New insights into soybean biological nitrogen fixation

Soybean biological N2 fixation (BNF) relationships with fertilizer N and yield response have been comprehensively reviewed in the scientific literature. However, the study of the N-gap between N uptake and N supplied by N2 fixation, and the partial N balance (fixed N in aboveground biomass – N seeds) needs further investigation. Therefore, the goals of this synthesis–analysis were to (i) quantify seed production per unit of fixed N under different amounts of N derived from the atmosphere (NDFA, %), (ii) study the N-gap and explore limitations of N2 fixation (kg ha–1) for satisfying plant N demand, and (iii) calculate a partial N balance for soybean and determine its relationship with the N2 fixation process. Data was gathered from 1955 through 2016 using studies reporting BNF, seed yield, and plant N uptake (n = 733 data points). The main outcomes of this review were (i) as NDFA increased, seed production per N2 fixation decreased (from 0.033 to 0.017 Mg yield kg–1 N from low, 28%, to high, 80%, NDFA); (ii) N-gap increased faster when NDFA values were above 80% and after plant N content was above 370 kg N ha–1 suggesting that the crop needs additional N for coping yield potential; and (iii) when excluding roots, the partial N balance calculation revealed negative values across all NDFA levels. Future studies should consider a holistic approach to quantify the contribution of BNF in overall N cycling, including N contribution from roots, and to better understand the soil × plant × rhizobia interactions.EEA OliverosFil: Ciampitti, Ignacio A. Kansas State University. Department of Agronomy; Estados UnidosFil: Salvagiotti, Fernando. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Oliveros. Departamento de Agronomía; Argentin

Historical Synthesis-Analysis of Changes in Grain Nitrogen Dynamics in Sorghum

Citation: Ciampitti IA and Prasad PVV (2016) Historical Synthesis-Analysis of Changes in Grain Nitrogen Dynamics in Sorghum. Front. Plant Sci. 7:275. doi: 10.3389/fpls.2016.00275Unraveling the complexity underpinning nitrogen (N) use efficiency (NUE) can be physiologically approached via examining grain N sources and N internal efficiency (NIE) (yield to plant N content ratio). The main objective of this original research paper is to document and understand sorghum NUE and physiological mechanisms related to grain N dynamics. The study of different grain N sources, herein defined as the reproductive-stage shoot N remobilization (Remobilized N), reproductive-stage whole-plant N content (Reproductive N), and vegetative-stage whole-plant N content (Vegetative N), was pursued with the goal of synthesizing scientific literature for sorghum [Sorghum bicolor (L.) Moench] crop. A detailed literature review was performed and summarized on sorghum NUE (13 studies; >250 means) with three Eras, defined by the year of the study, named as Old Era (1965–1980); Transient Era (1981–2000); and New Era (2001–2014). The most remarkable outcomes from this synthesis were: (1) overall historical (1965–2014) cumulative yield gain was >0.5 Mg ha-1 (yields >7 Mg ha-1); (2) NIE did not change across the same time period; (3) grain N concentration (grain %N) accounted for a large proportion (63%) of the variation in NIE; (4) NIE increased as grain %N diminished, regardless of the Eras; (5) Remobilized N was strongly (>R2 0.6) and positively associated with Vegetative N, presenting a unique slope across Eras; and (6) a trade-off was documented for the Remobilized N and Reproductive N (with large variation, <R2) relationship, suggesting complex regulation processes governing N forces. Improvements in NUE are subjected to the interplay between N supply (N from non-reproductive organs) and grain N demand, sink- (driven by grain number) and source-modulated (via restriction of grain N demand)

