US Soybean Research Articles

Study on the cross-correlation between two country for soybean futures price and exchange rate

The paper investigates the connection between two countries’ foreign exchange and futures market for soybean, DCE NO.1 soybean and CBOT soybean as the research object by using multifractal detrended cross-correlation analysis (MF-DCCA). Results indicate a significant multifractal cross-correlation among USDCNY and two country’s soybean futures. By contrasting the multifractality of the original series to processed series, we discover that the fat-tailed distribution serves as the primary cause for USDCNY-DCE sets while the long-range correlation explains the other. Our result shows that the soybean futures in China has a higher multifractality degree, but the fluctuation of exchange rate has a better pass-through effect on the price of US soybean futures’ market.

The Impact of the U.S.-China Trade Dispute and COVID-19 on the Korean Soybean Market

Purpose - This study examines the impact of the U.S.-China trade dispute and COVID-19 on the Korean soybean market. Design/Methodology/Approach - A bilateral trade soybean model considered the Armington and spatial equilibrium approaches is used to analyze scenarios: (1) Removing China’s retaliatory tariff on US soybean without COVID-19, (2) Removing China’s retaliatory tariff on US soybean with COVID-19, and (3) No change in retaliatory tariff on US soybean with COVID-19. These scenario results are compared with the baseline that the U.S.-China trade dispute is in place continuously. Findings - The results show that removing China’s retaliatory tariff decreases domestic soybean imports and rises prices in Korea. Moreover, if we take COVID-19 into account, the decrease in domestic soybean imports is relatively larger and COVID-19 falls the domestic soybean price because of the decrease in domestic consumption. The soybean price impact of the U.S.-China trade dispute along with COVID-19 is larger than the U.S.-China trade dispute without COVID-19 in the absolute difference. If China eliminates tariff on US soybean with COVID-19, then the fall in domestic soybean imports is larger and the price is smaller. Research Implications - This study provides the impact of the U.S.-China trade dispute with COVID-19 on the Korean soybean market. The results showing the price variation from the scenario analysis imply that the Korean agricultural market needs to be monitored because of the response in the agricultural market to shocks. Moreover, the model used for this study gives traders and policy makers a tool to analyze the Korean soybean market.

Modeling Gross Primary Production of Midwestern US Maize and Soybean Croplands with Satellite and Gridded Weather Data

Gross primary production (GPP) is a useful metric for determining trends in the terrestrial carbon cycle. To estimate daily GPP, the cloud-adjusted light use efficiency model (LUEc) was developed by adapting a light use efficiency (LUE, ε) model to include in situ meteorological data and biophysical parameters. The LUEc uses four scalars to quantify the impacts of temperature, water stress, and phenology on ε. This study continues the original investigation in using the LUEc, originally limited to three AmeriFlux sites (US-Ne1, US-Ne2, and US-Ne3) by applying gridded meteorological data sets and remotely sensed green leaf area index (gLAI) to estimate daily GPP over a larger spatial extent. This was achieved by including data from four additional AmeriFlux locations in the U.S. Corn Belt for a total of seven locations. Results show an increase in error (RMSE = 3.5 g C m−2 d−1) over the original study in which in situ data were used (RMSE = 2.6 g C m−2 d−1). This is attributed to poor representation of gridded weather inputs (vapor pressure and incoming solar radiation) and application of gLAI algorithms to sites in Iowa, Minnesota, and Illinois, calibrated using data from Nebraska sites only, as well as uncertainty due to climatic variation. Despite these constraints, the study showed good correlation between measured and LUEc-modeled GPP (R2 = 0.80 and RMSE of 3.5 g C m−2 d−1). The decrease in model accuracy is somewhat offset by the ability to function with gridded weather datasets and remotely sensed biophysical data. The level of acceptable error is dependent upon the scope and objectives of the research at hand; nevertheless, the approach holds promise in developing regional daily estimates of GPP.

VOLATILITIY OF WORLD FOOD COMMODITY PRICES AND RENEWABLE FUEL STANDARD POLICY

Biofuel as an alternative fuel which in recent years has become the world's demand for renewable energy fuels and is a major factor underlying the increase in prices of agricultural commodities, especially corn as the main commodity for biofuels in the US. The purpose of this study is to examine the volatility of several world food commodities, namely rice, wheat, corn, and soybeans and to analyze the impact of biofuel development on the price volatility of some world food commodities. This research uses coefficient of variation and volatility analysis with the ARCH GARCH method. Based on the results, the price of food commodities is more volatile after the adoption of the Renewable Fuel Standard 2 (RFS) policy in 2007. The results of the study show that development of biofuels (from corn and soybeans) have a higher level of volatility than the other two commodities (rice and wheat) due to the variance of rice and wheat was lower than corn and soybeans. It means that the greater the relevance of a commodity to the development of biofuels, the higher the price volatility of the commodity. Meanwhile, the expansion of biofuels also made US reduce the amount corn and soybean exports, of course this is what makes the supply of US corn and soybeans decreased and makes the price will increase.

