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Global warming, climate change, and environmental pollution present plants with unique combinations of different abiotic and biotic stresses. Although much is known about how plants acclimate to each of these individual stresses, little is known about how they respond to a combination of many of these stress factors occurring together, namely a multifactorial stress combination. Recent studies revealed that increasing the number of different co-occurring multifactorial stress factors causes a severe decline in plant growth and survival, as well as in the microbiome biodiversity that plants depend upon. This effect should serve as a dire warning to our society and prompt us to decisively act to reduce pollutants, fight global warming, and augment the tolerance of crops to multifactorial stress combinations. A multifactorial stress combination occurs when more than two to three abiotic and/or biotic stress factors simultaneously impact a plant. Global warming, climate change, and industrial pollution could result in an increase in the frequency, complexity, and intensity of multifactorial stress combinations impacting plants, soils, and microbial communities. With the increase in the number of factors simultaneously impacting plants, the survival and growth of plants declines, even if the levels of each of these individual stresses is very low. The response of plants to a multifactorial stress combination is unique and involves many transcripts and genes that are not altered in response to each of the different stresses applied individually. The harmful effects of a multifactorial stress combination on the survival and growth of plants, different soil properties, and diversity of microbial communities should serve as a dire warning to our society and prompt us to act drastically to reduce the different sources of multifactorial stresses in our environment. [ABSTRACT FROM AUTHOR]

Post-silking nitrogen (N) fluxes from vegetative tissues to developing kernels affect both N use efficiency (NUE) and grain yield in maize, while the impacts of various N applications at and especially after silking on temporal dynamics of post-silking N uptake and remobilization are poorly understood. Field experiments were conducted with N regimes ranging from low to high N levels. Nitrogen applications above optimal rates at and after silking neither increased late-season N uptake and leaf photosynthesis, nor reduced leaf N export during grain filling compared to the optimal N input, and thus significantly reduced the NUE. In most experiments, reductions in leaf N concentrations were observed around 15 days after silking (DAS). A 15 N labeling study revealed that remobilization of N taken up prior to silking from vegetative tissues during the entire grain-filling phase was 58%–60%, which contributed 53%–61% of the total grain N at maturity, and more than 60% of it was remobilized during the 0–30 DAS. N remobilization initially occurred preferentially from stems relative to leaves, while significant amounts of N were remobilized from leaves during late grain filling and deposited in the stem, particularly in high N treatments. No matter whether 15 N was applied before or at silking, a greater proportion of 15 N taken up was allocated to leaves under N deficient than under N sufficient conditions. At maturity, 70%–76% of the N taken up after silking was allocated to grain. Under N deficiency, direct N allocation to grains originating from post-silking uptake was 45%, 56%, 70% and 96% at 0–15, 15–30, 30–46 and 46–60 DAS, respectively, while these values were relatively lower and constant in N-sufficient plants (43%–50%). Overall, results indicated a strong developmental control over post-silking N fluxes with limited differences observed between N deficient and N sufficient maize, but no impact of high N applications to N-sufficient plants at or after silking. [ABSTRACT FROM AUTHOR]

As a measure of a plants ability to convert solar energy into biomass, radiation use efficiency (RUE) can be used to compare species and genotypes within species. Despite considerable research on RUE of biofuel species, few reports on sweet sorghum ( Sorghum bicolor (L.) Moench.) RUE are available. Radiation use efficiency and biomass yield of four sweet sorghum genotypes (‘Dale’, ‘M 81E’, ‘Topper 76-6’, and ‘Sugar Drip’) was assessed in response to two late planting dates in a two-year study. The late planting dates would coincide with abandoning double-crop plantings of soybean following wheat. Aboveground biomass yield and RUE (g biomass MJ −1 intercepted photosynthetically active radiation (IPAR)) was measured every two weeks beginning four weeks after planting. Two estimates of RUE were calculated differing only in growth periods used (emergence to anthesis [EA] and during rapid linear growth [Max]). Biomass yields, EA, and Max RUE were similar between years and sorghum cultivars, but differed between planting dates. Early-July plantings resulted in greater RUE than mid-July plantings. Averaged across cultivars at the first planting date both years EA and Max RUE were 3.11 and 3.96 g MJ −1 IPAR, respectively, compared to 2.40 (EA RUE) and 2.79 g MJ −1 IPAR (Max RUE) at the second planting date. Mean biomass yield across years and cultivars was 10.67 and 8.63 Mg ha −1 at the first and second planting dates, respectively. These results confirm expected decreases in RUE and biomass production of late-planted sweet sorghum, but also illustrate that, even when planted late, sweet sorghum efficiently converts intercepted PAR to biomass. [ABSTRACT FROM AUTHOR]

