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Seed expense is a critical component affecting soybean (Glycine max L.) production cost. Achieving potential benefits of adjusting seeding rates by yield environment requires translation from theory to practice through decision support tools. This article introduces the soybean variable‐rate seeding (VRS) simulator, an interactive web‐tool designed to facilitate VRS decisions. A group of agronomists and farmers provided input and feedback to the tool's original design, usability, interactive features, and tool outputs. The simulator generates variable rate seeding recommendations by (a) aggregating and classifying 3 yr of historical soybean yield maps using either yield level (low, medium, or high) or temporal yield stability (stable or unstable) classes, and (b) estimating the difference between the farmers current uniform seeding rate and the optimal seeding rates calibrated for different yield environments of the U.S. Midwest region. For each yield environment, the tool suggests a seeding rate change accompanied by an expected yield increase. Marginal economic and break‐even price analyses of each VRS prescription choice are also provided considering soybean plant survival rate, seed cost, market price, and crop production costs. A step‐by‐step description is provided using a dataset of real, historical, on‐farm soybean yield maps to illustrate the tool's features and limitations. Simulated results indicate that compared to typical fixed seeding rate choices, following the tool's recommendations could improve profits between US$5 and 57 ha–1. The development of this tool contributes to a growing trend of user‐friendly interfaces that assist in translating core agronomic knowledge into practical solutions. Core Ideas: The soybean variable‐rate seeding simulator is an interactive web‐tool designed to facilitate variable rate seeding decisions.The simulator converts 3 yr of yield maps into variable seeding rate recommendations.The simulator provides economic results based on yield environment, plant survival rate, seed cost, and market price.Potential benefits of recommendations ranged from US$5–57 ha–1 compared with fixed seeding rates.This tool contributes to translating core agronomic knowledge into practical solutions. [ABSTRACT FROM AUTHOR]

Limited knowledge about how nitrogen (N) dynamics are affected by climate change, weather variability, and crop management is a major barrier to improving the productivity and environmental performance of soybean-based cropping systems. To fill this knowledge gap, we created a systems understanding of agroecosystem N dynamics and quantified the impact of controllable (management) and uncontrollable (weather, climate) factors on N fluxes and soybean yields. We performed a simulation experiment across 10 soybean production environments in the United States using the Agricultural Production Systems sIMulator (APSIM) model and future climate projections from five global circulation models. Climate change (2020–2080) increased N mineralization (24%) and N2O emissions (19%) but decreased N fixation (32%), seed N (20%), and yields (19%). Soil and crop management practices altered N fluxes at a similar magnitude as climate change but in many different directions, revealing opportunities to improve soybean systems' performance. Among many practices explored, we identified two solutions with great potential: improved residue management (short-term) and water management (long-term). Inter-annual weather variability and management practices affected soybean yield less than N fluxes, which creates opportunities to manage N fluxes without compromising yields, especially in regions with adequate to excess soil moisture. This work provides actionable results (tradeoffs, synergies, directions) to inform decision-making for adapting crop management in a changing climate to improve soybean production systems. [ABSTRACT FROM AUTHOR]

Corn (Zea mays L.)–soybean [Glycine max (L.) Merr.] is among the most typical crop rotations in the U.S. Corn Belt, and N is the most limiting nutrient for both crops. This study aims to assess the effects of N management for corn on the following soybean crop. Two corn–soybean rotation N fertilizer rate studies—a long‐term study (1983–2020, Case Study I) and a two‐season study (2019–2020, Case Study II)—were conducted in Kansas (United States). Case Study I focused on soybean seed yield as the response variable, whereas Case Study II included a detailed seasonal characterization of soil N, symbiotic N fixation (SNF), and plant N uptake for soybean considering N fertilizer rates on the previous corn crop. Apparent N budgets from corn (N fertilizer minus grain N removal) ranged from approximately −100 to approximately +50 kg N ha−1, and soybean yields were slightly or not affected by corn N management. Case Study I showed that long‐term N budgets in corn crops did not affect the following soybean crop yields. In Case Study II, the previous corn N management produced negative or small N surplus that influenced neither soil residual N nor SNF, without compromising soybean productivity. Farmers applying close to economic optimum N rates on corn will likely not generate scenarios of N surplus to compromise SNF or soybean yields. Forthcoming research should further address how long‐term and large soil N mining or surplus in corn may enhance or inhibit N fixation for the next soybean crop. Core Ideas: Soybean yields were slightly or not affected by N management of the previous corn crop.Soil N during soybean season was not affected by previous corn N management.Apparent N budgets from previous corn were mostly below zero or slightly positive.Small N surplus (<50 kg N ha−1) did not influence soybean yields and N fixation.Long‐term N budgets in corn crops did not affect next‐season soybean yields. [ABSTRACT FROM AUTHOR]

