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Low seed and meal protein concentration in modern high-yielding soybean [Glycine max L. (Merr.)] cultivars is a major concern but there is limited information on effective cultural practices to address this issue. In the objective of dealing with this problem, this study conducted field experiments in 2019 and 2020 to evaluate the response of seed and meal protein concentrations to the interactive effects of late-season inputs [control, a liquid Bradyrhizobium japonicum inoculation at R3, and 202 kg ha−1 nitrogen (N) fertilizer applied after R5], previous cover crop (fallow or cereal cover crop with residue removed), and short- and full-season maturity group cultivars at three U.S. locations (Fayetteville, Arkansas; Lexington, Kentucky; and St. Paul, Minnesota). The results showed that cover crops had a negative effect on yield in two out of six site-years and decreased seed protein concentration by 8.2 mg g−1 on average in Minnesota. Inoculant applications at R3 did not affect seed protein concentration or yield. The applications of N fertilizer after R5 increased seed protein concentration by 6 to 15 mg g−1, and increased yield in Arkansas by 13% and in Minnesota by 11% relative to the unfertilized control. This study showed that late-season N applications can be an effective cultural practice to increase soybean meal protein concentration in modern high-yielding cultivars above the minimum threshold required by the industry. New research is necessary to investigate sustainable management practices that increase N availability to soybeans late in the season.

Manipulation of soybean [Glycine max (L.) Merr.] maturity group (MG) and planting date will increase the yield of a soybean crop while simultaneously influencing the potential soil‐nitrogen (N) credits. Variations in N returned to the soil by soybean can significantly affect the amount of fertilizer‐N needed for the subsequent crop. Four soybean MGs (3.5, 4.7, 5.4, and 5.6) were evaluated at optimal and late planting dates in Arkansas. Grain yield was significantly different among MGs in 2016 (P = .0012) and 2017 (P = .0004), with the 4.7 MG consistently yielding the highest at 3,232 kg ha−1. Plant total aboveground N uptake (TNU) increased with increasing grain yield (P = .0167) and was significantly higher when planted in an optimal planting window (P = .0004). The N removed from the cropping system through grain harvest (147–201 kg N ha−1) was significantly different among MGs in 2016 (P

Applying supplemental fertilizer N or inoculating soybean [Glycine max (L.) Merr.] seed with Bradyrhizobium japonicum led to mixed yield responses. We assessed the profitability of seed inoculation, fertilizing with N, or both, across different planting dates using maturity group (MG) IV and MG V soybean cultivars under irrigated conditions. Planting dates ranged from late May to late June at Fayetteville, AR, and Pine Tree, AR, from 2017 to 2019. Urea fertilizer was applied at R2 at 0 or 56 kg N ha−1 using inoculated soybean. Similarly, non‐inoculated treatments ranged from 0, 28, 56, 112, to 168 kg N ha−1. Although fertilizer did increase yield, the response varied by planting date, was small, and only significant at p = .141 and .171 for linear and non‐linear effects of N, respectively. Seed inoculation had a small negative impact (89 kg ha−1) on yield (p = .0157). Using historical prices over the last 10 yr, optimal fertilizer rates ranged from 3.6 to 6.6 kg N ha−1 with an attendant average yield increase of 32 kg ha−1 for early planting and from 2.6 to 4.1 kg N ha−1 for late planting with an average yield gain of 24 kg ha−1. Regardless of timing of planting, the added yield less attendant fertilizer cost resulted in an average net gain of US$7.39 and $6.00 ha−1, for early and late planting, respectively. That net gain was insufficient to cover additional custom fertilizer application charges of $17.30 ha−1. Hence, inoculation and fertilizer N are not recommended.

Drought restrains soybean (Glycine max L. [Merr.]) growth and production, but few tools are available to evaluate differences in drought tolerance among soybean genotypes. Carbon isotope discrimina...

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.

