UNITED STATES SOYBEA N QUALITY Annual 2019 Report

UNITED STATES SOYBEAN QUALITY

Dr. Seth L. Naeve and Dr. Jill Miller-Garvin

Annual Report 2019

TABLE OF CONTENTS

2019 Quality Report ............................................................................. 1

References ......................................................................................... 12

Figure 1 US Soybean Planting and Harvest Progress .......................... 13

Figure 2 US Soybean, Corn, Wheat Planted Hectares ........................ 14

Figure 3 US Protein and Oil State/Regional Summary……………………...15

Table 1: Production Data for the United States, 2019 Crop ................ 16

Table 2: Quality Survey, Protein & Oil Data ........................................ 17

Table 3: Quality Survey, Seed Data ..................................................... 18

Table 4: Quality Survey, Amino Acid Data .......................................... 19

Table 5: Historical Summary of Yield & Quality Data - US Soybeans .. 20

Contact Information ........................................................................... 21

QUALITY REPORT: 2019

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SUMMARY The US Soy Family, which includes the American Soybean Association, United Soybean Board,

and US Soybean Export Council, has supported a survey of the quality of the US soybean crop

since 1986. This survey is intended to provide new crop quality data to aid international

customers with their purchasing decisions.

2019 AREA, YIELDS, AND TOTAL PRODUCTION

In 2019, US soybean planting was at its lowest level since 2011. Planting intentions for

soybeans were reduced this spring due to low soybean prices as a result of ongoing trade

tensions with China. However, excessive rainfall throughout the spring reduced soybean

acreage further.

Across the US, soybean planting was delayed by about two weeks during the spring season

(Figure 1). In most years, weather-related delays promote soybean planting as intended corn

area is transitioned into soybean, since soybean is more tolerant of delayed planting.

However, the delays were so severe in 2019 that it occasionally became too late to plant

soybean. According to the October 1, 2019 USDA Acreage Data report (USDA Update of 2019

FSA Acreage Data – see References), unplanted acres of all crops totaled 7.9 M ha, including

4.6 M ha of corn and 1.8 M ha of soybean.

In South Dakota, only 15% of the soybeans had been planted by June 1. The relatively large

drop in planted acres of soybean compared with corn in 2019 was due in part to farmer’s

intentions to plant much more corn in 2019. Although planted area of soybean decreased in

2019, unplanted corn area was much larger. A more normal spring would have led to a very

large US corn crop.

Area planted to soy was reduced by 14% compared with 2018 (Figure 2). Of the major

soybean production states, North and South Dakota saw the greatest reductions at 19 and


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36%, respectively. Reductions in North Dakota were, to a large extent, due to soybean price,

as North Dakota farmers were able to plant 13% more corn in 2019. South Dakota reductions

were primarily weather-related as conditions there were so bad that corn plantings were

reduced by 17% compared with 2018. Reduced soybean planting was not limited to the

Northwestern Corn Belt. States such as Arkansas, Michigan, and Wisconsin even saw

soybean plantings down by 19, 25, and 21%, respectively.

Delayed planting was the largest individual factor impacting soybean yields in 2019. It has

been demonstrated that soybean yields decline at a rate of about 0.7% per day after June 1

in the US Corn Belt (Egli and Cornelius, 2009). Therefore, adverse spring conditions reduced

both total area planted to soybean and yield of the soybeans that were planted. Average

soybean yields decreased from 3.4 to 3.2 MT per hectare in 2019 (Table 1). Area devoted to

soybean was only 30.6 M hectares compared with 35.5 M ha in 2018. Factored together,

total production is estimated to be reduced from 120.6 MMT in 2018 to a mere 96.7 MMT in

2019. This will be the smallest crop since 2013.

QUALITY OF THE 2019 US SOYBEAN CROP

Sample kits were mailed to 5,724 producers that were selected based on total land devoted

to soybean production, so that response distribution would closely match that of soybean

production at a finer geographical resolution. Additional kits were sent, as requested, to

interested growers. By 6 December, 2019, 1,583 samples were received. The sample

collection period was extended in 2019 as a result of a significantly delayed soybean harvest

due to delayed maturity and excess autumn rainfall events.