Soybean [ Glycine max (L.) Merr.] seeds are of global importance for human and animal nutrition due to their high protein and oil concentrations, and their complete amino acid (AA) and fatty acid (FA) profiles. However, a detailed description of seed composition at different canopy portions (i.e., main stem and branch nodes) is currently lacking in scientific literature. This study aims to (1) characterize seed yield and composition (protein, oil, AA, and FA) at the main stem (exploring a vertical canopy profile) and stem branches and (2) quantify the impact of canopy yield allocation on seed composition, focusing on branches as a potential contributor for higher yields. Four genotypes were field-grown during the 2018 and 2019 seasons, with seeds manually harvested from all the branches and three main stem segments (lower, middle, and upper). Seed samples were analyzed for seed yield (Mg/ha), seed size (mg/seed), protein and oil content (mg/seed) and their respective concentrations (g/kg), and AA and FA concentrations within protein and oil (g/100 g), herein called abundance. The upper main stem produced greater protein (25%) and oil (15%) content relative to the lower section; however, oil concentration increased from top to bottom while protein concentration followed opposite vertical gradient. Limiting AAs (lysine, cysteine, methionine, threonine, and tryptophan) were more abundant in the lower main stem, while the oleic/(linoleic + linolenic) ratio was greater in the upper segment. Overall, branches produced seeds with inferior nutritional quality than the main stem. However, the contribution of branches to yield (%) was positively related to limiting AA abundance and oil concentration across soybean genotypes. Future research studies should consider the morphological process of stem branching as a critical factor intimately involved with soybean seed composition across environments, genotypes, and management practices. [ABSTRACT FROM AUTHOR]

Biological nitrogen (N)-fixation is the most important source of N for soybean [ Glycine max (L.) Merr.], with considerable implications for sustainable intensification. Therefore, this study aimed to investigate the relevance of environmental factors driving N-fixation and to develop predictive models defining the role of N-fixation for improved productivity and increased seed protein concentration. Using the elastic net regularization of multiple linear regression, we analyzed 40 environmental factors related to weather, soil, and crop management. We selected the most important factors associated with the relative abundance of ureides (RAU) as an indicator of the fraction of N derived from N-fixation. The most relevant RAU predictors were N fertilization, atmospheric vapor pressure deficit (VPD) and precipitation during early reproductive growth (R1–R4 stages), sowing date, drought stress during seed filling (R5–R6), soil cation exchange capacity (CEC), and soil sulfate concentration before sowing. Soybean N-fixation ranged from 60 to 98% across locations and years (n = 95). The predictive model for RAU showed relative mean square error (RRMSE) of 4.5% and an R2 value of 0.69, estimated via cross-validation. In addition, we built similar predictive models of yield and seed protein to assess the association of RAU and these plant traits. The variable RAU was selected as a covariable for the models predicting yield and seed protein, but with a small magnitude relative to the sowing date for yield or soil sulfate for protein. The early-reproductive period VPD affected all independent variables, namely RAU, yield, and seed protein. The elastic net algorithm successfully depicted some otherwise challenging empirical relationships to assess with bivariate associations in observational data. This approach provides inference about environmental variables while predicting N-fixation. The outcomes of this study will provide a foundation for improving the understanding of N-fixation within the context of sustainable intensification of soybean production. [ABSTRACT FROM AUTHOR]

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Soils and climate influence soil nutrient supply, crop nutrient demand, and potential yield. We collected soybean [Glycine max (L.) Merr.] data of seed yield and nutrient uptake from field students (n = 657) in Northeast China (2001–2017) to study spatial distribution of attainable yield, yield response to fertilizer, and crop nutrient requirements at regional scale. The study area was divided in four weather regions based on daily average temperature and cumulative precipitation during the soybean growth season. Average attainable yield was 3.2, 3.1, 2.9, and 2.6 Mg ha–1 in warm‐wet, warm‐dry, cold‐wet, and cold‐dry regions, respectively. Soybean yield response to N, P, and K fertilizers and requirement of these nutrients presented the following order for each region from high to low: cold‐wet > warm‐dry > cold‐dry > warm‐wet regions, with exception for K requirement. In overall, spatial correlation in yield response to fertilizer and nutrient requirement ranked in the following order: P > K > N across all the climate regions. Based on the variation in attainable yield, balanced fertilization should be pursued to more sustainable higher soybean yields in the warm‐dry and cold‐wet regions with favorable weather conditions; while for the cold‐dry region, fertilization needs to address the topic of improving P use efficiency, as future research prioritizes from both environmental and productivity standpoints. [ABSTRACT FROM AUTHOR]

