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Soybean is an essential crop to fight global food insecurity and is of great economic importance around the world. Along with genetic improvements aimed at boosting yield, soybean seed composition also changed. Since conditions during crop growth and development influences nutrient accumulation in soybean seeds, remote sensing offers a unique opportunity to estimate seed traits from the standing crops. Capturing phenological developments that influence seed composition requires frequent satellite observations at higher spatial and spectral resolutions. This study introduces a novel spectral fusion technique called multiheaded kernel-based spectral fusion (MKSF) that combines the higher spatial resolution of PlanetScope (PS) and spectral bands from Sentinel 2 (S2) satellites. The study also focuses on using the additional spectral bands and different statistical machine learning models to estimate seed traits, e.g., protein, oil, sucrose, starch, ash, fiber, and yield. The MKSF was trained using PS and S2 image pairs from different growth stages and predicted the potential VNIR1 (705 nm), VNIR2 (740 nm), VNIR3 (783 nm), SWIR1 (1610 nm), and SWIR2 (2190 nm) bands from the PS images. Our results indicate that VNIR3 prediction performance was the highest followed by VNIR2, VNIR1, SWIR1, and SWIR2. Among the seed traits, sucrose yielded the highest predictive performance with RFR model. Finally, the feature importance analysis revealed the importance of MKSF-generated vegetation indices from fused images. [ABSTRACT FROM AUTHOR]

SUMMARY: Global warming, climate change, and industrial pollution are altering our environment subjecting plants, microbiomes, and ecosystems to an increasing number and complexity of abiotic stress conditions, concurrently or sequentially. These conditions, termed, "multifactorial stress combination" (MFSC), can cause a significant decline in plant growth and survival. However, the impacts of MFSC on reproductive tissues and yield of major crop plants are largely unknown. We subjected soybean (Glycine max) plants to a MFSC of up to five different stresses (water deficit, salinity, low phosphate, acidity, and cadmium), in an increasing level of complexity, and conducted integrative transcriptomic‐phenotypic analysis of their reproductive and vegetative tissues. We reveal that MFSC has a negative cumulative effect on soybean yield, that each set of MFSC condition elicits a unique transcriptomic response (that is different between flowers and leaves), and that selected genes expressed in leaves or flowers of soybean are linked to the effects of MFSC on different vegetative, physiological, and/or reproductive parameters. Our study identified networks and pathways associated with reactive oxygen species, ascorbic acid and aldarate, and iron/copper signaling/metabolism as promising targets for future biotechnological efforts to augment the resilience of reproductive tissues of major crop plants to MFSC. In addition, we provide unique phenotypic and transcriptomic datasets for dissecting the mechanistic effects of MFSC on the vegetative, physiological, and reproductive processes of a crop plant. [ABSTRACT FROM AUTHOR]

Aims: Urea is the most commonly used N fertilizer worldwide, but can easily volatilize as ammonia and be lost from the soil. Enhanced Efficiency Fertilizers (EEFs) have been developed to increase nutrient use efficiency, reduce N losses, and increase crop yield. Methods: The efficacy of different EEF urea technologies was compared to untreated urea when surface applied to no-till maize (Zea mays L.) in three field seasons. Treatments included untreated urea, urea-ammonium nitrate (UAN), polymer-coated urea (ESN and Duration), urea treated with urease inhibitors (Agrotain) and urea treated with both urease and nitrification inhibitors (Nutrisphere and SuperU). Ammonia volatilization, soil nitrogen content and maize yield were determined in order to evaluate EEFs. Results: Volatilization losses, measured for 25 days after fertilization (DAF) in the first year, and 25 and 82 DAF in the second and third year, differed among products and years. Polymer-coated urea and urea treated with urease inhibitor effectively reduced ammonia volatilization peaks and resulted in a consequent decrease of ammonia losses at 25 DAF and 82 DAF in most years. The double inhibitor-treated urea (Nutrisphere and SuperU) showed similar ammonia losses as untreated urea. Overall, EEFs maintained maize grain yield produced with untreated urea, except for one polymer-coated urea product which increased yields. Conclusions: The efficacy of EEF in mitigating NH3 losses varied with precipitation and other environmental conditions. We found that the polymer-coated urea presented the best performance reducing ammonia losses and maintaining or even increasing maize grain yields in this study. [ABSTRACT FROM AUTHOR]