Interrelationships of US Corn and Soybean Cash and Futures Markets with Storage Price Dependence: The Role of Futures Prices and Model Development

This study develops a basic conceptual model of the link between supply, demand and international trade, storage and cash, future prices as well as basis (storage prices) of several popular crops, such as corn and soybean, grown in the United States. Corn and soybean are the most common crops in the United States and are the main source of feed grains for cattle, dairy, poultry and hog production. Basically, we provide a brief synopsis of the theoretical concepts that form the basis for the mathematical model of US corn and soybean sectors. The focus is on theories related to the conceptual framework of demand and supply response, as well as the theory of price-of-storage. The theoretical model of simultaneous equilibrium in cash, futures and storage markets is then developed. In particular, the role of futures price is of greater concern in model setting.

The Impact of Logistics Performance on Argentina, Brazil, and the US Soybean Exports from 2012 to 2018: A Gravity Model Approach

Soybean is one of the main sources of protein directly and indirectly in human nutrition, and it is highly dependent on logistics to connect country growers and international markets. Although recent studies deal with the impact of logistics on international trade, this impact in agricultural commodities is still an open research question. Moreover, these studies usually do not consider the influence of all components of the logistics on trade. This paper, therefore, aims at identifying the role of logistics performance in soybean exports among Argentina, Brazil, the US and their trading partners from 2012 to 2018. Using an extended gravity model, we examine whether the indicators of the World Bank Logistics Performance Index (LPI), adopted as a proxy of logistics efficiency, are an important determinant of bilateral soybean trade facilitation. The results lead to the conclusion that it is necessary to analyze the LPI throughout its indicators because they may affect trade differently. The novelty of this article is to provide an analysis of the impact of different logistics aspects on commodity trade, more specifically in the soybean case. Finally, regarding the model results, logistics infrastructure has a positive and significant correlation with soybean trade as supposed in most of the literature.

The value of insect management to US maize, soybean and cotton farmers.

Most US maize, soybean and cotton farmers use Bt crops, insecticidal seed treatments, soil-applied insecticides, and foliar sprays to manage insect pests. Given the global economic importance of these crops, we examine farmer benefits of this insecticide use. Using a telephone survey, we document pest management practices and concerns, estimate adoption and farmer perceived values for these practices, and determine factors besides yield and cost that impact adoption and perceived value. Seed-based technologies (Bt seed, seed treatments) dominated insecticide use. Almost 80% of respondents' planted hectares used Bt crops and more than half used seed treatments, while about one-sixth used soil insecticides and one-sixth to one-third used foliar insecticides. Perceived farmer values per treated hectare were greatest for Bt cotton and foliar insecticides in cotton, especially after first bloom. Values for maize and other cotton insecticide uses were greater than for soybean. Aggregating over treated areas, the largest total values for each crop were for seed-based technologies. In addition to yield and cost, farmers showed significant concern for economic risk and human and environmental safety when making pest management decisions. These non-monetary concerns significantly affected the likelihood farmers used these practices and their perceived value. For these crops, seed-based insecticides dominate farmer insecticide use and the value they derive from insecticides. Because seed purchase is months before planting, farmers rely on risk-based integrated pest management to make pest management decisions, weighing both monetary and non-monetary factors when deciding whether the risks are sufficient to justify the use of insecticides. © 2020 Society of Chemical Industry.

Resource-richness and economic growth in contemporary U.S.

Abstract We study the effects of energy innovation and policy on income growth. Between 1997 and 2014, US corn, soybean, and cotton production almost fully converted to genetically modified crops. Starting around 2007, improved tight oil and shale gas technologies turned the declining US fossil fuel production into a booming industry. We study the effects of these two resource technology revolutions on US state income. We find that the shale revolution increased income in states abundant in oil and gas resources. States dependent on agricultural production also saw an increase in income, which we, however, attribute not only to the GM innovation but to a demand increase brought by the Energy Policy Act of 2005.

