Soybean Yield Research Articles

Isolation and Identification of Salinity-Tolerant Rhizobia and Nodulation Phenotype Analysis in Different Soybean Germplasms.

Increasing the soybean-planting area and increasing the soybean yield per unit area are two effective solutions to improve the overall soybean yield. Northeast China has a large saline soil area, and if soybeans could be grown there with the help of isolated saline-tolerant rhizobia, the soybean cultivation area in China could be effectively expanded. In this study, soybeans were planted in soils at different latitudes in China, and four strains of rhizobia were isolated and identified from the soybean nodules. According to the latitudes of the soil-sampling sites from high to low, the four isolated strains were identified as HLNEAU1, HLNEAU2, HLNEAU3, and HLNEAU4. In this study, the isolated strains were identified for their resistances, and their acid and saline tolerances and nitrogen fixation capacities were preliminarily identified. Ten representative soybean germplasm resources in Northeast China were inoculated with these four strains, and the compatibilities of these four rhizobium strains with the soybean germplasm resources were analyzed. All four isolates were able to establish different extents of compatibility with 10 soybean resources. Hefeng 50 had good compatibility with the four isolated strains, while Suinong 14 showed the best compatibility with HLNEAU2. The isolated rhizobacteria could successfully establish symbiosis with the soybeans, but host specificity was also present. This study was a preliminary exploration of the use of salinity-tolerant rhizobacteria to help the soybean nitrogen fixation in saline soils in order to increase the soybean acreage, and it provides a valuable theoretical basis for the application of saline-tolerant rhizobia.

Combination Effects of Sulfur Fertilizer and Rhizobium Inoculant on Photosynthesis Dynamics and Yield Components of Soybean

Sulfur (S) fertilization and rhizobium inoculation are important agronomic practices for improving soybean growth and yield. However, their combined effects on yield components and the resultant impacts on yield need further investigation. Our study aimed to verify the combined effects of S fertilizer and rhizobium inoculant on the yield components and seed yield of soybeans, as well as photosynthesis dynamics during the V5–R6 growth stages. A randomized block design incorporating two factors was employed for field experiments on soybean, involving the application of five rates of sulfur (0, 5.0, 9.8, 14.8, and 19.6 kg S ha−1) with rhizobium inoculation or without. A reduction of 50% in mineral fertilizer according to farmer practice (FP) was applied alongside different rates of sulfur for field experiments on soybeans. The findings indicated that the application of sulfur fertilization significantly enhanced soybean yield by increasing the number of grains per plant (NG) and the number of pods per plant (NP). Maximum grain yield was reached under treatment with an S rate of 19.6 kg S ha−1, which increased NG by 39% more than an S rate of 0 kg S ha−1. Correlation analysis indicated that higher photosynthesis was closely associated with increased yield components. This study demonstrated that applying S fertilizers could improve soybean production by combining the appropriate sulfur concentration and rhizobia inoculation.

Knockout of miR396 genes increases seed size and yield in soybean.

Yield improvement has long been an important task for soybean breeding in the world in order to meet the increasing demand for food and animal feed. miR396 genes have been shown to negatively regulate grain size in rice, but whether miR396 family members may function in a similar manner in soybean is unknown. Here, we generated eight soybean mutants harboring different combinations of homozygous mutations in the six soybean miR396 genes through genome editing with clustered regularly interspaced palindromic repeats (CRISPR)/CRISPR-associated nuclease (Cas)12SF01 in the elite soybean cultivar Zhonghuang 302 (ZH302). Four triple mutants (mir396aci, mir396acd, mir396adf, and mir396cdf), two quadruple mutants (mir396abcd and mir396acfi), and two quintuple mutants (mir396abcdf and mir396bcdfi) were characterized. We found that plants of all the mir396 mutants produced larger seeds compared to ZH302 plants. Field tests showed that mir396adf and mir396cdf plants have significantly increased yield in growth zones with relatively high latitude which are suited for ZH302 and moderately increased yield in lower latitude. In contrast, mir396abcdf and mir396bcdfi plants have increased plant height and decreased yield in growth zones with relatively high latitude due to lodging issues, but they are suited for low latitude growth zones with increased yield without lodging problems. Taken together, our study demonstrated that loss-of-function of miR396 genes leads to significantly enlarged seed size and increased yield in soybean, providing valuable germplasms for breeding high-yield soybean.