• The co-occurrence of heat and water-deficit stress during flowering negatively impacts crop productivity. • Heat, water-deficit, and their combination alter developmental processes associated with plant reproduction. • Stress-induced changes in sugar metabolism, reactive oxygen species and hormone levels are thought to play a role in yield reduction during stress combination. • Understanding the molecular processes associated with yield reduction during stress combination would allow the development of climate-resilient crops. Historically, extended droughts combined with heat waves caused severe reductions in crop yields estimated at billions of dollars annually. Because global warming and climate change are driving an increase in the frequency and intensity of combined water-deficit and heat stress episodes, understanding how these episodes impact yield is critical for our efforts to develop climate change-resilient crops. Recent studies demonstrated that a combination of water-deficit and heat stress exacerbates the impacts of water-deficit or heat stress on reproductive processes of different cereals and legumes, directly impacting grain production. These studies identified several different mechanisms potentially underlying the effects of stress combination on anthers, pollen, and stigma development and function, as well as fertilization. Here we review some of these findings focusing on unbalanced reactive oxygen accumulation, altered sugar concentrations, and conflicting functions of different hormones, as contributing to the reduction in yield during a combination of water-deficit and heat stress. Future studies focused on the effects of water-deficit and heat stress combination on reproduction of different crops are likely to unravel additional mechanisms, as well as reveal novel ways to develop stress combination-resilient crops. These could mitigate some of the potentially devastating impacts of this stress combination on agriculture. [ABSTRACT FROM AUTHOR]

Abstract: An inverse relationship between soybean [Glycine max (L.) Merr.] seed protein and oil concentration is well documented in the literature. A negative correlation between protein and yield is also often reported. The objective of this study was to determine the effect of high rates of N applied at planting on seed protein and oil. Nitrogen was surface-applied at soybean emergence at rates of 290kgha−1 in 2002, 310kgha−1 in 2003, and 360kgha−1 in 2004. Eight cultivars ranging from Maturity Group II–IV were evaluated under the Early Soybean Production System (ESPS). However, not all cultivars were evaluated in all 3 years. Glyphosate herbicide was used in all 3 years and a non-glyphosate herbicide treatment was applied in 2002. Cultivars grown in 2003 were also evaluated under an application of 21.3kgha−1 of Mn. All cultivar, herbicide, and Mn treatments were evaluated in irrigated and non-irrigated environments with fertilizer N (PlusN treatment) or without fertilizer N (ZeroN treatment). When analyzed over all management practices (years, cultivars, herbicide, and Mn treatments), the PlusN treatment resulted in a significant decrease in protein concentration (2.7 and 1.9%), an increase in oil concentration (2.2 and 2.7%), and a decrease in the protein/oil ratio (4.7 and 4.6%) for the irrigated and non-irrigated environments, respectively. However, the overall protein and oil yield increased with the application of fertilizer N at planting (protein: 5.0% irrigated, 12.7% non-irrigated and oil: 9.9% irrigated and 18.9% non-irrigated). These increases were due to the increase in seed yield with the application of large amounts of fertilizer at planting. Additionally, a significant correlation (r =0.45, P =0.0001) was found between seed protein concentration and seed yield. No significant correlation was found between seed oil concentration and seed yield. The data demonstrate the inverse relationship between protein and oil and indicate that large amounts of N applied at planting do not change this relationship. [Copyright &y& Elsevier]