Samples were analyzed for protein, oil, and amino acid concentration by near-infrared

spectroscopy (NIRS) using a Perten DA7250 diode array instrument (Huddinge, Sweden)

equipped with calibrations developed by the University of Minnesota in cooperation with

Perten. A subset of samples was sent to two laboratories for assessment by AOCS-approved


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analytical chemical methods in order to validate NIR quality constituent predictions. Regional

and national average quality values were determined by computing weighted averages using

state and regional soybean production estimates, so that average values best represent the

crop as a whole. Results are in Tables 2 through 5.

PROTEIN AND OIL

Overall, 2019 soybean protein and oil results appear to be surprisingly similar to those seen

in 2018. The average US soybean protein declined by two tenths of a point to 34.1% protein

(on a 13% basis) and oil increased by one tenth to 19.0% (Table 2). Crop production

conditions were challenging in both 2018 and 2019, but excess rainfall was more evident in

the late-season in 2018, whereas it was a season-long issue in many states in 2019. The

similarity of results across these two years may indicate that the common factor (late-season

conditions) was more important for determining soybean quality. These challenging

conditions did result in lower protein levels than the historical averages, where the previous

ten-year average was 34.6. Oil was 0.1 point higher than the ten-year average of 18.9%.

Variation in soybean protein and oil by region was similar to historical trends. The lowest

regional protein values were found in the Western Corn Belt and the East Coast, while oil was

lower in both the Eastern and Western Corn Belt regions and in the East Coast region than in

the two southern regions. Regional average protein and oil values were similar to those seen

in 2018 and not largely different from historical trends. Protein was slightly lower in the

Western Corn Belt (0.2 percentage points) than in 2018. The Midsouth, Southeast, and East

coast regions had protein levels that were 0.0 to 0.7 points lower than in 2018. The East

Coast region produced soybeans with slightly lower oil levels (0.2 points) than in 2018, but

the Western Corn Belt and Southeast had similar oil levels to those in 2018 (18.8 and 19.2,

respectively).


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Among major soybean production states, protein levels dropped by 0.3 points or more in

Iowa, Minnesota, South Dakota, Michigan, and Arkansas. Protein increased by 0.5 points in

Illinois compared with the previous year. Oil increased by 0.1-0.4 points in Iowa, Kansas,

Missouri, Nebraska, and Arkansas. Oil decreased by 0.4 points in Wisconsin.

SEED WEIGHT, TEST WEIGHT AND FOREIGN MATERIAL

Seed weight in soybean is important for some food uses, but tends to impact value relatively

little for conventional processing. However, seed weight does help paint a picture of the

production environment and potential yield-limiting phases in crop growth. Seed weight is

an indicator of the relative differences in growing environment in the mid-summer vs the

late-summer. Under favorable early- and mid-season conditions, soybeans set large numbers

of seeds per plant. If late-season conditions deteriorate, the plant cannot fully fill the extra

seeds resulting in lower seed weight. Alternatively, if conditions improve from mid-season to

the seed-filling period in the late summer, the resulting seed weight will be higher.

Average seed weights increased from 16.7 in 2018 to 16.9 g per 100 seed in 2019 (Table 3).

This increase was primarily due to large increases in seed size in the Eastern Corn Belt states.

Seed size increased significantly in all ECB states except Michigan where seed weight was

unusually high in 2018. In the Western Corn Belt, North Dakota and Kansas tended to have

smaller seeds than the nearby states of South Dakota, Nebraska, and Minnesota.

Test weight (TW) is a measure of density of grains. It is an important quality factor in cereal

grains, but affects soybean quality little and is not a good indicator of value to the processor.

We report it here as it is often measured and reported with little context, which can lead to

confusion. Average TW increased from 56.1 pounds per bushel in 2018 to 56.8 in 2019 (Table

3). Test weight increased across most regions, but the largest increase was noted in the

Eastern Corn Belt where TW increased from 55.8 to 56.7 pounds per bushel in 2019. The


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Western Corn Belt average TW increased from 56.6 to 57.0 in 2019. Of the major production

states, North and South Dakota had the highest average TW.