Yield response and water productivity of soybean (Glycine max L.) to deficit irrigation and sowing time in south-eastern Australia

The aim of this study was to investigate irrigation strategies and sowing dates that would maximise soybean yield and water productivity. It is based on field experiments conducted during two seasons and simulation modelling. Irrigation treatments were 33%, 66%, 66% plus 100% during pod development and pod-fill stages, and 100% of crop evapotranspiration (ETc). In the first season experiment, cvs. Bidgee and Snowy were sown on 15 Nov. In the second season, cv. Bidgee was sown on 15 Nov and 15 Dec. Five sowing dates (1, 15, 30 Nov and 15, 31 Dec) and eight irrigation scenarios were analysed in-silico using the crop model APSIM. For the simulations, the first four irrigation scenarios were set by applying 50%ETc during one of the four growth stages: vegetative stage, flowering stage, pod development and pod-filling stage, and maturity stage. The other five irrigation treatments were 0%ETc, 25%ETc, 50%ETc, 75%ETc, and 100%ETc throughout the growing season. Soil water content and above-ground dry matter were measured at regular time intervals. Seed yield, 100-seed weight, oil and protein contents were determined at harvest. Water deficit during pod development and pod-filling stage had significant effect on seed yield. The flowering stage was the next most sensitive stage for water deficit. During both cropping seasons, the 33% treatment yielded 51% of the fully irrigated reference. The latter had a significantly higher water productivity than all the deficit treatments. Early-sown soybean had higher yield than the late sown soybean. Sowing as late as early December was found to be still suitable for double cropping without significant yield loss. The result of this study is particularly useful for soybean farmers in water-scarce regions, such as south-eastern Australia, who practice double cropping with a tight cropping calendar.

Genetic dissection of ten photosynthesis-related traits based on InDel- and SNP-GWAS in soybean.

A total of 416 InDels and 112 SNPs were significantly associated with soybean photosynthesis-related traits. GmIWS1 and GmCDC48 might be related to chlorophyll fluorescence and gas-exchange parameters, respectively. Photosynthesis is one of the main factors determining crop yield. A better understanding of the genetic architecture for photosynthesis is of great significance for soybean yield improvement. Our previous studies identified 5,410,112 single nucleotide polymorphisms (SNPs) from the resequencing data of 219 natural soybean accessions. Here, we identified 634,106 insertions and deletions (InDels) from these 219 accessions and used these InDel variations to perform principal component and linkage disequilibrium analysis of this population. The genome-wide association study (GWAS) were conducted on six chlorophyll fluorescence parameters (chlorophyll content, light energy absorbed per reaction center, quantum yield for electron transport, probability that a trapped exciton moves an electron into the electron transport chain beyond primary quinone acceptor, maximum quantum yield of photosystem II primary photochemistry in the dark-adapted state, performance index on absorption basis) and four gas-exchange parameters (intercellular carbon dioxide concentration, stomatal conductance, net photosynthesis rate, transpiration rate) and revealed 416 significant InDels and 112 significant SNPs. Based on GWAS results, GmIWS1 (encoding a transcription elongation factor) and GmCDC48 (encoding a cell division cycle protein) with the highest expression in the mapping region were determined as the candidate genes responsible for chlorophyll fluorescence and gas-exchange parameters, respectively. Further identification of favorable haplotypes with higher photosynthesis, seed weight and seed yield were carried out for GmIWS1 and GmCDC48. Overall, this study revealed the natural variations and candidate genes underlying the photosynthesis-related traits based on abundant phenotypic and genetic data, providing valuable insights into the genetic mechanisms controlling photosynthesis and yield in soybean.