Emerging biofuel feedstock systems are well suited for use on less productive marginal soils in the Midwestern USA. The systems could replace commodity crop agriculture that may not be economically feasible on these soils with current input and output prices, and meet a growing renewable energy demand. Three annual bioenergy crops, maize ( Zea mays L.), sweet sorghum ( Sorghum bicolor (L.) Moench), and high biomass sorghum (HBS) were grown in rotation with soybean ( Glycine max L.) for five years on marginal soils at two locations. Maize aboveground dry matter (DM) yield and grain yield, sweet sorghum aboveground DM yield, and juice yield and Brix, and HBS DM yield were evaluated and used to calculate theoretical ethanol yields. Intermittent drought occurred at both sites during three of the five years notably reducing yield; a terminal drought in 2011 reduced sorghum yields and inhibited maize grain development at both sites. Theoretical ethanol yields averaged across years from sweet sorghum and HBS were greater than from maize at both locations, and indicate that sweet sorghum has the greatest yield potential, but HBS yield was the most stable. The central Missouri site maintained greater dry matter yield, and theoretical ethanol yield than the southwestern Missouri site. Due to the occurrence of drought during the study, the findings have relevance for evaluating marginal land management for annual bioenergy crops in differing rainfall patterns with climate change. [ABSTRACT FROM AUTHOR]

Increasing demand for high-yielding, alternative biofuel feedstocks elicits the need to fully understand sweet sorghum ( Sorghum bicolor (L.) Moench) yield response to varying nitrogen (N) fertilization rates in the U.S. Midwest. The objective of this three-year study was to determine the optimum N fertilization rates for the production of two common sweet sorghum cultivars (Dale and Top 76-6) in central Missouri. Five N rates (0, 56, 112, 168, 224 kg N ha −1 ) were imposed and tested for their effects on dry matter yield, stem juice yield, Brix, fermentable sugar yield, theoretical juice ethanol yield, theoretical lignocellulosic ethanol yield, and total theoretical ethanol yield. Except for Brix, N treatment significantly influenced all yield parameters in all three years. The two varieties yielded similarly across most measured parameters. Total dry matter yields averaged 16.8 Mg ha −1 , juice yields averaged 9113 L ha −1 , and fermentable sugar yields averaged 1055 kg ha −1 across years and varieties. Total ethanol yields averaged 7488 L ha −1 and were highest at 168 kg N ha −1 across the three years, indicating that sweet sorghum in Missouri may reach maximum yields near that fertilization rate. Annual precipitation and temperature differences greatly influenced dry matter, stem juice, and sugar yields, thereby affecting theoretical ethanol yields, such that yields were lower in years with less rainfall and lower temperatures, which also limited the N response in these years. [ABSTRACT FROM AUTHOR]

Corn ( Zea mays L.) grain composition is important for human and livestock nutrition, when used as seed, and for ethanol production. However, few studies have evaluated the effects of common cultural practices on corn grain composition. This study was conducted to determine whether corn grain elemental composition is affected by tillage practices (tillage or no-tillage), and whether tillage affects grain, protein, and oil yield, and removal of elements from the field in grain. The concentration of protein, oil, P, K, Ca, Mg, Mn, Fe, Zn, Cu, and B, and grain yield were determined in years 20 and 22 of long-term tillage and no-tillage treatments. Tillage treatment did not affect any grain component across both years of sampling, but Cu concentrations were greater under no-tillage in one year. Grain, oil, and protein yield was not affected by tillage treatments across years, but was greater one year under tillage and one year under no-till. The removal of P and Fe was greater under tillage in 2010, and that of Ca and Mn was greater under no-till in 2012. Removal of Cu was greater one year under tillage and one year under no-tillage. Correlation and principle components analysis suggests that there are some differences in the relationships among the grain components between tillage treatments. However, results indicate that tillage is not a dominant factor affecting corn grain composition and removals of nutrients are dominated by grain yield and not the concentration in the grain. [ABSTRACT FROM AUTHOR]