State yield contests offer a unique opportunity to examine the high end of crop productivity. Yield-contest-entered and average-yielding areas on the same or a similar soil can provide large yield and soil property variations to better examine the relationships among various near-surface soil properties and soybean (Glycine max L. [Merr.]) yield. The objective of this study was to evaluate the relationships among a suite of near-surface soil properties and soybean yield across average- and high-yield areas using state yield-contest sites. Multiple regression analyses were conducted to evaluate best-fit relationships among various soil physical, chemical, and biological properties and yield separately for average- and high-yielding areas and for data combined across yield areas. Soybean yield variation was most explained for the high-yield-area dataset (R² = 73%) and less explained for the average-yield-area (R² = 51%) and the combined (R² = 50%) datasets. Extractable soil Ca and S explained the largest proportion of yield variation (37% and 31% of total sum of squares) in the high-yield setting and both were inversely related to yield. A better understanding of the soil environment may be a key component of more frequent attainment of the 6270 kg ha⁻¹ (100 bu acre⁻¹) soybean yield mark. Additional soil properties, beyond those evaluated in this study, may need to be included for a more complete understanding of the soil environment that is associated with high-yield soybean production.

Dynamic crop models that incorporate the effect of environmental variables can potentially explain yield differences associated with location, year, planting date, and cultivars with different growing cycles. Soybean ( Glycine max (L.) Mer.) cultivar coefficients for the DSSAT-CROPGRO model were calibrated from two growing seasons (2012 − 2013) comprising 58 irrigated environments (site × year × planting date combinations) for cultivars within maturity groups (MGs) 3 to 6 using end of season data (yield, seed weight, and seed oil and protein concentration) and previously calibrated phenology coefficients. Model accuracy after calibration of cultivar coefficients by MG (cultivars averaged within a MG) was similar compared to cultivar-specific coefficients. During the subsequent growing season in 2014 (33 environments), the model efficiency (ME) for predicting yield was 0.40, with a root mean square error (RMSE) of 571 kg ha − 1 . The model was less efficient predicting seed number and seed weight (ME = 0.06 and − 0.06, respectively) than yield. The model was able to simulate differences in seed oil concentration across environments and MGs (ME = 0.52), but not protein concentration (ME = − 0.25). The analysis of yield stability had similar slopes for the observed and predicted yield regressions against an observed environmental index (EI) that were only dependent on the MG. Simulated yields were significantly different from the observed when EI > 0, but yield differences in the highest yielding environments were still relatively small (245 to 608 kg ha − 1 ). The results indicate an overall robust model performance in capturing G × E responses with coefficients calibrated by MG.

The difference in yields of cultivars may be causing difference in soybean yield between Japan and the USA. The objective of this study was to identify the effect of the cultivar on dry matter production and to reveal the key factors causing the differences in yield by focusing utilization of solar radiation in recent Japanese and US soybean cultivars. Field experiments were conducted during two seasons in Takatsuki, Japan (34°50′), and in a single season in Fayetteville (36°04′), AR, USA. Five Japanese and 10 US cultivars were observed under near-optimal conditions in order to achieve yields as close to their physiological potential as possible. The seed yield and total aboveground dry matter (TDM) were measured at maturity as long as radiation was intercepted by the canopy. The seed yield ranged from 3.10t ha−1 to 5.91t ha−1. Throughout the three environments, the seed yield of US cultivars was significantly higher than that of Japanese cultivars. The seed yield correlated with the TDM rather than the HI with correlation coefficients from .519 to .928 for the TDM vs. .175 to .800 for the HI, for each of the three environments. The higher TDM of US cultivars was caused by a higher radiation use efficiency rather than higher total intercepted radiation throughout the three environments. The seasonal change in the TDM observed in four cultivars indicated that dry matter productivity was different between cultivars, specifically during the seed-filling period.