Benchmarking Nutraceutical Soybean Composition Relative to Protein and Oil

The aim of this study was to explore relationships between protein, oil, and seed weight with seed nutraceutical composition, focused on total isoflavone (TI) and total tocopherol (TT) contents across genotypic and environmental combinations in soybean. We conducted a synthesis-analysis of peer-reviewed published field studies reporting TI, TT, protein, oil, and seed weight (n = 1,908). The main outcomes from this synthesis-analysis were: (i) relationship of TI-to-protein concentration was positive, though for the upper boundary, TI decreases with increases in protein; (ii) relationship of TT-to-oil concentration was positive, but inconsistent when oil was expressed in mg per seed; and (iii) as seed weight increased, TI accumulation was less than proportional relative to protein concentration and TT decreased more proportional relative to oil concentration. Association between nutraceuticals and protein, oil, and seed weight for soybean reported in the present study can be used as a foundational knowledge for soybean breeding programs interested on predicting and selecting enhanced meal isoflavone and/or oil tocopherol contents.Instituto de Fisiología y Recursos Genéticos VegetalesFil: Carrera, Constanza Soledad. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Fisiología y Recursos Genéticos Vegetales; ArgentinaFil: Carrera, Constanza Soledad. Consejo Nacional de Investigaciones Científicas y Técnicas. Unidad de Estudios Agropecuarios (UDEA); ArgentinaFil: Carrera, Constanza Soledad. Kansas State University. Throckmorton Plant Science Center. Department of Agronomy; Estados UnidosFil: Salvagiotti, Fernando. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Oliveros; ArgentinaFil: Salvagiotti, Fernando. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Ciampitti, Ignacio A. Kansas State University. Throckmorton Plant Science Center. Department of Agronomy; Estados Unido

Impact of high temperature stress on floret fertility and individual grain weight of grain sorghum: sensitive stages and thresholds for temperature and duration

Citation: Prasad PVV, Djanaguiraman M, Perumal R and Ciampitti IA (2015) Impact of high temperature stress on floret fertility and individual grain weight of grain sorghum: sensitive stages and thresholds for temperature and duration. Front. Plant Sci. 6:820. doi: 10.3389/fpls.2015.00820Sorghum [Sorghum bicolor (L.) Moench] yield formation is severely affected by high temperature stress during reproductive stages. This study pursues to (i) identify the growth stage(s) most sensitive to high temperature stress during reproductive development, (ii) determine threshold temperature and duration of high temperature stress that decreases floret fertility and individual grain weight, and (iii) quantify impact of high daytime temperature during floret development, flowering and grain filling on reproductive traits and grain yield under field conditions. Periods between 10 and 5 d before anthesis; and between 5 d before- and 5 d after-anthesis were most sensitive to high temperatures causing maximum decreases in floret fertility. Mean daily temperatures >25°C quadratically decreased floret fertility (reaching 0% at 37°C) when imposed at the start of panicle emergence. Temperatures ranging from 25 to 37°C quadratically decreased individual grain weight when imposed at the start of grain filling. Both floret fertility and individual grain weights decreased quadratically with increasing duration (0–35 d or 49 d during floret development or grain filling stage, respectively) of high temperature stress. In field conditions, imposition of temperature stress (using heat tents) during floret development or grain filling stage also decreased floret fertility, individual grain weight, and grain weight per panicle

Drought-Tolerant Corn Hybrids Yield More in Drought-Stressed Environments with No Penalty in Non-stressed Environments

Citation: Adee, E., Roozeboom, K., Balboa, G. R., Schlegel, A., & Ciampitti, I. A. (2016). Drought-Tolerant Corn Hybrids Yield More in Drought-Stressed Environments with No Penalty in Non-stressed Environments. Frontiers in Plant Science, 7, 9. doi:10.3389/fpls.2016.01534The potential benefit of drought-tolerant (DT) corn (Zea mays L.) hybrids may depend on drought intensity, duration, crop growth stage (timing), and the array of drought tolerance mechanisms present in selected hybrids. We hypothesized that corn hybrids containing DT traits would produce more consistent yields compared to non-DT hybrids in the presence of drought stress. The objective of this study was to define types of production environments where DT hybrids have a yield advantage compared to non-DT hybrids. Drought tolerant and non-DT hybrid pairs of similar maturity were planted in six site-years with different soil types, seasonal evapotranspiration (ET), and vapor pressure deficit (VPD), representing a range of macro-environments. Irrigation regimes and seeding rates were used to create several micro-environments within each macro-environment. Hybrid response to the range of macro and micro-environmental stresses were characterized in terms of water use efficiency, grain yield, and environmental index. Yield advantage of DT hybrids was positively correlated with environment ET and VPD. Drought tolerant hybrids yielded 5 to 7% more than non-DT hybrids in high and medium ET environments (>430 mm ET), corresponding to seasonal VPD greater than 1200 Pa. Environmental index analysis confirmed that DT hybrids were superior in stressful environments. Yield advantage for DT hybrids appeared as yield dropped below 10.8 Mg ha(-1) and averaged as much as 0.6-1 Mg ha(-1) at the low yield range. Hybrids with DT technology can offer a degree of buffering against drought stress by minimizing yield reduction, but also maintaining a comparable yield potential in high yielding environments. Further studies should focus on the physiological mechanisms presented in the commercially available corn drought tolerant hybrids