Soybean (Glycine max [L.] Merr.) grain composition determines its uses, nutritional quality, value, and the amount of nutrients removed from agricultural ecosystems. Yet few studies have evaluated the effects of annual farming practices on composition. This study was conducted to determine whether soybean grain composition is altered by farming practices and how these practices impact yield and nutrient removal. The effects of long-term cropping systems (continuous soybean or soybean in rotation with corn (Zea mays L.), both tilled and no-till) on yield and concentrations of grain protein, oil, and nine mineral components, after 20 and 22 years of continuous management, were determined. Grain yield, protein, K, Zn, B, and Cu concentrations differed among cropping systems in both years while Mn concentration differed in one of two years. Oil, P, Ca, Mg, and Fe concentrations did not differ among cropping systems in either year, but across both years mean Fe concentration was affected. Differences in K, Fe, and Zn concentrations were mostly attributed to tillage each year, while those in protein and Cu concentrations were mostly attributed to rotation each year. Distinct B concentrations were attributed to tillage while distinct Mn concentrations were attributed to rotation. Grain yield differences were attributable to both rotation and tillage each year. In most instances, oil and protein yield, and mineral removal were dominated by grain yield differences and not concentration. Nonetheless, long-term tillage and rotation greatly affected soybean grain composition. Thus, rotation and tillage should be accounted for when assessing seed quality and seed composition. [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]

Abstract Accurately mapping heterogeneous agricultural landscape is an important prerequisite for agricultural field management (e.g., weed control), plant phenotyping and yield prediction, as well as ecological characterization. Compared to traditional mapping practices that require intensive field surveys, remote sensing technologies offer efficient and cost-effective means for crop type mapping from regional to global scales. However, mapping heterogeneous agricultural landscape is a challenge because of diverse and complex spectral profiles of crops. We propose a novel deep learning method, namely deep progressively expanded network (dPEN), for mapping nineteen different objects including crop types, weeds and crop residues, in a heterogeneous agricultural field using WorldView-3 (WV-3) imagery. To assess the mapping accuracy of dPEN, we created a calibrated WV-3 dataset with the corresponding ground truth. In addition, the suitability of visible/near-infrared (VNIR, 400–1040 nm) and short-wave infrared (SWIR, 1195 nm–2365 nm) bands of WV-3 to classification accuracy were examined and discussed in detail. To the best of our knowledge, this is the first effort to explore the significance of all SWIR bands in WV-3 for classification accuracy in a heterogeneous agricultural landscape. The results demonstrated that: (1) The proposed dPEN allows for building a deeper neural network from multispectral data which was the limitation of many convolutional neural networks; (2) dPEN was able to extract more discriminative features from VNIR and SWIR bands by producing the highest overall accuracy (OA: 86.06%) over competing methods such as support vector machine and random forest; (3) The inclusion of WV-3 SWIR bands greatly improved the classification accuracy; (4) SWIR bands were particularly beneficial to improve the classification accuracy of some individual classes such as weeds, crop residues, and corn and soybean during late developmental stages; (5) The red-edge band (705–745 nm) was identified as the most important band affecting the classification accuracy nearly 10%, whereas the coastal band (400–450 nm) provided the lowest contribution; and (6) SWIR-5 band (2145–2185 nm) contributed most to OA by enhancing it approximately 4% when combined with VNIR bands, while SWIR-1 (1195–1225 nm) yielded the lowest improvement (1.55%) for OA. These research outcomes provide useful information for efficiently mapping agricultural landscape, and indicate the potential practices of dPEN and contributions of spectral bands in WV-3 for plant phenotyping, weed control, and crop residue retention. Highlights • A novel deep learning paradigm for landscape mapping using Worldview-3 data • A solution to develop a deeper neural network for multispectral data • Systematically analyze the significance of spectral bands of Worldview-3 data • SWIR bands are important in mapping of crop types, weeds, soil and residue. • The Red-edge band contributes most in mapping of crop types, foxtail, and soil. [ABSTRACT FROM AUTHOR]

