Soybean Yield Potential Research Articles

Expression of a maize SOC1 gene enhances soybean yield potential through modulating plant growth and flowering

Yield enhancement is a top priority for soybean (Glycine max Merr.) breeding. SUPPRESSOR OF OVEREXPRESSION OF CONSTANS 1 (SOC1) is a major integrator in flowering pathway, and it is anticipated to be capable of regulating soybean reproductive stages through its interactions with other MADS-box genes. Thus, we produced transgenic soybean for a constitutive expression of a maize SOC1 (ZmSOC1). T1 transgenic plants, in comparison with the nontransgenic plants, showed early flowering, reduced height of mature plants, and no significant impact on grain quality. The transgenic plants also had a 13.5–23.2% of higher grain weight per plant than the nontransgenic plants in two experiments. Transcriptome analysis in the leaves of 34-day old plants revealed 58 differentially expressed genes (DEGs) responding to the expression of the ZmSOC1, of which the upregulated FRUITFULL MADS-box gene, as well as the transcription factor VASCULAR PLANT ONE-ZINC FINGER1, contributed to the promoted flowering. The downregulated gibberellin receptor GID1B could play a major role in reducing the plant height. The remaining DEGs suggested broader effects on the other unmeasured traits (e.g., photosynthesis efficiency and abiotic tolerance), which could contribute to yield increase. Overall, modulating expression of SOC1 in soybean provides a novel and promising approach to regulate plant growth and reproductive development and thus has a potential either to enhance grain yield or to change plant adaptability.

IRRIGATION WATER MANAGEMENT TECHNIQUES FOR LOWLAND FURROW-IRRIGATED SOYBEAN IN SOUTHERN BRAZIL

Different water management strategies should be investigated to ensure adequate water supply to furrow-irrigated soybean plants in lowlands. This study examined the performance and efficiency of furrow irrigation techniques and related them to the soybean yield potential in lowland fields of Southern Brazil in the 2017/18 growing season. An experiment was conducted on raised seedbeds to evaluate furrow irrigation techniques: full irrigation with cutback, irrigation during the advance phase with low inflow, irrigation during the advance phase (cutoff), surge irrigation, and no irrigation. The design parameters, efficiency of the techniques, agronomic characteristics, and the grain yield of the soybean crop, were evaluated. The overall performance of the cutback technique in furrow irrigation was superior, followed by the surge irrigation, cutoff, and low inflow techniques. Furrow irrigation increased soybean yield in lowlands, and the cutback technique was the best to guarantee the soybean yield potential in lowlands, resulting in a 29% yield increase compared to non-irrigated.

Biophysical and management factors causing yield gap in soybean in the subtropics of Brazil

AbstractLittle is known about the relationships between soybean [Glycine max (L.) Merr.] maturity grouping and the yield‐limiting factors in the subtropics. This information can be used to estimate soybean potential yield (Yp) and the water‐limited yield (Yw) and to optimize current soybean management practices to improve yield and resource use efficiency. The objectives were (a) to estimate the Yp, Yw, and yield gaps (YGs) of soybean in subtropical Brazil and (b) to identify the biophysical and management factors which potentially explain the YG. The CSM CROPGRO model that was calibrated with data collected between 2011 and 2019 was used to estimate the influence of sowing date and maturity group (MG) on yield potentials and water efficiencies. Yield varied from 6.1 to 7.2 Mg ha−1 and from 2.5 to 5.1 Mg ha−1 between buffer zones (BZs) for Yp and Yw, respectively. The YG caused by water deficit (YGw) ranged from 26% (1.8 Mg ha−1) to 62% (4.1 Mg ha−1) of the Yp and the YG caused by management (e.g., sowing date, MG, final density) ranged from 9% (0.6 Mg ha−1) to 39% (2.7 Mg ha−1) of the Yp. The main management factor of the YG was sowing date. The potential yield was higher in the early MGs, showing greater water use efficiency in MG ≤ 5.5 (9.6 kg ha−1 mm−1) than in high MGs (MG ≥ 5.6). Findings from this study can be used by agronomists in subtropical regions to optimize soybean yields.