Climate change and adaptation in agriculture: Evidence from US cropping patterns

Understanding how a changing climate alters regional comparative advantage is crucial for evaluating the economic impacts of climate change. I exploit temporal variation in decades-long averages of weather and estimate crop acreage elasticities with respect to climate change in the United States. I find substantial climate change adaptation through acreage adjustments in US agriculture. Climate change explains about 10–35% of the observed US corn and soybean expansion over the past 30 years, and climate-driven crop substitution has played an important role. The acreage response is heterogeneous across major and minor producing areas and across dryland and irrigated counties.

Do farmers manage weeds on owned and rented land differently? Evidence from US corn and soybean farms.

It has been frequently argued that growers have less incentive to manage the evolution and spread of herbicide-resistant weeds on leased than on owned land. This is because resistance management provides long-term rather than short-term benefits that operators may be less assured of capturing on land they do not own. Yet, empirical evidence supporting this argument has been lacking. This study reports on results from a large-scale national survey of weed management and other crop production practices on US agricultural fields. Up to 11 weed management practices were compared across owner-operated versus renter-operated fields. Analysis of survey data from corn and soybean fields did not support the hypothesis that adoption of resistance management practices is lower on rented acres. In most instances, there were no statistically significant differences in herbicide use or weed management practices on rented versus owned land. This was true at both national and regional levels of analysis. Where there were significant differences, practices associated with greater herbicide resistance management were, as often as not, more prevalent on rented than owned land. A useful area of future research would be to test for land tenure differences in resistance management using multivariate analysis to control for confounding effects. Unobserved farmer or land characteristics may be confounding results and masking land tenure effects. Results here, however, suggest that these other effects are dominating any obvious disincentive effects of land leasing on resistance management. Of greater concern, the adoption of key resistance management practices was low on both owned and rented land. © 2020 Society of Chemical Industry.

Nested association mapping of important agronomic traits in three interspecific soybean populations

Glycine soja germplasm can be used to successfully introduce new alleles with the potential to add valuable new genetic diversity to the current elite soybean gene pool. Given the demonstrated narrow genetic base of the US soybean production, it is essential to identify beneficial alleles from exotic germplasm, such as wild soybean, to enhance genetic gain for favorable traits. Nested association mapping (NAM) is an approach to population development that permits the comparison of allelic effects of the same QTL in multiple parents. Seed yield, plant maturity, plant height and plant lodging were evaluated in a NAM panel consisting of 392 recombinant inbred lines derived from three biparental interspecific soybean populations in eight environments during 2016 and 2017. Nested association mapping, combined with linkage mapping, identified three major QTL for plant maturity in chromosomes 6, 11 and 12 associated with alleles from wild soybean resulting in significant increases in days to maturity. A significant QTL for plant height was identified on chromosome 13 with the allele increasing plant height derived from wild soybean. A significant grain yield QTL was detected on chromosome 17, and theallele from Glycine soja had a positive effect of 166kgha-1; RIL's with the wild soybean allele yielded on average 6% more than the lines carrying the Glycine max allele. These findings demonstrate the usefulness and potential of alleles from wild soybean germplasm to enhance important agronomic traits in a soybean breeding program.

Dynamic gene expression changes in response to micronutrient, macronutrient, and multiple stress exposures in soybean

Preserving crop yield is critical for US soybean production and the global economy. Crop species have been selected for increased yield for thousands of years with individual lines selected for improved performance in unique environments, constraints not experienced by model species such as Arabidopsis. This selection likely resulted in novel stress adaptations, unique to crop species. Given that iron deficiency is a perennial problem in the soybean growing regions of the USA and phosphate deficiency looms as a limitation to global agricultural production, nutrient stress studies in crop species are critically important. In this study, we directly compared whole-genome expression responses of leaves and roots to iron (Fe) and phosphate (Pi) deficiency, representing a micronutrient and macronutrient, respectively. Conducting experiments side by side, we observed soybean responds to both nutrient deficiencies within 24 h. While soybean responds largely to –Fe deficiency, it responds strongly to Pi resupply. Though the timing of the responses was different, both nutrient stress signals used the same molecular pathways. Our study is the first to demonstrate the speed and diversity of the soybean stress response to multiple nutrient deficiencies. We also designed the study to examine gene expression changes in response to multiple stress events. We identified 865 and 3375 genes that either altered their direction of expression after a second stress exposure or were only differentially expressed after a second stress event. Understanding the molecular underpinnings of these responses in crop species could have major implications for improving stress tolerance and preserving yield.