Foreign material (FM) in soybeans sampled at the farm level continues to be very low in US

soybeans. Average FM level in US soy was 0.2% in 2019 (Table 3), similar to the long-term

trend. Of 1,583 samples, only seven had FM levels of greater than 2% and 14 had FM levels

between 1-2%. Almost 99% (98.7%) of samples had FM levels below 1%. With very low FM,

average FM levels are very dependent on the amount of FM in a small number of samples,

but the Midsouth and Southeast states tended to have higher FM levels and the Eastern Corn

Belt states tended to be the lowest. Note: the seven samples with greater than 2% FM were

from four different regions.

SUCROSE

Soybean products provide not only protein in animal feed, but also energy (Stein et al., 2008).

Sucrose in soybean and soybean meal contributes to total Metabolizable Energy (ME) in

livestock feed. Although soybean meal is an important contributor to a ration’s total ME,

nutritionists often use ‘book values’ for energy from soybean meal across origins. Our work

highlights the potential variation in ME in soybean meal based on varying sucrose levels in

soybeans. This variation tends to have a strong geographical basis to it. We have found that

soybeans from the US have higher sucrose than soybeans from Brazil (Naeve, unpublished

data), which is desirable since sucrose is positive for ME. In studies of soybean meal quality

by origin, the apparent ME in US soybean meal was significantly higher than that in meal

from Argentina and Brazil, and the higher sugar level in US soybean meal is likely a primary

driver of differences in metabolizable energy (Ravindran et al., 2014).

Within the US, we have found that soybeans produced in cooler regions have lower protein

without offsetting increases in oil, but higher sucrose levels. Average sucrose levels were 1

percentage point lower in 2019 than in 2018 (Table 3). In 2018, the Eastern and Western


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Corn Belt regions had much higher sucrose than the more southern regions. This year, these

differences were not as large, and the regions with highest sucrose were the Western Corn

Belt and East Coast.

AMINO ACIDS

Amino acids are the “building block” organic compounds linked in various combinations to

form unique proteins. Optimal animal performance occurs when the feed protein contains an

ideal amount and proportion of all essential amino acids (those amino acids which cannot be

produced by animals).

In whole soybeans, lower crude protein soybeans have a higher relative proportion of the five

most critical essential amino acids (lysine, cysteine, methionine, threonine, and tryptophan),

indicating that meal made from those soybeans will likely be of higher feed quality for a given

feed ration than meal made from higher crude protein soybeans (Thakur and Hurburgh, 2007;

Medic et al., 2014; Naeve unpublished data). We have even detected this relationship in the

thousands of samples from highly variable US regions, varieties, and management tactics.

The relative abundance of lysine (expressed as a percent of the 18 primary amino acids)

within the soybean protein fraction increased very slightly in 2019 from 6.9% of the total

amino acid fraction in 2018 to 7.1% in 2019 (Table 4). This increase was uniform across

regions and there was little variation in this value across states and regions. The sum of the

five essential amino acids (5 EAA, expressed as a percent of the 18 primary amino acids) was

high in 2018, and yet increased very slightly in 2019 (15.5) compared with 2018 (15.4).

CORRELATIONS

Understanding how soybean compositional factors are related to one another can help us

understand not only the trade-offs between attributes, but it can also lead to a better

understanding of the fundamental biology behind these factors. The relatedness of two


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factors can be measured by the Pearson correlation coefficient expressed as a number

between +1 and -1, where 1 is a total positive linear correlation, 0 is no linear correlation,

and −1 is a total negative linear correlation. Correlations do not demonstrate causation.

Correlations between factors can be found in the correlation matrix on page 8.

Because most of the attributes that we describe here are expressed as a percent of the seed

basis, trade-offs between factors naturally result in negative regressions. In 2019, protein

and oil were negatively correlated (r = -0.4). This indicates that the typical trend is to see a

tradeoff between these important constituents, but because this is not a perfect correlation,

it is possible to produce soybeans that have both high protein and oil, or that are low in both.

The 5 EAAs value is negatively correlated with protein (r = -0.8) and positively correlated with

oil (r = 0.3). This supports our recent research findings (Pfarr et al., 2018) that lower protein

soybeans have protein enriched in these five essential amino acids. There is clearly a

tradeoff between protein quantity and quality.