Assessment of nutritional status of soybean by the DRIS method in western of Bahia State

ABSTRACT Increasing soybean yield in the MATOPIBA region can be attributed to fertility management, which is crucial to achieving maximum agronomic efficiency. Therefore, the proper management begins with the assessment of plant nutrition. This study aimed to evaluate soybean nutritional status in western Bahia using the Diagnosis and Recommendation Integrated System (DRIS). Database comprised 153 samples from commercial fields located in the research area. To carry out the evaluation using the DRIS method, the database contained information on nutritional levels and leaf productivity of the sampled areas. Database was divided into high-productivity populations (reference population) and low-productivity populations, based on the inflection point value of the cumulative cubic function of yield. The DRIS method allowed for evaluating the potential response to fertilization; however, this method was inefficient in recommending fertilizer doses in both subpopulations. For the sufficiency levels proposed by DRIS, the nutrients N, K, Ca, Mg and S had their maximum and minimum limits reduced, while Cu, Fe and Zn had their ranges of sufficiency expanded, when compared with ranges proposed by other authors. In addition, Zn and Mn were more limiting due to lack for the high-yield subpopulation, and P and Mn for the low-yield subpopulation. The most limiting nutrients due to excess were P and Zn for the high-yield, while K and S were limiting for the low yield subpopulation.

Negative synergistic effects of drought and heat during flowering and seed setting in soybean

Rising intense heat waves combined with lower precipitations are the new norms of current global scenarios. These altered climatic conditions negatively impact soybean yield potential and quality. Ten soybean cultivars were subjected to four different growing conditions: control, drought, heat, and combined drought and heat to understand the physiological, yield, quality and molecular changes. Stomatal conductance was reduced by 62% and 10% under drought and heat, respectively. This reduction was further exacerbated to 93% when exposed to combined stress. The highest canopy temperature was recorded at +8 °C with combined stress treatment, whereas drought and heat exhibited +2 °C and +5.4 °C, respectively. Furthermore, combined stress displayed a more pronounced negative impact on greenness-associated vegetative index; the gene expression analysis further corroborated these findings. Each degree Celsius increase in temperature during flowering and seed-filling reduced seed weight by approximately 7% and 4% with and without drought, respectively. The seed protein increased under drought, whereas the oil showed a converse trend under drought and combined stresses. Most physiological and yield traits showed no significant correlations between control and individual or combined stress. This suggests that selecting crops for combined stress tolerance may not be appropriate based on nonstress or individual stress performance. Thus, incorporating combined stress-resilient traits into elite soybean cultivars could significantly boost soybean production under hot and dry climatic conditions.

Positive Correlation of Lodging Resistance and Soybean Yield under the Influence of Uniconazole

Increasing planting density is one of the most effective ways to increase soybean yield, but supra-optimum density leads to an increase in the risk of lodged soybean. In this study, two varieties were selected. Heinong84 (lodging-susceptible variety, HN84) had planting densities of 200,000 plants/hm2, 300,000 plants/hm2, and 400,000 plants/hm2. Henong60 (lodging-resistant, HN60) had planting densities of 300,000 plants/hm2, 400,000 plants/hm2, and 500,000 plants/hm2. When the foliar application of uniconazole (50 mg/L) occurred at the beginning of the flowering stage (R1), the plant morphology, fiber composition, and mechanical properties of soybean internodes were determined at the podding and seed filling stages, and the yield was measured at the harvest stage. The results showed that spraying uniconazole at the R1 stage changed the morphology structure of soybean plants (i.e., plant height and petiole length reduction; stem diameter and leafstalk angle increase), improved the internode quality (i.e., increased breaking force, lignin content, cellulose content, hemicellulose content, and stem dry weight per unit length), and increased the number of grains per plant at the harvest stage. Thus, it is concluded that the application of uniconazole improved the plant population structure by changing the morphology of soybean plants, which was conducive to good light transmission and ventilation, improved the internode quality and lodging resistance, and increased the yield.