Drought stress is a global constraint for crop production, and improving crop tolerance to drought is of critical importance. Because transpiration cools a crop canopy, a cool canopy under drought indicates a genotype still has access to soil moisture. Because measurements of canopy temperature may be increased in scale in field environments, it is particularly attractive for large-scale, phenotypic evaluations. Our objectives were to identify genomic regions associated with canopy temperature (CT) and to identify extreme genotypes for CT. A diverse panel consisting of 345 maturity group IV soybean accessions was evaluated in three environments for CT. Within each environment CT was normalized (nCT) on a scale from 0 to 1. A set of 31,260 polymorphic single nucleotide polymorphisms (SNPs) with a minor allele frequency ≥ 5% was used for association mapping of nCT. Association mapping identified 52 SNPs significantly associated with nCT, and these SNPs likely tagged 34 different genomic regions. Averaged across all environments, eight genomic regions showed significant associations with nCT. Several genes in the identified genomic regions had reported functions related to transpiration or water acquisition including root development, response to abscisic acid, water deprivation, stomatal complex morphogenesis, and signal transduction. Fifteen of the SNPs associated with nCT were coincident with SNPs for canopy wilting. Favorable alleles from significant SNPs may be an important resource for pyramiding genes, and several genotypes were identified as sources of drought-tolerant alleles that could be used in breeding programs for improving drought tolerance.

The largest reported soybean grain yield is approximately three-fold more than the highest reported U.S. average yield. An understanding of yield determination is needed to identify avenues for increasing yield and for defining the yield potential of soybean. To illustrate physiological traits important for yield determination, we used a framework that models yield as the product of seed number (seed m −2 ) and individual seed mass (mass seed ). Developmentally, seed m −2 is determined first and is proportional to the biomass accumulation rate (BAR, g m −2 d −1 ) and the fraction of assimilate allocated to reproductive structures. Seed m −2 is inversely proportional to the individual seed growth rate (ISGR, mg seed −1 d −1 ) where the ISGR represents the minimum amount of assimilate necessary to prevent a flower or pod from aborting. Hence, seed m −2 can be increased by optimizing conditions for crop growth (e.g., radiation interception, stress-free environment, high soil fertility levels) and having a low ISGR. Determination of mass seed occurs later during ontogeny than seed m −2 and can be expressed as the product of the ISGR and the effective seedfilling period (EFP, d). Variation among genotypes for ISGR is quite large and is generally not affected greatly by the environment. There is also genotypic variation in the EFP, but the EFP is decreased by a variety of biotic and abiotic stresses. Our analysis indicates that reaching the potential yield of soybean depends upon high BAR and extending the EFP, and a key factor affecting both of these variables is ensuring non-limiting crop nutrition, especially nitrogen. Strategies for increasing soybean maximum yield include early planting (which extends the EFP), optimizing crop nutrition, minimizing biotic and abiotic stresses, and developing breeding programs tailored for high yield environments. Characterizing physiological traits important for yield with genetic markers offers tools for combining favorable traits for high-yield environments.

Soybean (Glycine max [L.] Merr.) production tradeoffs across maturity group (MG) I through V were analyzed using data on irrigation applied, harvest index (HI), yield, and nitrogen (N) fixed in crop residue at two locations and a range of years. Water use efficiency (WUE), defined as grain yield/water (irrigation and rainfall) and nitrogen (N2) fixation prediction equations allowed analysis of tradeoffs between irrigation use and N2 fixation by MG under both irrigated and non-irrigated conditions. Analysis of partial returns by year and location revealed: (i) no consistent optimal MG choice under irrigated conditions; (ii) that irrigated soybean always outperformed non-irrigated production; and (iii) that non-irrigated MG V soybean had higher yields than earlier MG. Further, WUE, averaged across location and study years, was highest for MGs II and III with less loss in yield potential with restricted irrigation compared to MG IV and V. N2 fixation was inversely related to HI and positively correlated with Y. MG V compared to MG I, II and III thus displayed multi-fold increases in N2 fixation regardless of irrigation. Adding N fertilizer value for a subsequent crop from N2 fixation and potential implications of net GHG emissions to partial returns did not modify optimal MG choice.

Agronomic management practices that maximize monoculture switchgrass (Panicum virgatum L.) yield are generally well understood; however, little is known about corresponding effects of differing switchgrass management practices on near-surface soil properties and processes. The objective of the study was to evaluate the effects of cultivar (“Alamo” and “Cave-in-Rock”), harvest frequency (1- and 2-cuts per year), fertilizer source (poultry litter and commercial fertilizer), and irrigation management (irrigated and non-irrigated) on near-surface soil properties and surface infiltration in a Leadvale silt loam (fine-silty, siliceous, semiactive, thermic, Typic Fragiudult) after four years (2008 through 2011) of consistent management in west-central Arkansas. Irrigating switchgrass increased (P 0.05) and averaged 0.79 mm∙min−1. Results from this study indicate that management decisions to maximize switchgrass biomass production affect soil properties over relatively short periods of time, and further research is needed to develop local best management practices to maximize yield while maintaining or improving soil quality.

