 3217 9.39 3.62 41.12 90.12 3.86 43.12 74.33 0.88 11.02 75.1 1.85 10.98

120613 Origin 8/8/2012 Taiwan 75.4 88.2 3014 10.19 5.50 44.95 89.36 5.74 44.56 76.58 -0.21 10.97 76.95 0.65 11.11

122141 Dest. 9/18/2012 Taiwan 74.0 87.1 2965 10.36 5.07 44.51 88.98 5.34 43.12 76.92 0.03 10.8 77.25 0.68 11.11

Sample Identification

ICIA Processing Results

Soymilk and Tofu Results Soymilk Color Tofu Color

Page 51


Sample

ID

Sample

Type

Date Shipped

or Received*

Country

Delivered

to

Glucose/

Dextrose

% DB

Sucros

e % DB

Maltose

% DB

Fructose

% DB

Stachy

ose %

DB

Raffinos

e % DB

Free

Fatty

Acid Palmitic Stearic Oleic Linoleic Linolenic

112063 Origin 02/15/12 Taiwan 0.00 6.57 0.25 0.00 4.43 0.60 1.86 11.28 4.37 21.45 53.47 8.38

112064 Dest. 04/18/12 Taiwan 0.06 6.91 0.26 0.00 4.48 0.62 1.63 11.26 4.47 21.77 53.21 8.19

112065 Origin 03/01/12 Japan 0.05 6.61 0.40 0.00 4.40 0.81 1.65 10.83 3.8 21.27 55.11 7.92

112066 Dest. 04/13/12 Japan 0.00 6.58 0.29 0.00 4.59 0.77 1.65 10.73 3.82 21.02 55.31 8.05

112067 Origin 03/06/12 Japan 0.00 6.91 0.24 0.00 4.32 0.56 1.8 11.24 3.91 25.56 50.76 6.97

112068 Dest. 04/20/12 Japan 0.05 7.16 0.33 0.00 4.18 0.55 1.89 11.21 3.88 25.14 50.97 7.28

112160 Origin 05/10/12 Indonesia 0.09 7.14 0.33 0.00 4.76 0.63 1.95 10.76 4.27 21.80 53.23 8.62

120193 Dest. 6/27/2012 Indonesia 0.00 7.02 0.42 0.00 4.61 0.57 0.78 10.84 4.47 21.8 53.51 8.58


120192 Dest. 6/27/2012 Indonesia 0.00 6.74 0.40 0.00 4.60 0.63 0.83 10.87 4.57 21.85 53.5 8.24


120189 Dest. 6/27/2012 Indonesia 0.07 7.02 0.47 0.00 4.58 0.57 0.72 11.07 4.44 21.17 53.71 8.62


120191 Dest. 6/27/2012 Indonesia 0.00 7.03 0.44 0.00 4.61 0.65 0.76 10.79 4.49 22.43 53.13 8.22


120190 Dest. 6/27/2012 Indonesia 0.00 7.12 0.46 0.00 4.83 0.67 0.79 10.89 4.42 22.11 53.25 8.41

112172 Origin 05/22/12 Japan 0.09 5.63 0.21 0.06 4.19 0.84 1.18 10.87 3.56 20.94 55.41 7.97

120097 Dest. 07/05/12 Japan 0.00 5.69 0.22 0.00 4.41 0.86 0.67 10.85 3.55 21.04 55.96 7.92

112173 Origin 05/23/12 Japan 0.09 5.31 0.34 0.06 3.97 0.78 1.2 10.92 3.53 20.90 55.34 8.05

120088 Dest. 07/05/12 Japan 0.00 5.87 0.20 0.00 4.56 0.85 0.88 10.93 3.52 20.73 55.66 8.09

112174 Origin 05/25/12 Japan 0.08 4.20 0.16 0.00 4.31 0.71 1.07 10.37 4.50 24.67 52.44 6.15

120089 Dest. 07/05/12 Japan 0.16 4.34 0.15 0.00 4.57 0.72 0.67 10.24 4.57 24.95 52.97 6.41

120148 Origin 07/16/12 Taiwan 0.07 7.01 0.61 0.00 4.96 0.64 0.8 10.93 4.45 22.52 52.81 8.33

122140 Dest. 8/28/2012 Taiwan 0.29 7.12 0.34 0.12 4.92 0.58 0.83 10.87 4.46 22.55 52.61 8.14

120606 Origin 8/7/2012 Japan 0.18 6.54 0.15 0.08 5.57 0.83 1.13 10.18 4.27 20.56 55.67 8.39

122142 Dest. 10/15/2012 Japan 0.30 5.79 0.24 0.18 4.99 0.81 0.94 10.27 4.25 21.23 54.82 7.94

120607 Origin 8/8/2012 Japan 0.20 6.09 0.12 0.09 5.52 0.86 1.07 10.37 4.21 21.15 55.34 8.1

122143 Dest. 10/15/2012 Japan 0.35 5.88 0.23 0.21 4.82 0.68 0.9 10.25 4.24 20.92 54.96 8.18