Episodes of prolonged drought coupled with heat waves (i.e. drought and heat combination) can have a devastating impact on agricultural production and crop yield. It is therefore not surprising that improving tolerance to drought and heat combination has been a major goal for breeders and biotech companies. Although much is known about the physiological and molecular responses of vegetative tissues to a combination of drought and heat stress, less is known about the impact of this stress combination on yield and different yield components. Here, we used a meta‐analysis approach to synthesize results from over 120 published case studies of crop responses to combined drought and heat stress. Our findings reveal that drought and heat stress combination significantly impacts yield by decreasing harvest index, shortening the life cycle of crops, and altering seed number, size and composition. Furthermore, these impacts are more severe when the stress combination is applied during the reproductive stage of plants. We further identify differences in how legumes and cereals respond to the stress combination and reveal that utilizing C3 or C4 metabolism may not provide an advantage to plants during stress combinations. Taken together our study highlights a need to focus future studies, as well as breeding efforts, on crop responses to drought and heat combination at the reproductive stage of different crop species. [ABSTRACT FROM AUTHOR]

Accurate assessment of crop water uptake (WU) and water use efficiency (WUE) is not easy under field conditions. Carbon isotope discrimination (Δ13C) has been used as a surrogate of WUE to examine crop yield responses to drought and its relationship with WU and WUE. A 2‐yr study was conducted (i) to characterize genotypic variation in Δ13C, grain yield, and other physiological parameters in common bean (Phaseolus vulgaris L.) parental lines, and (ii) to examine the relationships between grain Δ13C, shoot Δ13C, and grain yield under well‐watered and terminal drought stress conditions. All measured plant traits were strongly influenced by water availability, and genotypic differences in grain yield, shoot Δ13C, and grain Δ13C were found in both watered and terminal drought stress environments. The parental lines were classified into two drought adaptation groups, drought resistant and drought sensitive, based on a yield drought index. High yields under drought conditions were related to (i) greater water uptake, as indicated by high Δ13C in genotypes previously shown to have deeper roots (e.g., SEA 5 and BAT 477), and (ii) increased WUE, denoted by lower Δ13C and greater pod harvest index (PHI) (e.g., SER 16). Coupling of Δ13C measurements with measured yield and yield components analyses, such as PHI, provided an avenue to distinguish different physiological traits among drought resistant genotypes underlying adaptation to water deficit stress. [ABSTRACT FROM AUTHOR]

Maize (Zea mays) plants exhibit altered carbon partitioning under nitrogen (N) deficiency, but the mechanisms by which N availability affects sugar export out of leaves and transport into developing ears remain unclear. Maize was grown under field conditions with different N supply. Plant growth, sugar movement, and starch turnover in source or sink tissues were investigated at silking and 20 or 21 days after silking. Nitrogen deficiency stunted plant growth and grain yield compared with N-sufficient plants, and resulted in greater starch concentrations in leaves due to more as well as larger starch granules in bundle sheath cells. Transmission electron microscopy revealed an open symplastic pathway for sucrose movement in N-deficient leaves, while the expression levels of transporters responsible for sucrose efflux and phloem loading were lower than in N-sufficient leaves. Nonetheless, greater starch concentrations in the apical cob portion of N-deficient plants implied sufficient carbon supply relative to the diminished sink strength (decreased kernel number and weight). Together with the high sugar concentrations in the developing kernels, the results indicated that reduced sink capacity and sugar utilization during grain filling may limit the yield in N-deficient plants, which in turn imposes a feedback inhibition on sugar export from leaves. [ABSTRACT FROM AUTHOR]

High biomass sorghum [Sorghum bicolor (L.) Moench] could potentially produce high yields in the midwestern United States with minimal fertilizer inputs. However, little is known about the yield response, N uptake, nitrogen use efficiency (NUE), and nitrogen recovery efficiency (NRE) of high biomass sorghum (HBS) at varying N fertilization rates when grown for lignocellulosic ethanol. The objectives of this 2-yr study were to determine the effect of five N rates (0, 56, 112, 168, 224 kg N-1) on the dry matter (DM) yield and lignocellulosic ethanol yield (LEY), and the NRE and NUE of two HBS varieties in the midwestern United States. The two varieties responded similarly for most measured parameters. Total DM yield averaged 13.1 Mg-1 and estimated LEY averaged 5519 L-1 across N rates when grown in central Missouri. Nitrogen rates between 56 and 224 kg N -1 resulted in similar DM yield and LEY in 2010, and there were no yield differences among N rates ranging from 0 to 224 kg N-1 in 2011. The greatest N removal in DM was at or above 56 kg N-1. Nitrogen recovery efficiency and NUE differed by year, where low rainfall and a shortened growing season in the second year resulted in reduced NRE and NUE. Lack of NUE and DM yield differences at N rates above 56 kg N-1 indicates the potential for producing high biomass sorghum with minimal amounts of fertilizer N in the Midwest. [ABSTRACT FROM AUTHOR]