Genome-wide association analysis identified 61 SNP markers for canopy wilting, which likely tagged 51 different loci. Based on the allelic effects of the significant SNPs, the slowest and fastest wilting genotypes were identified. Drought stress is a major global constraint for crop production, and slow canopy wilting is a promising trait for improving drought tolerance. The objective of this study was to identify genetic loci associated with canopy wilting and to confirm those loci with previously reported canopy wilting QTLs. A panel of 373 maturity group (MG) IV soybean genotypes was grown in four environments to evaluate canopy wilting. Statistical analysis of phenotype indicated wide variation for the trait, with significant effects of genotype (G), environment (E), and G × E interaction. Over 42,000 SNP markers were obtained from the Illumina Infinium SoySNP50K iSelect SNP Beadchip. After filtration for quality control, 31,260 SNPs with a minor allele frequency (MAF) ≥5% were used for association mapping using the Fixed and random model Circulating Probability Unification (FarmCPU) model. There were 61 environment-specific significant SNP-canopy wilting associations, and 21 SNPs that associated with canopy wilting in more than one environment. There were 34 significant SNPs associated with canopy wilting when averaged across environments. Together, these SNPs tagged 23 putative loci associated with canopy wilting. Six of the putative loci were located within previously reported chromosomal regions that were associated with canopy wilting through bi-parental mapping. Several significant SNPs were located within a gene or very close to genes that had a reported biological connection to transpiration or water transport. Favorable alleles from significant SNPs may be an important resource for pyramiding genes to improve drought tolerance and for identifying parental genotypes for use in breeding programs.

Soybean [Glycine max (L.) Merr.] shoot nitrogen (N) traits are important for seed production and may hold potential for improving seed yield and quality. Field experiments were established to survey shoot N traits in i) plant introductions, ii) a recombinant inbred line (RIL) population, and iii) modern cultivars. A wide range of N concentrations was observed at beginning seed fill for leaves, petioles, and stems and at maturity for stems. Significant genotypic variations in stem N traits were found in modern cultivars and the RIL population. Molecular marker analysis identified multiple loci associated with stem N concentration. Significant relationships between various tissue N traits and seed yield and quality were also observed. These results illustrate the importance of N dynamics in vegetative tissues for soybean yield and seed composition. The observed variation in N traits indicates that selecting for vegetative N traits could potentially increase yield and improve seed quality.

Soybean research has found that nodule traits, especially nodule biomass, are associated with N2 fixation ability. Two genotypes, differing in nodule number per plant and individual nodule weight, KS4895 and Jackson, were mated to create 17 F3- and 80 F5-derived RILs. The population was mapped with 664 informative markers with an average distance of less than 20 cM between adjacent markers. Nodule traits were evaluated in 3-year field trials. Broad-sense heritability for nodule number (no. plant−1), individual nodule dry weight (mg nodule−1), individual nodule size (mm nodule−1), and total nodule dry weight (g plant−1) was 0.41, 0.42, 0.45, and 0.27, respectively. Nodule number was negatively correlated with individual nodule weight and size. Nodule number, individual nodule weight, and size are major components which likely contributed to increased total nodule weight per plant. Composite interval mapping (CIM) identified eight QTLs for nodule number with R2 values ranging from 0.14 to 0.20. Multiple interval mapping (MIM) identified two QTLs for nodule number, one of which was located close to the QTL identified with CIM. Six QTLs for individual nodule weight were detected with CIM, and one QTL was identified with MIM. For nodule size, CIM identified seven QTLs with R2 values ranging from 0.14 to 0.27. Five QTLs for total nodule weight were detected with CIM, one of which was located close to a QTL identified with MIM. These results document the first QTL information on nodule traits in soybean from field experiments utilizing a dense, complete linkage map.

