Quality Characteristics of Midwestern Soybeans

Hurburgh, Charles R.; ., Jr.; Paynter, Lynn N.; Schmitt, Steven G.

doi:10.13031/2013.26665

Cited by 17 publications

(3 citation statements)

References 2 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The concentrations of these two components are genetically predetermined but can vary depending on the environment [18]. The protein and oil content of soybean seeds are negatively correlated [19,20]. A higher temperature during reproductive growth tends to result in higher oil content [21,22].…”

Section: Introductionmentioning

confidence: 99%

Environmental Effects on Soybean (Glycine Max (L.) Merr) Production in Central and South Germany

et al. 2020

View full text Add to dashboard Cite

The cultivation area of soybean (Glycine max (L.) Merr) is increasing in Germany as a way to ensure self-sufficiency through its use as feed and food. However, climatic conditions needed for soybean cultivation are not appropriate in all parts of the country. The objective of this study was to determine the influence of solar radiation, temperature, and precipitation on soybean seed productivity and quality in central and south Germany. A multi-factorial field trial was carried out with three replicates at four locations in 2016 and five locations in 2017, testing 13 soybean varieties from the maturity groups MG 00 and MG 000. Considering all the tested factors, “variety” was highly significant concerning protein content (Ø 41.1% dry matter (DM)) and oil content (Ø 19.1% in DM), but not seed yield (Ø 40.5 dt ha−1).The broad sense heritability of protein content was H2 = 0.80 and of oil content H2 = 0.7. Protein and oil content were significantly negatively correlated (r = −0.82). Seed yield was significantly positively correlated with solar radiation (r = 0.32) and precipitation (r = 0.33), but significantly negatively with Crop Heat Units (CHU) (r = −0.42). Over both experimental years, varieties from maturity group MG 00 were less significantly correlated with the tested environmental factors than varieties from maturity group MG 000. None of the environmental factors tested significantly increased the protein or oil content of soybean. In growing areas with heat periods during ripening, protein content tended to be higher than in cooler areas; in areas with high solar radiation during flowering, protein content tended to be reduced.

show abstract

Section: Introductionmentioning

confidence: 99%

Environmental Effects on Soybean (Glycine Max (L.) Merr) Production in Central and South Germany

et al. 2020

View full text Add to dashboard Cite

show abstract

“…They also reported that the effects of year and location on oil content were both significant, but that there was little effect of either on protein content. Hurburgh et al (1987) studied soybean samples from grain elevators in four states of the United States. The oil concentration of soybean was higher in the hotter, drier year and the soybean samples with highest contents of oil were from the area with the most severe drought.…”

mentioning

confidence: 99%

Regional Distribution of Protein and Oil Compositions of Soybean Cultivars in China

et al. 2014

View full text Add to dashboard Cite

Soybean [Glycine max (L.) Merr.] seed, which contains high levels of oil and protein, is one of China's most important native crops. The aim of this study was to investigate how regional and environmental factors affect the compositions of protein, amino acids, oil, and fatty acids. A total of 127 soybean cultivars from four main regions of China were analyzed. The levels of total protein and most of amino acids showed a trend of increasing from Northern to Southern China, while the levels of total oil, stearic acid, linolenic acid, and proline showed a trend of decreasing. The variation of protein, oil, palmitic acid, and linoleic acid content of soybean grown in the four regions was low, while variation of other constituents remained high. Most amino acids contents were positively correlated with protein content. The total oil content showed a negative correlation with protein content. The content of linolenic acid was positively correlated with the content of palmitic acid and stearic acid but negatively correlated with the oleic acid content. The southern regions have the potential for high‐protein soybean production, while the northern regions of China have the potential for high‐oil soybean production.

show abstract

“…The typical trade between producers and elevators and elevators and processors are stand-alone decisions not involving composition. Elevators and processors pay based on U.S. Grades of test weight, moisture, and foreign material, not on protein and oil content (Hurburgh et al, 1987;Laux et al, 2015). This procedure takes place despite the importance of protein and oil content for end users (Brumm and Hurburgh, 2006;Medic et al, 2014).…”

mentioning

confidence: 99%

Maximizing Processing Value with Selective Handling Strategies: An Analysis of Soybeans Received at Iowa Elevators

Barr¹,

Hurburgh²,

Mosher³

2021

Applied Engineering in Agriculture

View full text Add to dashboard Cite

Highlights Levels of protein and oil influence the marketability of soybeans Geographic differences in soybeans have economic implications for grain elevators Random errors in the receiving and analysis process mask these differences For soybeans to be marketed on protein and oil levels, errors in handling and analysis must be addressed Abstract . A better ability to understand and use geographic variations in protein and oil is one way to maximize the value potential of soybeans for handlers and processors. An Iowa cooperative had been sourcing soybeans for processing from nearby elevator locations and wanted to know whether this strategy was maximizing the net processing value of the soybeans. Random and systematic errors from testing and measurement instruments also impact marketing decisions and were investigated as part of this project. During the Fall 2018 soybean harvest, soybean samples were collected from 32 country elevator locations belonging to one Iowa-based cooperative which has its own soybean processing plant. Samples were analyzed using near-infrared spectroscopy (NIR), and protein and oil content data were entered into an Estimated Processing Value (EPV) model to determine value differences of soybeans among elevator locations. Results showed substantial variability among locations that represented a $0.23/bushel EPV spread. No significant variation was found in soybean quality over the harvest season, suggesting that marketing decisions can be made at the beginning of the season. To determine the incidence of random errors, a simulated Excel-based model was used with three test cases. The introduction of random error lowered value gaps between locations, which made the discrimination of high-value locations from average or low-value locations difficult. Although protein and oil measurement with the NIR instrument was feasible even on busy harvest season days, the validity of marketing decisions using these data depended highly on the error involved in sample analysis. Future studies should identify specific sources of error and attempt to eliminate them. Specifically, one of the largest sources of error in a commodity-based market system is in the measuring units. The ability to isolate and quantify measurement error will improve the capability of the commodity-based soybean market system to focus trade decisions on end use traits, maximizing soybean value and providing incentive for improvement. Keywords: Error analysis, Grain elevators, Selective handling, Soybean processing, Soybean value.

show abstract

Quality Characteristics of Midwestern Soybeans

Cited by 17 publications

References 2 publications

Environmental Effects on Soybean (Glycine Max (L.) Merr) Production in Central and South Germany

Environmental Effects on Soybean (Glycine Max (L.) Merr) Production in Central and South Germany

Regional Distribution of Protein and Oil Compositions of Soybean Cultivars in China

Maximizing Processing Value with Selective Handling Strategies: An Analysis of Soybeans Received at Iowa Elevators

Contact Info

Product

Resources

About