Determination of soybean yield gap and potential production in Iran using modeling approach and GIS

Increasing crop production is necessary to maintain food security for the growing global population. Reducing the gap between actual and potential yield is one of the important ways to increase yield per unit area. Potential yield and the yield gap of soybean were determined for Golestan Province, Iran, using Soybean Simulation Model (SSM-iCrop2) and Geographical Information System (GIS). Information from 24 weather stations and soil data of the region were used. Yield gap and production gap were calculated at county and province levels. The average actual yield of soybean in this province was 2.28 t ha–1 while the province’s potential yield was 4.73 t ha–1, so the yield gap was estimated 2.44 t ha–1. Thus, there is a great potential for increasing soybean yield in Golestan, which is possible through improving crop management of soybean in farmers’ fields. The average water productivity of soybean was estimated to be 0.81 kg m–3. Spatial distribution of water productivity in soybean farms showed that the highest and the lowest water productivities (0.99 and 0.44 kg m–3) were in western and eastern regions of the province, respectively, in accordance to vapour pressure deficit. It was concluded that soybean production in the province could increase by 66% (from 109 970 to 182 170 tons) if 80% of the current yield gap could be removed.

Evolutionary QTL-allele changes in main stem node number among geographic and seasonal subpopulations of Chinese cultivated soybeans.

The main stem node number (MSN) is a trait related to geographic adaptation, plant architecture and yield potential of soybean. The QTL-allele constitution of the Chinese Cultivated Soybean Population (CCSP) was identified using the RTM-GWAS (restricted two-stage multi-locus genome-wide association study) procedure, from which a QTL-allele matrix was established and then separated into submatrices to explore the genetic structure, evolutionary differentiation, breeding potential and candidate genes of MSN in CCSP. The MSN of 821 accessions varied from 8.8 to 31.1, with an average of 16.3 in Nanjing, China (32.07° N, 118.62° E), where the MSNs of all the materials could be evaluated in a standardized manner. Among the six geo-seasonal subpopulations, the MSN varied from 21.7 in a southern summer-autumn-sowing subpopulation (SA-IV) down to 13.5 in a northeastern spring-sowing subpopulation (SP-I). The materials were genotyped with restriction site-associated DNA-sequencing. Totally 142 main-effect QTLs (73.24% new) with 560 alleles contributing 72.98% to the phenotypic variance were identified. The evolutionary QTL-allele changes in MSN from SA-IV through SP-I showed that inheritance (78.93% of alleles) was the primary factor influencing the evolution of this trait, followed by allele emergence (19.64% alleles), allele exclusion (1.43% alleles), and recombination among retained alleles. In the evolutionary changes, 70 QTLs, including 12 newly emerged QTLs, with 118 alleles were involved. An increase potential of 2-8 nodes was predicted and 112 candidate genes were annotated and preliminarily verified with χ2-tests in the CCSP. The RTM-GWAS showed powerful in detecting QTL-allele system, assessing evolution factors, predicting optimal crosses and identifying candidate genes in a germplasm population.

Evaluation of soybean (Glycine max L.) adaptation to northern European regions under different agro-climatic scenarios

Abstract Soybean is a candidate crop to increase the independency of Europe in leguminous protein crops. However, its adaptation to northern European regions is not yet well defined due to the lack of long-term references. Herein, we simulated soybean yield potential in northern France and identified the main yield limiting factors under rainfed vs. irrigated conditions. Two cultivars representing maturity groups 000 and 00 were planted within three different trials. Leaf area index, shoot and pod biomass, main phenological stages and yield were recorded to evaluate CROPGRO-soybean model predictability. Adjustment of genetic coefficients was performed prior to simulate yield on 21-years weather database (1999–2018) at Beauvais (France, N 49.46°, E 2.07°) and Estrées-Mons (France, N 49.88°, E 3.01°) under different water regimes and planting dates. Predictions showed that adding irrigation at grain filling period would increase yield potential to the level of non-water limited scenarios. Although simulated yield variability is reduced with irrigation, the remaining variability suggests that water is not the only yield-limiting factor. A tentative explanation is proposed by deriving environmental covariates from the model. The analysis confirmed the importance of precipitation amount (optimum around 200 mm) and duration (optimum around 60 days) of the flowering to physiological maturity period under rainfed conditions. Under irrigated conditions, increasing evapotranspiration and average minimum temperature affected simulated yield positively while increasing the number of days below 10 °C had a negative impact. These results give insights for soybean crop management and bring indications to breeders for adapting the existing genetic material to northern Europe.