Soybean ( Glycine max [L.] Merr.) N 2 fixation is a primary plant mechanism responsible for meeting plant-N demand during seed development. Nitrogen fixation is recognized as a drought-sensitive mechanism; however, N 2 fixation response to water deficit and N 2 fixation recovery at different reproductive stages are not well documented. We tested the hypothesis that water deficit during late reproductive stages would inhibit N 2 fixation and lead to the breakdown of essential leaf proteins and an inability to recover N 2 fixation. Acetylene reduction activity (ARA) and N redistribution response to a 5-d drought period at flowering (R2), early seed fill (R5), and late seed fill (R6) were evaluated in one genotype (Hendricks, maturity group 0). Control plants maintained high rates of nodule activity until late seed fill. Plants drought stressed at R2 and R5 recovered ARA after rewatering and in some cases had higher nitrogenase activity than control plants during mid-seed fill. Recovery of ARA on plants stressed at R2 and R5 was associated with higher shoot N concentration than control plants at maturity. Drought stress at R6 reduced ARA, and the inability to recover ARA after stress alleviation at R6 resulted in decreased individual seed mass, which was likely caused by an acceleration of leaf N redistribution and a shorter seed-fill period. Results emphasized the importance of soybean N 2 fixation during late seed development on seed yield and that the ability to recover N 2 fixation following drought is dependent upon crop developmental stage.

Slow canopy wilting in soybean has been identified as a potentially beneficial trait for ameliorating drought effects on yield. Previous research identified QTLs for slow wilting from two different biparental populations, and this information was combined with data from three other populations to identify nine QTL clusters for slow wilting on Gm02, Gm05, Gm11, Gm 14, Gm17, and Gm19. The QTL cluster on Gm14 was eliminated because these QTLs appeared to be false positives. In the present research, QTLs from these remaining eight clusters were compiled onto the soybean consensus map for meta-QTL analysis. Five model selection criteria were used to determine the most appropriate number of meta-QTLs at these eight chromosomal regions. For a QTL cluster on Gm02, two meta-QTLs were identified, whereas for the remaining seven QTL clusters the single meta-QTL model was most appropriate. Thus, the analysis identified nine meta-QTLs associated with slow wilting. Meta-analysis decreased the confidence intervals from an average of 21.4 cM for the eight QTL clusters to 10.8 cM for the meta-QTLs. Averaged R2 values of the nine meta-QTLs in eight QTL clusters were 0.13 and ranged from 0.09 to 0.22. Meta-QTLs on Gm11 and Gm19 had the highest R2 values (0.22 and 0.20, respectively).

Delayed wilting is observed in a few unusual soy-bean [ Glycine max (L.) Merr.] genotypes, but the reasons and importance of this trait for conferring agronomic drought tolerance are poorly under-stood. We hypothesized that soybean genotypes with delayed wilting conserve soil moisture by restricting transpiration and that this would be refl ected in decreased radiation use effi ciency (RUE) and/or improved water use effi ciency (WUE). Water conserved when soil moisture was plentiful would be available later in the season when drought is usually more severe. Irrigated fi eld experiments in eight environments com-pared RUE of genotypes known to wilt differently during drought. In addition, we measured stoma-tal conductance, carbon isotope discrimination (CID), volumetric soil-moisture content, stomatal density, and canopy temperature depression. In six of the eight environments, slow-wilting geno-types generally had lower RUE than fast-wilting genotypes, which is consistent with our hypoth-esis. Three of four slow-wilting genotypes had higher soil moisture immediately before irrigation than fast-wilting genotypes, which is also consis-tent with the hypothesis. Genotypic differences in CID (a proxy for WUE) were present but were not consistently related with slow wilting. No geno-typic differences were detected in stomatal con-ductance or canopy temperature. These results suggest that multiple mechanisms involving RUE and WUE could result in soil-water conservation in these diverse genotypes.L.L. Ries, Dep. of Agronomy and Plant Genetics, Univ. of Minne-sota, 1991 Upper Buford Cir., 411 Borlaug Hall, St. Paul, MN 55108; L.C. Purcell and C.A. King, Dep. of Crop, Soil, and Environmental Sciences, Univ. of Arkansas, 1366 W. Altheimer Dr., Fayetteville, AR 72704; T.E. Carter, Jr., USDA-ARS, 3127 Ligon St., Raleigh, NC 27607; J.T. Edwards, Dep. of Plant and Soil Science., Oklahoma State Univ., 368 Agricultural Hall, Stillwater, OK 74078. Received 20 May 2011. *Corresponding author (lpurcell@uark.edu).