Both yields of maize and soybean and soil carbon sequestration in typical Mollisols cropland decrease under future climate change: SPACSYS simulation

Although Mollisols are renowned for their fertility and high-productivity, high carbon (C) losses pose a substantial challenge to the sustainable provision of ecosystem services, including food security and climate regulation. Protecting these soils with a specific focus on revitalizing their C sequestration potential emerges as a crucial measure to address various threats associated with climate change. In this study, we employed a modeling approach to assess the impact of different fertilization strategies on crop yield, soil organic carbon (SOC) stock, and C sequestration efficiency (CSE) under various climate change scenarios (baseline, RCP 2.6, RCP 4.5, and RCP 8.5). The process-based SPACSYS model was calibrated and validated using data from two representative Mollisol long-term experiments in Northeast China, including three crops (wheat, maize and soyabean) and four fertilizations (no-fertilizer (CK), mineral nitrogen, phosphorus and potassium (NPK), manure only (M), and chemical fertilizers plus M (NPKM or NM)). SPACSYS effectively simulated crop yields and the dynamics of SOC stock. According to SPACSYS projections, climate change, especially the increased temperature, is anticipated to reduce maize yield by an average of 14.5% in Harbin and 13.3% in Gongzhuling, and soybean yield by an average of 10.6%, across all the treatments and climatic scenarios. Conversely, a slight but not statistically significant average yield increase of 2.5% was predicted for spring wheat. SOC stock showed a decrease of 8.2% for Harbin and 7.6% for Gonghzuling by 2,100 under the RCP scenarios. Future climates also led to a reduction in CSE by an average of 6.0% in Harbin (except NPK) and 13.4% in Gongzhuling. In addition, the higher average crop yields, annual SOC stocks, and annual CSE (10.15–15.16%) were found when manure amendments were performed under all climate scenarios compared with the chemical fertilization. Soil CSE displayed an exponential decrease with the C accumulated input, asymptotically approaching a constant. Importantly, the CSE asymptote associated with manure application was higher than that of other treatments. Our findings emphasize the consequences of climate change on crop yields, SOC stock, and CSE in the Mollisol regions, identifying manure application as a targeted fertilizer practice for effective climate change mitigation.

Overexpression of soybean GmDHN9 gene enhances drought resistance of transgenic Arabidopsis

ABSTRACT Soybean is one of the important oil crops and a major source of protein and lipids. Drought can cause severe soybean yields. Dehydrin protein (DHN) is a subfamily of LEA proteins that play an important role in plant responses to abiotic stresses. In this study, the soybean GmDHN9 gene was cloned and induced under a variety of abiotic stresses. Results showed that the GmDHN9 gene response was more pronounced under drought induction. Subcellular localization results indicated that the protein was localized in the cytoplasm. The role of transgenic Arabidopsis plants in drought stress response was further studied. Under drought stress, the germination rate, root length, chlorophyll, proline, relative water content, and antioxidant enzyme content of transgenic Arabidopsis thaliana transgenic genes were higher than those of wild-type plants, and transgenic plants contained less O2 −, H2O2 and MDA contents. In short, the GmDHN9 gene can regulate the homeostasis of ROS and enhance the drought resistance of plants.

Cover crop inclusion and residue retention improves soybean production and physiology in drought conditions

Soybean (Glycine max (L.) Merr.) planting has increased in central and western North Dakota despite frequent drought occurrences that limit productivity. Soybean plants need high photosynthetic and transpiration rates to be productive, but they also need high water use efficiency when water is limited. Crop residues and cover crops in crop rotations may improve soybean drought tolerance in northern Great Plains. We aimed to examine how a management practice that included cover crops and residue retention impacts agronomic, ecosystem water and carbon dioxide flux, and canopy-scale physiological attributes of soybeans in the northern Great Plains under drought conditions. The experiment consisted of two soybean fields over two years with business-as-usual (no-cover crops and spring wheat residue removal) and aspirational management (cover crops and spring wheat residue retention) during a drought year. We compared yield; aboveground biomass; green chromatic coordinates, and CO2 and H2O fluxes from eddy covariance, Phenocam images, and ancillary micrometeorological measurements. These measurements were used to derive ecosystem-scale physical, and physiological attributes with the ‘big leaf’ framework to diagnose underlying processes. Soybean yields were 29 % higher under drought conditions in the field managed in a system that included cover crops and residue retention. This yield increase was associated with a 5 day increase in the green-chromatic-coordinate defined maturity phenophase, increasing agronomic and intrinsic water use efficiency by 27 % and 33 %, respectively, increasing water uptake, and increasing the rubisco-limited photosynthetic capacity (Vcmax25) by 42 %. The inclusion of cover crops and residue retention into a cropping system improved soybean productivity because of differences in water use, phenology timing, and photosynthetic capacity. These results suggest that farmers can improve soybean productivity and yield stability by incorporating cover crops and residue retention into their management suite because these practices to facilitate more aggressive water uptake.

