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BACKGROUND: Optimizing biochar application is vital for enhancing crop production and ensuring sustainable agricultural production. A 3‐year field experiment was established to explore the effects of varying the biochar application rate (BAR) on crop growth, quality, productivity and yields. BAR was set at 0, 10, 50 and 100 t ha−1 in 2018; 0, 10, 25, 50 and 100 t ha−1 in 2019; and 0, 10, 25 and 30 t ha−1 in 2020. Crop quality and growth status and production were evaluated using the dynamic technique for order preference by similarity to ideal solution with the entropy weighted method (DTOPSIS‐EW), principal component analysis (PCA), membership function analysis (MFA), gray relation analysis (GRA) and the fuzzy Borda combination evaluation method. RESULTS: Low‐dose BAR (≤ 25 t ha−1 for cotton; ≤ 50 t ha−1 for sugar beet) effectively increased biomass, plant height, leaf area index (LAI), water and fertility (N, P and K) productivities, and yield. Biochar application increased the salt absorption and sugar content in sugar beet, with the most notable increases being 116.45% and 20.35%, respectively. Conversely, BAR had no significant effect on cotton fiber quality. The GRA method was the most appropriate for assessing crop growth and quality. The most indicative parameters for reflecting cotton and sugarbeet growth and quality status were biomass and LAI. The 10 t ha−1 BAR consistently produced the highest scores and was the most economically viable option, as evaluated by DTOPSIS‐EW. CONCLUSION: The optimal biochar application strategy for improving cotton and sugar beet cultivation in Xinjiang, China, is 10 t ha−1 biochar applied continuously. © 2024 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

The leaf area index (LAI) is a crucial physiological indicator of crop growth. This paper introduces a new spectral index to overcome angle effects in estimating the LAI of crops. This study quantitatively analyzes the relationship between LAI and multi-angle hyperspectral reflectance from the canopy of winter oilseed rape (Brassica napus L.) at various growth stages, nitrogen application levels and coverage methods. The angular stability of 16 traditional vegetation indices (VIs) for monitoring the LAI was tested under nine view zenith angles (VZAs). These multi-angle VIs were input into machine learning models including support vector machine (SVM), eXtreme gradient boosting (XGBoost), and Random Forest (RF) to determine the optimal monitoring strategy. The results indicated that the back-scattering direction outperformed the vertical and forward-scattering direction in terms of monitoring the LAI. In the solar principal plane (SPP), EVI-1 and REP showed angle stability and high accuracy in monitoring the LAI. Nevertheless, this relationship was influenced by experimental conditions and growth stages. Compared with traditional VIs, the observation perspective insensitivity vegetation index (OPIVI) had the highest correlation with the LAI (r = 0.77–0.85). The linear regression model based on single-angle OPIVI was most accurate at −15° (R2 = 0.71). The LAI monitoring achieved using a multi-angle OPIVI-RF model had the higher accuracy, with an R2 of 0.77 and with a root mean square error (RMSE) of 0.38 cm2·cm−2. This study provides valuable insights for selecting VIs that overcome the angle effect in future drone and satellite applications. [ABSTRACT FROM AUTHOR]

Drip fertigation (DF) is a widely used technology to increase grain yield with water and fertilizer conservation. However, the mechanism of high grain yield (GY) under DF is still unclear. Here, a four-year field experiment assessed the impacts of four treatments (i.e., conventional irrigation and nitrogen application, CK; drip irrigation with conventional nitrogen fertilization, DI; split-nitrogen fertigation with conventional irrigation, SF; and drip fertigation, DF) on maize phenology, leaf photosynthetic rates, grain filling processes, plant biomass, and GY. The results showed that DF significantly increased maize GY by affecting phenology, grain filling traits, aboveground biomass (BIO) accumulation, and translocation. Specifically, DF significantly increased leaf chlorophyll content, which enhanced leaf photosynthetic rates, and together with an increase of leaf area index, promoted BIO accumulation. As a result, the BIO at the silking stage of DF increased by 29.5%, transported biomass increased by 109.2% (1.2 t ha−1), and the accumulation of BIO after silking increased by 23.1% (1.7 t ha−1) compared with CK. Meanwhile, DF prolonged grain filling days, significantly increased the grain weight of 100 kernels, and promoted GY increase. Compared with CK, the four-year averaged GY and BIO increased by 34.3% and 26.8% under DF; a 29.7%, 46.1%, and 24.2% GY increase and a 30.7%, 39.5%, and 29.9% BIO increase were contributed by irrigation, nitrogen, and coupling effects of irrigation and nitrogen, respectively. These results reveal the high yield mechanism of drip-fertigated maize, and are of important significance for promoting the application of drip fertigation. [ABSTRACT FROM AUTHOR]

Ridge and furrow plastic mulch (RFPM) and nitrogen (N) application are effective strategies for improving crop productivity in China's Loess Plain. However, it is not clear how the ridge–furrow ratio and nitrogen fertilizer type (NT) affect the use of water, nitrogen, heat, and radiation resources for the enhancement of rain-fed wheat production. Two nitrogen fertilizer types (traditional urea (TU) and controlled-release urea (CRU)) and four planting patterns (conventional flat planting (F) and the RFPM system of 20 cm ridges with 40 cm furrows (R2F4), 40 cm ridges with 40 cm furrows (R4F4), and 60 cm ridges with 40 cm furrows (R6F4)) were tested from September 2018 to June 2021 during the winter wheat growing season. It was found that the RFPM system can increase soil thermal time (TTsoil) from 41.0 to 152.1 °C d compared to the F. RFPM system thermal effect, which reduced the vegetative growth period and prolonged the reproductive growth period for 2 to 7 days, which promoted an increase in the leaf area index (LAI) and final dry matter (DM) accumulation. These significantly increased the grain yield (GY) in the RFPM system by 51.6–115.2% and enhanced the thermal time use efficiency (TUE) by 48–99.5%, water productivity (WP) by 37.4–76.3%, radiation use efficiency (RUE) by 16.3–34.4%, and partial factor productivity of nitrogen (PFPN) by 51.6–115.2% compared to F. Although a high ridge and furrow ratio in combination with CRU increased the GY and resource use efficiency, it also exacerbated the soil water depletion, especially in the soil layer between 40 and 140 cm. Overall, CRU combined with the 40 cm ridge and 40 cm furrow RFPM system maximized resource efficiency and increased wheat production on China's Loess Plateau. [ABSTRACT FROM AUTHOR]

Leaf area index (LAI) is essential for evaluating crop growth and development. Destructive manual measurement methods mainly achieve traditional crop LAI acquisition. Due to the advantages of being fast and non-destructive, spectroscopy technology provides a feasible method for obtaining crop LAI. In order to achieve efficient acquisition of winter oilseed rape LAI, this study collected hyperspectral data and LAI data at the full-bloom stage of winter oilseed rape. It calculated the spectral indexes related to the LAI of the original spectrum and the first-order differential spectrum, respectively. The index with the highest correlation with the LAI of winter oilseed rape at the flowering stage was selected as the optimal spectral index for input. Subsequently, three machine learning methods, Back Propagation Neural Network (BPNN), Support Vector Machine (SVM), and Random Forest (RF), were used to construct the LAI model of winter oilseed rape, and the model was tested. The results show that the correlation coefficient between the spectral index calculated by the first-order differential processing of the original spectral data and the LAI of winter rapeseed is significantly improved compared with the original data. Among them, the spectral index NDVI with the best correlation coefficient with LAI can be obtained under the first-order differential: the correlation coefficient is 0.734, and the wavelength combination is 716 nm and 724 nm. At the same time, we found that when the input variables are the same, the RF model has higher estimation accuracy than the other models. The best estimation accuracy is obtained when the input variable is the first-order differential spectral index. The R2 of the model validation set is 0.810, RMSE is 0.455 cm2/cm2, MRE is 10.465%, and the model accuracy is high. The results of this study can provide a theoretical basis for crop monitoring based on spectral technology and provide a theoretical basis for crop growth. [ABSTRACT FROM AUTHOR]