Efficient use of N fertilizer has become crucial due to fertilizer costs and the impact of excessive N on the environment. Diagnostic tools for estimating plant N status have an important role in reducing N inputs while maintaining yield. The objective of our study was to quantify corn (Zea mays L.) leaf greenness with a digital camera and image-analysis software and establish the relationship with yield, leafN concentration, and chlorophyll meter (or SPAD, soil plant analysis development) values. In 2008 and 2009, field experiments were conducted at five sites with N treatments ranging from 0 to 336 kg N ha ―1 . At tasseling, the ear leaf was sampled for color analysis and SPAD measurements, and then analyzed for total N. Hue, saturation, and brightness (HSB) values from digital images were processed into a dark green color index (DGCI), which combines HSB values into one composite number. Including calibration disks in images and changing the background color in photographs to pink greatly improved DGCI precision in 2009 over 2008. There was a close relationship (typically r 2 ≥ 0.70) of SPAD and DGCI with leaf N concentration. Within a location, yield increased linearly in most cases with both SPAD (average r 2 = 0.79) and DGCI (average r 2 = 0.78). Digital-image analysis was a simple method of determining corn N status that has potential as a diagnostic tool for determining crop N needs.

Glyphosate and phosphorus (P) fertilizer may alter arbuscular mycorrhizal (AM) fungal infection rates of glyphosate-tolerant cotton, maize, and soybean in low-P soil. Microbial biomass, water soluble P, Mehlich-3 P, and acid and alkaline phosphatase activities were not significantly impacted by glyphosate or P in the greenhouse. Phosphorus fertilization decreased mycorrhizal infection rates in cotton and maize and increased shoot biomass and shoot P in soybean in 2005, and decreased mycorrhizal infection in soybean and increased shoot biomass in cotton and maize and shoot P in all three crops in 2006. In pasteurized soil, glyphosate decreased percent mycorrhizal infection in maize, increased infection in cotton, and did not significantly affect infection in soybean. When soil was not pasteurized, glyphosate did not significantly alter mycorrhizal infection in any crop. The potential for glyphosate to alter AM fungal infection in glyphosate-tolerant plants may depend on whether soil microbial comm...

Genotypic differences for canopy wilting have been reported for soybean [Glycine max (L.) Merr.], but no wilting data have been published, and mechanisms for differences remain unresolved. In fi eld studies in 2002 and 2003, differences for wilting among 19 genotypes were consistent across years. Plant introductions (PI 416937 and PI 471938) were among the slowest wilting genotypes, and breeding lines (93705-34 and 93705-95) were among the fastest wilting. Row spacing (18 vs. 80 cm wide) did not affect wilting, indicating that lateral rooting did not contribute to genotypic differences. In a separate fi eld study, volumetric soil water content at 15- and 50-cm depths was generally greater for slow-wilting PI 416937 than for fast-wilting 93705-95. Wilting for both genotypes responded similarly to soil water content (r 2 = 0.63–0.74). In a growth chamber study, transpiration declined similarly for fast- and slow-wilting genotypes in response to soil water defi cit. Wilting response to soil water was the same for slow-wilting PI 416937 and fast-wilting genotypes 93705-34 and A5959. Slow-wilting 93705-36 began wilting at a lower soil water content than did PI416937, 93705-34, and A5959, indicating that more than one mechanism may be responsible for slow wilting.