It is widely recognized that planting soybean [Glycine max (L.) Merr.] early is critical to maximizing yield, but the influence of changing management factors when soybean planting is delayed is not well understood. The objectives of this research were to (a) identify management decisions that increase seed yield in either early‐ or late‐planted soybean scenarios, and (b) estimate the maximum break‐even price of each management factor identified to influence soybean seed yield in early‐ or late‐planted soybean. Producer data on seed yield and management decisions were collected from 5682 fields planted with soybean during 2014−2016 and grouped into 10 technology extrapolation domains (TEDs) based on growing environment. A subsample of 1512 fields was classified into early‐ and late‐planted categories using terciles. Conditional inference trees were created for each TED to evaluate the effect of management decisions within the two planting date timeframes on seed yield. Management strategies that maximized yield and associated maximum break‐even prices varied across TEDs and planting date. For early‐planted fields, higher yields were associated with artificial drainage, insecticide seed treatment, and lower seeding rates. For late‐planted fields, herbicide application timing and tillage intensity were related to higher yields. There was no individual management decision that consistently increased seed yield across all TEDs. [ABSTRACT FROM AUTHOR]

Soybean [Glycine max (L.) Merr.] seeding rate research across North America is typically conducted in small geo‐political regions where environmental effects on the seeding rate × yield relationship are minimized. Data from 211 individual field studies (∼21,000 data points, 2007–2017) were combined from across North America ranging in yield from 1,000– 7,500 kg ha−1. Cluster analysis was used to stratify each individual field study into similar environmental (soil × climate) clusters and into high (HYL), medium (MYL), and low (LYL) yield levels. Agronomically optimal seeding rates (AOSR) were calculated and Monte Carlo risk analysis was implemented. Within the two northern most clusters the AOSR was higher in the LYL followed by the MYL and then HYL. Within the farthest south cluster, a relatively small (±15,000 seeds ha−1) change in seeding rate from the MYL was required to reach the AOSR of the LYL and HYL, respectively. The increase in seeding rate to reach the LYL AOSR was relatively greater (5x) than the decrease to reach the HYL AOSR within the northern most cluster. Regardless, seeding rates below the AOSR presented substantial risk and potential yield loss, while seeding rates above provided slight risk reduction and yield increases. Specific to LYLs and MYLs, establishing and maintaining an adequate plant stand until harvest maximized yield regardless of the seeding rate, while maximizing seed number was important with lower seeding rates. These findings will help growers manage their soybean seed investment by adjusting seeding rates based upon the productivity of the environment. [ABSTRACT FROM AUTHOR]

Soybean [Glycine max (L.) Merr.] responses to seed inoculation with rhizobium are inconsistent in sites with inoculation history. Field trials were conducted in South-central region of Paraná State (Southern Brazil) aiming to evaluate yield response to inoculation in areas with history of inoculation at a regional-scale (21 trials, 1999/2000 to 2014/2015), and identify nodulation, plant dry weight and nitrogen (N) components underpinning yield formation (10 trials, 2015/2016 and 2016/2017). Seed yield varied from 1853 to 5352 kg ha−1 (first dataset), characterizing a wide range of environmental conditions across seasons. Response to inoculation was inconsistent at regional-scale, with a similar seed yield of inoculated (3286 kg ha−1) and non-inoculated (3298 kg ha−1) soybean. Lack of differences were also observed in all the variables analyzed of second dataset. Research efforts should be applied aiming to identify rhizobia persistence in the soil and its efficacy at N fixation after continuous cropping without inoculation. [ABSTRACT FROM AUTHOR]

Inconsistent soybean [Glycine max (L.) Merr.] seed yield response to plant density has been previously reported. Moreover, recent economic and productive circumstances have caused interest in within-field variation of the agronomic optimal plant density (AOPD) for soybean. Thus, the objectives of this study were to: (i) determine the AOPD by yield environments (YE) and (ii) study variations in yield components (seed number and weight) related to the changes in seed yield response to plant density for soybean in North America. During 2013 and 2014, a total of 78 yield-to-plant density responses were evaluated in different regions of the United States and Canada. A soybean database evaluating multiple seeding rates ranging from 170,000 to 670,000 seeds ha-1 was collected, including final number of plants, seed yield, and its components (seed number and weight). The data was classified in YEs: low (LYE, <4 Mg ha-1), medium (MYE, 4-4.3 Mg ha-1), and high (HYE, >4.3 Mg ha-1). The main outcomes were: (i) AOPD increased by 24% from HYE to LYE, (ii) per-plant yield increased due to a decrease in plant density: HYE > MYE > LYE, and (iii) per-plant yield was mainly driven by seed number across plant densities within a YE, but both yield components influenced per-plant yield across YEs. This study presents the first attempt to investigate the seed yieldto- plant density relationship via the understanding of plant establishment and yield components and by exploring the influence of weather variables defining soybean YEs. [ABSTRACT FROM AUTHOR]

