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Estimating plant nitrogen concentrations (PNCs) with remote sensing technology is critical for ensuring precise field nitrogen (N) management. Compared with other remote sensing platforms, low-altitude unmanned aerial vehicles (UAVs) produce images with high spatial resolutions that can be used to clearly identify soil and vegetation. Previously, many spectral indices were designed to remove soil effects to obtain optimal PNC predictions. Herein, we attempt to enhance the PNC prediction accuracy only by removing soil pixels in high-resolution images. Thus, we aimed to collect a dataset containing different crops and image types to investigate whether removing soil pixels to purify crop spectra can improve PNC estimations. For this purpose, N fertilizer experiments were conducted on cotton (Gossypium hirsutum L.), wheat (Triticum aestivum L.) and maize (Zea mays L.), and multispectral and hyperspectral UAV images and PNCs were collected at different growth stages. The multispectral images had actual high spatial resolutions, while the hyperspectral images had virtual high spatial resolutions constructed by fusing high resolution panchromatic images and coarse resolution hyperspectral images. These images represent two typical UAV image types. First, for each crop, the relative changes and driving forces associated with the purified and nonpurified spectra were analyzed under different growth stage, N treatment. Then, three commonly used methods, the spectral index (SI), partial least squares regression (PLSR) and artificial neural network (ANN) methods were used to design PNC prediction model using purified and nonpurified spectra respectively. The results showed the differences between purified and nonpurified spectra were affected by the proportion of crop pixel, sunlit soil pixel and sunshade soil pixel in image. This influence had various trends and magnitudes among different N treatment, growth stages and crop types. It is better to remove soil pixels in imagery, when designing PNC prediction model for plants across growth stages, crop types or even in a single growth stage. The results from actual high spatial resolution images demonstrated this point, with the best PNC prediction model from purified spectra. When considering virtual high spatial resolution image, as the spectrum obtained for each vegetation pixel still represented a mixed vegetation and soil spectrum, removing soil pixels showed no improved performance for PNC estimation. These results provide a reference for others to reasonably choose an optimal data-processing method for constructing PNC prediction models. • Plant nitrogen concentration can be estimated using UAV-based images. • Purified and nonpurified spectra exist significant difference. • Plant nitrogen concentration can be better estimated using purified spectra. [ABSTRACT FROM AUTHOR]

Cadmium (Cd) toxicity in agricultural soils is serious concern these days which needs continuous attention. Little is known about the combined use of berseem and/or maize residues soil applied as a green manure alone or along with foliar dressing of zinc oxide nanoparticles (ZnONPs) on Cd accumulation in wheat (Triticum aestivum L.). A pot experiment under ambient conditions with wheat grown in Cd-contaminated soil was performed after soil applied different green manure amendments and foliar dressing of ZnONPs was done during plant growth and plants were harvested at full maturity. Compared with control, plant growth attributes and biomass of above ground parts substantially increased with applied amendments being maximum with combined use of ZnONPs + B75 (berseem residue, 75 mg/kg) followed by ZnONPs + M75 (maize residue, 75 mg/kg). All the treatments improved the leaf chlorophyll contents and improved the leaf antioxidant enzyme activities thereby reduced the leaf electrolyte leakage. The Cd accumulation in roots and aboveground parts of the wheat was reduced especially in ZnONPs + B75 followed by ZnONPs + M75. The higher rate of soil applied amendments along with NPs minimized the available Cd in soil extracts but soil post-harvest pH was not much affected by the applied amendments. In conclusion, incorporation of berseem and maize residues as a green manure applied in Cd-contaminated soil combined with foliar NPs may decrease Cd phytoavailability and its accumulation in wheat grains. However, substantial field studies are required under various environmental conditions before final recommendations at field levels. [Display omitted] • The highest Cd concentrations were found in plants without any treatments. • ZnONPs and green manure increased growth and biomass of wheat. • ZnONPs and green manure enhanced activities of antioxidants enzymes in leaves. • ZnONPs and green manure decreased Cd contents in grains of wheat. [ABSTRACT FROM AUTHOR]