Economic Impact of Fluopyram-Amended Seed Treatments to Reduce Soybean Yield Loss Associated with Sudden Death Syndrome.

Soybean (Glycine max) sudden death syndrome (SDS), caused by Fusarium virguliforme, is a key limitation in reaching soybean yield potential, stemming from incomplete disease management through cultural practices and partial host resistance. A fungicidal seed treatment was released in 2014 with the active ingredient fluopyram and was the first chemical management strategy to reduce soybean yield loss stemming from SDS. Although farm level studies have found fluopyram profitable, we were curious to discover whether fluopyram would be beneficial nationally if targeted to soybean fields at risk for SDS yield loss. To estimate economic benefits of fluopyram adoption in SDS at-risk acres, in the light of U.S. public research and outreach from a privately developed product, we applied an economic surplus approach, calculating ex ante net benefits from 2018 to 2032. Through this framework of logistic adoption of fluopyram for alleviation of SDS-associated yield losses, we projected a net benefit of $5.8 billion over 15 years, considering the costs of public seed treatment research and future extension communication. Although the sensitivity analysis indicates that overall net benefits from fluopyram adoption on SDS at-risk acres are highly dependent upon the market price of soybean, the incidence of SDS, the adoption path, and ceiling of this seed treatment, the net benefits still exceeded $407 million in the worst-case scenario.

Pertumbuhan dan hasil genotipe kedelai (Glycine max (L.) Merril) pada tiga tingkat cekaman kekeringan

Drought stress is a major constraint to the production and yield stability of soybean (Glycine max (L.) Merr). Drought stress at the generative phase had a negative impact on soybean potential yield significantly. This study evaluated variation in five soybean genotypes (G1, G2, G3, G4 and G5) in their response to the three levels (100% of field capacity (D1), 80% from field capacity (D2) and 60% from field capacity (D3)) of drought stress in a glass house. This study was arranged in a factorial randomized completely block design with three replications. Results showed that all five genotypes responded significantly (P<0.05) to the drought stress treatments in soybean yield. The average yield was respectively reduced by 8.4% and 11.6% in the D2 and D3 treatments, respectively, compared to the D1 (control). Percent reduction of yield for genotype G4 (19.8%) was lower compared to other genotypes. This is indicated that genotype G4 tolerance to drought stress. The evaluation on the morphological character was potentially to become a screening tool for soybean breeding program.

Spatial arrangement of plants on leaf growth and development and the yield potential of soybean

This study aimed at determining the effect of a variety of plants arrangements on foliar growth and development as well as the productive potential in soybean. The field experiments were performed over two agricultural years (2015/16 and 2016/17) on Argisoil in subtropical environment. The two selected cultivars, viz., BMX Tornado RR and FPS Urano RR were sown in four spatial distribution of the plants such as conventional spacing (0.45 m spacing between rows), reduced spacing (0.225 m spacing between rows), paired spacing (two rows with 0.225 m and 0.45 m spacing from the other rows) and crossed spacing (0.45 m spacing between the rows with crosses of two rows, at a 90° angle). The randomized block design was adopted for the experiments with the treatments in a 2x4 factorial distribution and four replications. The first factor was the cultivar and the second types of plant distribution. The results showed that plant arrangement affected the plant profile regarding the behavior of the ecophysiological variables like plastochron, leaf lifetime and yield distribution. Leaf life in each stratum was caused by the foliar senescence rhythm, explained by a 4th degree polynomial model, revealing two peaks in the senescence rate, one during pre-flowering stage and the other when the grain filling stage was completed. According to the results, we do not recommend changes in conventional spacing.