The effect of tire inflation pressure and tillage systems on soil properties, growth and yield of maize and soybean in a silty clay loam soil

AbstractSoil compaction causes adverse effects on soil structure and the performance of crops. There is significant literature supporting the hypothesis that reducing tire inflation pressure can help to minimize compaction, but there is no data on the potential benefits of high flexion tires operating at reduced tire pressures in Midwestern United States agriculture. Hence, a field‐scale study was established in Illinois to determine the potential benefits of high flexion tires at low tire pressure (LTP) in comparison with those operated at standard tire inflation pressure (STP) on soil condition, crop growth and yield of maize and soybean for three tillage systems; deep tillage (450 mm), shallow tillage (100 mm) and no‐till. Two adjacent experiments were established in typical maize/soybean and soybean/maize rotations, respectively. The experiment used a 2 × 3 factorial design with five completely randomized blocks. The results showed that the use of LTP tires resulted in lower soil penetrometer resistance for three tillage systems in 2017 and 2018 in the maize field and 2018 in the soybean field. This improved plant establishment and the number of plants per hectare of maize in both 2016 (*p ≤ .05) and 2018 (**p ≤ .01) and plant establishment (***p ≤ .001) and the number of plants per hectare (***p ≤ .001) of soybean in 2018. The penetrometer resistance was higher in the no‐till plots compared to deep and shallow tillage plots in maize and was higher in the deep tillage plots compared to the shallow tillage in the soybean field. The use of LTP tires resulted in an increased grain yield of maize by 4.31% (15.02 Mg ha−1) and 2.70% (14.76 Mg ha−1) in 2017 (**p ≤ .01) and 2018 (*p ≤ .05), respectively, and soybean by 3.70% (4.25 Mg ha−1) in 2018 (*p ≤ .05). The depth of tillage had a significant effect on soybean and maize yields in 2017 (***p ≤ .001) and 2018 (***p ≤ .001), respectively, with higher yields of both soybean and maize in the deep and shallow tillage compared to no‐till plots. The study concludes that the use of the LTP systems can be a potential means of addressing soil compaction and maintaining soil porosity while increasing crop productivity in silty clay loam soils in Central Illinois.

Assessing the impact of climate change on soybean production in Argentina

Soy is the most important agricultural commodity in Argentina, with relevance in public revenues and international reserves accumulation. However, a proper impact evaluation of future losses in the context of climate change has not yet been developed. Therefore, the aim of this paper is to provide future estimates of impact evaluation for macroeconomic adaptation policies. By means of a multiple partial regression, the relation between total country soybean yields and different combinations of 28 territorial weather stations was estimated for the period 2001–2021. With the optimal model, the output was projected using future rainfall and temperature data from 150 climate models from 4 different climate change scenarios from the Copernicus database during 2022–2042. Results show a strong statistical relationship between rainfall levels and maximum temperature and total soybean yields, explaining on average 91.2% of the yield variation. The future projections showed that the general average of the four climate change scenarios projected future output at 3.8% higher than the current levels, with 30% of projections with lower and 70% with higher output values than the current production. Variability analysis showed an increase in the frequency and intensity of extreme negative events and higher aggregate than in the past: relative loss is on average 3.6% of production (USD million $13,000) compared to 2.3% of production in the historical data (USD million $7,492). The main application is the estimation of macro-fiscal impact for long-term budgetary and fiscal planning, with a parsimonious approach and open-access data that allows permanent actualization.