Production costs change with harvest date of switchgrass ( Panicum virgatum L.) as a result of nutrient recycling and changes in yield of this perennial crop. This study examines the range of cost of production from an early, yield-maximizing harvest date to a late winter harvest date at low moisture and low nutrient concentration using different harvest systems as dictated by the moisture content of the standing crop. Harvest systems with a field-drying interval and multiple harvest passes were compared to a single-pass harvest when moisture content had naturally declined to storage-safe conditions or when artificial drying at the plant would be required. Results showed that the single-pass harvest requiring artificial drying was either i) as costly or more so than declines in yield observed with letting the standing crop dry to 20% moisture in the field; or ii) not economically viable in comparison to multi-pass harvest with a field drying interval at higher yield. Sites where yield losses due to harvest delays were small showed promise for the single-pass harvest at storage-safe moisture, as nutrient replacement costs with greater nutrient recycling and harvest cost savings with a single pass offset yield losses with delayed harvest. Extending the harvest season had different producer cost ramifications amongst environments and led to large changes in nutrient concentrations in harvested biomass. This may be problematic for biorefineries seeking stable nutrient content in feedstock. [ABSTRACT FROM AUTHOR]

Use of perennial bioenergy grasses would be enhanced if they produced sustainable ratoon crops across a wide geographic region. Our objective was to compare ratoon cold tolerance (defined as shoot emergence during the first-ratoon crop), and plant cane dry mass yield and feedstock quality [acid detergent lignin, cellulose, hemicellulose, total nonstructural carbohydrates (TNC), and combustible energy] of elephantgrass ( Pennisetum purpureum ), Old World Erianthus ( Saccharum arundinaceum , formerly E. arundinaceus , subsequently referred to as Erianthus ), and sugarcane ( Saccharum sp. hybrids). The experiment (Test 1) was conducted near Booneville, Arkansas (35.08°N latitude) and consisted of three varieties of elephantgrass and Erianthus , and six of sugarcane, evaluated in plant cane (first year growth, 2008) and first-ratoon (second year growth, 2009). The experiment was repeated in 2009–2010 (Test 2). Absolute minimum air temperatures were −12.7 and −17.3 °C in Test 1 and 2, respectively. Second-year emergence in Test 1 was in the order sugarcane = Erianthus (92%) > elephantgrass (25%). In Test 2, sugarcane and Erianthus had 63 and 3% second-year emergence, respectively, whereas elephantgrass shoots did not emerge. Elephantgrass had twice the plant cane yield of the other species. Feedstock quality was generally similar among species, although sugarcane had greater TNC (220 g kg −1 ) than other species (≤131 g kg −1 ). Poor ratooning of all 12 varieties would limit their use as perennial bioenergy feedstocks in similar environments, however, breeders using germplasm selected under these conditions could ultimately enhance ratoon cold tolerance of commercial sugarcane varieties for more southerly latitudes. [ABSTRACT FROM AUTHOR]