Leaf area index (LAI) and above-ground biomass are both vital indicators for evaluating crop growth and development, while rapid and non-destructive estimation of crop LAI and above-ground biomass is of considerable significance for crop field management. Owing to the advantages of repeatable and high-throughput observations, spectral technology provides a feasible method for obtaining LAI and above-ground biomass of crops. In the present study, the spectral, LAI and above-ground biomass data of winter wheat were collected, and 7 species (14 in total) were calculated based on the original and first-order differential spectrum correlation spectral indices with LAI. Then, the correlation matrix method was used for correlation with LAI. The optimal wavelength combination was extracted, and the results were calculated as the optimal spectral index related to LAI. The calculation process of the optimal spectral index related to above-ground biomass was the same as that aforementioned. Finally, the optimal spectral index was divided into three groups of model input variables, winter wheat LAI and above-ground biomass estimation models were constructed using support vector machine (SVM), random forest (RF) and a back propagation neural network (BPNN), and the models were verified. The results show that the correlation coefficient between the highest of the optimal spectral indices, the LAI, and the above-ground biomass of winter wheat exceeded 0.6, and the correlation was good. The methods for establishing the optimal estimation models for LAI and above-ground biomass of winter wheat are all modeling methods in which the input variables are the combination of the first-order differential spectral index (combination 2) and RF. The R2 of the LAI estimation model validation set was 0.830, the RMSE was 0.276, and the MRE was 6.920; the R2 of the above-ground biomass estimation model validation set was 0.682, RMSE was 235.016, MRE was 4.336, and the accuracies of both models were high. The present research results can provide a theoretical basis for crop monitoring based on spectral technology and provide an application reference for the rapid estimation of crop growth parameters. [ABSTRACT FROM AUTHOR]

The effects of water and nutrient control measures on the cotton plant height, stem diameter, biomass, seed yield, and soil moisture under an irrigated plastic mulch production system were studied. Using field experiments in the 2018 cotton-growing season, 6 fertilization treatments (30-10.5-4.5 (N-P2O5-K2O), 24-8.4-3.6 (N-P2O5-K2O), 20-7-3 (N-P2O5-K2O), 16-5.6-2.4 (N-P2O5-K2O), 10-3.5-1.5 (N-P2O5-K2O), and 0-0-0 (N-P2O5-K2O) kg/mu) and 6 deficit irrigation treatments (40% PET, 60% PET, and 80% PET) were established at the cotton budding and flowering stages. Analysis of variance (ANOVA) (P < 0.05) was used to evaluate the significant differences among the treatments. The results showed that the effects of the water and nutrient control measures were obvious. The irrigation water use efficiency (IWUE) was the highest under the 80% deficit irrigation (T7) treatment at the flowering stage (2.62 kg/m3). Increases in cotton plant height and stem diameter were promoted by mild or moderate deficit irrigation at the flowering stage, but normal growth and development were affected by severe deficit irrigation at any growth stage. The growth indexes of cotton increased with increasing fertilization, but significant differences between each fertilization gradient were not obvious. At the same time, excessive fertilization not only had a positive effect on the LAI (leaf area index) and yield but also caused fertilizer waste and unnecessary cotton growth. The cotton seed yield and single boll yield reached their highest values (566 kg/mu) under the 1.2 times fertilizer treatment (T9), but the 0.8 times fertilizer treatment had the highest IWUE among the nutrient control treatments (1.91 kg/m3). Therefore, it is suggested that deficit irrigation at 60~80% of the potential evapotranspiration (PET) at the flowering stage and 16-5.6-2.4 (N-P2O5-K2O) fertilizer be applied as an optimal water and nutrient management strategy to maximize the seed cotton yield, IWUE, and overall growth and development of cotton. [ABSTRACT FROM AUTHOR]

• Irrigation and fertilization effects on maize yield, grain nitrogen accumulation and economic benefit were explored. • Grain yield and grain nitrogen accumulation were highest under I 90 F 300-150-150. • Soil NO 3 −-N increased with increasing fertilization rate, but decreased with increasing irrigation amount. • Irrigation of 447∼452 mm and N-P 2 O 5 -K 2 O of 290-145-145∼303-152-152 kg ha−1 were recommended. Inappropriate water and fertilizer management can lead to unstable crop yield, and excessive irrigation and fertilization can potentially cause soil degradation and groundwater pollution. A two-year field experiment was conducted on drip-fertigated spring maize (Zea mays L.) in Ningxia of northwest China to explore the effects of four irrigation amounts (I 75 : 0.75 ET c , I 90 : 0.90 ET c , I 105 : 1.05 ET c and I 120 : 1.20 ET c , where ET c is the crop evapotranspiration) and four N-P 2 O 5 -K 2 O fertilization rates (F 60-30-30 , F 120-60-60 , F 180-90-90 and F 240-120-120 in 2016; F 150-70-70 , F 225-110-110 , F 300-150-150 and F 375-180-180 in 2017) on maize growth, grain yield, grain nitrogen accumulation, economic benefit and soil nitrate residue (NO 3 -N). Considering the goal of conserving both water and fertilizer while maintaining relatively high yields and minimizing soil NO 3 -N, a management strategy to optimize irrigation and fertilization regimes was developed based on the response surface methodology. The results showed that irrigation amount and fertilization rate significantly affected leaf area index, aboveground biomass, grain yield and harvest index. The irrigation-fertilization interaction significantly affected plant and grain nitrogen accumulation. In 2016 with lower fertilization range, grain yield and grain nitrogen accumulation were highest under I 120 F 240-120-120 , reaching 14,440 kg ha-1 and 184.50 kg ha-1, respectively. In 2017 with higher fertilization range, both grain yield and grain nitrogen accumulation initially increased and then decreased with increasing irrigation and fertilization regimes. Grain yield and grain nitrogen accumulation were highest under I 90 F 300-150-150 , reaching 16,884 kg ha-1 and 195.09 kg ha-1, respectively. Although plant nitrogen uptake was dramatically higher under I 90 F 375-180-180 than those in the other treatments, grain yield was markedly lower under I 90 F 300-150-150 and nitrogen harvest index was also lower. Soil NO 3 −-N increased with increasing fertilization rate, but it decreased with increasing irrigation amount. When irrigation amount and fertilization rate increased at the same time, the soil NO 3 −-N accumulation area moved deeper in the soil profile. Soil NO 3 --N content and distribution in the 60−100 cm soil layer showed an increasing trend, but this trend was less obvious than that in the 0−60 cm soil layer. When the irrigation amount was 447−452 mm and the N-P 2 O 5 -K 2 O fertilization rate ranged from 290−145-145 to-303−152-152 kg ha-1, grain yield, grain nitrogen accumulation and economic benefit (≥13,688 CNY ha-1) can reach 95 % confidence interval of their maximum values simultaneously. This study can provide a theoretical basis for high-efficient water and fertilizer utilization in sustainable spring maize (Zea mays L.) production in northwest China. [ABSTRACT FROM AUTHOR]

• The CSM-CROPGRO-Cotton model was modified for drip irrigation under plastic film mulch. • The calculation of potential evapotranspiration, extinction coefficients and soil evaporation were improved. • The genetic coefficients of cotton were determined using data from different irrigation treatments. • The modified model well simulated cotton growth and soil water content under film-mulched drip irrigation. Cotton is one of the major cash crops in Xinjiang, an arid region in northwestern China. Most cotton fields in this region are drip irrigated with plastic film mulch. However, few studies have tested the performance of the DSSAT (Decision Support System for Agrotechnology Transfer) model on cotton under film-mulched drip irrigation. The objective of this study is to evaluate the performance of the modified CSM-CROPGRO-Cotton model and determine the genetic coefficients of cotton using data from different irrigation treatments conducted at the irrigation experiment station in Bayingol Mongolian Autonomous Prefecture, Korla, China. Based on the selected genetic coefficients, the model was calibrated using field experiment datasets in 2016 and validated using datasets in 2015. The simulation results of soil water content, leaf area index, phenological period and cotton yield were compared with their corresponding measurements. Absolute relative error (ARE) of seeding emergence date, flowing date, maturity date and cotton yield simulated by the original model were 5.8%, 7.3%, 5.0% and 70.6%, respectively, while those of the modified model were 1.7%, 1.1%, 1.1% and 0.1%, respectively. Simulated leaf area index agreed well with the field observations with the coefficient of determination (R2) > 0.739, the index of agreement (d) > 0.910 and the root mean square error (RMSE) < 0.965. Simulated soil water content in the 20–40 cm soil layer were generally consistent with the measured values with R2 = 0.724, d = 0.639 and RMSE = 0.087 cm3/cm3, while the simulated soil water content in the 40–60 cm was slightly worse than the observations with R2 = 0.708, d = 0.519 and RMSE = 0.109 cm3/cm3. Overall, the modified CSM-CROPGRO-Cotton model can be used as a practical tool to simulate the cotton growth under film-mulched drip irrigation in this region. Potential opportunities for the model improvement in cotton growth include the influence of various scenarios such as soil types, climates and irrigation strategies. [ABSTRACT FROM AUTHOR]