Nodulation and Yields of Soybean (Glycine max L. Merrill) Varieties at Varying Phosphorus Fertilizer Rates in Lafia, Nigeria

Soybean production in Lafia, southern Guinea savanna zone of Nigeria, is impacted by soil phosphorus deficiency, affecting nodulation, nitrogen fixation, and overall crop productivity. Field experiments were conducted in 2018 and 2019 cropping seasons with different phosphorus fertilizer rates (0, 13, 26 & 39 Kg P2O5 ha-1) and six improved soybean varieties (TGX 1985-10F, TGX 1987-10F, TGX 1448-2E, TGX 1987-62F, TGX 1989-19F & TGX 1835-10E) to determine the effects of phosphorus fertilizer rates on nodulation and yields of soybean varieties. The results showed significant variation in soybean nodulation and yields when different phosphorus fertilizer rates were used. Among the six improved soybean varieties tested, TGX 1989-19F and TGX 1987-62F varieties performed best with 39 kg P2O5 ha-1. The results also show that plots that received a 39 kg P2O5 ha-1 produced the highest nodule number (26.3 & 28.7) and nodule weight (203.5 & 221.2 mg/plant) significantly in 2018 and 2019, respectively, compared to those with lower phosphorus rates. The effect of phosphorus fertilizer rates on soybean yields was apparent, with the 39 kg ha-1 phosphorus treatment yielding significantly higher yields than the lower phosphorus treatments. Notably, the TGX 1989-19F variety consistently outperformed the others, yielding the highest yield (1624.0 kg/ha). Based on the results, it is recommended that soybean farmers in the Lafia region consider increasing their phosphorus rates to 39 kg ha-1 for improved nodulation and subsequent yield gains. The TGX 1989-19F variety, due to its exceptional response to this phosphorus level, could be prioritized for cultivation to maximize returns. However, further research and on-farm trials must validate these findings across multiple growing seasons and farm management practices.

MAIZE-SOYBEAN INTERCROPPING WITH ORGANIC FERTILIZATION AS A SOLUTION TO ENHANCE CROP AND SOIL PRODUCTIVITY

An ever-increasing population and a decreasing cultivated land are challenging global food security. There is a massive difference between domestic production and demand. It is critical to improve the various index of land in order to secure food for future generations. Intercropping maize and soybeans can be a successful approach for addressing the gap between supply and demand. Due to low crop production per unit area, insufficient crop diversity, a lack of quality seeds and fertilizers, poor crop management, and the unfavorable effects of climate change. The experiment was conducted to understand the relationship of maize-soybean intercropping system with farm yard manure as a source of fertilizer. Our results showed that the farm yard manure has positively affected the overall soil fertility and also improved the crops production. Farm yard manure addition has given more fruitful results under maize-soybean intercropping. Maize-soybean intercropping with farm yard manure had a significant impact on growth and grain yield of both maize and soybean. The agronomic parameters plant height, shoot dry matter yield, grain yield and nitrogen uptake were recorded highest in the farm yard manure treatment under maize-soybean intercropping. Similarly, soil building attributes soil pH, total organic carbon, dissolved organic carbon and soil mineral nitrogen were positively affected by the interaction of farm yard manure and maize-soybean intercropping. Overall, we have concluded that maize-soybean intercropping system is most resilient cropping system with the implementation of farm yard manure to improve the crop productivity, soil health and to overcome the impact of climate change.

European soybean to benefit people and the environment

Europe imports large amounts of soybean that are predominantly used for livestock feed, mainly sourced from Brazil, USA and Argentina. In addition, the demand for GM-free soybean for human consumption is project to increase. Soybean has higher protein quality and digestibility than other legumes, along with high concentrations of isoflavones, phytosterols and minerals that enhance the nutritional value as a human food ingredient. Here, we examine the potential to increase soybean production across Europe for livestock feed and direct human consumption, and review possible effects on the environment and human health. Simulations and field data indicate rainfed soybean yields of 3.1 ± 1.2 t ha−1 from southern UK through to southern Europe (compared to a 3.5 t ha−1 average from North America). Drought-prone southern regions and cooler northern regions require breeding to incorporate stress-tolerance traits. Literature synthesized in this work evidenced soybean properties important to human nutrition, health, and traits related to food processing compared to alternative protein sources. While acknowledging the uncertainties inherent in any modelling exercise, our findings suggest that further integrating soybean into European agriculture could reduce GHG emissions by 37–291 Mt CO2e year−1 and fertiliser N use by 0.6–1.2 Mt year−1, concurrently improving human health and nutrition.