Spatial and Multivariate Analysis of Soybean Yield in the State of Paraná-Brazil

In this work, the aim was to evaluate the existence of spatial association of the municipal average official soybean yield (t ha-1) with agrometeorological data and vegetation indices. The information was observed by ten-day periods, in crop years 2010/2011, 2011/2012 and 2012/2013 in the State of Paraná. Local univariate spatial correlation (LISA index), as well as global bivariate correlation (L statistics) were calculated. With this study, we identified neighboring municipalities with high yield in the West as well as municipalities that are located with low-low yield Northwestern, showing positive spatial autocorrelation (IMG=1), significative (p-value < 0.05). In addition, there were differences between seeding times in different regions, and climate irregularity during flowering periods and grain filling in crop year 2011/2012 throughout the state, which caused a large drop in production in all municipalities of the state of Paraná. The analysis of local spatial association showed that in the three crop years, the Northwest region presented a significant low yield potential of soybean (p-value < 0.05). In addition, it was observed that the period from the 3rd ten-day period of October to the 2nd ten-day period of January was essential for the soybean cycle in the different regions of the state, since this period encompasses the critical phases of crop. Differences were also observed between the crop years studied, regarding the agrometeorological variables, which affected soybean yield mainly in the Western region of Paraná – Brazil.

The effects and interaction of soybean maturity gene alleles controlling flowering time, maturity, and adaptation in tropical environments

BackgroundSoybean is native to the temperate zones of East Asia. Poor yields of soybean in West African countries may be partially attributed to inadequate adaptation of soybean to tropical environments. Adaptation will require knowledge of the effects of allelic combinations of major maturity genes (E1, E2, and E3) and stem architecture. The long juvenile trait (J) influences soybean flowering time in short, ~ 12 h days, which characterize tropical latitudes. Soybean plant architecture includes determinate or indeterminate stem phenotypes controlled by the Dt1 gene. Understanding the influence of these genetic components on plant development and adaptation is key to optimize phenology and improve soybean yield potential in tropical environments.ResultsSoybean lines from five recombinant inbred populations were developed that varied in their combinations of targeted genes. The soybean lines were field tested in multiple environments and characterized for days to flowering (DTF), days to maturity (DTM), and plant height in locations throughout northern Ghana, and allelic combinations were determined for each line for associating genotype with phenotype. The results revealed significant differences based on genotype for DTF and DTM and allowed the comparison of different variant alleles of those genes. The mutant alleles of J and E1 had significant impact on DTF and DTM, and alleles of those genes interacted with each other for DTF but not DTM. The Dt1 gene significantly influenced plant height but not DTF or DTM.ConclusionsThis research identified major and minor effect alleles of soybean genes that can be combined to control DTF, DTM, and plant height in short day tropical environments in Ghana. These phenotypes contribute to adaptation to a low latitude environment that can be optimized in a soybean breeding program with targeted selection of desired allele combinations. The knowledge of the genetic control of these traits will enhance molecular breeding to produce optimally adapted soybean varieties targeted to tropical environments.

Estimating crop model parameters for simulating soybean production in Iran conditions

Crop modelling has the potential to contribute to food security. In this study, to provide a simple model for estimating the soybean potential yield and phenological stages in Iran, a simulation model (SSM_iCrop2) was parameterized and tested. This model estimates the soybean phenological stages and potential yield based on the weather data (minimum and maximum temperature, solar radiation and rainfall) using the phenological models such as leaf area development, mass production and partitioning and soil water balance. Regarding the model parametrization, the two maturities groups of 3 and 5 with the temperature unit of 2000 and 2400 growth degrees day (GDD) were chosen. The model evaluation results indicated that the soybean yield ranged between 1.9 and 4.8 with the average of 3.5 t.ha−1, while the range of simulated yield changes between 1.8 and 4.7 with the average of 3.7 t.ha−1. Comparing the observed yield to the simulated yield, values of r, CV and RMSE were obtained 0.84, 13%, 0.5 t.ha−1 which indicates the high accuracy of the model. All of these results indicated that the estimated model parameters are high accuracy for use in the simulation of soybean yield at the country level.