The knowledge of seasonal nutrient demand is necessary for maximizing potato yield and resources use efficiency under drip fertigation, and it also can effectively mitigate the risk of nutrient leaching caused by excessive fertilization. To explore the coupling effects of irrigation level and fertilization rate on drip-fertigated potato growth, nutrient accumulation and determine the multi-objective optimal irrigation and fertilization regimes, a two-year (2018 and 2019) field experiment was conducted in the sandy regions of northern China. The experiments included three irrigation levels (I 60 , 60% ET C ; I 80 , 80% ET C and I 100 , 100% ET C , where ETc is the crop evapotranspiration) and five fertilization rates (N 0 P 0 K 0 , 0 kg ha−1; N 1 P 1 K 1 , 100–17.5–124.5 kg ha−1; N 2 P 2 K 2 , 150–26.2–186.7 kg ha−1; N 3 P 3 K 3 , 200–34.9–248.9 kg ha−1 and N 4 P 4 K 4 , 250–43.7–311.2 kg ha−1, where the ratio of N, P and K was 1:0.17:1.24). The results showed that N, P and K accumulated rapidly from 42th to 95th, 50th to 96th and 46th to 91th days after sowing, respectively. For producing 1000 kg tuber yield, the required amounts of N, P and K were 1.97–4.16 kg, 0.55–0.81 kg and 4.83–7.65 kg, respectively. The uptakes of N, P and K in 1000 kg tubers across all treatments were 1:0.18–0.34:1.61–2.59, with the average N:P:K ratio of 1:0.23:2.05. Besides, irrigation level, fertilization rate and their interaction had significant effects on potato leaf area index, biomass, N, P and K accumulation. Deficit irrigation reduced seasonal LAI, biomass, N, P and K accumulation, tuber yield and apparent fertilizer recovery (AFR), but increased water productivity. High fertilization rate was conducive to promoting nutrient absorption, plant growth and improving tuber yield, while it reduced the unit nutrient productivity. The AFR increased first and then decreased with the increase of fertilization rate. To simultaneously achieve high potato yield and resources use efficiency, a multi-objective optimization model was established using the binary quadratic regression analysis between tuber yield, net income, water productivity, AFR and water–fertilizer regimes, which showed that tuber yield, net income, water productivity, and AFR could obtained ≥ 90% of their maximum values simultaneously when the irrigation interval was 204–262 mm and fertilization (N-P-K) interval ranged from 200–24–248 to 247–42–306 kg ha−1. The findings can provide useful information for optimizing irrigation and fertilization regimes in sandy regions of northern China. ● Nutrient uptake process under virous drip fertigation combinations was explored. ● Water and fertilization had significant effects on nutrient accumulation and yield. ● 1.97–4.16 kg N, 0.55–0.81 kg P and 4.83–7.65 kg K were needed to produce 1 t tuber. ● Interval of fertigation was put forward through a multi-objective optimization model. [ABSTRACT FROM AUTHOR]

Rainfall or sprinkler irrigation water partitioning by the crop canopy is an important way of affecting the effective use of water by maize. To investigate the rainfall partitioning by maize canopy at different growth stages as well as its influencing factors on the water-limited Loess Plateau of China, the gross rainfall, throughfall and stemflow were measured during the growing seasons of 2015 and 2016. The effects of rainfall characteristics (gross rainfall and rainfall intensity) and canopy structure (leaf area index) on rainfall partitioning were further evaluated, based on which multiple regression models were developed to predict the partitioned rainfall components. Results showed that the measured throughfall, stemflow and derived interception loss accounted for 65.2%, 22.3% and 12.5% of cumulative gross rainfall during the whole growing season of maize, respectively. Specifically, the relative throughfall declined from 83.2% at the seedling stage to 52.2% at the tasseling stage, and then increased to 58.6% at the maturity stage. The relative stemflow and interception loss increased from 13.6% and 3.1% at the seedling stage to 30.6% and 17.3% at the tasseling stage, and then declined to 25.0% and 16.5% at the maturity stage, respectively. Smaller rainfall events contributed to a lower percentage of throughfall and stemflow but higher percentage of canopy interception loss. The percentages of stemflow and throughfall showed an increased tendency with increasing gross rainfall and rainfall intensity, while the increasing leaf area index resulted in a decrease in the relative throughfall but an increase in relative stemflow and interception loss. Generally, the amount of throughfall, stemflow and canopy interception loss can be predicted reasonably well using the developed multiple linear regression models, but the proportions of partitioned rainfall components generally had a relatively lower accuracy using the developed nonlinear models, especially for relative stemflow. This study can help to determine more precise irrigation schedule by the water balance method and give implications for the operation of sprinkler irrigation systems for higher irrigation water use efficiency. [ABSTRACT FROM AUTHOR]

• Multi-angle spectral-texture observation presents new opportunity for diagnosis. • Non-nadir spectral-texture observation cover more crop growth information. • Stacking ensemble can effectively integrate multiple spectral-texture features. The leaf chlorophyll content (LCC) and leaf area index (LAI) play a crucial role in assessing crop growth status and optimizing field water-fertilizer management. Compared to labor-intensive traditional measurement methods, low-cost unmanned aerial vehicle (UAV) remote sensing technology provides a unique opportunity for monitoring small-scale farmland crop growth information. Currently, the estimation method combining machine learning with spectral or texture information from UAV images has attracted much attention. However, most studies commonly used spectral or texture information from vertical observation, and the potential of multi-angle spectral-texture information has not been fully explored. Meanwhile, the simultaneous usage of multiple characteristic information increases the computational complexity of the model, presenting challenges for crop growth parameter estimation. To address this, this study proposes a multi-feature fusion framework for canola growth parameter estimation using stacking-based ensemble learning algorithm. Firstly, 17 spectral features (VI s and Band) and 136 texture features (TF s) are extracted from UAV spectral images with seven view zenith angle (Nadir, ±20◦, ±40◦ and ± 60◦), respectively. Secondly, important feature variables are selected through correlation analysis and then feature datasets are constructed. Finally, a base learners-meta learner stacking structure was employed to ensemble four machine learning models (SVM,PLSR,RF and GBDT) to predict canola growth parameters. The result shows that: (1) Compared with nadir observation, off-nadir observations (especially for −20◦ and −40◦) can provide more spectral-texture information related to canola growth; (2) The stacking-based ensemble learning can achieve accurate estimation of canola LAI (R2 = 0.72; RMSE = 0.74) and LCC (R2 = 0.78; RMSE = 6.4 ug/cm 2); (3) Compared with single machine learning model (LAI: R2 = 0.56 ∼ 0.67, RMSE = 0.87 ∼ 1.08; LCC: R2 = 0.56 ∼ 0.75, RMSE = 8.1 ∼ 10.6 ug/cm 2), the stacking-based ensemble learning has advantage in growth parameters estimation. The corresponding spatiotemporal mapping reflects the impact of field treatment on the canola growth. Overall, These above results demonstrate the application value of multi-angle spectral-textural information and stacking-based ensemble learning in accessing crop growth, providing new insights into remotely quantitative diagnosis of crop growth. [ABSTRACT FROM AUTHOR]