Bridging the gap between crop breeding and GeoAI: Soybean yield prediction from multispectral UAV images with transfer learning

Despite significant progress has been made towards crop yield prediction with remote sensing, there exist knowledge gaps on (1) the impacts of temporal resolution of imaging frequencies on yield prediction, (2) transferability of the models among different genotypes and test sites, and (3) translation of these research developments to crop breeding that benefit farmers. Existing research predominantly provides an on-site perspective, frequently missing the complexities of real-world applications. The objectives of this paper are to investigate the transferability and generalization capabilities of yield prediction models for crop breeding across test sites located in North and South Americas. Toward that goal, we tested different machine learning techniques including Random Forest Regressor (RF), Gradient Boosting Regression (GB), and Deep Neural Networks (DNN) for soybean yield prediction with experiments conducted in different climate and growth conditions. A novel transfer learning approach was proposed for genotype selection and categorizing soybean yield for screening high-yield varieties. Furthermore, we studied the effect of temporal resolution on yield prediction, focusing on the critical development stages and optimal aerial survey frequencies for precise yield prediction using large 31,404 sample data. Results demonstrated that the combined dataset of Argentina and United States representing different climate regimes provided the highest performance with an R2 of 0.76 using RF and GB algorithms. The classification approach was proven to be most useful for crop breeding as demonstrated by accurately identifying the high-yielding genotypes. Increasing temporal sampling of key phenological stages significantly improved yield prediction. Although transfer learning yielded promising outcomes across trials within Argentina the efficacy of transferring models from Argentina to the United States was limited, attributed to significant seasonal and climate variations. This study pioneered the use of transfer learning for model adaptability in real-world breeding scenarios, training and transferring models within the South and North Americas, providing actionable insights and strategies for the breeding community, aiming to facilitate improved decision-making for agricultural productivity.

SoybeanTracer: An In-Field scene property-based framework for high-throughput soybean canopy coverage extraction and evaluation

Soybean is a crucial plant-based protein and vegetable oil source for the global population and a significant cereal-oil dual-purpose crop. Extracting soybean canopy coverage, subsequently implementing evaluation in a low-cost, high-throughput and accurate manner, is highly valuable for soybean breeding and yield increase. Although the utilization of RGB remote sensing images for soybean analysis offers distinct advantages in terms of its cost effectiveness, there are still issues to be addressed. Specifically, the in-field scene properties of soybean canopy data have rarely been developed and there is a gap in automatic evaluation of soybean canopy coverage. For purpose of tackling these pending issues, this study proposed SoybeanTracer, a novel framework designed to achieve accurate soybean canopy coverage extraction and enable specialized evaluation with low cost and high throughput. The proposed framework comprised two components: Soybean Canopy Segmentation Network (SCSNet) and an agronomic soybean coverage evaluation system. Specifically, SCSNet employed a feature extraction network integrating the homogeneity within plot regions and soybean distribution characteristics. To further address the segmentation challenge of soybean plants with sparse growth posed by genotypes, a soybean multiscale feature fusion module was designed. As a result, SCSNet achieved a mean intersection over union (mIoU) and mean pixel accuracy (mPA) of 89.39% and 94.42%, respectively, on soybean canopy segmentation. Therefore, accurate and low-cost extraction of soybean canopy coverage was achieved through the use of RGB remote sensing data. Furthermore, the soybean canopy coverage evaluation system proposed in this study encompassed five levels, characterized by wider spacing at the two ends and narrower spacing in the middle. This agronomic evaluation system had been effectively implemented on 196 plots. The variance in the pairwise levels of the coverage evaluation results demonstrated the robustness of the evaluation system. SoybeanTracer could indeed help to extract soybean canopy coverage and provide valuable reference for implementing soybean genotype selection, laying a useful foundation for other crops in similar scientific tasks. The source code and trained models were available at https://github.com/KLoAS-Research/SCSNet-SoybeanTracer.