Mid-Season High-Resolution Satellite Imagery for Forecasting Site-Specific Corn Yield

Citation: Peralta, N.R.; Assefa, Y.; Du, J.; Barden, C.J.; Ciampitti, I.A. Mid-Season High-Resolution Satellite Imagery for Forecasting Site-Specific Corn Yield. Remote Sens. 2016, 8, 848.This technical note presents the first Sentinel-2 data service platform for obtaining atmospherically-corrected images and generating the corresponding value-added products for any land surface on Earth (http://s2.boku.eodc.eu/). Using the European Space Agency’s (ESA) Sen2Cor algorithm, the platform processes ESA’s Level-1C top-of-atmosphere reflectance to atmospherically-corrected bottom-of-atmosphere (BoA) reflectance (Level-2A). The processing runs on-demand, with a global coverage, on the Earth Observation Data Centre (EODC), which is a public-private collaborative IT infrastructure in Vienna (Austria) for archiving, processing, and distributing Earth observation (EO) data (http://www.eodc.eu). Using the data service platform, users can submit processing requests and access the results via a user-friendly web page or using a dedicated application programming interface (API). Building on the processed Level-2A data, the platform also creates value-added products with a particular focus on agricultural vegetation monitoring, such as leaf area index (LAI) and broadband hemispherical-directional reflectance factor (HDRF). An analysis of the performance of the data service platform, along with processing capacity, is presented. Some preliminary consistency checks of the algorithm implementation are included to demonstrate the expected product quality. In particular, Sentinel-2 data were compared to atmospherically-corrected Landsat-8 data for six test sites achieving a R2 = 0.90 and Root Mean Square Error (RMSE) = 0.031. LAI was validated for one test site using ground estimations. Results show a very good agreement (R2 = 0.83) and a RMSE of 0.32 m2/m2 (12% of mean value)

Mid-Season High-Resolution Satellite Imagery for Forecasting Site-Specific Corn Yield

A timely and accurate crop yield forecast is crucial to make better decisions on crop management, marketing, and storage by assessing ahead and implementing based on expected crop performance. The objective of this study was to investigate the potential of high-resolution satellite imagery data collected at midgrowing season for identification of within-field variability and to forecast corn yield at different sites within a field. A test was conducted on yield monitor data and RapidEye satellite imagery obtained for 22 cornfields located in five different counties (Clay, Dickinson, Rice, Saline, and Washington) of Kansas (total of 457 ha). Three basic tests were conducted on the data: (1) spatial dependence on each of the yield and vegetation indices (VIs) using Moran’s I test; (2) model selection for the relationship between imagery data and actual yield using ordinary least square regression (OLS) and spatial econometric (SPL) models; and (3) model validation for yield forecasting purposes. Spatial autocorrelation analysis (Moran’s I test) for both yield and VIs (red edge NDVI = NDVIre, normalized difference vegetation index = NDVIr, SRre = red-edge simple ratio, near infrared = NIR and green-NDVI = NDVIG) was tested positive and statistically significant for most of the fields (p < 0.05), except for one. Inclusion of spatial adjustment to model improved the model fit on most fields as compared to OLS models, with the spatial adjustment coefficient significant for half of the fields studied. When selected models were used for prediction to validate dataset, a striking similarity (RMSE = 0.02) was obtained between predicted and observed yield within a field. Yield maps could assist implementing more effective site-specific management tools and could be utilized as a proxy of yield monitor data. In summary, high-resolution satellite imagery data can be reasonably used to forecast yield via utilization of models that include spatial adjustment to inform precision agricultural management decisions.Sociedad Argentina de Informática e Investigación Operativ