Sucrose is part of the residual fraction in soybean and therefore it is negatively correlated

with both protein and oil (r = -0.4 each). Soybeans that are lower in both protein and oil tend

to have higher sucrose levels.

Test weight is not tightly correlated with any measured compositional factor or seed weight.

It is loosely negatively correlated with both protein and oil (r = -0.1 and -0.2, respectively),

but positively correlated with sucrose (r = 0.3). Foreign material is weakly correlated with TW

(r = -0.2). This is likely due to the direct contribution of the low density FM to the soybeans.


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Correlation Matrix

Protein (13%)

Oil (13%)

Sucrose (db)

TW (lb/bu)

FM (%)

Lysine (% 18AA)

5EAAs (% 18AA)

Protein (13%) 1.00 -0.36 -0.38 -0.12 0.06 -0.83 -0.80

Oil (13%) 1.00 -0.44 -0.21 0.04 0.17 0.29

Sucrose (db) 1.00 0.30 -0.07 0.43 0.27

TW (lb/bu) 1.00 -0.20 0.13 0.05

FM (%) 1.00 -0.08 -0.02

Lysine (% 18AA) 1.00 0.78

5 EAAs (% 18AA) 1.00


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WEATHER AND CROP SUMMARY

Record-setting precipitation during planting (Weather Figure 1) and, in some regions,

throughout the growing season and harvest (Weather Figures 2 & 3), summarizes the 2019

US growing season.

Planting: In April, soybean-producing states experienced average temperatures overall, but

record lows exceeded record highs. Widespread and persistent flooding occurred in April in

the Midwest and planting was delayed because of wet, cold conditions in states west of the

Ohio River Valley (Weather Figure 1); temperatures were average or above average east of

this area. By the end of May, the 18 states that produce 95% of the U.S. acreage were at 29%

planted, 37 percentage points behind the 2014-2018 5-year average. By the middle of June,

those 18 states were at 77% planted rather than in the 90% range as in the 5-year average.

Excess rainfall also caused severe flooding that affected more than crop production itself;

flooding damaged stored grains and inhibited barge traffic on major waterways.

Mid-Season: Temperatures were mostly average during the growing season, but rainfall

continued to be either in excess or deficit depending on the region (Weather Figure 2). Some

states that had been experiencing excessive rainfall turned dry (Minnesota, Iowa, northern

Illinois and Michigan) or remained too wet (South Dakota, Nebraska, parts of Kansas,

Missouri, Ohio, southern Indiana, and Michigan), while other areas that had earlier been dry

received excessive rainfall (Tennessee, parts of Kentucky). Crop development lagged behind

that of 2018 and the US 5-year average; by the end of July, 21% of the US soybean crop was

setting pods, 37% behind 2018 and 24% behind the 5-year average.

Harvest: By September 1, only 86% of the crop was setting pods, the slowest US soybean

development on record back to 1995. Moreover, above and much above average rainfall

returned to areas previously affected by the wet spring (Weather Figure 3), including the

major soybean-producing states Iowa, Minnesota, South Dakota and North Dakota, and


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northern parts of Illinois and Indiana. States in the Ohio River Valley and eastward faced

much below to record dry conditions. October for the majority of the top 10 soybean-

producing states brought well above average rainfall that severely delayed harvest in many

states (Weather Figure 4).


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Weather Figure 1 Weather Figure 2