Abstract: An assessment of contamination of cereals with the Fusarium mycotoxins deoxynivalenol (DON) and zearalenone (ZEA) is difficult because of the complexity and interactions of various driving factors. We study the mycotoxin accumulation in winter wheat growing after maize or oilseed rape at different topographic positions within fields consisting of alternating hilltop and depression positions across a transect in the Uckermark region in the Northeast of German Lowlands. A linear mixed-effects model and censored regression are used to account for spatial autocorrelation and non-detects in determining factors controlling DON content in 304 samples from 19 fields in 2006 and 2007. Environmental factors (actual rainfall during the anthesis, long-term mean annual precipitation), topographic factors (relief position, topographic wetness index TWI) and management factors (tillage, preceding crop, susceptibility ranking of wheat cultivars to Fusarium spp.) as well as the year of investigation were included as explanatory factors in this analysis. The spatial linear mixed-effects model indicates that DON on wheat fields with maize as preceding crop was one order of magnitude higher than in wheat grown after oilseed rape (significant at the 5% level). Tillage had a similar effect: Ploughing significantly reduced DON by more than one order of magnitude. Humid areas (mean annual precipitation >550mm) showed a significantly higher DON contamination (3.7-fold increase) than the drier areas. TWI and topographic position had significant influences on DON levels. Their combined effect lead to a 68% higher DON at depressions with high TWI compared to hilltops with low TWI. The results of the censored regression were very similar to those of the mixed model. The susceptibility ranking score of the wheat cultivars to Fusarium infection did not have a significant influence on DON in these models. Overall, the statistical models revealed a combined influence of climatic, topographic, and crop management factors on DON concentration in winter wheat on different spatial scales for the environmental setting of our study area. [Copyright &y& Elsevier]

Abstract: Wheat (Triticum aestivum L.), rice (Oryza sativa) and maize (Zea mays L.) are the most important cereals worldwide. However, in the last few years, soil has been submitted to both use and handling pressures due to the increase in agricultural practices, which are leading to its degradation. The use of plant growth-promoting rhizobacteria (PGPR) as inoculants constitutes a biological alternative for sustainable production. Pseudomonas aurantiaca SR1 was formulated as an inoculant in order to evaluate its growth promotion effect in the field when applied on maize and wheat seeds at the sowing time. P and N fertilization treatments were also included in the assays. P. aurantiaca SR1 colonized the root system of both crops and it persisted at appropriate population densities. It also showed a significant plant growth-promoting effect that was reflected in the yield. Another relevant finding was that both crops, when inoculated with P. aurantiaca SR1, presented higher yields with fertilization doses lower than those conventionally applied. This indicated its potential use as a reasonable alternative for crop production, with a minimization of the ecological impact. [Copyright &y& Elsevier]

• Microbial communities clearly undergo cyclical patterns within the growing season. • Bacteria cycled at shorter periods, associated with soil physical/weather conditions. • Fungi cycled at longer periods, associated with soil chemical properties. • Fertilizer and tillage may modulate microbial community cycles in the growing season. • Time lags with associated soil conditions was strongly influenced by microtopography. Soil microbial communities maintain many ecosystem functions including decomposition and symbiotic nutrient uptake. Prior field studies have focused on either geospatial or relatively large-time scale trends in these communities. Whereas, their small-time scale (e.g., weekly) dynamics in agricultural fields have largely been overlooked. Our objective was to determine the effects and characteristics of short-time scales on five phospholipid fatty acid (PLFA) microbial groups throughout the whole growing season, while under two soil disturbance levels. The microbial community groups included total microbial abundance (TMA), arbuscular mycorrhizal fungi (AMF), total fungi, actinomycetes, and total bacteria. The fungal to bacterial ratio (F:B) was also determined. Soils were sampled twice per week from planting to harvest during two consecutive growing seasons (N = 62) and analyzed for microbial abundances and chemical and physical properties. The study was conducted at an on-farm site with a corn [ Zea mays ] – soybean [ Glycine max] – wheat [ Triticum aestivum ] rotation and two soil disturbance levels [high (chisel plow) and low (shallow vertical till)] using a randomized complete block design. Data analysis included 1) spatial and temporal coefficients of variations, 2) a mixed linear model to test for time and disturbance level effects, and 3) a Fourier analysis to detect and characterize cyclical patterns via autocorrelation spectral densities. The Fourier analysis also included cross spectral densities and phase lags with a large suite of soil chemical, soil physical, and weather states. Temporal variations of microbial communities were one to threefold greater than their spatial variations. Significant time effects were observed for TMA, AMF, and bacteria, where these communities behaved as sine and consine functions over time. However, strong cyclical patterns were above white noise levels at the experimental plots level for all microbial groups during each growing season. Cross spectral densities indicated that bacteria and actinomycetes tended to cycle at short and long periods (biweekly to whole season) associated with soil physical and weather states, whereas TMA, AMF, fungi, and F:B cycles at long periods (bimonthly to whole season) associated with soil chemical states. These microbial communities in a field setting clearly undergo cyclical patterns over small periods with some modulations from soil disturbance levels, fertilization, and microtopography. Further research on these cyclical and cross-correlated dynamics is warranted to determine the magnitude of influence on ecosystem services and crop productivity. [ABSTRACT FROM AUTHOR]