Remote estimation of leaf nitrogen (N) or pigments through hyperspectral reflectance offers an opportunity to non-destructively diagnose plant N status. Two sweet sorghum ( Sorghum bicolor [L.] Moench) cultivars (Top 76-6 and Dale) were grown with 0, 56, 112, 168, and 224 kg N ha −1 in 2009 and 2010. Reflectance measurements were coupled with plant height, main-stem node number, leaf N concentration, and total chlorophyll content to establish the relationship of these traits with canopy reflectance. Canopy reflectance was most sensitive to N status in the visible region, specifically near green (595 nm) and red (701 nm) wavebands. Simple-ratio spectral models comprised of visible wavebands or wavebands from the visible and near infrared region outperformed models developed using only the most sensitive single-waveband. Based on the cross-validation of spectral models between data from two years and two cultivars, the simple-ratio models comprising the reflectance (R) ratios of 595 nm vs. 1676 nm and 595 nm vs. 508 nm predicted leaf N concentration and chlorophyll content with the greatest accuracy (highest r 2 and lowest relative error, RE). These simple-ratio models were used to develop general-purpose spectral models to derive coefficients to estimate leaf N concentration (-66.63 × R 595 /R 1676 + 34.14; r 2 0.52; RE 16.8%) and chlorophyll content (-49.12 × R 595 /R 508 + 107.47; R 2 0.64; RE 17%). The identified spectral models can be used to assess growth, diagnose sweet sorghum N status and may be useful to make N management decisions for site-specific fertilizer applications. [ABSTRACT FROM AUTHOR]

The U.S. Department of Energy has initiated efforts to decrease the nation’s dependence on imported oil by developing domestic renewable sources. In this study, giant miscanthus ( Miscanthus × giganteus), miscane ( Saccharum hybrid × Miscanthus spp.), and giant reed ( Arundo donax ) were grown on an upland site (35.08°N) to determine the potential of these perennial grasses as bioenergy feedstocks, with or without irrigation. Irrigated and rainfed plots with subplots of each species were planted on a silt loam, and biomass yields were assessed in plant-cane, first ratoon, and second ratoon seasons. In the establishment year, giant reed biomass yield was greater than that of giant miscanthus, but not significantly different from that of miscane. Biomass yields of giant reed continued to increase significantly with every season, while giant miscanthus yields only increased from plant-cane to first ratoon, and miscane yields did not change with season. The miscane clone did not have sufficient cold tolerance to ensure vigorous growth of ratoon crops at this latitude. Giant miscanthus had the smallest stalk diameter each season, and the largest leaf:stem ratio in the plant-cane and first ratoon seasons. Irrigation increased dry matter yield of giant reed in the plant-cane and first ratoon seasons, but not in the second ratoon season. In both ratoon seasons, giant reed produced the tallest stalks, largest stalk diameters, and the greatest stem, leaf, and total dry matter yields. Giant reed was the most productive of the three species despite growing on an upland site away from its usual lowland habitat. [ABSTRACT FROM AUTHOR]

• A criterion for grading lodging risk levels based on probability was established. • The wind speed risks in three main quinoa production areas of China were analyzed. • Optimizing plant height to counter lodging risks under high-yielding conditions. • The spatial distribution of recommended plant height in study areas was drawn. Stem lodging is a major restriction for further quinoa yield improvement under high-yielding conditions. Plant height is one of the most important factors to affect stem lodging resistance, but how to determine the optimal plant height to meet specific lodging resistance requirements in different areas is rarely discussed. This study analyzed the long-term wind speed data in three main quinoa production regions of China (Inner Mongolia, Qinghai, and Gansu), and calculated the wind speed under different risk conditions (probability = 0.1, 0.3 and 0.5). Then, three high yielding conditions were selected based on a field experiment, and their optimal quinoa plant heights were calculated to ensure adequate lodging resistance in every specific area by using the generalized crop lodging model. Results showed that during the susceptible lodging period, 70–97% of the study regions experienced a maximum daily wind speed of 4–6 m s–1 with a probability of 0.3–0.5. As the probability decreased to 0.1, a higher maximum daily wind speed of 6–8 m s–1 would prevail in 69–75% of the study regions. Besides, central Inner Mongolia, western Qinghai, and northern Gansu experienced higher maximum daily wind speeds than other regions during the susceptible lodging period. To achieve adequate lodging resistance under a probability of 0.3–0.5, quinoa height should be decreased to be lower than 1.2–1.6 m in 72–99% of the study regions. Furthermore, under a probability of 0.1, quinoa height needed to be lower by at least another 0.2 m more in 86–98% of the study regions. [ABSTRACT FROM AUTHOR]