Weather Figure 3 Weather Figure 4


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REFERENCES Egli, D.B., and P.L. Cornelius. 2009. A Regional Analysis of the Response of Soybean Yield to Planting Date. Agron. J. 101(2): 330-335. Federal Grain Inspection Service. 2004. Test Weight. In Grain Inspection Handbook II (Chapter 10). Washington DC: USDA-GIPSA-FGIS. Medic, J., C. Atkinson, and C.R. Hurburgh Jr. 2014. Current knowledge in soybean composition. J. Am. Oil Chem. Soc. 91(3):363-384. Midwest Climate Watch. 2019. Available at: <mcc.sws.uiuc.edu/cliwatch/watch.htm> National Agricultural Statistics Service: NASS. 2019. Available at: <nass.usda.gov> Pfarr, M.D., M.J. Kazula, J.E. Miller-Garvin, and S.L. Naeve. 2018. Amino acid balance is affected by protein concentration in soybean. Crop Sci. 58:1-13. Ravindran, V., M.R. Abdollahi, and S.M. Bootwalla. 2014. Nutrient analysis, metabolizable energy, and digestible amino acids of soybean meals of different origins for broilers. Poultry Sci. 93:2567-2577. Stein, H.H., L.L. Berger, J.K. Drackley, G.F. Fahey, Jr., D.C. Hernot, and C.M. Parsons. 2008. Nutritional properties and feeding values of soybeans and their coproducts. pp. 613-660 In Soybeans, Chemistry, Production, Processing, and Utilization. L.A. Johnson, P.J. White, and R. Galloway, eds. AOCS Press, Urbana, IL. Thakur, M., and C.R. Hurburgh. 2007. Quality of US soybean meal compared to the quality of soybean meal from other origins. J. Am. Oil Chem. Soc. 84:835-843. USDA Update of 2019 FSA Acreage Data, August 27, 2019. Available at: https://www.usda.gov/oce/commodity/reports/NASSandFSAacreage_08222019.pdf Weekly Weather and Crop Bulletin. 2019. Jointly prepared by the U.S. Department of Commerce, National Oceanic and Atmospheric Administration (NOAA), and the U.S. Department of Agriculture (USDA). Available at: <usda.gov/oce/weather/pubs/Weekly/Wwcb/>

https://www.usda.gov/oce/commodity/reports/NASSandFSAacreage_08222019.pdf


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Figure 1

US Soybean Planting and Harvest Progress

Day of the Year4/25 5/2 5/95/16

5/235/30 6/66/13

6/206/27 7/49/19

9/2610/3

10/1010/17

10/2410/31

11/711/14

11/2111/28

% o

f US

Cro

p Pl

ante

d or

Har

vest

ed b

y da

te

0

20

40

60

80

100

2019 Planting Progress'14 - '18 Average2019 Harvest Progress'14 - '18 Average

source: USDA NASS


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Figure 2

Soybean, Corn, and Wheat in the US (planted ha)

19881990

19921994

19961998

20002002

20042006

20082010

20122014

20162018

2020

Plan

ted

area

(M H

a)

15

20

25

30

35

40

45SoybeanCornWheat


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Figure 3


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Table 1. Soybean production data for the United States, 2019 crop

Region StateYield

(MT ha-1)Area Harvested

(1000 ha)Production

(MMT)

Iowa 3.6 3,698 13.2Kansas 3.0 1,839 5.4Minnesota 3.0 2,762 8.4Missouri 3.1 2,037 6.3Nebraska 3.8 2,005 7.7North Dakota 2.2 2,248 5.0South Dakota 2.9 1,442 4.2

Western Corn Belt 3.1 16,030 50.151.8%

Illinois 3.4 4,026 13.8Indiana 3.3 2,175 7.2Michigan 2.8 697 2.0Ohio 3.2 1,729 5.6Wisconsin 3.1 701 2.2

Eastern Corn Belt 3.2 9,327 30.731.7%

Arkansas 3.4 1,053 3.5Kentucky 3.4 684 2.3Louisiana 3.2 348 1.1Mississippi 3.4 656 2.2Oklahoma 1.7 178 0.3Tennessee 3.2 559 1.8Texas 2.1 28 0.1

Midsouth 2.9 3,506 11.311.7%

Alabama 2.5 107 0.3Georgia 1.7 38 0.1North Carolina 2.4 620 1.5South Carolina 2.0 134 0.3

Southeast 2.2 899 2.12.2%

Delaware 2.6 62 0.2Maryland 3.0 192 0.6New Jersey 2.8 38 0.1New York 3.1 93 0.3Pennsylvania 3.2 253 0.8Virginia 2.3 227 0.5

East Coast 2.8 866 2.52.6%

US 2019 3.2 30,629 96.7US 2018 3.4 35,476 120.6Source: United States Department of Agriculture, NASS 2018 Crop Production Report (November 2019)