Camelina [Camelina sativa (L.) Crantz] has been identified as a potential oilseed crop for fallow replacement in cropping systems in the semiarid US Great Plains. However, camelina production is limited to the northern Great Plains region. We investigated the effects of three planting dates [mid-March, early-April, and mid-April] and three cultivars (Blaine Creek, Pronghorn, and Shoshone) on spring camelina seed yield and oil quality under non-irrigated conditions in western Kansas. Results showed planting in April increased seed yield by 34% compared with mid-March planting date. Blaine Creek produced greatest seed yield among the cultivars. Planting in mid-March increased oil, polyunsaturated fatty acids (PUFA), and linolenic acid concentrations compared with April planting dates. Saturated fatty acid (SFA) concentration increased with an April planting date. Heat stress in the growing season reduced seed yield, oil, PUFA, linoleic, and linolenic acid concentrations. However, increase in precipitation amounts improved seed yield, oil, PUFA, and linolenic acid concentrations. Our findings showed early- to mid-April is the best-planting window for optimum spring camelina stands and seed yield in this environment. [ABSTRACT FROM AUTHOR]

Equidistant plant arrangements have shown positive impacts, in the United States over the last century, on soybean (Glycine max L.) yield and seed quality by reducing intraspecific plant competition and enhancing early canopy cover. This study aims to (i) assess the effects of equidistant versus non‐equidistant plant arrangements on soybean yield and seed quality across different regions in the United States; (ii) explore the effect of modified soybean plant canopy resulting from different plant arrangements on yield and seed quality. In 2021 and 2022, 13 trials were conducted in Kansas, Mississippi, and South Dakota. The treatments consisted of three equidistant plant arrangements of 13 cm × 13 cm, 15 cm × 15 cm, and 20 cm × 20 cm (620,000, 430,000, 242,363 seeds ha−1, respectively), and a non‐equidistant with 38 cm of row space (321,236 seeds ha−1). Soybean yield and yield components were collected, and canopy coverage (%) was monitored throughout the growing season. Overall, there is no evidence of any advantage of equidistant over non‐equidistant arrangements in soybeans. Yield differences related to spatial arrangement were observed in only three trials: the non‐equidistant increased yield compared to the 20 cm × 20 cm equidistant arrangement (lowest density) in two trials, while the 13 × 13 and 15 × 15 patterns (highest density) showed higher yield compared to the 20 cm × 20 cm arrangement in one trial. Furthermore, seed quality remained constant across spatial arrangements in the 13 trials. In contrast to prior research, our study found no correlation between canopy coverage development and yield improvement. The tested equidistant arrangement while promising did not provide substantial evidence of yield improvement relative to the non‐equidistant. [ABSTRACT FROM AUTHOR]

Highlights • We developed an approach to evaluate influence of management on yield using both producer and experimental data. • We assessed influence of row spacing on US soybean yield. • Experimental data showed a consistent yield advantage of narrow versus wide row spacing. • However, data from producer fields indicate no yield difference between narrow and wide rows. • This complementary approach can help evaluate yield increase derived from a management practice. Abstract Narrowing row width in soybean fields leads to earlier canopy closure, which may increase capture of incoming solar radiation during critical crop stages for yield determination. Theoretically, this should enhance seed yield. However, in prior studies, the impact of narrowing row spacing on soybean yield has been inconsistent. To explore on a broader scale the potential factors underlying this inconsistency, we evaluated the yield difference between narrow (NR; ≈38 cm) and wide (WR; ≈76 cm) row spacing using two sources of yield and management information: (i) data collected from 4879 soybean production fields via a multi-year, multi-state survey of soybean producers in the North Central US region; and (ii) data extracted from 129 site-year experiments that quantified NR-WR yield difference. The producer fields were allocated to their respective climate-soil domains to enable analysis of the NR-WR yield difference within each domain. The experimental trial data originated from three US geographic regions: south, central, and north. Key crop developmental stages in each trial were estimated using a soybean crop simulation model to discern if changes in crop phenology or any weather variable occurring before versus after a specific crop stage modulated the magnitude of the NR-WR yield difference. Analysis of experimental trial data indicated that, while NR yields were overall higher than WR yields, the NR-WR yield difference varied by region: 540 (south), 104 (central), and 240 kg ha−1 (north); the respective NR yields were greater than WR yields in 92%, 68%, and 84% of the cases. In the north and south regions, the NR-WR yield difference increased when the crop cycle length decreased as a consequence of later sowing date, earlier cultivar maturity group, and/or higher temperature. The relatively smaller (and occasionally negative) NR-WR yield difference detected in the central region was likely the result of environmental conditions that favored canopy closure irrespective of row spacing. In contrast to the analysis of the experimental database, no consistent NR-WR yield differences were detected in the producer field database. We hypothesize that the apparent absence of a significant NR-WR effect in the producer dataset is likely associated with the background management used with narrow spacing, together with yield losses due to wheel damage and greater disease pressure. This complementary approach using both producer and experimental data can help evaluate if practices documented in experimental trials to enhance yield realize equivalent yield increases in producer fields and, if not, explore underlying causes for the discrepancy. [ABSTRACT FROM AUTHOR]