High crop water productivity (WP c) and fertilizer use efficiency are the key to ensuring the sustainable development of agriculture in water-deficient areas, such as the northwest China. In order to determine the irrigation amount and potassium rate for optimizing potato yield, plant potassium accumulation and WP c of drip-irrigated potato, a two-year field experiment was conducted on the Loess Plateau of northwest China, with three irrigation levels (W1: 60% ET c , W2: 80% ET c and W3: 100% ET c , where ET c is the crop evapotranspiration) and four potassium levels (K0: kg ha−1, K1: 135 kg ha−1, K2: 270 kg ha−1 and K3: 405 kg ha−1). The results showed that leaf area index, chlorophyll content, aboveground dry matter, tuber yield, starch, vitamin C content and WP c generally increased with the increase of irrigation amount, while they first increased and then decreased with the increasing potassium rate. The trends of reducing sugar and potassium use efficiency were contrary to the above trends. The residue of available potassium in the soil increased with the increase of potassium rate, but decreased with the increase of irrigation amount. Irrigation amount and potassium rate had interaction effects on chlorophyll content, dry matter, tuber yield, reducing sugar, plant potassium accumulation and potassium use efficiency. To ensure high-yield, high-quality, water-saving and fertilizer-saving potato production, a water input (irrigation plus effective rainfall) range of 498–520 mm combined with a potassium rate range of 201–393 kg ha−1 was recommended. These results can provide a theoretical basis for the rational application of irrigation water and potassium fertilizer to improve tuber yield, quality and soil environment of drip-irrigated potato in northwest China. • Coupling effects of irrigation amount and potassium rate on potato yield, quality and water productivity were explored. • Significant correlations existed between yield and chlorophyll content, dry matter, starch and reducing sugar content. • Irrigation and potassium had coupling effects on chlorophyll, dry matter, yield, reducing sugar, potassium use efficiency. • Water input (irrigation plus rainfall) of 498–520 mm and potassium rate of 201–393 kg ha−1 were recommended. [ABSTRACT FROM AUTHOR]

In both arid and semi-arid regions, adopting field mulching can effectively optimize soil moisture distribution, enhance crop yields, and improve water productivity. While acknowledging its advantages, field mulching seems insufficient for maintaining high crop productivity due to the increasing frequency of extreme weather. Furthermore, drought often coincides with critical crop growth stages, necessitating the implementation of agricultural irrigation to ensure normal crop growth. Accordingly, we conducted a three-year field experiment from 2021 to 2023 including three typical field mulching methods (no mulching, NM; straw mulching, SM; plastic film mulching, FM) and three supplementary irrigation strategies (irrigated at the branching stage (V4), W1; irrigated at the pod-filling stage (R2), W2; irrigated at both the V4 and R2 stage, W3). Throughout the entire growth period, we monitored soil moisture conditions for each treatment, measured leaf physiological parameters at crucial growth stages, and assessed soybean yields and water productivity (WP). Our findings indicated that, relative to SM and NM, FM maintains optimal soil moisture balance, augments chlorophyll content, and enhances photosynthesis, resulting in an average yield increase of 17.0% and 38.3% over three growing seasons. Additionally, supplementary irrigation also significantly affects the growth and seed yield of soybean. FMW2 achieved the higher seed yield (4307.5 kg ha−1, 3-year averaged), had insignificant difference with the highest seed yield of 4568.6 kg ha−1, both significantly higher than other treatments. Similarly, the leaf area index, chlorophyll content, net photosynthetic rate (P n) and transpiration rate (T r) also presented insignificant difference between FMW2 and FMW3, while WUE leaf (P n /T r) of FMW2 obviously higher than that of FMW3. As a result, FMW2 achieved the highest WP of 12.2 kg ha−1 mm−1 over the three growing seasons, compared to the three-year average of the other treatments, the increase ranges from 5.6% to 46.7%. In summary, the FMW2 treatment optimized water distribution to meet the water demands of soybeans during the reproductive growth stages, achieving a beneficial balance between soybean seed production and WP by regulating leaf functional parameters. Future research will explore more specific irrigation scheduling techniques (e.g., precision irrigation, deficit irrigation, and sensor-based irrigation management systems) while integrating innovative agricultural film materials (e.g., biodegradable films) to further enhance crop resilience and productivity under evolving climatic conditions. • Both farmland mulching (FM) and supplementary irrigation (W) were used in this study. • FM increases yield by 17.0–38.3% and water productivity (WP) by 15.6–30.1%. • W in pod-filling stage raises yield by 12.0% and WP by 10.8% vs. in branching stage. • FM combined W at pod-filling stage simultaneously achieved higher yield and WP. [ABSTRACT FROM AUTHOR]

Formulating warning signals for canopy growth status at different stages are an effective way to dynamically regulate the water and fertilizer management based on the relationship between growth information and orchard productivity. In the study, the response of leaf nitrogen content (LNC), leaf area index (LAI), fruit yield, quality and water and nitrogen use efficiency to irrigation levels and nitrogen rates was investigated in a field experiment from 2017 to 2022. Principal component analysis was used to construct an orchard production comprehensive evaluation index (OPCEI) to assess orchard productivity, and the relationship between LAI, LNC and OPCEI was analyzed by the structural equation modeling. The results showed that nitrogen rates had significant effect on OPCEI in the different years, but irrigation levels had significant effect in 2019 and 2021. Compared to no fertilization, the OPCEI of 120, 240, and 360 kg ha−1 under low irrigation amount showed average increased 28.90%, 48.54%, and 25.85%, while it increased by an average of 33.51%, 55.65%, and 32.44% for 120, 240, and 360 kg ha−1 under high irrigation amount. Also, low irrigation amount did not significantly reduce OPCEI at 240 kg ha−1 compared to high irrigation amount. Structural equation modeling revealed that LNC had significant positive effect on fruit yield, while had significant negative effect on total soluble solids. Furthermore, LAI had a significant positive effect on fruit yield and sugar-acid ratio. On the basis of the relationship of LAI, LNC and OPCEI, the reference value of LNC was proposed. The suitable range of LNC in the shoot growth and young fruit stage is 2.96%-3.79% and 2.62%-3.30%, and that is 2.43%-3.17%, 2.21%-2.97%, and 2.13%-2.63% in the early, middle and late fruit expansion stage, respectively. The study results provide a basis for canopy nitrogen diagnosis, which is guide for achieving precise nitrogen application in apple orchards. • Orchard production comprehensive evaluation index is constructed. • Combing low irrigation amount and 240 kg N ha−1 obtain an optimal orchard productivity. • It is feasible that using leaf nitrogen content and leaf area index to assess orchard productivity. • The suitable range of leaf nitrogen content is determined in different growth stages. [ABSTRACT FROM AUTHOR]

Soil mulching can effectively modify the crop growth environment and increase crop productivity in rainfed agriculture. Accurate estimation of crop evapotranspiration (ET), especially its transpiration (T) component, is crucial for understanding the crop water use and predicting crop yield in agricultural ecosystems. Nevertheless, direct measurement of T in the field is often difficult, expensive, destructive and time-consuming. Daily rainfed maize T under four mulching methods (NM: non-mulching, SM: straw mulching, RPBF: plastic-mulched ridge with bare furrow, and RPSF: plastic-mulched ridge with straw-mulched furrow) was obtained from sap flow measurements over four maize growing seasons (2015–2018) in Northwest China. A modified Jarvis-Stewart model (MJS) and a support vector machine model optimized by the whale optimization algorithm (SVM-WOA) were further proposed to estimate daily maize T based on solar radiation (R s), vapor pressure deficit (VPD), soil water content (SWC) and leaf area index (LAI), which were compared to the simple multiple linear regression model (MLR). The three models were calibrated using data obtained in 2015 and 2017, and validated using data from 2016 and 2018. The measured seasonal T under SM, RPBF and RPSF was increased by 6.9–19.1%, 12.1–31.3% and 15.3–36.7% compared to that under NM, respectively. The SVM-WOA model (R2 = 0.83–0.89, RMSE = 0.55–0.73 mm d−1, MAE = 0.42–0.53 mm d−1) was superior to the MJS model (R2 = 0.61–0.79, RMSE = 0.75–1.12 mm d−1, MAE = 0.58–0.88 mm d−1) during validation, both of which greatly outperformed the MLR model (R2 = 0.57–0.60, RMSE = 1.28–1.41 mm d−1, MAE = 0.99–1.09 mm d−1) under various mulching methods. The prediction accuracy of the SVM-WOA and MJS models was improved by 47–57% and 19–41% in terms of RMSE compared with that of the MLR model, respectively. Although the physically-based MJS model satisfactorily described the dynamics of rainfed maize T under various mulching methods, the blackbox-type SVM-WOA model was more suitable for estimating daily maize T after a careful calibration with adequate experimental data due to its advantage in modeling complex nonlinear relationships between T and its driving variables. ● Daily rainfed maize T under four mulching methods was measured during 2015–2018. ● MLR, MJS and SVM-WOA models were compared for estimation of daily maize T. ● SM, RPBF and RPSF increased T by 6.9–19.1%, 12.1–31.3% and 15.3–36.7% relative to NM. ● SVM-WOA model produced the best T estimates, followed by MJS and MLR models. [ABSTRACT FROM AUTHOR]