East Coast (EC)

Western Corn Belt (WCB)

Eastern Corn Belt (ECB)

Midsouth (MDS)

Southeast (SE)


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Protein Oil(%)* (%)*

Iowa 208 33.5 1.0 19.2 0.6Kansas 65 34.9 1.0 18.9 0.6Minnesota 217 33.6 1.0 18.5 0.6Missouri 79 34.5 1.4 19.3 0.6Nebraska 128 33.8 0.9 19.1 0.6North Dakota 70 33.3 1.3 18.1 0.7South Dakota 80 33.7 0.9 18.4 0.7

Averages† Western Corn Belt 847 33.8 1.1 18.8 0.6

Illinois 270 34.3 1.0 19.1 0.6Indiana 94 34.6 1.2 19.0 0.7Michigan 48 34.5 1.3 18.5 0.6Ohio 106 35.0 1.2 18.7 0.8Wisconsin 26 33.8 1.4 18.3 0.6

Averages† Eastern Corn Belt 544 34.5 1.1 18.9 0.7

Arkansas 33 34.6 1.4 19.8 0.7Kentucky 23 34.4 1.5 19.5 0.7Louisiana 14 35.4 1.0 19.7 0.6Mississippi 23 34.5 0.9 19.7 0.6Oklahoma 2 33.7 0.4 19.5 1.0Tennessee 19 33.9 1.1 20.0 0.7Texas 0

Averages† Midsouth 114 34.5 1.2 19.7 0.7

Alabama 4 34.5 2.1 20.0 1.1Georgia 3 35.1 0.4 19.2 0.3North Carolina 22 34.9 1.5 19.2 0.9South Carolina 6 35.4 1.7 18.7 0.8

Averages† Southeast 35 34.9 1.6 19.2 0.9

Delaware 5 34.9 0.8 19.6 0.3Maryland 11 34.6 1.2 19.0 0.7New Jersey 4 35.9 1.0 18.5 0.3New York 11 34.7 1.0 17.8 0.6Pennsylvania 8 34.0 1.5 18.4 0.6Virginia 4 33.6 1.8 19.6 0.7

Averages† East Coast 43 34.3 1.4 18.9 0.6

US Averages 1,583 34.1 18.9Average of 2019 Crop† 34.1 1.1 19.0 0.6US 2009-2018 avg.† 34.6 1.3 18.9 1.0

* 13% moisture basis† Regional, US, and 10-year average values w eighted based on estimated production by state as estimated by USDA, NASS Crop Production Report (November 2019)


Midsouth (MDS)

Southeast (SE)

East Coast (EC)

Table 2. USB 2019 Soybean Quality Survey Data

Region State Number of Samples


Std. Dev. Std. Dev.


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SeedWeight

(g 100 seeds-1)











USA Averages 1,583 17.0 56.9 0.2 4.8Average of 2019 Crop† 16.9 56.8 0.2 4.8

† Regional and US average values w eighted based on estimated production by state as estimated byUSDA, NASS Crop Production Report (November 2019)

Table 3. USB 2019 Soybean Quality Survey Seed Data

Region StateNumber of Samples

Test Weight (lb bu-1)

Foreign Material

(%)

Sucrose (db)


Midsouth (MDS)

Southeast (SE)

East Coast (EC)



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Protein(%)*











US Averages 1,583 34.1 7.1 15.5 25.2Average of 2019 Crop† 34.1 7.1 15.5 25.2

* 13% moisture basis‡ Five essential amino acids (also know n as CAAV): cysteine, lysine, methionine, threonine, and tryptophan§ Seven essential amino acids: f ive listed above and isoleucine, valine† Regional and US average values w eighted based on estimated production by state as estimated byUSDA, NASS Crop Production Report (November 2019)

7 EAAs§

(%18 AAs)


Midsouth (MDS)

Southeast (SE)

East Coast (EC)


5 EAAs‡

(%18 AAs)

Table 4. USB 2019 Soybean Quality Survey Amino Acid (AA) Data

Region StateNumber of Samples

Lysine (%18 AAs)


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Year Yield Protein* Oil* Sum† Harvested Production Protein Oil(kg ha-1) (%) (%) (%) (M ha-1) (M MT) Std. Dev. Std. Dev.