Allelopathy is the process whereby an organic chemical (allelochemical) released from one plant influences the growth and development of other plants. Allelochemicals produced by specific rice ( Oryza sativa L.) cultivars have potential to manage barnyard grass ( Echinochloa crus-galli L.), a major yield-limiting weed species in rice production systems in Asia and North America. In this study, isolation and identification of an allelopathic compound, N-trans -cinnamoyltyramine (NTCT), in a Vietnamese rice cultivar ‘OM 5930’ was accomplished through bioassay-guided purification using reversed-phase liquid chromatography coupled with spectroscopic techniques, including tandem mass spectrometry, high resolution mass spectrometry, as well as one-dimensional and two-dimensional 1 H NMR and 13 C NMR spectroscopy. The identified compound, NTCT is considered a β-phenylethylamine. NTCT inhibited root and hypocotyl growth of cress ( Lepidium sativum L.), barnyard grass and red sprangletop ( Leptochloa chinensis L. Nees) at concentrations as low as 0.24 μM. The ED 50 (concentration required for 50% inhibition) of NTCT on barnyard grass root and hypocotyl elongation were 1.35 and 1.85 μM, respectively. Results further demonstrated that mortality of barnyard grass and red sprangletop seedlings was >80% at a concentration of 2.4 μM of NTCT. By 20 days after transplanting, 0.425 nmol of NTCT per OM 5930 rice seedling was released into the culture solution. With concentrations of 42 μg g −1 fresh weight, production of NTCT in intact rice plants can be considered high. These findings suggest that developing plants of Vietnamese rice cultivar OM 5930 release NTCT and may be utilized to suppress barnyard grass in rice fields. The potency of NTCT may encourage development of this compound as a bio-herbicide. [ABSTRACT FROM AUTHOR]

Highlights: [•] We examined the relationship between soybean leaf pigments and reflectance spectra. [•] Models developed using transformed spectra outperformed the original reflectance spectra. [•] Among tested methods, fitness and accuracy of a multiple linear regression model were greatest. [•] Models primarily integrated visible as compared to NIR regions of the spectrum. [•] Continuous wavelet transformed spectra using ‘Mexican hat’ family produced the best model. [ABSTRACT FROM AUTHOR]

Abstract: The amount of plant available soil water is strongly influenced by soil type and rooting depth. This study was conducted to investigate the influence of limited plant available soil water on soybean (Glycine max (L.) Merr.) yield and seed composition. Six soybean cultivars were grown in 2007, 2008, and 2009 in a field with plastic liners inserted at depths of 0.30, 0.45, 0.60, 0.75, and 0.90m to limit the rooting depth and thus the amount of available water. Compared to the long term mean (508mm), distinct distribution patterns and amounts of rainfall among the three growing seasons (290, 675, and 440mm in 2007, 2008 and 2009, respectively) resulted in significant differences in yield and seed composition among years. The overall yield, seed weight (gseed−1), oil concentration, linoleic acid and linolenic acid were the lowest and protein concentration, palmitic acid, stearic acid and oleic acid were the highest in 2007 compared to the other two years. These differences were greater in plants grown under severe rooting depth restrictions. Restricted rooting depth affected soybean seed quality such as protein and oil concentration and fatty acid composition, not only when rainfall was below average, but also when it was above average. The amount of rainfall received from beginning of pod development through full pod (R3–R4) stages was highly correlated with yield, seed weight, oil and protein. Yield and seed weight were negatively correlated with protein and positively with oil, and protein and oil were strongly negatively correlated. Linoleic and linolenic acids were negatively correlated with palmitic, stearic and oleic acids. Under non-limiting moisture conditions (2008), a rooting depth of 0.30m appeared to provide ample resources for plant growth, indicating that effects observed in drier years were largely a function of water availability. Results presented in this study illustrate that artificially limiting rooting depth under field conditions may serve as means to manipulate plant-available soil water to study plant responses to water deficit stress without modifying the above-ground environment. [Copyright &y& Elsevier]