Changes in leaflet shape and seeds per pod modify crop growth parameters, canopy light environment, and yield components in soybean

Seed number (SN) is the component most strongly associated with yield in soybean. SN depends on pod number (PN) and seeds per pod (SPP). Whereas SPP is a relatively stable component, PN is strongly influenced by environmental and management factors. However, the environmental cues involved in PN regulation are not completely understood. The influence of increasing SPP on other yield components is controversial. Field trials were conducted in two growing seasons using two pairs of lanceolate (L) and ovate (O) near-isogenic lines, sown at low (LD) and high (HD) plant densities to evaluate the effect of leaflet shape on crop growth parameters, canopy red/far-red (R/FR) ratio, their relationships with pod initiation, PN, and yield; and the effect of increasing SPP on PN, SN, and yield. L canopies showed a higher number of pods initiated (PI) than O canopies owing to the increase of PI on branches. No association between PI and crop growth rate during the pod set period was found. PI was negatively associated with leaf area index (LAI) and light interception. In contrast, a positive association between PI and canopy R/FR ratio was found. This latter association was sustained irrespective of whether the LAI was below or above its critical value, providing experimental evidence that R/FR ratio is positively associated with pod initiation in soybean canopies. An increase in SPP produced a direct and steady increase in SN regardless of PN and plant density. A yield increase was observed for the L-LD treatment, which combined the increased SPP of L lines with the highest PN of L-LD canopies. These results have implications for crop management and breeding strategies aimed at increasing the yield potential of soybean.

Effect of amino acid biostimulant on the yield and nutraceutical potential of soybean

Advancement in crop cultivation technologies strives to increase the yield and improve the quality of crops under minimized threats posed to the natural environment. Application of biostimulants is a treatment which increases crop yield and quality particularly after plants exposure to stress conditions. The objective of the work was to determine changes in yield and nutraceutical potential of soybean (Glycine max [L.] Merr.) ‘Atlanta’ after application of biostimulant. A field experiment was conducted in three growing seasons (2014-2016). Terra Sorb Complex biostimulant was applied in the growing season in the form of single or double spraying in two concentrations (0.3% and 0.5%). Number of biostimulant applications and its concentration modified yield and quality of crop and also the nutraceutical and antioxidative potential of soybean. Foliar application of biostimulant improved yield of soybean (increased by 25% compared to the control) without any negative effect on the nutritive value of seeds. The application of biostimulant increased (compared to the control) number of pods and seeds (32%), plant height (38%), phenolic content (34%), flavonoids content (74%), and reducing power (210%). Taking into account biometric traits of soybean plants, positive effects were observed in the case of single biostimulant applications with lower concentration. The conducted study demonstrated a significant increase in the soybean yield and antioxidant potential after double application of the tested biostimulant at higher concentration. On the other hand, total fat and protein content was higher in plants treated once with a lower product concentration.

Genome-wide association study of inflorescence length of cultivated soybean based on the high-throughout single-nucleotide markers.

As an important and complex trait, inflorescence length (IL) of soybean [Glycine max (L.) Merr.] significantly affected seed yields. Therefore, elucidating molecular basis of inflorescence architecture, especially for IL, was important for improving soybean yield potentials. Longer IL meaned to have more pod and seed in soybean. Hence, increasing IL and improving yield are targets for soybean breeding. In this study, a association panel, comprising 283 diverse samples, was used to dissect the genetic basis of IL based on genome-wide association analysis (GWAS) and haplotype analysis. GWAS and haplotype analysis were conducted through high-throughout single-nucleotide polymorphisms (SNP) developed by SLAF-seq methodology. A total of 39, 057 SNPs (minor allele frequency ≥ 0.2 and missing data ≤ 10%) were utilized to evaluate linkage disequilibrium (LD) level in the tested association panel. A total of 30 association signals were identified to be associated with IL via GWAS. Among them, 13 SNPs were novel, and another 17 SNPs were overlapped or located near the linked regions of known quantitative trait nucleotide (QTN) with soybean seed yield or yield component. The functional genes, located in the 200-kb genomic region of each peak SNP, were considered as candidate genes, such as the cell division/ elongation, specific enzymes, and signaling or transport of specific proteins. These genes have been reported to participant in the regulation of IL. Ten typical long-IL lines and ten typical short-IL lines were re-sequencing, and then, six SNPs from five genes were obtained based on candidate gene-based association. In addition, 42 haplotypes were defined based on haplotype analysis. Of them, 11 haplotypes were found to regulate long IL (> 14mm) in soybean. The identified 30 QTN with beneficial alleles and their candidate genes might be valuable for dissecting the molecular mechanisms of IL and further improving the yield potential of soybean.