The Decision Support System for Agrotechnology Transfer – Cropping System Model was used with an objective to evaluate maize (Zea mays L.), winter wheat (Triticum aestivum L.) and grain sorghum (Sorghum bicolor L. Moench) yield, crop water productivity (CWP) and return after variable cost (RAVC) under different combinations of irrigation interval/capacity and plant available soil water (PASW) thresholds on three soil types in southwestern Kansas. Maize, grain sorghum and winter wheat yields were maximized under irrigation capacity of 4.2–6.3, 3.1–4.2 and 2.5–3.1 mm/d, respectively. The lowest and highest values in the range corresponded to silt loam and fine sand soils, respectively. For maize, maximum RAVC ($630–710/ha) and CWP (25–27 kg/ha/mm) were achieved with a relatively shorter irrigation interval (25 mm/4–8 d). RAVC values for grain sorghum and winter wheat were not substantially affected by irrigation interval. The RAVC for grain sorghum and winter wheat ranged from $150 to $200/ha and $310 to $370/ha, respectively. The CWP of grain sorghum peaked at shorter irrigation interval (25 mm/6–8 d), whereas, high CWP of wheat was simulated even at longer irrigation interval (25 mm/26 d). Overall, for winter wheat and grain sorghum, irrigation strategy for attaining higher RAVC values is different from irrigation strategy for attaining higher yield. Whereas, for maize, irrigation strategy for higher yield is the same as that irrigation strategy for higher RAVC. This study guides producers to identify and prioritize the most suitable irrigation strategy for optimizing yield, CWP and/or income while enhancing sustainability of environment and management of ground water. The present work assumes all factors except water are optimal and findings are sensitive to dynamics of price changes, productivity levels and variations in crop management and climate. • Irrigation scheduling for maize, winter wheat and grain sorghum was evaluated. • Yield, crop water productivity (CWP) and income were used as evaluation criteria. • For maize, maximum income, CWP and yield were met at shorter irrigation interval. • Irrigation strategy for high income in wheat is different from that for high yield. • Grain sorghum and wheat income was not substantially affected by irrigation. [ABSTRACT FROM AUTHOR]

Biophysical simulation models can help to satisfactorily estimate the crop performance for grain production, their stability across years and their impact on components of hydrological balance in diverse areas once those models have been calibrated and validated with field data. The Inner Argentinian Pampas (IAP) region is very susceptible to both frequent flooding and random droughts due to flat landscape, sub-humid to semi-arid climate, coarse- textured soils and shallow water tables. The Soil Water Balance (SWB) model appears to be suitable for the IAP region since it includes most of the necessary requirements for the particular conditions of such an environment. The objectives of this study were: i) to identify the most sensitive crop parameters of the SWB model for a satisfactory estimation of aerial biomass, grain yield and crop evapotranspiration in the IAP region; ii) to parameterise and calibrate the SWB model for simulation of aerial biomass, grain yield and crop evapotranspiration of wheat (Triticum aestivum L.), soybean [ Glycine max L. (Merr.)] and maize (Zea mays L.); iii) to validate the SWB model using an independent dataset over a wide area in the IAP region. We used data from 9 field experiments for calibration and from 116 field experiments for validation. The most critical parameters, as indicated by a sensitivity analysis, were biomass-transpiration coefficient (K b), radiation use efficiency (e), and extinction coefficient (k), suggesting that they should be locally obtained before promoting the use of the SWB model in a given region. The SWB model, after calibration, was able to accurately estimate crop aerial biomass (d = 0.97–0.99, GSD = 9.5–23.9% and RMSE = 786–2,438 kg ha−1), grain yield (d = 0.95–0.96, GSD = 4.5–10.7% and RMSE = 357–637 kg ha−1), crop evapotranspiration (d = 0.97–0.99; GSD = 8.1–16.1%, RMSE = 17–51 mm) and soil water content (d = 0.87–0.96, GSD = 11.2–15.5% and RMSE = 9.6–13.2 mm). The robustness to estimate water balance, aerial biomass and grain yield fluctuations for wheat, soybean, and maize across different soil textures and rainfall variability reflects the potential of SWB model as a valuable tool to face the main challenges of the agricultural systems in our region. [ABSTRACT FROM AUTHOR]