• Long-term soybean breeding for yield has increased plant N demands. • Total shoot N and N from BNF increased with cultivar year of release. • Sensitivity of BNF to soil mineral N has not changed over years of soybean breeding. Long-term soybean [ Glycine max (L) Merr.] breeding for yield has increased plant nitrogen (N) demands. On one hand, because N fertilizer application in soybean production systems continues to be insignificant, increased plant N demands over time may have been satisfied from greater biological N fixation (BNF). On the other hand, increased soil residual N over time may have affected the sensitivity of nodulation and BNF. To understand the impact of breeding for greater yield and the effect of soil residual N on nodulation and BNF, two field and a greenhouse study were conducted. Field studies were conducted with maturity group IV soybean cultivars released from 1930 to 2005 and included experiments in four environments. Total shoot N and N from BNF increased with cultivar year of release in two of the four environments. Simulation of different levels of residual soil mineral N by application of 0, 34, 67, and 101 kg N ha−1 shortly after planting resulted in linear increases in shoot N content and δ15N, and linear decreases in nodule number and nodule dry matter in the field. Consistent with these results, fertigation of greenhouse-grown soybean cultivars with different levels of NH 4 NO 3 led to a reduction in nodule number, dry matter, and size. Overall, results from these studies indicate that increases in seed yields with cultivar year of release were associated with greater amounts of N derived from BNF as well as greater total shoot N accumulation, but the relative contribution of BNF to total shoot N did not change over time. Analysis also suggest that the sensitivity of nodulation and BNF to soil mineral N has not been altered over the course of soybean breeding. [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]

Preharvest crop yield prediction is critical for grain policy making and food security. Early estimation of yield at field or plot scale also contributes to high-throughput plant phenotyping and precision agriculture. New developments in Unmanned Aerial Vehicle (UAV) platforms and sensor technology facilitate cost-effective data collection through simultaneous multi-sensor/multimodal data collection at very high spatial and spectral resolutions. The objective of this study is to evaluate the power of UAV-based multimodal data fusion using RGB, multispectral and thermal sensors to estimate soybean (Glycine max) grain yield within the framework of Deep Neural Network (DNN). RGB, multispectral, and thermal images were collected using a low-cost multi-sensory UAV from a test site in Columbia, Missouri, USA. Multimodal information, such as canopy spectral, structure, thermal and texture features, was extracted and combined to predict crop grain yield using Partial Least Squares Regression (PLSR), Random Forest Regression (RFR), Support Vector Regression (SVR), input-level feature fusion based DNN (DNN-F1) and intermediate-level feature fusion based DNN (DNN-F2). The results can be summarized in three messages: (1) multimodal data fusion improves the yield prediction accuracy and is more adaptable to spatial variations; (2) DNN-based models improve yield prediction model accuracy: the highest accuracy was obtained by DNN-F2 with an R2 of 0.720 and a relative root mean square error (RMSE%) of 15.9%; (3) DNN-based models were less prone to saturation effects, and exhibited more adaptive performance in predicting grain yields across the Dwight, Pana and AG3432 soybean genotypes in our study. Furthermore, DNN-based models demonstrated consistent performance over space with less spatial dependency and variations. This study indicates that multimodal data fusion using low-cost UAV within a DNN framework can provide a relatively accurate and robust estimation of crop yield, and deliver valuable insight for high-throughput phenotyping and crop field management with high spatial precision. • A low-cost multi-sensor UAV for crop monitoring & phenotyping was developed. • Canopy structure, temperature and texture are important features for yield model. • Multimodal data fusion showed effectiveness in yield prediction. • DNN provided promising results in yield prediction across genotypes and over space. [ABSTRACT FROM AUTHOR]