Combined metagenomics and metabolomic analysis of microbial community structure and metabolic function in continuous soybean cropping soils of Songnen Plain, China

Continuous cropping has a negative effect on soybean yield. In this study, a positioning experiment was conducted starting in 2015, with three treatments: maize–soybean rotation (SMR), 2-year maize, 2-year soybean rotation cropping (SC2), and 8-year soybean continuous cropping (SC8). We determined soybean yields (2015–2022) and analyzed soil microbial communities, functions, and metabolites composition in the 0–20 cm tillage layer using metagenomics technology and GC–MS technology during soybean flowering in 2022. Results indicated that continuous cropping (SC8) significantly reduced soybean yield compared to crop rotation (SMR) during the experimental period, while SC8 showed higher yield than SC2 in 2022. Compared to SMR, SC8 significantly increased soil N content and significantly decreased pH and TP, AP, and AK content. However, the pH and AK contents of SC8 were significantly higher than those of SC2. LeFSe analysis showed that Friedmanniella, Microlunatus, Nitrososphaera, Rubrobacter, Geodermatophilus, Nitriliruptor were enriched in SC8. Gaiella, Sphaerobacter, Methyloceanibacter were enriched in SC2. Sphingomonas, Cryobacterium, Marmoricola, Haliangium, Arthrobacter, Ramlibacter, Rhizobacter, Pseudolabrys, Methylibium, Variovorax were enriched in SMR. And the relative abundance of Cryobacterium, Marmoricola, Haliangium, Arthrobacter, Ramlibacter, Rhizobacter, Methylibium, Variovorax was significantly positively correlated with yield, while the relative abundance of Gaiella and Sphaerobacter was significantly negatively correlated with yield. SC8 significantly increased the abundance of genes in nitrogen metabolism and significantly decreased the abundance of genes related to phosphorus and potassium metabolism compared with SMR. However, the abundance of genes in potassium metabolism was significantly higher in SC8 than in SC2. Metabolomic analysis showed that compared to SMR, SC8 decreased the abundance of carbohydrates, ketones, and lipid. However, the abundance of carbohydrates, ketones, and lipid was significantly higher in SC8 than in SC2. Mantel test showed that soil pH and AK significantly affected soil microbial community, function, and metabolite composition. Correlation analysis showed significant correlation between soil metabolites and microorganisms, metabolic functions.Graphical

Ecophysiological mechanisms underlying the positive relationship between seed protein concentration and yield in soybean under field heat and drought stress

AbstractA positive relationship between protein concentration and yield has been documented in different combinations of genotype and environment, often under potential conditions. However, the ecophysiological bases underlying this positive relationship under heat stress (HS) and drought stress (DS) during seed filling are still lacking. Our objective was to evaluate the relationship between seed protein content and concentration with yield in field experiments exposed to HS, DS and HS × DS interaction during the seed filling. Two field experiments were conducted and assimilates accumulation, remobilization and redistribution patterns were analysed in high and low seed protein soybean genotypes. The crop was exposed to four treatments: control (ambient temperature and soil water content near field capacity), HS (episodes above 32°C, 6 h d−1) during 15 days, DS (soil water content ≤25% of field capacity) during the whole seed filling and HS × DS. Significant and positive relationships between seed protein content and concentration with yield were observed across treatments and genotypes. Under DS and HS × DS, assimilates available during the seed filling decreased, and assimilates remobilization and partition to seeds were limited, responses significantly associated with seed protein content and concentration, and yield reductions. Furthermore, we demonstrated here that the high leaf N content at the beginning of seed filling, the short early reproductive phase duration, the high source to sink ratio and the high dry matter stem remobilization capacity, as well as the low seed number and high seed weight are intrinsic characteristics of the high protein genotype that could be associated with its high seed protein content and concentration and yield under stressful conditions. This knowledge is key to develop soybean management strategies to improve seed protein level and yield under contrasting productive scenarios.