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Determining the best management practices (BMPs) for farmland under different soil textures can provide technical support for improving maize yield, water- and nitrogen-use efficiencies (WUE and NUE), and reducing environmental N losses. In this study, a two-year (2013–2014) maize cultivation experiment was conducted on two pieces of farmland with different textural soils (loamy clay and sandy loam) in the Phaeozems zone of Northeast China. Three N fertilizer treatments were designed for each farmland: N168, N240, and N312, with N rates of 168, 240, and 312 kg ha−1, respectively. The WHCNS (soil Water Heat Carbon Nitrogen Simulator) model was calibrated and validated using the observed soil water content, soil nitrate concentration, and crop biological indicators. Then, the effects of soil texture combined with different N rates on maize yield, water consumption, and N fates were simulated. The integrated index considering the agronomic, economic, and environmental impacts was used to determine the BMPs for two textural soils. Results indicated that simulated soil water content and nitrate concentration at different soil depths, leaf area index, dry matter, and grain yield all agreed well with the measured values. Both soil texture and N rates significantly affected maize yield, N fates, WUE, and NUE. The annual average grain yield, WUE, and NUE under three N rates in sandy loam soil were 8257 kg ha−1, 1.9 kg m−3, and 41.2 kg kg−1, respectively, which were lower than those of loam clay, 11440 kg ha−1, 2.7 kg m−3, and 46.7 kg kg−1. The order of annual average yield and WUE under two textural soils was N240 > N312 > N168. The average evapotranspiration of sandy loam (447.3 mm) was higher than that of loamy clay (404.9 mm). The annual average N-leaching amount of different N treatments for sandy loam ranged from 5.1 to 13.2 kg ha−1, which was higher than that of loamy clay soil, with a range of 1.8–5.0 kg ha−1. The gaseous N loss in sandy loam soil accounted for 14.7% of the fertilizer N application rate, while it was 11.1%in loamy clay soil. The order of the NUEs of two textural soils was: N168 > N240 > N312. The recommended N fertilizer rates for sandy loam and loamy clay soils determined by the integrated index were 180 and 200 kg ha−1, respectively. [ABSTRACT FROM AUTHOR]

Experiments were conducted to study the adsorption kinetics and isothermal adsorption mechanism of nitrification inhibitor nitrapyrin onto the black soil of northeastern China. The nitrapyrin adsorption kinetics of the black soil were fitted with a quasi-second-order kinetics equation before and after organic matter removal (R2 ≥ 0.8320, p <.05). The adsorption isotherm was obtained by the Langmuir equation (R2 ≥ 0.9400, p <.05). Isothermal adsorption requires less energy and is a spontaneous endothermic reaction with an L-type isothermal curve (n > 1), dominated by surface physical adsorption. With the decrease of organic matter content in black soil, the adsorption mechanism of nitrapyin changed from distribution mechanism to surface adsorption. The black soil's organic matter content exhibited a quadratic relation with the maximum adsorption capacity and adsorption constant (Kf) at the different temperatures, reaching significant levels (R2 ≥ 0.6484, p <.05). [ABSTRACT FROM AUTHOR]

To increase crop productivity while reducing environmental costs, an integrated soil–crop system management (ISSM) strategy was developed and successfully adopted in China. However, little information is available on the long-term ISSM effects on maize agronomic and environmental performance. Therefore, we evaluated the effects of ISSM with combining inorganic and organic fertilizers on maize productivity, N use efficiency (NUE) and N balance and losses as compared with farmers' practice (FP) and high-yielding practice (HY), based on an 11-year field experiment in Northeast China. Maize yield in ISSM (11.7–14.3 Mg ha−1) achieved 97.7% of that in HY and was increased by 27% relative to FP. The excellent yield performance in ISSM was mainly attributed to optimum plant population structure and yield components. Annual N surplus in ISSM was only 7 kg ha−1, which was considerably lower than that in FP (52 kg ha−1) and HY (109 kg ha−1). Consequently, ISSM obtained significantly lower N losses and greenhouse gases emissions and higher NUE. In contrast to FP, crop performance in ISSM showing better sustainability and inter-annual stability. In conclusion, ISSM is an effective strategy to achieve long-term sustainable high crop yields and NUE with less environmental costs in the intensive agricultural system. [ABSTRACT FROM AUTHOR]