Numerous strategies for mitigating ammonia volatilization (AV) from agricultural land have been investigated with limited evaluation of their efficacy and response to differing field conditions across China. Therefore, this meta-analysis seeks to draw conclusions about AV in China, and assess the effect of crop type (wheat, maize, and rice as staple crops), climatic conditions, and soil properties on AV and variations in responses that can guide selection of appropriate strategies under different conditions. Novel analysis indicates nitrogen (NH 3 –N) losses of 7.62 Tg due to AV from these three crops in China. AV is 12.8 and 18.0% (95% CI) higher from maize than from wheat and rice, respectively, without N application under warm and sub-humid conditions (MM), and 13.8 and 2.8% higher under hot and humid conditions (HH). AV increases notably under HH as compared with cold and sub-arid conditions (LL) by 11.5% and 28.4% under the control treatment and application of 150 kg N ha−1, respectively in rice fields while it is most substantially under maize (52.5%) with application of 150 kg N ha−1. The ratio of change in AV between soil grades 3 and 1 (potential AV >1.0 and < 0 cmol kg−1) is significantly greater for wheat and rice (2.5%) than for maize (1.9%). The strategy of reducing N rate is more effective for maize and rice than wheat, where applying N at a rate of 150–220 kg N ha−1 to them has similar effects to applying 300 kg N ha−1 to wheat. For wheat and maize, urea should be partially substituted with organic amendments, while improved urea is the preferable N source for rice. Subsurface application has competitive efficacy, especially for maize, and higher N rates. Applying inhibitors achieves the highest AV reduction, especially with rice under various conditions, creating more actively options for future research to increase applicability. Image 1 • About 7.62 Tg N–NH 3 from main staple crops in China was indicated using CMA outputs. • Higher AV from maize fields than wheat and rice by (95% CI = 12.8 and 18%) even without N applications. • AV under maize and rice is higher under warm-humid conditions than cold-dry but wheat showed reverse response. • Improved urea and inhibitor usage is optimum strategy in reducing AV especially under rice. • Organic amendments, mulching and subsurface application are efficient strategies in reducing AV for wheat and maize. [ABSTRACT FROM AUTHOR]

• Low-cost biochar was used to ameliorate salt-affected soil. • 12 t ha–1 biochar reduced soil bulk density and increased saturated hydraulic conductivity. • 12 t ha–1 biochar decreased sodium adsorption ratio and increased nitrogen use efficiency. • 6–12 t ha–1 biochar maintained crop yields while fertilizer use was reduced by 25%. Soil salinity and its associated soil compaction and low fertility is a big problem for land management in the arid region or coastal zone. Here, a low-cost and potassium (K)-rich biochar of reed (phragmites communis) was demonstrated effective in alleviating the problem in wheat-maize rotation in the Yellow River Delta region. Adding the biochar at 0, 3, 6, and 12 t ha–1 to a soil with a 2.8‰ salt content via rotary tillage with straw returning, with or without fertilizers, reduced soil bulk density (BD) and increased saturated hydraulic conductivity (K s). At 12 t ha–1 dose and by wheat and maize harvests, respectively, biochar lowered soil BD by 9.1% and 14.5%, increased K s by 82.7% and 91.2%, and reduced sodium adsorption ratio (SAR) by 64.9% and 92.8% in comparison with the control (CK). Further, in comparison with conventional fertilization (CF: 375 kg ha–1 for each crop), biochar use (6 and 12 t ha–1), together with 75% of CF, enhanced the nitrogen use efficiency (NUE) by 20.5%–31.4% for wheat and 15.9%–30.9% for maize. It raised the yields of wheat by 11.3%–17.1% and maize by 9.7%–14.8%. By reducing BD, increasing K s, and decreasing SAR, biochar alleviated soil compaction and salt stress and increased NUE and crop yields. This outcome suggests that the conversion of local bio-waste into biochar as a soil amendment is of agronomic and environmental benefits. [ABSTRACT FROM AUTHOR]

• Water conservation is the best way to increase water management efficiency in agriculture and reduce potential negative environmental impacts. • Residue improves soil tilth and adds organic matter to the soil as it decomposes. • Crop residue can reduce the rate of water evaporation and runoff, increase penetration of water and therefore improve soil water conservation. Wheat (Triticum aestivum L.) residues and water management are major problems in southern part of Iran where irrigated wheat-corn (Zea mays L.)-wheat rotation is a common practice. A 2-year (2015–2016) field experiment was conducted as a split plot design with four replications to determine the influence of different irrigation regimes (50, 70, and 100% of water requirement) and wheat residue rates (0, 25, and 50%) incorporation into the soil on sweet corn (Zea mays L V. Saccharata) growth, grain yield, and some soil properties at School of Agriculture, Shiraz University, Shiraz, Iran. The results showed that the highest plant height (187.12 cm) and leaf area index (3.49) were obtained when the crop was normally irrigated (100% of water requirement) and sown into the 25% incorporated wheat residues. Furthermore, canned yield (68%) and water use efficiency (WUE) increased with normal irrigation and 25% residue incorporation compared to the 50% wheat residue rate. The highest grain protein (14.67%) was achieved under incorporation of either 25 or 50% wheat residue into the soil, while the highest grain sugar (2643.5 mg g−1) was obtained when the crop was moderately irrigated (70% of water requirement) with 25% residue incorporation into the soil. The highest soil nitrogen (N) and soil organic carbon (SOC) were achieved with normal irrigation and 50% residue incorporation in both years.In general, adopting an adequate rate of wheat residue (between 25%–50%) accompanied by decreasing irrigation volume to 70% water requirement of corn is recommended in semi-arid agroecosystems. [ABSTRACT FROM AUTHOR]