• ET partitioning into I c , E s and T p by rainfed maize with contrasting mulching was explored. • Seasonal ET was insignificantly higher under SM, RPBF and RPSF compared with NM. • SM, RPBF and RPSF decreased E s /ET but increased T p /ET and I c /ET relative to NM. • ET partitioning differences among mulching were attributed to variations of SWC and LAI. • Soil mulching largely promoted T p and restrained E s in spite of slight increase in I c. Soil mulching can effectively modify crop growth environments and increase crop productivity in rainfed agriculture, and the knowledge about water fluxes within the soil-crop-atmosphere ecosystem is essential for improving water productivity (WP) in water-limited regions such as Northwest China. This study systematically investigated seasonal and inter-annual dynamics of evapotranspiration (ET) partitioning into canopy interception (I c), soil evaporation (E s) and plant transpiration (T p) in rainfed maize fields under four mulching conditions (NM: non-mulching, SM: straw mulching, RPBF: plastic-mulched ridge with bare furrow, and RPSF: plastic-mulched ridge with straw-mulched furrow) from June to October in 2015, 2016 and 2017 characterized by various seasonal rainfall distributions. The results showed that seasonal ET was slightly higher under mulching conditions compared with NM during each growing season, but the difference was not statistically significant. Soil mulching decreased E s /ET (22.0–29.8 %, 14.3–19.5 % and 11.3–15.1 % under SM, RPBF and RPSF, respectively) relative to NM (27.6–34.5 %), while it increased T p /ET (55.8–63.7 %, 63.0–71.0 % and 65.6–73.2 %, respectively) and I c /ET (13.2–16.0 %, 14.7–17.4 % and 15.4–19.3 %, respectively) relative to NM (52.4–58.7 % and 13.0–15.7 %, respectively). Differences in ET partitioning under contrasting mulching conditions were related largely to variations in leaf area index and soil water stress. Although seasonal ET under various mulching conditions varied among the three seasons (264.8–286.6 mm in 2015, 241.2–242.5 mm in 2016 and 296.6–324.4 mm in 2017), the proportions of I c (13.0–15.4 %, 13.3–19.3 % and 15.7–17.7 %), E s (11.3–28.3 %, 15.1–34.5 % and 11.4–27.6 %) and T p (58.7–73.2 %, 52.4–65.6 % and 56.7–70.9 %) to total ET were similar. Soil mulching greatly enhanced maize yield by 9.5–26.1 %, 27.0–186.5 % and 30.8–209.7 % under SM, RPBF and RPSF compared with NM, respectively, resulting in 1.5–15.8 %, 19.0–184.7 % and 20.8–214.8 % higher WP, respectively. It was concluded that soil mulching largely promoted T p and restrained E s in spite of slight increase in I c , thereby improving maize yield and WP during the three seasons. The present study gives a better understanding of rainwater cycle and crop water use, which is critical to sustainable management of rainfed agriculture. [ABSTRACT FROM AUTHOR]

• Calculation of water stress factors has been modified in the model. • The genetic coefficients of cotton used in the model have been determined. • Using data from other site for verification the modified model under plastic mulch. • The modified model can be used as a practical tool to simulate cotton growth and yield under various deficit irrigation levels. Cotton (Gossypium hirsutum L.) is one of the main crops in Southern Xinjiang of China, and it is the major component of the regional economy. However, cotton cultivation in this region is facing severe challenges, e.g., the projected increase in the frequency of droughts and the decrease in precipitation in the future. Development and evaluation of deficit irrigation strategies in this region can potentially conserve irrigation water while maintaining cotton yields. In this study, the actual soil evaporation was introduced into the calculation process of stress factors in the Decision Support System for Agrotechnology Transfer (DSSAT) Cropping System Model (CSM-CROPGRO-Cotton) to simulate and evaluate the growth and yield of drip-irrigated cotton under mulching in response to various deficit irrigation strategies. The modified CSM-CROPGRO-Cotton model was calibrated using field data under full irrigation (100% reference evapotranspiration (ET 0)) and validated by deficit irrigation data (0.4 ET 0 , 0.6 ET 0 and 0.8 ET 0 at the bud, flowering and boll stages) during the two cotton growing seasons of 2018 and 2019. The results showed that the modified model CSM-CROPGRO-Cotton simulated the growth index of cotton well under various deficit irrigation conditions. The index of agreement (d) of the simulated and measured biomass was greater than 0.845, and the coefficient of determination (R2) was greater than 0.967 (P < 0.01). Although the simulation of leaf area index was not as good as biomass, it also yielded satisfactory estimates, with d > 0.934 and R2 > 0.817 (P < 0.01). The simulated photoperiods in various deficit irrigation treatments were consistent with the observations. The averaged absolute relative error (ARE) in seed cotton yield over the deficit irrigation treatments was 2.1%, indicating high simulation accuracy. The results showed that the modified CSM-CROPGRO-Cotton model was appropriate for simulating cotton growth and yield under various water deficit strategies, which is a reasonable decision support system in managing irrigation for sustainable agriculture. The simulations also indicated that adopting deficit irrigation practices under normal weather conditions could conserve water without adversely affecting seed cotton yield, but there was a risk of increased yield loss under dry conditions. [ABSTRACT FROM AUTHOR]

Seed cotton yield and fiber quality are two primary factors that influence the international competitiveness of cotton. To enhance the water-nitrogen utilization efficiency and promote the sustainable cotton production, field experiments were performed in 2020 and 2021 to explore the effects of irrigation depth and nitrogen (N) fertilization rate on N uptake and distribution, seed cotton yield, fiber quality traits and water-nitrogen utilization efficiency in the Korla region of southern Xinjiang, China. Three irrigation depths (W 1 : 60% ET c , W 2 : 80% ET c , W 3 : 100% ET c ; ET c was crop water consumption) and four N rates (N 0 : 0 kg ha−1, N 200 : 200 kg ha−1, N 300 : 300 kg ha−1, N 400 : 400 kg ha−1) were applied. The results showed irrigation depth and N rate significantly influenced N uptake and distribution in plant organs, seed cotton yield, crop water productivity (WP), partial factor productivity of nitrogen (PFPN) and some fiber quality traits. Increasing irrigation depth improved plant height, leaf area index, aboveground dry matter and seed cotton yield, while increasing N rate increased and then declined these indicators. At the squaring and flowering stages, the N accumulation in all parts of cotton increased as irrigation depth and N rate increased, whereas it increased and then declined with increasing N rate at the boll-setting and harvesting stages. At the squaring and flowering stages, N was mainly accumulated in the leaves. As the growth period progressed, N was transported to bolls and the proportion of N content in leaves decreased. The proportion of N accumulation in cotton bolls was largest at the boll-setting and harvesting stages, and the N accumulation in plant organs followed the order of boll > leaf > stem > root. As irrigation depth increased, PFPN increased but WP decreased. As N rate increased, PFPN decreased but WP increased and then declined. The increases in N rate improved fiber quality. The maximum seed cotton yield (7578 kg ha−1 in 2020 and 7173 kg ha−1 in 2021) and greater WP, PFPN and fiber quality occurred in W 3 N 300 , which was recommended as a sustainable cotton production strategy in the Korla region of southern Xinjiang and elsewhere with similar environments to improve water-nitrogen utilization efficiency, seed cotton yield and alleviate soil nitrate pollution risk. [Display omitted] ● The interaction of irrigation depth and nitrogen rate significantly affected seed cotton yield. ● Rational irrigation depth and nitrogen rate improved water productivity and partial factor productivity of fertilizer. ● Cotton bolls had the largest proportion of nitrogen accumulation at boll-opening and harvest stages. ● The combination of 100% crop evapotranspiration and 300 kg N ha−1 was recommended. [ABSTRACT FROM AUTHOR]