• Rectangular MZs providing a basis for site-specific management in the maize field. • Correlations of soil-crop attributes and yield varied across MZs and growth stages. • Main factors' contributions to yield had various characteristics among MZs. Spatial variability of soil properties, crop performance, fertilization management, and tillage methods play an important role in yield prediction and improvement. However, the farm nutrient management in most regions of the world is still based on conventional and uniform management strategies, without take into consideration the spatial variability of the above factors. Therefore, the objectives of this study were to delineate potential management zones (MZs), with the considering of spatial variability of soil properties, crop performance, fertilization management, tillage methods, and investigate their relationships with yield, and their contributions to yield in each management zone. A 1.60 ha maize field with fertilizer and tillage management, in Lishu County, Jilin Province, China, was selected as the study area and soil samples with soil organic matter, total nitrogen and soil pH measured values, crop samples with crop height, leaf nitrogen content, above ground biomass at V6, silking, and maturity growth stages, and yield measured values were collected in 2019 and 2020. Firstly, the rectangular MZs were defined to divide the study area into relatively homogeneous areas based on the spatial variability of soil properties, crop performance, and yield of 2019 and 2020. Secondly, the correlations of soil properties and crop performance with yield were obtained across MZs and growth stages in 2019 and 2020. Lastly, the yield prediction models were established based on the above four types of factors by using random forest (RF) model and the contributions of main factors were obtained quantitatively across different MZs and years. The results showed that (1) the small maize field was divided into three rectangular MZs and most of the soil and crop attributes presented homogeneous characteristics in each zone; (2) correlations of soil properties and crop performance with yield varied across different MZs and growth stages, and even different years; (3) RF model obtained good performance across MZs and years, with R2 = 0.86 and RMSE = 0.77 kg/ha in 2019 and R2 = 0.89 and RMSE = 1.04 kg/ha in 2020 both for the whole field. The contribution of main factors for yield varied across both MZs and years, while some characteristics of the main factors' contributions remain unchanged. This study would open the opportunity to farmers and agricultural experts for site-specific nutrient management in the maize field. [ABSTRACT FROM AUTHOR]

• Crop height explained the most variability in maize AGB estimation of V6 stage. • EVI and VARI were selected as the most important narrowband VIs at the R1 stage. • mSR 705 , Vi opt , SRPI, REIP-LI, NDI, Maccioni were important VIs at the R3 stage. • XGBoost model outperformed stepwise and RF regression model in maize AGB estimation. • UAV-based hyperspectral imagery has some advantages for AGB estimation. Monitoring the aboveground biomass (AGB) of maize is essential for improving site-specific nutrient management and predicting yield to ensure food safety. A low-altitude unmanned aerial vehicle (UAV) was employed to acquire hyperspectral imagery of the maize canopy at three growth stages (V6, R1, R3) to estimate the maize AGB. Five maize nitrogen (N) rate experiments were conducted in Lishu County, Jilin Province, Northeastern China, to create different biomass conditions. Combined with crop height data obtained from the field measurements, 30 narrowband vegetation indices (VIs) were extracted using surface reflectance data from the hyperspectral imagery. Stepwise regression, random forest (RF) regression and XGBoost regression models were used to predict the fresh and dry AGB of the 2019 growth season. The study revealed that (1) crop height explained the most variability (60–70%) in the maize dry and fresh AGB estimation of the V6 growth stage, while different VIs exhibited various importance for AGB estimation at other maize growth stages; (2) XGBoost regression models demonstrated high prediction accuracy in both fresh and dry AGB estimation, compared with stepwise regression and RF models. (3) XGBoost models also presented high prediction accuracy at each single-growth stage and the whole-growth stage, with the highest accuracy for the dry AGB at V6 growth stage (R2 = 0.81, RMSE = 0.27 t/ha). This study demonstrated the capability of UAV-based hyperspectral imagery for estimating maize AGB at the field scale, which can be used to assist precision agriculture. [ABSTRACT FROM AUTHOR]

Agricultural production in China is facing great challenges to ensure food security and cleaner environment; further improvements are therefore required in crop nutrient management to increase grain yield and nutrient use efficiency while synchronously reducing environmental pollution. In this study, a total of 87 site-years of on-farm experiments were conducted from 2013 to 2018 in the main agro-ecological areas in Northeast China, to evaluate the agronomic and environmental benefits of nutrient expert (NE) system in maize and rice production. Results showed that NE had general and significant advantages in agronomic and environmental benefits relative to FP, by dramatically reducing N and P fertilizer inputs and optimizing nutrient management. As compared to FP, on average, NE increased grain yield by 8.4% and 6.6% significantly higher grain yield and N uptake for maize, respectively, while it obtained equal yield performance and 3.0% higher N uptake for rice, and consequently resulted in significantly higher N use efficiency. Environmental effects assessment showed that NE reduced substantially reactive N losses and greenhouse gas emissions by 46.9% and 37.2% for maize, respectively, and 10.1% and 6.6% for rice, respectively. Regression analysis indicated that NE effectively improved N use efficiency and mitigated environmental pollution was mainly associated with increasing plant N uptake and reduced N surplus. As compared to fertilization recommendation based on soil testing, NE system showed higher N use efficiency and better environmental benefits for both maize and rice. In conclusion, our results demonstrated that NE system is a feasible and promising approach to optimize crop nutrient management and promote cleaner agricultural production in Northeast China.