Productivity Spillovers From Pollution Reduction: Reducing Coal Use Increases Crop Yields

Air pollution reduces crop yields by slowing down photosynthesis. We estimate the increase in US corn and soybean yields attributed to the recent dramatic reductions in emissions of nitrogen oxides (NOx) from electric power plants. In response to the observed changes in power plant NOx emissions over the eight‐year period from 2003–05 to 2011–13, we estimate that average corn yields improved by 2.46% and soybean yields by 1.62%. These improvements imply an increase in total surplus of $1.60 billion annually across the two crops. The estimated yield improvements vary substantially across states depending on the change in NOx emissions. For corn, they range from 0.32% to 6.87% and for soybeans, they range from 0.21% to 4.30%. The demand for the two crops is quite inelastic, which means that prices decrease by more than production increases in response to this positive productivity shock and the implied rightward shift of the crop supply curve. Due to the low elasticities of supply and demand for U.S. corn and soybeans, we conclude from a welfare analysis that these changes made consumers better off and farmers worse off.

Genetic Improvement of US Soybean in Maturity Groups V, VI, and VII

Soybean [Glycine max (L.) Merr.] is an important source of protein and vegetable oil. Genetic improvement of soybean seed yield and composition are ultimate breeding goals. During the past 80 yr, breeders have selected for high yield and other desired traits to make genetic improvements. To quantify the genetic changes to seed yield, yield stability, and other important agronomic and end‐use quality traits, we evaluated 93 soybean cultivars in Maturity Groups (MG) V, VI, and VII that were released from 1928 to 2008. Replicated yield trials specific for each MG set of cultivars were conducted during 2010 to 2011 in a total of 27 southeastern US year‐location environments. A mixed linear model was used to calculate best linear unbiased predictors (BLUPs) for each cultivar for each measured trait within each MG. Regressed cultivar effect BLUPs of each trait by year of cultivar release revealed positive linear trends for annualized genetic yield gains of 17.6, 13.5, and 10.3 kg ha−1 yr−1 for MG V, VI, and VII, respectively. Averaged across MGs, the annualized rate of genetic gain was estimated to be 13.7 kg ha−1 yr−1. Yield stability analyses revealed significant differences in regression coefficients (b), which were >1.0 for newer cultivars but <1.0 for older cultivars. Overall, the average annualized rate of genetic gains for seed yield reported herein are equivalent to those previously reported, indicating that a yield plateau has not been reached for MG V, VI or VII soybean cultivars.

How Amaranthus Palmeri Evolved from an Obscure North American Plant to Become the Biggest Weed Problem in the US Corn and Soybean Belt

How <i>Amaranthus Palmeri</i> Evolved from an Obscure North American Plant to Become the Biggest Weed Problem in the US Corn and Soybean Belt

Valuing product innovation: genetically engineered varieties in US corn and soybeans

AbstractWe develop a discrete‐choice model of differentiated products for US corn and soybean seed demand to study the welfare impact of genetically engineered (GE) crop varieties. Using a unique data set spanning the period 1996–2011, we find that the welfare impact of the GE innovation is significant. In the last five years of the period analyzed, our preferred counterfactual indicates that total surplus due to GE traits was $5.18 billion per year, with seed manufacturers appropriating 56% of this surplus. The seed industry obtained more surplus from GE corn, whereas farmers received more surplus from GE soybeans.

Environmental Stability Study of Soybeans with Modified Carbohydrate Profiles in Maturity Groups 0 to V

ABSTRACTSoybean [Glycine max (L.) Merr.] is an important crop in the United States that is processed into two main products: a vegetable oil and a high‐protein meal used in livestock rations. Soybean cultivar development involves the incorporation of new traits that enhance value for the producer, processor, or end user. Soybean varieties that have seed composition characteristics that improve the value of the meal while still allowing high yields are desirable. The raffinose family of oligosaccharides (RFO) are antinutritional carbohydrates that reduce the nutritional energy of soybean meal, whereas sucrose can be considered nutritionally beneficial in soybean meal. The objective of this study was to expand the understanding of the environmental stability of the carbohydrate profiles for soybean lines containing different allele combinations of two key raffinose synthase (RS2 and RS3) genes, as well as targeted maturity gene combinations in a range of US soybean production environments. The results indicated that soybean genotypes with combinations of variant alleles of the RS2 and RS3 genes, as well as maturity genes appropriate for their targeted environment, produced characteristic carbohydrate profiles. Environmental factors did have an effect on carbohydrate components, particularly for sucrose. None of the genotype classes was stable for sucrose, although most of the variant RS2 genotypes accumulated at least 7% sucrose over the studied environments. In addition, five of the six genotype classes were stable for stachyose. The results establish the genotype classes with rs2W331− alleles suitable to develop soybean cultivars in broad maturity group backgrounds that have an enhanced energy meal trait.

Variation in the Resistance of Japanese Soybean Cultivars to Phytophthora Root and Stem Rot during the Early Plant Growth Stages and the Effects of a Fungicide Seed Treatment.