Soybean [ Glycine max (L.) Merr.] is the most important legume grown worldwide. The effect of nitrogen (N) and sulfur (S) fertilization on seed yield is commonly studied in the United States (US). However, soybean yield response to fertilization remains inconsistent, partly due to the lack of standardized field designs and a better understanding of the plant nutrition processes underpinning yield formation. The aims of this study were to assess the i) seed yield, (ii) plant N status (as N nutrition index, NNI), (iii) the contribution of N fixation, and (iv) the uncertainties on i), ii), and iii) in response to N-S fertilization using a uniform protocol across environments. Twenty-six trials in twelve US states tested five fertilization strategies that combined N and S at varying rates and timings. Using Bayesian statistics, seed yield response to fertilizer, NNI, and contribution of N fixation were analyzed at site and treatment levels providing both magnitude of responses and estimation of their uncertainties. From the significance of responses on seed yield, sites were split into two groups: non-responsive (18 sites) and responsive (8 sites). The NNI, ratio of the actual to the critical plant N concentration, was calculated to diagnose soybean N deficiency, and the N derived from the atmosphere (Ndfa, %) as N fixation contribution were investigated to better understand the source of plant N across all sites. Roughly for three-fourths of the sites, fertilization resulted in an unlikely (non-responsive) yield effect, with uncertainties ranging from 0.09 to 2.62 Mg ha−1. The other one-third of the sites were mainly responsive to S or both N + S, with the yield responses ranging from − 0.42–1.1 Mg ha−1 and uncertainties varying from 0.47 to 1.36 Mg ha−1. For the yield responsive sites, NNI presented a high proportion of deficiency (NNI<1) for most of the treatments, except for the "Full" signaling to a potential for yield response. Likewise, only 6% of the changes in Ndfa were not related to the treatment "Full", and regardless of the seed yield response to fertilization, within the same site, soil and N fixation showed similar contributions to plant N demand. Due to the high uncertainty in treatment response and contribution of N fixation, N fertilization is unlikely to increase yields, leading to non-profitable recommendations. Sulfur deficiency, on the other hand, should be explored under site-specific conditions. A decision support system should include appropriate diagnosis methods for identifying N and S deficiencies, such as NNI in soybean. Attainable maximum Ndfa did not appear to be affected by fertilization but largely varying depending on the site. Future research should assess the role of soil and meteorological variables underpinning N fixation and soil N, along with the impact on seed quality composition, as a critical trait for this crop. • Uncertainties were greater than effects on yield, N status, and N fixation. • Yield uncertainties were up to 2.6 Mg ha−1 for yield response to fertilizer. • 8 out of 26 sites showed seed yield response to fertilization from 0.45 to 1.1 Mg ha−1. • Changes in plant N status were positively correlated to yield response to sulfur. • Low N rates in soybeans resulted minor or no impact on N fixation. [ABSTRACT FROM AUTHOR]

Canola (Brassica napus L.) is a major oilseed crop for edible and industrial uses. Climate change, characterized by extreme heat and drought conditions, can affect canola seed yield and quality (protein and oil), restricting grower capacity to keep pace with growing demand. However, estimating the influence of future climate on such complex traits is challenging due to biophysical interactions and crop adaptations to abiotic stresses. Current scientific literature reports contrasting impacts on the effect of heat and drought for canola productivity, mainly linked to changes in magnitude and duration of the stress. To better understand how drought and heat affect canola seed yield and quality (mainly protein and oil), a meta-analysis was executed to compile a total of 39 papers (1794 observations). The aims of this research were to i) quantify the impact of different timing and duration of heat and drought stresses on canola seed yield, oil yield, and seed quality (oil and protein concentration), and ii) study the effect of short-term stresses on seed quality, yield and its components (seed number and seed weight). This review study highlighted the magnitude and direction of overall and different stress impacts on canola; and some of the main limitations in the current scientific literature. Briefly, the main outcomes of this review highlighted that i) early heat stress(before end of flowering) had the largest impact on canola seed yield, as a short stress, ii) drought caused greatest yield impact when imposed for a long duration during flowering or a shorter duration during pod setting, and iii) short stresses had large impacts on seed oil concentration mainly during pod setting. More studies with standard stress levels and detailed information of abiotic stresses on reproductive growth stages are needed. This meta-analysis provides critical information for crop management, guiding development of cultivars linked to tolerance to abiotic stresses for breeding programs, and the future direction of canola adoption and production. • Contrasting heat and drought impacts on canola/rapeseed were reported in the literature. • This meta-analysis dissected abiotic stress timing and duration. • Highest negative impacts on yield were observed with stresses imposed before the end of flowering. • Seed oil and protein concentration were affected following abiotic short stresses during pod setting. [ABSTRACT FROM AUTHOR]