• Exogenous silicon application effect on drip-irrigated greenhouse tomato was explored. • Drought-salt stress significantly reduced tomato growth and physiological characteristics. • Exogenous silicon application improved yield by 6.5−17.7% under drought-salt stress. • Silicon application increased total soluble solids, vitamin C, soluble sugars and lycopene content. Improving crop productivity in drought-stressed and salt-affected regions is the key to promoting sustainable agriculture. Silicon is considered to improve the stress tolerance of crops, but how exogenous silicon application affects the fruit yield and quality of tomato under combined drought and salt stress remains unclear. A greenhouse experiment was conducted over two consecutive growing seasons (autumn 2021 and spring 2022) to investigate the effects of exogenous silicon application on leaf greenness, photosynthesis and chlorophyll fluorescence parameters, fruit yield and quality of drip-fertigated greenhouse tomato under various drought and salt stresses. There were three irrigation levels: I 1 (90–100% θ f , where θ f is the field capacity), I 2 (70%–80% θ f) and I 3 (50%–60% θ f), two soil salinity levels: S 0 (0.1%) and S 1 (0.4%), and two silicon application rates: T 0 (0 mmol L−1) and T 1 (2.4 mmol L−1), resulting in a total of 12 treatments with three replicates. The results showed that the combined drought and salt stress significantly reduced leaf silicon content, plant height, leaf area index, aboveground biomass, net photosynthetic rate, transpiration rate and stomatal conductance of tomato plants, while the exogenous silicon application promoted these parameters. Irrigation level, salinity level, silicon rate and the interaction of irrigation level and salinity level had significant effects on fruit yield. Compared to S 0, S 1 decreased fruit yield by 18.42%, 17.91% and 20.64% under I 1 , I 2 and I 3 , respectively. Exogenous silicon application significantly improved fruit yield by 6.52% (I 3 S 0) - 17.73% (I 2 S 1). Irrigation level, salinity level and silicon rate had inconsistent effects on fruit quality. Exogenous silicon application significantly increased total soluble solids, Vitamin C, soluble sugars and lycopene content, without significant effect on titratable acid. The lower irrigation level and higher salinity level resulted in better fruit quality. The path analysis showed that leaf silicon content, net photosynthetic rate, lycopene, average fruit weight had significant direct positive effects on fruit yield. The results are informative for improving drip-fertigated greenhouse tomato productivity and quality under drought-stressed and salt-affected conditions. [ABSTRACT FROM AUTHOR]

Soil mulching has been widely used to improve crop productivity around the world, but how various mulching practices affect soil hydrothermal conditions, water-temperature-radiation utilization and finally grain yield of rainfed maize has been poorly understood. A two-season field experiment was conducted on rainfed summer maize in 2021 and 2022 on the Loess Plateau of China, with six soil mulching practices: flat planting with non-mulching (FPNM), flat planting with full straw mulching (FPSM), flat planting with full black film mulching (FPBF), flat planting with full transparent film mulching (FPTF), ridge-furrow planting with black film mulching on the ridge (RFBF) and ridge-furrow planting with transparent film mulching on the ridge (RFTF). The results showed that compared with the traditional FPNM, the five mulching treatments (FPSM, FPBF, FPTF, RFBF and RFTF) greatly regulated root-zone soil hydrothermal conditions and resulted in obvious soil drying-wetting alternation, which significantly changed the daytime average root-zone soil temperature in the 0 – 25 cm soil layer (by − 1.1 ℃, − 1.9 ℃, + 2.7 ℃, − 1.6℃ and + 0.8 ℃, respectively) and significantly reduced crop evapotranspiration. The five mulching treatments promoted the root growth, leaf area index and canopy light interception rate due to the improved soil water and/or temperature conditions. The structural equation modeling indicated that soil hydrothermal condition and water-temperature-radiation use efficiency could directly or indirectly explain 98% of the grain yield variation under various soil mulching practices; radiation use efficiency (RUE) determined maize production in the water-sufficient year (2021), whereas maize production was mainly determined by crop water productivity (WP) in the water-limited year (2022). The RFBF increased maize production most, followed by RFTF. Compared with FPNM, RFBF increased leaf area index by 45.4%, canopy light interception rate by 19.1%, aboveground biomass by 68.8%, 1000-grain weight by 15.1%, grain yield by 58.6%, WP by 71.8%, thermal time use efficiency by 64.6% and RUE by 30.5%. In conclusion, RFBF optimized the root-zone soil hydrothermal conditions for root growth, which in turn promoted aboveground growth and water-temperature-radiation use efficiency, and finally improved the gain yield of rainfed summer maize on the Loess Plateau of China. Therefore, RFBF was considered as a promising agricultural practice to improve rain-fed summer maize production and resource utilization efficiency on the Loess Plateau of China. • The warming effect of transparent plastic film may lead to negative effects for rainfed summer maize. • Ridge-furrow planting with black film mulching provided the optimal soil hydrothermal conditions. • Ridge-furrow planting with black film mulching increased water-temperature-light use efficiency. • Water productivity determined maize production in the dry year, not radiation use efficiency. [ABSTRACT FROM AUTHOR]

Optimising the management of water and fertilizer, and fully exploiting the positive effects of the coupling of water and fertilizer, are important ways of achieving high crop yields and promoting the sustainable development of water-efficient agriculture. The objective of this study was to investigate the coupling effects of different irrigation levels and different mixing ratios of slow-release nitrogen fertilizers on the physiological growth characteristics and yield of winter wheat in Guanzhong region under drip irrigation. In this study, field experiments were conducted in two winter wheat growing seasons, 2018–2019 and 2019–2020. The study included three irrigation levels: W1 (60% ETc, where ETc is the evapotranspiration of the crop), W2 (80% ETc), and W3 (100% ETc); and four N fertilizer treatments: U (100% urea), UNS1 (urea: slow-release N fertilizer = 1:1), UNS2 (urea: slow-release N fertilizer = 1:3) and SRF (100% slow-release N fertilizer). Compared to W1 and W2, W3 prolonged the winter wheat leaf functional period, increased leaf area index and net photosynthetic rate (P n), and promoted dry matter accumulation. The total N content of winter wheat decreased by 22.67% and 9.93% under W1 and W2 conditions, respectively. The nitrogen use efficiency (NUE) decreased by 5.87% and 1.97%, respectively, leading to a decrease in yield. Slow-release nitrogen fertilizer (SRF) and its mixture treatments (UNS1, UNS2) increased post-flowering nitrogen uptake in winter wheat compared to U. At the same irrigation level, water use efficiency (WUE) was increased by 34.03%, 13.35%, and 20.86% in the UNS2 treatment compared to U, UNS1, and SRF, respectively. W3UNS2 obtained the highest grain yield: 8026.32 kg hm−2 (2018–2019) and 8993.25 (2019–2020) kg hm−2, with a 9.85–68.24% yield increase compared to other treatments. Und4er the treatments of this study, yield, WUE, and NUE of winter wheat reached 90% of the maximum at irrigation levels of 82.04–91.83% ETc and 59.18–83.67% of slow-release N fertilizer in blended fertilizer. Under water stress conditions, UNS1 and UNS2 can mitigate the effects of water deficit on plant growth and stabilize grain yield. This study provides useful information for optimising water and nitrogen management decisions for winter wheat in semi-arid climatic regions, and contributes to the promotion of sustainable development of wheat production and water-efficient agriculture. • The two-year drip trial was conducted in a sheltered canopy in GuanZhong. • Field trial address in the coupling impacts of irrigation&fertilizer on winter wheat. • Recommended irrigation volumes and mixing ratios were obtained using modelling. • Blended slow-release nitrogen fertilizer can effectively mitigate the drought effects. • 100% ETc with U:SRF = 1:3 is the most recommended irrigation and fertilization option. [ABSTRACT FROM AUTHOR]