Early-maturing soybean [Glycine max (L.) Merr.] cultivars require less irrigation than full-season cultivars and may mature before drought periods most often occur in the midsouthern United States. These cultivars require high plant-population densities for radiation interception and acceptable yields, which increase costs. We hypothesized that seven-leaflet genotypes would have greater leaf area per plant, resulting in more radiation interception and higher yield than near-isogenic three-leaflet genotypes at similar populations. Near-isogenic lines from maturity groups 00 to 1.8 were seeded at rates from 4 to 80 m -2 . The fraction of photosynthetically active radiation (PAR) intercepted by plots was measured using digital imagery and used to estimate cumulative intercepted PAR (CIPAR). Although seven-leaflet isolines had greater leaf area per leaf than three-leaflet isolines, leaf area per plant was similar between three- and seven-leaflet isolines because the three-leaflet isolines had a slightly greater number of main-stem leaves than seven-leaflet isolines. Generally, seven-leaflet isolines had 10 to 21% greater CIPAR at populations

Maize (Zea mays L.) grain yield responds greatly to plant density (D). However, the hybrid-plant density interaction usually found is not well understood. The objective of this work was to analyze responses of different maize hybrids to D considering their biomass plasticity and reproductive partitioning. Responses to D were analyzed during 2 yr in three hybrids with contrasting maturity and plasticity. The relationships between aboveground biomass per plant at maturity (Bp) and D and between grain yield per plant (Yp) and Bp were used to explain hybrid responses to D. Optimum D ranged from 10.3 to 13.7 plants m -2 . The hybrid with the lowest optimum D presented the greatest biomass plasticity and reproductive partitioning. Increasing D produced an increase in biomass production per unit area in all hybrids. Contrarily, a greater harvest index (HI) with increasing D was only observed in the hybrids with the least plasticity. Increments in grain yield with increasing D were, in all cases, more associated with increases in biomass production than with increments in HI. Parameters of the equations B P - D and Yp -Bp were related to optimum D. To validate these relationships, an independent data set was used. Some of these parameters were associated with biomass plasticity and reproductive partitioning and could be used to explain and estimate the responses to D.

Recent changes in management of soybean production in Argentina may have large impacts on the soil water balance and on crop yield response. Changes in this system have included widespread adoption of a no-till management leaving crop residue on the soil surface, intensive cropping rotations (e.g. double cropping of wheat and soybean) so that the soil may not be fully recharged with water at the time of soybean sowing, and the occurrence of high water tables in a number of areas. The objective of this analysis was to assess the need to account for these factors in simulating soybean yields in Argentina. The influence of no-till management was simulated by simply decreasing the soil evaporation estimated for a bare soil by 70%. However, this alteration resulted in an over prediction in yield in many cases when it was assumed that the soil water content had been fully recharged at the initiation of the simulations. The difficulty with assuming a full soil water profile was confirmed when simulated yields were found to match well with observed yields when measured soil water content was used as an input to the model at the beginning of the soybean season. Finally, even with decreased soil evaporation there were still a few cases where simulated yield was less than observed yield. In these cases, a hypothetical water table, which relieved any drought stress once roots reached a depth of 1 m, resulted in yields that more closely matched observations. Overall, these results highlighted the need to estimate well both the influence of crop residue on soil evaporation and the soil water profile at sowing in simulating soybean yields in Argentina.

Drought is by far the most important environmental factor contributing to crop yield loss, especially in soyabean [Glycine max (L.) Merr.] where symbiotic fixation of atmospheric nitrogen (N2) is sensitive to even modest soil water deficits. Decline of N2 fixation with soil drying causes yield reductions due to inadequate N for protein production, which is the critical seed product. In this paper, we present a combined physiological and breeding research effort to develop soyabean lines that have diminished sensitivity of N2 fixation to drought. A preliminary physiological screen was used to identify lines that potentially expressed N2 fixation drought tolerance. One hundred progeny lines derived from a cross between Jackson, a cultivar proven to have N2 fixation tolerance to drought, and KS4895, a high-yielding line, were tested in the screen. Seventeen lines were identified for subsequent yield trials in moderate- and low-yielding rainfed environments. Two lines, found to have higher yields than commercial checks in these environments were then tested in the greenhouse for their N2 fixation activity in drying soil. Nitrogen fixation activity was found to persist at lower soil water contents than exhibited by the sensitive parent. These two soyabean lines offer a genetic resource for increased yields under rainfed conditions as a result of decreased sensitivity of N2 fixation to water deficit