1986 2241 35.8 18.5 54.3 23.6 52.9 1.4 0.71987 2281 35.5 19.1 54.6 23.2 52.8 1.6 0.71988 1817 35.1 19.3 54.4 23.2 42.2 1.5 0.81989 2173 35.2 18.7 53.9 24.1 52.4 1.5 0.81990 2295 35.4 19.2 54.6 22.9 52.5 1.2 0.71991 2301 35.5 18.7 54.1 23.5 54.0 1.4 0.91992 2530 35.6 17.3 52.8 23.6 59.6 1.4 1.01993 2194 35.7 18.0 53.8 23.2 50.9 1.2 0.91994 2786 35.4 18.2 53.6 24.6 68.6 1.4 0.91995 2375 35.5 18.2 53.6 24.9 59.2 1.4 0.91996 2530 35.6 17.9 53.5 25.7 64.9 1.3 0.91997 2618 34.6 18.5 53.0 28.0 73.2 1.5 1.01998 2618 36.1 19.1 55.3 28.5 74.6 1.5 0.81999 2456 34.6 18.6 53.2 29.4 72.1 1.9 1.12000 2557 36.2 18.7 54.9 29.6 75.6 1.7 0.92001 2651 35.0 19.0 54.0 30.0 79.6 2.0 1.12002 2490 35.4 19.4 54.8 29.1 72.2 1.6 0.92003 2288 35.7 18.7 54.3 29.4 67.2 1.7 1.22004 2826 35.1 18.6 53.7 30.0 84.6 1.5 0.92005 2893 34.9 19.4 54.3 29.2 83.4 1.5 0.9

2006‡ 2873 34.5 19.2 53.7 30.2 86.8 1.6 1.0

2007‡ 2806 35.2 18.6 53.9 26.0 72.9 1.2 0.8

2008‡ 2644 34.1 19.1 53.2 30.1 79.6 1.4 0.8

2009‡ 2961 35.3 18.6 53.9 30.9 91.5 1.2 0.9

2010‡ 2954 35.0 18.6 53.6 31.1 91.9 1.4 1.2

2011‡ 2793 34.9 18.1 53.0 29.8 83.4 2.2 1.8

2012‡ 2678 34.3 18.5 52.8 30.8 82.6 1.6 0.9

2013‡ 2961 34.7 19.0 53.7 30.9 91.5 1.1 1.02014‡ 3196 34.4 18.6 53.0 33.8 107.8 1.3 0.92015‡ 3176 34.3 19.8 54.1 33.1 105.9 1.1 0.82016‡ 3459 34.5 19.3 53.8 33.6 116.3 1.2 0.72017‡ 3331 34.1 19.1 53.2 36.2 120.5 1.2 0.92018‡ 3573 34.1 19.0 53.1 35.8 127.7 1.1 0.72019‡ 3156 34.1 19.0 53.1 30.6 96.7 1.1 0.6

Averages (2009-2018) 3108 34.6 18.9 53.4 32.6 101.9 1.3 1.0

Averages (1986-2018) 2677 35.1 18.7 53.8 28.4 77.3 1.4 0.9

Sources: US Dept. of Agriculture, Iowa State University, and University of Minnesota*Protein and oil concentrations expressed on a 13% moisture basis†Sum represents sum of protein and oil concentrations‡2006 - 2019 quality estimates are weighted by yearly production estimates by state

Table 5. Historical Summary of Yield and Quality Data for U.S. Soybeans


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Contact Information

DR. SETH L. NAEVE SOYBEAN EXTENSION AGRONOMIST

DR. JILL MILLER-GARVIN RESEARCHER

[email protected] [email protected]

University of Minnesota Department of Agronomy & Plant Genetics 411 Borlaug Hall 1991 Upper Buford Circle St. Paul, MN 55108 Tel 612-625-4298 http://z.umn.edu/soybean-quality

Funding provided by the United Soybean Board

UNITED STATES SOYBEA N QUALITY Annual 2019 Report

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