Yield potential of soybean as influenced by planting techniques under heavy soil of Jabalpur, Madhya Pradesh

Yield potential of soybean as influenced by planting techniques under heavy soil of Jabalpur, Madhya Pradesh

Simulating Soybean Yield Potential under Optimum Management

Core Ideas Soybean yield and crop growth was measured in high‐yield contest fields. Radiation use efficiency and nitrogen uptake were greater than recorded values. Yield was grossly under‐predicted using default growth parameters. Yield predictions were greatly improved using measured growth parameters. Crop models have played important roles in identifying potential constraints for crop growth and yield. A relatively simple soybean [Glycine max (L.) Merr.] model consisting of a daily C, N, and water budget was used to simulate yields for optimum production environments at Fayetteville, AR, and at a farmer's contest field in Missouri for 2012 to 2013. Data were collected on radiation use efficiency (RUE), N accumulation rate, specific leaf nitrogen (SLN), and the dry matter accumulation coefficient (DMAC) as a measure of whole‐crop seed growth rate. In Fayetteville, measured yields ranged from 4977 to 7144 kg ha−1, and simulated yields averaged 34.0% below the measured yields using the default model parameters. Using measured parameters in a modified model, predicted yields were 2.8% above observed. Default parameter simulations for the contest fields were 39.0% below measured yield and were 18.7% below measured yield when using measured parameters. Sensitivity analyses indicated that lower DMAC values increased yields due to slower seedfill rates, allowing additional N accumulation and a slower translocation of N to the growing seeds. Simulating an increased SLN and RUE increased predicted yields in 2012 and 2013 when N accumulation rates were great enough to supply the required N for new biomass. Alternatively, increasing N accumulation rates increased yield up to a plateau when all N requirements were met. These results illustrate the importance and interconnectivity of the crop growth processes relating to C and N metabolism and that current bounds for crop growth characteristics should be reconsidered.

Optimum Leaf Area Index to Reach Soybean Yield Potential in Subtropical Environment

Core Ideas The optimum leaf area index (LAI) at beginning bloom to reach the yield potential is between 3.6 (indeterminate stem termination) and 4.5 (determinate stem termination).The optimum LAI maximum to reach the yield potential is between 6.0 and 6.5 for indeterminate and determined cultivars.The optimum LAI for high yield potential should be adjusted according to the maturity group, stem termination and sowing date.The increase in yield was observed with the increase of LAI for experiments and farms with a high technological level (soybean yield more than 4.5 Mg ha−1). The interactive influence of climate and management factors on leaf area index (LAI) of soybean yield potential has not been investigated in subtropical environments. Such information can help in optimizing current soybean management practices to increase seed yield and efficiency of resource use. The objective of this study was to identify the optimum leaf area index for attaining yield potential in modern soybean cultivars grown in a subtropical environment. A large soybean yield, LAI, and phenology database collected from a combination of on‐farm and research‐station experiments conducted during four soybean growing seasons (2011–2015) in southern Brazil was used. The database represented a wide range of weather conditions, soil types, sowing dates, and cultivar maturity groups (MGs). A boundary function was derived for the relationship between soybean yield and LAI at R1 and R5 developmental stages for cultivars of determinate and indeterminate growth habit, and for both types combined. An increase in yield was in line with the increase of LAI for experiments with a small yield gap (soybean yield more than 4.5 Mg ha−1). In this case, optimum LAI at R1 growth stage (LAIR1, opt) to reach the soybean yield potential was between 3.4 (indeterminate) and 4.5 (determinate) whereas the optimal maximum LAI (LAImax,opt) is between 6.0 and 6.5 for indeterminate and determinate cultivars, respectively. These results suggested that management practices for soybean crops that involve the LAI and high yield potential must be adjusted according to the maturity group, growth habit and sowing date in a subtropical environment.