Maize (Zea mays L.) grain yield is considered to be highly associated with carbohydrate dynamics in leaves and developing ears during the critical period bracketing silking. Carbohydrate changes are sensitive to variation in nitrogen (N) availability, yet a comprehensive analysis of the N effect on various carbohydrate concentrations around silking remains elusive. A 2-yr field study was conducted to investigate grain yield, N uptake, ear dry matter and carbohydrate concentrations in ear-leaves and whole ears (prior to silking) and kernels (after silking) of maize grown with 0, 150, and 300 kg N ha-1. Greater N availability increased maize shoot dry matter and N content at silking and physiological maturity, as well as grain yield. While N had little effect on ear-leaf glucose concentration, sucrose concentration increased but starch concentration decreased with increasing N, regardless of sampling time. Prior to silking, glucose and fructose concentrations in the developing ear responded positively to increasing N availability, but sucrose and starch concentrations declined. In growing kernels shortly after silking, glucose and fructose concentrations in N fertilized treatments were significantly lower than those in the zero-N treatment. In contrast, a significant increase in kernel starch concentration was found in response to 300 kg N ha-1. These observations point to an important role of the carbohydrate composition of unpollinated ears prior to silking with regard to kernel set and post-silking kernel starch accumulation, and thus final crop yield. [ABSTRACT FROM AUTHOR]

Growing conditions in the U.S. Midsouth allow for large soybean [Glycine max L. (Merr.)] yields under irrigation, but there is limited information on planting dates (PD) and maturity group (MG) choices to aid in cultivar selection. Analysis of variance across eight (2012) and 10 (2013) locations, four PD, and 16 cultivars (MG 3-6), revealed that the genotype by environment (GxE) interaction accounted for 38 to 22% of the total yield variability. Stability-analysis techniques and probability of low yields were used to investigate this interaction. Planting dates were grouped within early- and late-planting systems. Results showed that MG 4 and 5 cultivars in early-planting systems had the largest average yields, whereas for late-planting systems, late MG 3 to late MG 4 cultivars had the largest yields. Least square means by MG within planting systems at each environment showed that MG 4 cultivars had the greatest yields or were not significantly different from the MG with the greatest yields in 100% of the environments for both early- and late-planting systems. Yields of MG 5 cultivars were similar to those of MG 4 in 100% of the environments with an early planting but only in 20% of the environments with a late planting. The MG 3 cultivars were the best second choice for late plantings, with similar yields to MG 4 cultivars in 55 to 75% of the environments. These results have profound implications for MG recommendations in irrigated soybean in the U.S. Midsouth and indicate the need to reconsider common MG recommendations. [ABSTRACT FROM AUTHOR]

Highlights: [•] Diurnal response of maize photosynthesis, nonstructural carbohydrates and ear dry matter were examined in response to N. [•] Nitrogen application increased plant N uptake, yield, leaf area, chlorophyll content, and soluble protein concentration. [•] Nitrogen application increased photosynthetic rates only during periods of high light intensities in the diurnal cycle. [•] Clear diurnal pattern of leaf sucrose and starch concentrations were found. [Copyright &y& Elsevier]