In the semi-arid and semi-humid areas, ridge-furrow planting with film mulch on the ridge (R) has been found to significantly enhance crop yields and water productivity, but the interaction effects of supplemental irrigation and plant density on the growth, photosynthesis, grain yield and water productivity (WP) of winter wheat under ridge-furrow mulching are still poorly understood. A two-season experiment (during October 2020 - June 2021 and October 2021 - June 2022) was undertaken on winter wheat in a semi-humid but drought-prone area in northwest China, with two cultivation patterns (R, with ridge width of 40 cm and furrow width of 60 cm; F: traditional flat planting), two supplemental irrigation amounts (I 0 : rainfed; I 60 : 60 mm of supplemental irrigation equally applied at the overwintering and regreening stages) and three plant densities (D 1 :240 × 104 plants ha−1; D 2 : 360 × 104 plants ha−1; D 3 : 480 × 104 plants ha−1; with row spacing of 20 cm). The results showed that cultivation pattern, supplemental irrigation and plant density had significant effects on soil water content, leaf area index (LAI), aboveground biomass, relative chlorophyll content (SPAD value), photosynthesis, chlorophyll fluorescence parameters and grain yield of winter wheat. In addition, the interaction effects of cultivation pattern, supplemental irrigation and plant density on SPAD value, fluorescence parameters, grain yield, evapotranspiration and WP were significant. Compared to F and I 0 , R and I 60 significantly increased LAI (4.8 % and 4.6 %), aboveground biomass (9.3 % and 8.1 %), SPAD value (5.0 % and 6.4 %), net photosynthetic rate (19.8 % and 11.7 %), maximal PSII quantum yield (F v /F m) (5.2 % and 2.4 %), energy transformation potential activities of PSII (F v /F o) (4.1 % and 1.5 %), effective PSII quantum yield (ΦPSII) (12.2 % and 9.5 %), grain yield (10.4 % and 13.5 %) and WP (11.8 % and 7.7 %), while they reduced the relative energy excess at the PSII level. Increasing plant density generally improved LAI, aboveground biomass, but it reduced SPAD value, net photosynthetic rate and fluorescence parameters. Grain yield and WP reached their maximum values at D 2 under R and at D 3 under F, which was because R had a higher plant number (by 25 %) in each row at D 3 compared to F due to the decreased row number resulting from the existence of 40-cm-wide ridge under R. The greatest grain yield (7383.5 kg ha−1 and 8577.4 kg ha−1) and WP (20.03 kg ha−1 mm−1 and 21.77 kg ha−1 mm−1) were obtained under RI 60 D 2 during the two growing seasons. These results suggest that ridge-furrow mulching combined with supplemental irrigation and modified plant density of 360 × 104 plants ha−1 can produce high grain yield and WP for winter wheat in the semi-humid but drought-prone areas of northwest China. • Effects of supplemental irrigation and plant density on winter wheat under ridge-furrow mulching were explored. • Cultivation pattern, supplemental irrigation and plant density had significant effects on soil water content and wheat growth. • Compared to flat planting and rainfed, ridge-furrow mulching and supplemental irrigation increased wheat yield and WP. • Grain yield and WP peaked at medium density under ridge-furrow mulching and at high density under flat planting. • The greatest grain yield and WP occurred under ridge-furrow mulching with supplemental irrigation and medium density. [ABSTRACT FROM AUTHOR]

Intensification of greenhouse production is always closely related to massive nitrogen (N) losses to the environment. Therefore, precisely assessing crop N status and optimizing N fertilizer management are essential for the sustainability of greenhouse system. The study was endeavored to (1) assess whether the parameters of critical nitrogen (Nc) dilution curves were significantly affected by the irrigation level, and (2) compare if both leaf area index (LAI) and aboveground biomass (AGB) based Nc dilution curves could accurately diagnose cherry tomato N status using a recent Bayesian statistical approach. A three-year greenhouse cherry tomato experiment containing five N levels (0, 180, 270, 360 and 450 kg N ha−1) and three irrigation levels (60 %, 80 % and 100 % ET 0 , where ET 0 was the reference evapotranspiration) was conducted from 2019 to 2021. The width of the 95 % credibility intervals of Nc dilution curves based on AGB and LAI decreased with the increasing AGB and LAI. Taking the 95 % credibility intervals of parameters A1 and A2 into consideration, water availability of 60 %–100 % ET 0 had no significant effect on AGB-based Nc dilution curves in 2019 and 2021, and it also had no significant effect on LAI-based Nc dilution curves during 2019–2021. Delaying the transplanting date of greenhouse cherry tomato would significantly decrease parameter A1, while parameter A2 was not affected. The differences of nitrogen nutrition index (NNI) calculated from the AGB- and LAI-based Nc dilution curves were negligible under different irrigation levels and sampling dates. The maximum relative yield was associated with an NNI of 0.99 for both AGB and LAI. These results indicate that Nc dilution curves established based on both AGB and LAI could precisely diagnose cherry tomato N status. There is no need to establish specific Nc dilution curves for greenhouse cherry tomato under non-extremely water-stressed conditions. • Biomass- and LAI-based critical N dilution curves were constructed with Bayesian model. • There were no significant differences in LAI-based curves under 60 %–100 % ET 0. • Delaying the transplanting date significantly decreased parameter A1. • Both biomass- and LAI-based curves could assess cherry tomato N status. [ABSTRACT FROM AUTHOR]

The ridge-furrow plastic mulching system has been reported to increase crop yield and water-nitrogen use efficiency in semi-arid and semi-humid regions, but the effects of plant density, nitrogen (N) rate and supplemental irrigation on chlorophyll, photosynthesis, root growth and seed yield of soybean under ridge-furrow plastic mulching are poorly understood. A two-year field experiment (2019 and 2020) was conducted on soybean in a split-split plot design, with two plant densities (D 16 : 160,000 plants ha−1; D 32 : 320,000 plants ha−1) as main plots, two N rates (N 30 : 30 kg N ha−1; N 60 : 60 kg N ha−1) as sub plots, and two irrigation levels (W 0 : rainfed; W 30 : supplemental irrigation of 30 mm at the flowering-podding stage) as sub-sub plots. The results showed that plant density, N rate and supplemental irrigation had significant effects on leaf chlorophyll content, chlorophyll fluorescence parameters, photosynthesis, aboveground/root growth and seed yield. Increasing plant density enhanced leaf area index (LAI) by 31.9% and aboveground biomass (AGB) by 59.4%, seed yield by 27.4%, water use efficiency of seed yield (WUE s) by 27.9% and nitrogen partial factor productivity (NPFP) by 26.6%. Increasing N rate increased leaf chlorophyll content by 11.9% and photosynthetic rate by 5.5%, thereby increasing LAI by 11.5%, AGB by 10.3%, seed yield by 8.9% and WUE s by 8.2%. Supplemental irrigation increased chlorophyll content by 7.6% and photosynthetic rate by 3.7%, thereby increasing LAI by 4.7%, AGB by 11.0%, seed yield by 4.7% and NPFP by 4.0%, while supplemental irrigation only increased WUE s under D 32. Compared with D 16 N 30 W 0 , D 32 N 60 W 30 enhanced seed yield by 44.0% and WUE s by 37.0%, but reduced NPFP by 28.8%. Compared with D 32 N 30 W 30 , D 32 N 60 W 30 increased both seed yield and WUE s by 8.5%, but it reduced NPFP by 45.5% with 100% higher N input. LAI, AGB, WUE s , NPFP and some leaf physiological (EXC, Chl a /Chl b , EWT leaf and L s) and root (TRLD, TRVD and TRSD) indexes were closely related to soybean yield. This study provides a better understanding how plant density, N rate and supplemental irrigation improved soybean productivity and water-nitrogen use efficiency by regulating chlorophyll, photosynthesis and aboveground/root growth. ● Plant density, nitrogen rate and supplemental irrigation effects on soybean were explored. ● They significantly affected chlorophyll, photosynthesis, root growth and seed yield. ● D 32 N 60 W 30 enhanced seed yield by 44.0% and WUE s by 37.0%, but reduced NPFP by 28.8% than D 16 N 30 W 0. ● D 32 N 60 W 30 increased seed yield and WUE s by only 8.5%, but reduced NPFP by 45.5% than D 32 N 30 W 30. [ABSTRACT FROM AUTHOR]