Assessment of different gridded weather data for soybean yield simulations in Brazil

A high-density, well-distributed, and consistent historical weather data series is of major importance for agricultural planning and climatic risk evaluation. A possible option for regions where weather station network is irregular is the use of gridded weather data (GWD), which can be downloaded online from different sources. Based on that, the aim of this study was to assess the suitability of two GWD, AgMERRA and XAVIER, by comparing them with measured weather data (MWD) for estimating soybean yield in Brazil. The GWD and MWD were obtained for 24 locations across Brazil, considering the period between 1980 and 2010. These data were used to estimate soybean yield with DSSAT-CROPGRO-Soybean model. The comparison of MWD with GWD resulted in a good agreement between climate variables, except for solar radiation. The crop simulations with GWD and MWD resulted in a good agreement for vegetative and reproductive phases. Soybean potential yield (Yp) simulated with AgMERRA and XAVIER had a high correlation (r > 0.88) when compared to the estimates with MWD, with the RMSE of about 400 kg ha−1. For attainable yield (Ya), estimates with XAVIER resulted in a RMSE of 700 kg ha−1 against 864 kg ha−1 from AgMERRA, both compared to the simulations using MWD. Even with these differences in Ya simulations, both GWD can be considered suitable for simulating soybean growth, development, and yield in Brazil; however, with XAVIER GWD presenting a better performance for weather and crop variables assessed.

Assessing causes of yield gaps in agricultural areas with diversity in climate and soils

Identification of causes of gaps between yield potential and producer yields has been restricted to small geographic areas. In the present study, we developed a novel approach for identifying causes of yield gaps over large agricultural areas with diversity in climate and soils. This approach was applied to quantify and explain yield gaps in rainfed and irrigated soybean in the North-Central USA (NC USA) region, which accounts for about one third of soybean global production. Survey data on yield and management were collected from 3568 producer fields over two crop seasons and grouped into 10 technology extrapolation domains (TEDs) according to their soil, climate, and water regime. Yield potential was estimated using a combination of crop modeling and boundary functions for water productivity and compared against highest producer yields derived from the yield distribution in each TED-year. Yield gaps were calculated as the difference between yield potential and average producer yield. Explanatory factors for yield gaps were investigated by identifying management practices that were concordantly associated with high- and low-yield fields. Management×TED interactions were then evaluated to elucidate the underlying causes of yield gaps. The chosen spatial TED framework accounted for about half of the regional variation in producer yield within the NC USA region. Across the 10 TEDs, soybean average yield potential ranged from 3.3 to 5.3 Mgha−1 for rainfed fields and from 5.3 to 5.6Mgha−1 for irrigated fields. Highest producer yields in each TED were similar (±12%) to the estimated yield potential. Yield gap, calculated as percentage of yield potential, was larger in rainfed (range: 15–28%) than in irrigated (range: 11–16%) soybean. Upscaled to the NC USA region, yield potential was 4.8Mgha−1 (rainfed) and 5.7Mgha−1 (irrigated), with a respective yield gap of 22 and 13% of yield potential. Sowing date, tillage, and in-season foliar fungicide and/or insecticide were identified as explanatory causes for yield variation in half or more of the 10 TEDs. However, the degree to which these three factors influenced producer yield varied across TEDs. Analysis of in-season weather helped interpret management×TED interactions. For example, yield increase due to advances in sowing date was greater in TEDs with less water limitation during the pod-setting phase. The present study highlights the strength of combining producer survey data with a spatial framework to measure yield gaps, identify management factors explaining these gaps, and understand the biophysical drivers influencing yield responses to crop management.