Soybean [ Glycine max (L.) Merr.] plays a critical role in global food security and sustainability, acquiring most of the nitrogen (N) required for growth and high-protein seeds from symbiotic N fixation (SNF). However, there is scarce information on how soil N supply interacts with N fixation (kg ha−1) throughout the growing season. This study aims to (1) evaluate the allometric relationships between the total N uptake and dry matter by N source (soil and fixation), (2) describe seasonal changes on soil-plant N dynamics among genotypes with contrasting genetic background (released between 1981 and 2019), and (3) assess the influence of soil NO 3 and NH 4 on the temporal SNF changes during the growing season. Four genotypes were field grown during 2019 and 2020. Bayesian non-linear models described seasonal change on dry matter, N uptake, soil NO 3 , and NH 4 (60 cm depth). The allometric relationship between N uptake and dry matter indicated that total N status is more sensitive to variations in N uptake from the soil than from fixation. Seasonal exposure to NH 4 (given by the area under the curve) and a delay on maximum NO 3 availability from early to mid-season suppressed end-season N fixation by two-fold the benefit on soil N uptake (kg ha−1). Both the magnitude and timing of soil N sources affected N uptake in all tested genotypes. Future research must explore broader SNF levels for understanding to what extent soil N can affect the N uptake sources, especially SNF, without decreasing seed yield in soybeans. • This study evaluates synchrony between in-season dynamics of soil N and SNF. • Allometric relationships indicate a stable balance between dry matter and N sources. • In-season soil ammonium exposure significantly reduced the end-season N fixation. • The in-season peak of nitrate decreased N fixation more than increased soil uptake. [ABSTRACT FROM AUTHOR]

In the semiarid pampas region of Argentina, peanut (Arachis hypogaea L.) crop undergoes frequent and unpredictable drought stress periods, with high probability of occurrence under future climate change projections. However, the overall frequency of occurrence and timing of different drought stress patterns under current and future climates has not been well investigated for the main peanut region in central Argentina. The aims of this study were to: (i) define the main peanut drought stress patterns and their occurrence (frequency) during the peanut growing season, via a crop growth modeling approach, (ii) test seed yield stability of the formerly defined (in i) drought stress patterns under future climate scenarios, and (iii) analyze the effect of sowing dates on peanut seed yield as a management strategy to mitigate the impact of future climate scenarios for peanut seed yield in the semiarid pampas region of Argentina. The APSIM-peanut growth model was calibrated and validated for local genotypes and production environments. Our study simulated seasonal drought stress patterns at five representative locations across the region under current and future climate scenarios, and tested six sowing dates as a practice to mitigate the impact of climate change. Clustering analysis identified two contrasting environment types (ETs). The high stress ET showed greater frequency of occurrence (>50%) at the southern locations. Future climate conditions increased the frequency of high stress ET by roughly 6% and reduced peanut seed yield by 12%, as average across locations. For both current and future climates, earlier sowing dates maximized peanut seed yield, regardless the locations. Changing sowing date was not an effective practice to mitigate the negative impact of climate change on peanut seed yield. The defined ETs allowed identifying a target population of environments (TPE) having implications for optimizing peanut breeding and management strategies. The projected increase in the frequency of drought stress for all tested locations provides a challenging scenario for sustaining peanut productivity in this region. [Display omitted] • The aims were to determine drought patterns under current and future climate, and to test sowing date as a mitigation tool • The defined drought stress patterns changed the frequency across locations, identifying a target population of environments • ·Future climate increased the frequency of drought stress by ~6% and reduced peanut seed yield by ~12% • Sowing date did not mitigate climate change impact. • This study provides insights to optimize breeding and management, and assists policy makers to address climate change. [ABSTRACT FROM AUTHOR]