Soybean cultivars susceptible to Phytophthora root and stem rot are vulnerable to seed rot and damping-off of seedlings and young plants following an infection by Phytophthora sojae. In this study, the disease responses of Japanese soybean cultivars including currently grown main cultivars during the early growth stages were investigated following infections by multiple P. sojae isolates from Japanese fields. The extent of the resistance to 17 P. sojae isolates after inoculations at 14, 21, and 28 days after seeding varied significantly among 18 Japanese and two US soybean cultivars. Moreover, the disease responses of each cultivar differed significantly depending on the P. sojae isolate and the plant age at inoculation. Additionally, the treatment of ‘Nattosyo-ryu’ seeds with three fungicidal agrochemicals provided significant protection from P. sojae when plants were inoculated at 14–28 days after seeding. These results indicate that none of the Japanese soybean cultivars are completely resistant to all tested P. sojae isolates during the first month after sowing. However, the severity of the disease was limited when plants were inoculated during the later growth stages. Furthermore, the protective effects of the tested agrochemicals were maintained for at least 28 days after the seed treatment. Japanese soybean cultivars susceptible to Phytophthora root and stem rot that are grown under environmental conditions favorable for P. sojae infections require the implementation of certain practices, such as seed treatments with appropriate agrochemicals, to ensure they are protected from P. sojae during the early part of the soybean growing season.

Soybean nitrogen fixation dynamics in Iowa, USA

The rainfed USA Midwestern region has deep, fertile soils and leads the USA in soybean [Glycine max, (L.) Merr.] production. Biological nitrogen (N) fixation (BNF) contributes a portion of the soybean N requirement, but variability in BNF is poorly understood and estimates of BNF for this region are rare. We established experiments in Iowa, USA to gain a better understanding of BNF and increase its predictability. We collected in-season BNF measurements accompanied by high temporal resolution soil and plant growth measurements. Across two years, two locations and two planting dates, we found that BNF contributed 23–65% of total aboveground N accumulation in soybean. The BNF rate was maximized at the early seed-filling period and varied from 1 to 3 kg N ha−1day−1. During seed filling period, the rate of BNF was related to crop growth rate (carbon (C) supply) but not to N accumulation by the reproductive organs (N demand). We found that a minimum crop growth rate of 135 kg dry matter ha−1day-1 is required to sustain maximum BNF rates. In contrast to BNF, the soil inorganic N uptake rate was related to seed N demand but not to C supply. Biomass production was the best predictor of total soybean BNF (R2 > 0.83). On average, 0.013 kg N was fixed per kg biomass produced. Across all trials, the N exported via seed was greater than the N imported via BNF, which suggests that Midwest US soybeans may reduce soil organic matter. We concluded that future research efforts should focus on increasing C – rather than N – availability during the seed filling period towards improving both grain yields and environmental sustainability.

Registration of USDA‐Max × Soja Core Set‐1: Recovering 99% of Wild Soybean Genome from PI 366122 in 17 Agronomic Interspecific Germplasm Lines

USDA‐Max × Soja Core Set‐1 (USDA‐MxS‐CS1‐1 to USDA‐MxS‐CS1‐17 [Reg. No. GP‐417 to GP‐433, PI 689053 to PI 689069]) is a group of 17 interspecific breeding lines developed from the hybridization of lodging‐resistant soybean cultivar N7103 [Glycine max (L.) Merr.] with wild soybean plant introduction PI 366122 [G. soja Siebold &amp; Zucc.]. These materials were released by the USDA‐ARS and the North Carolina Agricultural Research Service (March 2017) to expand the North American soybean breeding pool. The full‐sib breeding lines are 50% wild soybean by pedigree and developed through bulk breeding and pedigree selection. Marker analysis of 2455 well‐distributed polymorphic single‐nucleotide polymorphism loci revealed that individual breeding lines ranged from 21 to 40% alleles derived from wild soybean. Collectively, most of the wild soybean genome was transferred to the core set in that 5, 10, and 17 breeding lines captured 83, 98, and 99% of G. soja–derived polymorphic alleles. Physical linkage maps suggested that extensive recombination occurred between the G. max and G. soja genomes. The 17 breeding lines are well adapted to the southeastern United States, exhibited seed yield ranging from 75 to 97% of the domesticated parent, and are group VI or VII maturity. Some breeding lines displayed increased seed protein, oil, or methionine content, and all exhibited increased seed size as compared to the domesticated parent. The novel genetic diversity, positive agronomic performance, and improved seed composition of these lines suggest that they are valuable genetic resources for US soybean breeding.