Agricultural management at field-scale is critical for improving yield to address global food security, as providing enough food for the world's growing population has become a wicked problem for both scientists and policymakers. County- or regional-scale data do not provide meaningful information to farmers who are interested in field-scale yield forecasting for effective and timely field management. No studies directly utilized raw satellite imagery for field-scale yield prediction using deep learning. The objectives of this paper were twofold: (1) to develop a raw imagery-based deep learning approach for field-scale yield prediction, (2) investigate the contribution of in-season multitemporal imagery for grain yield prediction with hand-crafted features and WorldView-3 (WV) and PlanetScope (PS) imagery as the direct input, respectively. Four WV-3 and 25 PS imagery collected during the growing season of soybean were utilized. Both 2-dimensional (2D) and 3-dimensional (3D) convolution neural network (CNN) architectures were developed that integrated spectral, spatial, temporal information contained in the satellite data. For comparison, hundreds of carefully selected spectral, spatial, textural, and temporal features that are optimal for crop growth monitoring were extracted and fed into the same deep learning model. Our results demonstrated that (1) deep learning was able to predict yield directly using raw satellite imagery to the extent that was comparable to feature-fed deep learning approaches; (2) both 2D and 3D CNN models were able to explain nearly 90% variance in field-scale yield; (3) limited number of WV-3 outperformed multi-temporal PS data collected during entire growing season mainly attributed to RedEdge and SWIR bands available with WV-3; and (4) 3D CNN increased the prediction power of PS data compared to 2D CNN due to its ability to digest temporal features extracted from PS data. [ABSTRACT FROM AUTHOR]

• First report on content of 11 mineral nutrients in shoot of high biomass sorghum grown across a range of N fertilizer rates. • Nitrogen treatment influence on concentrations of macro- and micronutrients in leaf and stem tissues varied among nutrients. • Consistent with a growth dilution effect, concentrations of most nutrients were greater in the drier than in the wetter year. • Nitrogen fertilization increased shoot content of most nutrients despite a varied response on tissue concentrations. High biomass sorghum (HBS) (Sorghum bicolor (L.) Moench) is an emerging biofuel feedstock that can produce high yields in the Midwestern U.S. and is known for high nitrogen (N) use efficiency at low N fertilizer input. This two-year study examined the effect of five N fertilization treatments (0, 56, 112, 168, 224 kg N ha−1) on the uptake of 11 macro- and micronutrients by photoperiod sensitive HBS. Leaf, stem, and shoot nutrient concentrations and contents were determined and nutrient relationships examined. Few consistent relationships existed across all nutrients, but concentrations were generally greater in the drier and shorter growing season with less dry matter (DM) accumulation, and, when present, N treatment response often resulted in decreased concentrations with increasing N. Inversely, the amount of nutrients present in the shoot generally were associated with greater DM production in the wetter year with longer growing season. Content of nutrients in the shoot did not increase beyond the 56 kg N ha−1 treatment in the wetter year, but there was a nutrient uptake response to higher N rates in the drier crop year. This suggests more so than other nutrients that N was more of a limitation that year. Even though shoot mineral nutrient removal is often similar at higher N treatments, applying a minimal N fertilizer rate results in minimized tissue mineral concentrations, thereby creating an optimal crop management balance of targeting high crop yield, low concentrations to optimize conversion efficiency, and sustainable agronomic management. [ABSTRACT FROM AUTHOR]

• Breeding for high WUE will not limit yield response to elevated CO 2. • The high WUE cultivar showed lower leaf level photosynthetic capacity than low WUE cultivar. • The high WUE cultivar compensate the lower photosynthetic activity with a bigger leaf area. • High yield response to elevated CO2 was also associated with high HI. The predicted increase in atmospheric CO 2 concentration [CO 2 ] is expected to enhance photosynthesis and seed yield in crops such as soybean [ Glycine max (L.) Merr.]. However, future breeding for high water use efficiency (WUE) could interfere with the amount of carbon (C) fixed by leaves and seed mineral composition under elevated [CO 2 ] due to lower stomatal conductance (g s). In the present study, two genotypes with contrasting WUE were grown in open top chambers (OTC) under ambient (410 ppm; a[CO 2 ]) and elevated (610 ppm; e[CO 2 ]). In order to test performance of both cultivars to changing CO 2 conditions, growth, photosynthetic performance (leaf and canopy level) and seed mineral composition were analyzed. The low WUE genotype had a greater response to e[CO 2 ] in terms of leaf daily photosynthetic C gain due to greater g s , which was compensated in the high WUE genotype by an increase in leaf area (LA). However, in the low WUE genotype, improved daily photosynthetic C gain did not translate into greater biomass or seed yield [CO 2 ] response compared to the high WUE genotype, suggesting better assimilate partitioning by the high WUE genotype. In terms of seed composition, the high WUE genotype generally had lower mineral concentrations at e[CO 2 ] compared to a[CO 2 ], but greater total amounts of nutrient (due to higher seed yield) under e[CO 2 ] compared to the low WUE genotype. Findings presented here highlight importance of genetic variation in soybean response to future atmospheric [CO 2 ] which should be considered when breeding for future climates. [ABSTRACT FROM AUTHOR]