Symbiotic nitrogen (N) fixation (SNF) is critical to satisfying the nutritional need of soybean (Glycine max (L.) Merr.) and maintaining productivity and high seed protein concentration. Due to its low environmental impact, a key factor for increasing the sustainability of soybean systems is to enhance SNF. Seed inoculation with the free-living Azospirillum brasilense alone or with Bradyrhizobium japonicum (herein called co-inoculation) are plausible strategies that have been explored in tropical environments but lack information in temperate regions. Following this rationale, this study aimed to evaluate the impact of seed inoculation with Azospirillum brasilense (herein called Azospirillum) alone or combined with Bradyrhizobium japonicum (herein called Bradyrhizobium) in a range of environments in the United States (US) for: (i) seed yield, (ii) relative abundance of ureides (RAU) as a proxy of SNF, and (iii) seed protein concentration. Twenty-five field studies across the US states with the same experimental design were performed during the 2019 and 2020 growing seasons. The primary outcomes of this research were: (i) yield responses to co-inoculation were considered significant in only 2 out of 25 site-years, (ii) RAU was not increased by Azospirillum inoculation or co-inoculation, and lastly, (iii) seed protein concentration was marginally associated with the inoculation strategies. Although Azospirillum did not impose remarkable gain in any observed plant traits, future studies should focus on mechanistically understanding whether Azospirillum can naturalize in temperate region soils. Still, strategies for enhancing SNF are required for sustainably improving productivity and quality for US soybean systems. • Strong yield response to co-inoculation was observed in only 2 out of 25 site-year. • Relative abundance of ureides was not affected by Azospirillum or co-inoculation. • The probability of maximum yield response (0.124 Mg ha−1) to Azospirillum was 5.3%. • Seed yield responses were linked to soil phosphorus and were reduced under drought. • There is negligible chance of inoculation to increase seed protein concentration. [ABSTRACT FROM AUTHOR]

• Non-linear models better describe the relationship between nutrient uptake and seed yield. • Nutrient requirements per unit of seed yield in soybean decreased as seed yield increased. • Non-linear quantile regressions provide probabilistic values for estimating nutrient uptake. Estimation of crop nutrient demand, seed nutrient removal, and nutrient use efficiency (yield to nutrient uptake ratio) are crucial for pursuing both balanced nutrition and more sustainable farming systems. However, the estimation of the nutrient requirements as the nutrient uptake per unit of seed yields is impaired in many situations due to the narrow variation of the dataset used to obtain these values or by the overgeneralization of considering a constant value for the nutrient demand at varying yield levels. Past studies focused on other crops and using linear models for estimation of the nutrient requirements, but not yet for soybeans (Glycine max L.). The aims of this research study were to: (i) quantify nitrogen (N), phosphorus (P), potassium (K), and sulfur (S) requirements in soybean and (ii) compare linear and non-linear (spherical) models in their relationship between plant and seed nutrient content all relative to seed yield at varying probabilities utilizing quantile regression. A large dataset from different studies conducted between 2009–2018 period, including data of seed yield, total biomass at physiological maturity, and N, P, K, and S uptake. Soybean seed yield ranged from 955 to 6525 kg ha−1, aboveground biomass from 1990 to 15,814 kg ha−1, and harvest index from 0.16 to 0.57. On average, nutrient uptake was 261 kg N ha−1, 25 kg P ha−1, 133 kg K ha−1, and 16 kg S ha−1 (N:P:K:S ratio = 17:1.6:8.5:1), while nutrient content in seeds averaged 191 kg N ha−1, 17 kg P ha−1, 54 kg K ha−1, and 9 kg S ha−1 (N:P:K:S ratio = 21:1.8:5.8:1). The spherical model described better than the linear model the relationship between plant nutrient uptake or nutrient content in seeds with seed yield in soybean, and thus, nutrient requirements per unit of yield decreased as seed yield increased. A relationship between nutrient internal efficiency and seed yield for the different percentiles as determined by the non-linear quantile regression offered probabilistic values for estimating nutrient uptake in soybean, providing useful information for obtaining more reliable estimates of nutrient balances at the system-level. [ABSTRACT FROM AUTHOR]