Exploring nitrogen limitation for historical and modern soybean genotypes

The United States (USA) and Argentina (ARG) account for over 50% of the global soybean [Glycine max (L.) Merr.] production. Soybean N demand is partially met (50–60%) by the biological nitrogen fixation (BNF) process; however, an unanswered scientific knowledge gap exists on the ability of the BNF process to fulfill soybean N demand at varying yield levels. The overall objective of this study is to explore the potential N limitation using different N strategies for historical and modern soybean genotypes. Four field experiments were conducted during 2016 and 2017 growing seasons in Kansas (USA) and Santa Fe (ARG). Twenty-one historical and modern soybean genotypes released from the 1980s to 2010s were tested under three N treatments: (i) control, without N application (Zero-N); (ii) 56 kg N ha–1 applied at R3-R4 growth stages (Late-N); and (iii) 670 kg ha–1 equally split at planting, R1, and R3–R4 growth stages (Full-N). Historical soybean yield gains, from the 1980s to 2010s, were 29% in the USA and 21% in ARG. Following the yield trend, seed N content increased for modern genotypes in parallel to the reduction on seed protein concentration. Regarding N treatments, Full-N produced 12% yield increase in the USA and 4% in ARG. Yield improvement was mainly related to increases in aboveground biomass, seed number (genotype effect), and to a lesser extent, to seed weight (N effect). This study suggests a potential N limitation for soybean, although there are still questions about the way in which N must be provided to the plant.EEA OliverosFil: Ortez, O.A. Kansas State University. Department of Agronomy; Estados UnidosFil: Salvagiotti, Fernando. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Oliveros. Departamento de Agronomía; ArgentinaFil: Enrico, Juan Martin. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Oliveros. Departamento de Agronomía; ArgentinaFil: Prasad, P.V.V. Kansas State University. Department of Agronomy; Estados Unidos. USDA-ARS. Center for Grain and Animal Health Research; Estados UnidosFil: Armstrong, P. USDA-ARS. Center for Grain and Animal Health Research; Estados UnidosFil: Ciampitti, Ignacio A. Kansas State University. Department of Agronomy; Estados Unido

Mid-Season High-Resolution Satellite Imagery for Forecasting Site-Specific Corn Yield

A timely and accurate crop yield forecast is crucial to make better decisions on crop management, marketing, and storage by assessing ahead and implementing based on expected crop performance. The objective of this study was to investigate the potential of high-resolution satellite imagery data collected at midgrowing season for identification of within-field variability and to forecast corn yield at different sites within a field. A test was conducted on yield monitor data and RapidEye satellite imagery obtained for 22 cornfields located in five different counties (Clay, Dickinson, Rice, Saline, and Washington) of Kansas (total of 457 ha). Three basic tests were conducted on the data: (1) spatial dependence on each of the yield and vegetation indices (VIs) using Moran’s I test; (2) model selection for the relationship between imagery data and actual yield using ordinary least square regression (OLS) and spatial econometric (SPL) models; and (3) model validation for yield forecasting purposes. Spatial autocorrelation analysis (Moran’s I test) for both yield and VIs (red edge NDVI = NDVIre, normalized difference vegetation index = NDVIr, SRre = red-edge simple ratio, near infrared = NIR and green-NDVI = NDVIG) was tested positive and statistically significant for most of the fields (p < 0.05), except for one. Inclusion of spatial adjustment to model improved the model fit on most fields as compared to OLS models, with the spatial adjustment coefficient significant for half of the fields studied. When selected models were used for prediction to validate dataset, a striking similarity (RMSE = 0.02) was obtained between predicted and observed yield within a field. Yield maps could assist implementing more effective site-specific management tools and could be utilized as a proxy of yield monitor data. In summary, high-resolution satellite imagery data can be reasonably used to forecast yield via utilization of models that include spatial adjustment to inform precision agricultural management decisions.Sociedad Argentina de Informática e Investigación Operativ

Soja de alto rendimiento: ganancia genética y limitación por nitrógeno

La mejora genética del rendimiento de soja desde la década de 1980 hasta la del 2010 representó 30% promediando en sitios ubicados en los Estados Unidos y Argentina. Para todas las pocas de liberación, la fertilización ad-libitum con N generó hasta un 20% de aumento en rendimientos en EE.UU., y un 5% en Argentina. Los resultados sugieren que soja de alta producción estaría limitada por N para expresar altos rendimientos y contenidos de proteínas, aunque quedan incógnitas acerca de la forma en que este N deba ser provisto. Cabe aclarar que el objetivo del ensayo no es recomendar aplicaciones de fertilizante nitrogenado en soja, pero entender mejor si el N es un factor limitante en el cultivo.EEA OliverosFil: Ortez, O.A. Kansas State University. Department of Agronomy; Estados UnidosFil: Salvagiotti, Fernando. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Oliveros; ArgentinaFil: Enrico, Juan Martin. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Oliveros; ArgentinaFil: Ciampitti, Ignacio A. Kansas State University. Department of Agronomy; Estados Unido