The effects of water deficit on maize growth and physiological activities have been extensively studied. However, there are few studies about how various nitrogen (N) fertilizer types alleviate the impact of water stress on maize yield. A two-year field experiment was conducted to explore the effects of N type on maize growth, physiological characteristics and gain yield under various water-stressed conditions in 2019 and 2020. This experiment included three irrigation levels of W1 (60% ET c , ET c is crop evapotranspiration), W2 (80% ET c) and W3 (100% ET c), and three N fertilizer types of urea (U), slow-release nitrogen fertilizer (SRF) and blending U and SRF (UNS). The results showed that W1 and W2 significantly reduced maize leaf area index and leaf N content, which declined maize net photosynthetic rate (P n), transpiration rate (T r) and chlorophyll fluorescence, inhibited chlorophyll synthesis and thus reduced maize yield. W3 not only increased maize growth, P n and T r , but also enhanced the correlation between P n , chlorophyll content, chlorophyll fluorescence parameters and leaf area index/leaf N content. The application of UNS alleviated the grain yield reduction associated with water stress. Under W1 (W2), the grain yield in UNS were 3.6–22.1% (10.4–25.0%) and 4.4–24.2% (5.3–15.4%) greater than that in U and SRF, respectively. Although W3SRF obtained the highest yield grain among all the treatments, no significant difference was found between W3UNS and W3SRF. Under the same irrigation amount, UNS increased the water productivity compared with U. In conclusion, UNS could stabilize grain yield by regulating maize leaf functional traits to cope with future climate change and ensure regional food security. • LAI and leaf N content can evaluate the response of leaf development process to water deficit. • W3 increased the correlation coefficients between leaf function index and LAI/leaf N content. • UNS alleviated the negative effects of water deficit on leaf functional index of maize. • UNS could stabilize grain yield by regulating maize leaf functional traits. [ABSTRACT FROM AUTHOR]

Soybean (Glycine max L. Merr) is an important crop around the world. Adaptive soil and crop managements are crucial for improving rainfed soybean productivity and resource use efficiency under changing climate. The ridge-furrow plastic mulching system was applied for the first time to rainfed soybean, and its combined effects with dense planting and reduced nitrogen (N) on soil water and temperature, soybean growth, yield, water use efficiency (WUE) and economic return were explored in 2019 and 2020 in a semi-humid drought-prone region of China. There were two planting modes: flat cultivation with no mulching and ridge-furrow cultivation with plastic film mulching on the ridge, and four crop management practices: sparse planting (160,000 plants ha−1) with reduced N rate (30 kg N ha−1), sparse planting with high N rate (60 kg N ha−1), dense planting (320,000 plants ha−1) with reduced N rate (30 kg N ha−1) and dense planting with high N rate (60 kg N ha−1). Compared with flat cultivation with no mulching, ridge-furrow plastic mulching significantly increased average surface soil water (0–20 cm) by 6.7% and soil temperature (by 0.5–1.5 ℃ at 10–25 cm depths), which promoted leaf area index (LAI) by 9.0%, total chlorophyll content (Chl) by 10.4%, net photosynthesis rate (P n) by 1.6%, resulting in increases in soybean yield, WUE and net income (NI) by 11.1%, 10.7% and 8.6%, respectively. Compared with sparse planting, dense planting decreased average P n by 7.5%, aboveground biomass per plant by 15.7%, pods per plant by 29.9% and hundred-grain weight by 3.8%; however, it improved LAI by 15.7%, soybean yield by 32.3%, WUE by 28.8% and NI by 44.3%. Compared with reduced N rate, high N rate improved average LAI by 14.0%, Chl by 11.1% and P n by 4.2%, resulting in increases in soybean yield by 10.1%, WUE by 9.7% but NI by only 2.4%. Compared with the traditional flat cultivation with no mulching and sparse planting with high N rate, ridge-furrow plastic mulching and dense planting with reduced or high N rate significantly improved soybean yield (by 25.6% or 38.8%) and WUE (by 23.8% or 38.0%) (P < 0.05), but the former produced greater net income (12,749.7 CNY ha−1) than the latter (12,433.4 CNY ha−1) with 50% less N input. In conclusion, ridge-furrow plastic mulching and dense planting with reduced N rate is a more promising practice to trade off yield, water productivity, economic return and environmental benefit of rainfed soybean. • Ridge-furrow plastic mulching was applied for the first time to rainfed soybean. • Ridge-furrow plastic mulching improved soil hydrothermal condition. • Dense planting with low N decreased yield per plant, but improved population yield. • Ridge-furrow plastic mulching and dense planting with low N improved soybean yield. [ABSTRACT FROM AUTHOR]

The arid and semi-arid region of northwest China is an important region for spring maize production in China, but improper water and fertilizer management has caused ecological problems in these regions. A two-year field experiment was conducted in 2015 and 2016 in the Gansu Province of China to investigate the effects of different irrigation amounts and fertilization rates on growth, grain yield, water and fertilizer use efficiency, and soil nutrient residue of drip-fertigated spring maize, and explore the optimal combination of irrigation amount and fertilization rate based on a multi-level fuzzy comprehensive evaluation (MFCE) model. The irrigation levels included I 60 (60% of crop evapotranspiration), I 75 , I 90 and I 105 in 2015 and I 60 , I 80 , I 100 and I 120 in 2016. The N-P 2 O 5 -K 2 O fertilization rates (kg ha−1) were F 60–30–30 , F 120–60–60 , F 180–90–90 and F 240–120–120. The results showed that plant height, stem diameter and leaf area index were highest under F 240–120–120. Maize yield, dry matter, water use efficiency (WUE) followed a upward opening parabola with irrigation amount and fertilization rate, and reached the maximum under I 90 F 180–90–90 in 2015 and under I 100 F 180–90–90 in 2016. With the simultaneous increase in irrigation amount and fertilization rate, nitrate nitrogen content in the 60–120 cm soil layer showed an increasing trend. Based on the MFCE model, the irrigation amount of 415–450 mm combined with the N-P 2 O 5 -K 2 O rate of 144–77–77 to 180–90–90 kg ha−1 obtained the optimal comprehensive benefit of maize growth, economic return, water and fertilizer utilization and environmental benefit. This work can provide a scientific basis for the optimization and management of spring maize irrigation and fertilization in northwest China. • Irrigation and fertilization coupling model was established based on multi-level fuzzy comprehensive evaluation. • Irrigation and fertilization significantly affected maize growth, yield, water use efficiency and soil nutrient residue. • Irrigation amount of nearly 100% ET c and N-P 2 O 5 -K 2 O rate of 180–90–90 kg ha−1 obtained the highest yield, water and fertilizer efficiency. [ABSTRACT FROM AUTHOR]

• Full irrigation (100 %ET c) improved plant growth and yield of greenhouse tomato. • 75 %ET c obtained higher WUE and lower unmarketable yield. • 100 %ET c tended to shorten rapid growth period of aboveground biomass and improve maximum growth rate. • The lowest total water consumption occurred at the blooming and setting stage. Agriculture is the largest consumer of scarce water resources and irrigation serves as the sole source of water for greenhouse tomato production. It is an urgent task to seek an appropriate deficit irrigation strategy that is beneficial for high marketable yield, fruit quality, saving irrigation water and ultimately improving water use efficiency. A four-season experiment was conducted on drip-irrigated greenhouse tomato during Autumn 2015-Spring 2017 with three irrigation regimes, i.e., 100 %ET c (crop evapotranspiration) (W1), 75 %ET c (W2) and 50 %ET c (W3). The results showed that aboveground biomass, leaf area index (LAI), plant height and fruit yield increased with increasing irrigation amount. However, soluble solids, vitamin C and soluble sugar of tomato fruits were lowest under W1. W2 markedly reduced unmarketable fruits and more small-sized fruits were harvested at the late stage under W1. Through fitting the relationship between cumulative temperature and aboveground biomass using logistic equations, it was found that average duration of the rapid growth period (t d) and the time when growth rate reached the maximum value (t m) increased as irrigation amount decreased. Conversely, the maximum growth rate during the rapid growth period (v m) decreased with the increase of water deficit. The highest total water consumption (278.05 mm), lowest total yield water use efficiency (25.12 kg m−3) and marketable yield water use efficiency (22.87 kg m−3) were obtained under W1. The smallest total water consumption (27.01–50.75 mm) occurred at the blooming and setting stage. Based on the results of path analysis, aboveground biomass and average fruit weight were important indexes affecting yield positively. It is concluded that deficit drip irrigation with 75 %ET c has the potential of supporting tomato growth, improving marketable yield and WUE as a result of less unmarketable yield and bigger fruit size. [ABSTRACT FROM AUTHOR]