• Seed protein concentration increased by 0.3 % when sulfur (S) was applied at sowing. • An increment of 1% in SAA was observed regardless of the timing of S application. • There are no seed traits response to S fertilization under drought stress. • Soil with SOM range of 28−32 g kg-1 were associated with responses to S fertilization. Sulfur (S) deficiency has been recently reported in soybean Glycine max (L.) Merr.] producing regions across the United States. However, field studies have often failed to demonstrate a strong relationship between yield and S fertilization and generally attributing the lack of yield response to unfavorable weather and high soil S supply. In addition, only a few reports described seed composition changes due to S availability under contrasting field conditions. Therefore, our goals were (i) to implement a meta-analytic model to quantify the effect of S application at different growth stages on yield and seed concentration of protein, oil, essential non-S amino acids, and S amino acids (SAA, cysteine and methionine); ii) identify environmental factors underpinning the response of S to these plant traits. Field experiments were carried out from 2017 to 2019 growing seasons with a total of 44 unique site-years conditions across 18 locations in 8 states. Mineral S fertilizer (sulfate/ elemental S) was supplied depending on the study at sowing, vegetative and/or reproductive stages. A random-effects multilevel meta-analysis was conducted. The effect sizes compared yield and seed composition responses relative to the unfertilized control. A principal component analysis (PCA) separated distinctive environmental conditions and a sub-grouped meta-analysis with the main environmental factors was later executed to understand the response of the plant traits with those factors. Seed protein concentration increased by 0.3 % when S was applied at sowing. The concentration of SAA increased by ca. 1% regardless of the fertilization timing. Sites exposed to drought stress (18–29% reduction of potential transpiration) neither presented changes in yield nor seed composition due to S fertilization. Soils with organic matter between 25 and 32 g kg-1 (medium cluster) displayed significant responses to S application. This research brings extensive data and provides a comprehensive analysis of weather and soil attributes influencing soybean yield and seed composition responses to S availability. [ABSTRACT FROM AUTHOR]

• Past breeding efforts have not modified fatty acid (FA) profile in soybean. • Total oil and FA content in the seeds is mainly associated to the duration of the seed filling period. • Changes in total oil and fatty acid contents are not associated to changes in concentration. Soybean seed oil concentration and fatty acid (FA) composition are relevant traits defining oil quality and economic value for industry. In spite of the importance of FA composition for soybean value, a detailed description of FA profile and accumulation during seed filling in contrasting soybean varieties and management conditions is currently lacking. This study aims to: i) evaluate whether genetic progress in soybean yield indirectly affected FA profile, ii) assess the influence of N fertilization on FA profile, iii) characterize the temporal dynamics of FA accumulation during seed filling, and iv) evaluate the relative contribution of FA accumulation rate vs. duration on final FA seed content. Seven soybean varieties released between 1980 and 2013 were field grown under control (0 kg N ha−1) and fertilized (670 kg N ha−1 added) treatments. In addition to seed yield, total seed oil and FA contents during seed filling were recorded by sampling seeds from the beginning of seed formation to maturity. Genetic progress was evident in seed yield with an increase of 31.3 kg ha year−1. Total oil concentration (g oil kg−1) slightly decreased across year of release for the control. Fatty acid concentration (g FA 100 g oil−1) profile was not associated with year of release but affected by varieties. Variation in total oil and FA contents (mg seed−1) across varieties and N treatments was mostly associated to longer filling but was also affected by accumulation rates. Interestingly, individual FA concentration at maturity was independent from FA content. Our results indicate past breeding efforts have not modified soybean FA profile. The fact that changes in FA contents were not translated in changes in FA concentration indicates that seed control of FA profile is narrow. Disentangling the physiological mechanism associated with FA homeostasis warrants further examination. [ABSTRACT FROM AUTHOR]

• Harvest index is inconsistent across literature to describe genetic gain in reproductive allocation at maturity. • Allometric analysis was used to characterize genetic gain in reproductive allocation in R5 in seven soybean varieties. • Allometric analysis at the end of the seed set revealed an increase in relative allocation into pods. • Allocation to seed must have increased, but HI did not capture this necessary change in allocation. Seed yield is commonly expressed as the product of shoot biomass and harvest index (HI) at physiological maturity. However, HI is a size-dependent ratio unsuitable to describe shifts in reproductive partitioning in historical soybean [ Glycine max (L.) Merr.] studies where selection has enhanced shoot biomass. The aim of this work was to analyze allocation of biomass to reproductive organs in the onset of seed filling (R5) using allometric analysis in a set of historical soybean varieties. Seven varieties released between 1980 and 2013 were evaluated in field trials in Rossville (Kansas, United States) under two N fertilizer rates (0 and 670 kg N ha−1) in 2016 and 2017. Seed yield increased at a rate of 0.74 % yr−1 (p < 0.001); while the shoot biomass increased at a rate of 0.41 % yr−1 (p < 0.001), suggesting an increase in allocation to reproduction. However, the rate of increase in HI at maturity was not different from zero highlighting the inadequacy of this trait. Allometric exponents (slopes of the log-log relationships) relating pod and shoot biomass, pod and leaf, and pod and stem plant fractions increased linearly with the year of release (p < 0.05). Allometric analyses thus revealed genetic gains in reproductive allocation not detected by HI at maturity. The latter outcome highlights the contribution of improved reproductive partitioning to soybean yield gains, and the need for allometric analyses to account for size-dependence in allocation of shoot biomass. [ABSTRACT FROM AUTHOR]