120608 Origin 8/8/2012 Japan 0.18 5.96 0.11 0.09 5.32 0.80 0.89 10.14 4.3 20.35 55.76 8.53

122144 Dest. 10/15/2012 Japan 0.35 5.79 0.23 0.19 4.93 0.76 0.93 10.21 4.22 20.29 55.43 8.41

120609 Origin 8/7/2012 Japan 0.16 3.81 0.17 0.09 3.52 0.53 0.93 10.07 4.2 20.16 56.02 8.59

122145 Dest. 10/15/2012 Japan 0.27 5.87 0.17 0.15 5.13 0.91 0.92 10.1 4.31 20.24 55.47 8.39

120613 Origin 8/8/2012 Taiwan 0.22 5.57 0.26 0.06 4.00 0.33 0.59 10.95 4.61 22.18 53.09 8.24

122141 Dest. 9/18/2012 Taiwan 0.25 7.09 0.39 0.13 4.99 0.57 0.73 10.76 4.61 22.37 52.87 7.95

Sugar Profile (DB) Fatty Acid ProfileSample Identification

Page 52


Samp

le

ID

Samp

le

Type

Date

Ship

pe

d

or R

ece

ived

*

Co

un

try

De

livere

d

to

Taurine

Hydroxyproline

Aspartic Acid

Threonine

Serine

Glutamic Acid

Proline

Lanthionine

Glycine

Alanine

Cysteine

Valine

Methionine

Isoleucine

Leucine

Tyrosine

Phenylalanine

Hydroxylysine

Ornithine

Lysine

Histidine

Arginine

Tryptophan

112063O

rigin02/15/12

Taiwan

0.010.00

4.621.56

1.677.18

2.100.00

1.801.80

0.612.19

0.591.99

3.231.49

2.090.02

0.022.74

1.073.11

0.43

112064D

est.

04/18/12Taiw

an0.01

0.004.51

1.511.66

7.102.13

0.001.77

1.780.60

2.150.56

1.993.22

1.582.13

0.020.02

2.691.05

3.040.46

112065O

rigin03/01/12

Japan

0.010.00

4.441.53

1.676.88

2.060.00

1.741.75

0.672.10

0.591.89

3.091.45

1.960.02

0.022.67

1.042.87

0.46

112066D

est.

04/13/12Jap

an0.01

0.004.39

1.521.64

6.772.10

0.001.74

1.740.66

2.070.58

1.893.05

1.451.93

0.020.02

2.651.03

2.820.46

112067O

rigin03/06/12

Japan

0.010.00

4.761.66

1.897.27

2.270.00

1.841.85

0.672.13

0.612.00

3.291.55

2.100.02

0.022.82

1.103.12

0.45

112068D

est.

04/20/12Jap

an0.01

0.004.70

1.621.81

7.162.21

0.001.84

1.860.67

2.140.60

1.983.25

1.522.06

0.020.03

2.771.10

3.040.48

112160O

rigin05/10/12

Ind

on

esia

0.090.09

4.351.52

1.766.60

2.000.00

1.691.67

0.551.82

0.551.82

3.041.50

2.010.04

0.022.69

1.002.88

0.47

120193D

est.

6/27/2012In

do

ne

sia0.10

0.094.31

1.481.69

6.491.89

0.001.67

1.640.53

1.790.52

1.802.99

1.481.99

0.080.02

2.600.98

2.790.39

112161O

rigin05/10/12

Ind

on

esia

0.100.13

4.301.51

1.766.53

1.920.00

1.681.67

0.541.87

0.541.82

3.031.51

2.000.04

0.032.67

1.002.84

0.48

120192D

est.

6/27/2012In

do

ne

sia0.11

0.114.52

1.531.72

6.751.93

0.001.74

1.720.56

1.910.56

1.903.11

1.532.08

0.070.03

2.711.03

2.940.38

112162O

rigin05/10/12

Ind

on

esia

0.100.07

4.311.49

1.676.53

1.970.00

1.671.66

0.551.84

0.541.85

3.031.49

2.000.04

0.022.68

1.002.87

0.47

120189D

est.

6/27/2012In

do

ne

sia0.10

0.114.55

1.541.75

6.861.97

0.001.73

1.720.57

1.900.56

1.893.13

1.532.08

0.070.03

2.711.03

2.950.36

112163O

rigin05/11/12

Ind

on

esia

0.120.09

4.381.49

1.666.66

2.030.00

1.711.70

0.551.91

0.551.91

3.091.52

2.030.04

0.022.73

1.032.94

0.49

120191D

est.

6/27/2012In

do

ne

sia0.11

0.124.38

1.501.70

6.581.91

0.001.70

1.670.53

1.810.53

1.833.02

1.492.00

0.070.02

2.630.99

2.850.36

112164O

rigin05/11/12

Ind

on

esia

0.090.08

4.441.55

1.786.73

2.060.00

1.711.70

0.571.85

0.551.87

3.111.53

2.060.04

0.022.74

1.032.96

0.48

120190D

est.

6/27/2012In

do

ne

sia0.10

0.094.47

1.541.76

6.691.93

0.001.70

1.700.53

1.850.53

1.853.10

1.532.06

0.080.02

2.671.01

2.940.39

112172O

rigin05/22/12

Japan

0.120.11

4.651.58

1.787.07

2.140.00

1.821.76

0.632.00

0.581.99

3.241.60

2.130.04

0.032.83

1.093.09

0.54

120097D

est.

07/05/12Jap

an0.09

0.114.75

1.581.80

7.342.12

0.001.82

1.790.63

2.300.58

2.023.28

1.592.15

0.040.03

2.861.10

3.090.50

112173O

rigin05/23/12

Japan

0.100.10

4.691.59

1.817.19

2.160.00

1.821.77

0.632.05

0.592.02

3.261.61

2.140.04

0.032.84

1.093.08

0.50

120088D

est.

07/05/12Jap

an0.09

0.114.77

1.581.85

7.402.13

0.001.83

1.790.63

2.290.59

2.033.29

1.602.15

0.040.03

2.871.10

3.130.49

112174O

rigin05/25/12

Japan

0.100.10

4.651.57

1.817.11

2.170.00

1.831.77

0.661.97

0.592.02

3.231.62

2.120.04

0.032.85

1.083.01

0.54

120089D

est.

07/05/12Jap

an0.08

0.134.64

1.551.82

7.192.06

0.011.81

1.770.64

2.240.57

2.003.22

1.552.11

0.040.03

2.811.06

2.970.50

120148O

rigin07/16/12

Taiwan

0.100.08

4.291.44

1.606.46

1.880.00

1.681.64

0.531.85

0.521.84

2.991.45

1.980.06

0.032.57

0.982.74

0.28

122140D

est.

8/28/2012Taiw

an0.02

0.094.31

1.441.60

6.511.65

0.001.68

1.650.52

2.050.52

1.792.95

1.311.95

0.030.03

2.520.99

2.770.42

120606O

rigin8/7/2012

Japan

0.050.09

4.511.58

1.886.63

1.960.00

1.751.75

0.611.73

0.561.78

3.151.47

1.980.05

0.032.68

1.052.89

0.50

122142D

est.

10/15/2012Jap

an0.02

0.064.43

1.521.69

6.651.96

0.001.72

1.700.57

2.070.54

1.833.05

1.392.01

0.040.03

2.601.03

2.830.60

120607O

rigin8/8/2012

Japan

0.060.08

4.541.58

1.886.64

1.970.00

1.681.71

0.621.74

0.571.85

3.121.43

1.970.03

0.022.70

1.052.89

0.48

122143D

est.

10/15/2012Jap

an0.02

0.104.49

1.501.68

6.911.97

0.001.75

1.740.56

2.200.55

1.873.06

1.382.01

0.030.03

2.661.04

2.820.41

120608O

rigin8/8/2012

Japan

0.030.08

4.571.57

1.876.78

1.990.00

1.751.76

0.611.87

0.571.86

3.191.48

2.020.03

0.022.73

1.062.93

0.48

122144D

est.

10/15/2012Jap

an0.02

0.064.48

1.531.68

6.811.97

0.001.74

1.740.55

2.140.55

1.883.09

1.382.02

0.040.03

2.651.04

2.860.43

120609O

rigin8/7/2012

Japan

0.040.07

4.481.53

1.756.64

1.960.00

1.751.75

0.611.89

0.571.85

3.111.42

1.960.03

0.032.71

1.042.89

0.43

122145D

est.

10/15/2012Jap

an0.03

0.064.44

1.521.70

6.721.98

0.001.73

1.720.56

2.110.55

1.873.08

1.392.02

0.040.03

2.631.04

2.860.42

120613O

rigin8/8/2012

Taiwan

0.030.09

4.351.46

1.676.43

1.910.00

1.671.67

0.561.82

0.531.81

3.031.39

1.920.02

0.032.59

1.002.80

0.47

122141D

est.

9/18/2012Taiw

an0.02

0.104.35

1.451.60

6.591.89

0.001.68

1.680.52

2.070.51

1.822.99

1.321.97

0.030.03

2.561.00

2.790.40

Am

ino

Acid

Pro

file (D

B)

Samp

le Id

en

tification

Page 53

Appendix G: Supplementary Temperature and Humidity Figures

Page 54


Page 55


Page 56


Page 57


Page 58