Intercropping has been shown to increase crop yields and improve land utilization in many cases but it is unknown how the interspecies relationship is enhanced with improved crop management schemes. In this study, we investigated the effect of different maize densities and N rates on the growth, crop yields and economic benefits of pea (Pisum sativum L.)/maize (Zea mays L.) intercropping. The results indicated that total yields of pea/maize intercropping were higher than the yield of maize alone, and that pea/maize intercropping improved land use efficiency significantly compared to sole crops, the partial land equivalent ratio (LER) of maize and pea with high planting density increased from 0.98% to 9.36% compared to low planting densities during 2012 and 2013. The pea strips provided significant compensatory effects on the growing maize after the earlier-sown, shorter-seasoned pea was harvested. The crop growth rate (CGR) of the intercropped maize was 18.5% to 216.9% greater than that of sole maize after pea harvest, the leaf area index (LAI) of pea/maize intercropping was 6.9% and 45.4% greater compared with the weighted average of sole maize and sole pea in 2012 and 2013, respectively. Net returns and benefit to cost ratios of pea/maize intercropping were increased with an increase of maize planting density. A low rate of N fertilizer was coupled with increased maize plant density, allowing interspecific facilitation to be fully expressed, thus improving the land utilization rate and increasing economic benefits. Overall, our findings show that a higher density of maize and lower N application can be used to increase grain production with no adverse effects on the growth components of either pea or maize crops. It could be considered an advanced farming system for agricultural sustainable development in the oasis region of northwest China.

Nitrogen (N) fixation is essential in the development of sustainable agriculture, but nodulation of legumes is usually inhibited by N fertilization. In this study, we evaluated the increased density of intercropped maize (Zea mays L.) as a means to alleviate the inhibitory effect of soil mineral N on intercropped pea (Pisum sativum L.) and improve system performance. A field experiment was conducted in the Hexi Corridor region of northwestern China from 2012 to 2014. The experiment consisted of monoculture pea, monoculture maize, and a pea/maize strip-intercropping system. Two levels of N fertilization were evaluated in both cropping systems during the co-growth period of intercropping, i.e., 0 kg N ha⁻¹ (N0) and 135 kg N ha⁻¹ (N1), and three maize densities were evaluated with both levels of N fertilization in the intercropping system, i.e., 45,000 plants ha⁻¹ (D1), 52,500 plants ha⁻¹ (D2), and 60,000 plants ha⁻¹ (D3). The application of N reduced the number of nodules of intercropped pea by 135% at D1 and by 9% at D2 compared to no application of N, in all the years examined. The alleviation of the inhibitory effect of soil mineral N on the nodulation of intercropped pea (C_is) was calculated as the percentage increase in nodulation with intercropping relative to monoculture for a given level of N fertilization. With the application of N, C_is was improved by increased intercropped maize density (D3 > D2 > D1) at all stages. The internal efficiency of nitrogen (IEN) of pea was improved with intercropping and, on average, was 19% and 12% greater at D3 than at D1 and D2, respectively. These results demonstrate that increased maize density can alleviate the inhibitory effect of soil N on the nodulation of pea and sustain the productivity of maize/pea intercropping while reducing N fertilizer requirements in arid regions.

Precise estimation of reference evapotranspiration (ET₀) is of significant importance in hydrologic processes. In this study, a genetic algorithm (GA) optimized back propagation (BP) neural network model was developed to estimate ET₀ using different combinations of meteorological data across various climatic zones and seasons in China. Fourteen climatic locations were selected to represent five major climates. Meteorological datasets in 2018–2020, including maximum, minimum and mean air temperature (T_max, T_min, T_mean, °C) and diurnal temperature range (∆T, °C), solar radiation (R_a, MJ m⁻² d⁻¹), sunshine duration (S, h), relative humidity (RH, %) and wind speed (U₂, m s⁻¹), were first subjected to correlation analysis to determine which variables were suitable as input parameters. Datasets in 2018 and 2019 were utilized for training the models, while datasets in 2020 were for testing. Coefficients of determination (r²) of 0.50 and 0.70 were adopted as threshold values for selection of correlated variables to run the models. Results showed that U₂ had the least r² with ET₀, followed by ∆T. T_max had the greatest r² with ET₀, followed by T_mean, R_a and T_min. GA significantly improved the performance of BP models across different climatic zones, with the accuracy of GABP models significantly higher than that of BP models. GABP_0.5 model (input variables based on r² > 0.50) had the best ET₀ estimation performance for different seasons and significantly reduced estimation errors, especially for autumn and winter seasons whose errors were larger with other BP and GABP models. GABP_0.5 model using radiation/temperature data is highly recommended as a promising tool for modelling and predicting ET₀ in various climatic locations.

No-till and cereal–legume intercropping have been recognized as favorable cropping practices to increase crop yields while maintaining soil quality in arid and semiarid environments, but the biological mechanisms are poorly understood. The present study aimed to determine the response of yields, soil properties, enzyme activities, and microbial community diversity and composition in mono- and inter-cropping under conventional and no-tillage conditions. We initiated a field experiment in Wuwei, a typical arid area of China, in 2014. Soil was sampled in August 2022 and, yields, soil properties, enzyme activities, and the microbial community diversity and composition were determined in the maize and pea strips in inter- and mono-cropping systems. Results revealed that the maize and pea strips in the no-till intercropping significantly increased yields, total and organic carbon stocks, decreased NO₃⁻-N, and obtained the highest total and organic P in the soil. No-tillage significantly enhanced the Shannon index and Pielou evenness of the bacterial community and total microbial community over conventional tillage, with the α-diversity of the bacterial community and total microbial community distinctly higher in the NTIM treatment than in the CTIM treatment. The α-diversity of the total microbial community was significantly related to yield, soil IC and OC, and the α-diversity of the archaea community was significantly related to soil TC, TC/TP, TN/TP, and BX. Meanwhile, the α-diversity of the eukaryote community was significantly related to soil yield, soil TC/TP. Both no-tillage and intercropped maize significantly increased the abundance of archaea phylum Thaumarchaeota and bacterial phylum Nitrospirae, and were significantly positively associated with soil OC and NH₄⁺-N, benefiting nitrogen fixation of intercropped pea from the atmosphere under the no-tillage cereal/legume intercropping. No-till intercropping was conducive to the accumulation of organic carbon, while decreasing the abundance of Proteobacteria, Acidobacteria, and Verrucomicrobia. Limited soil enzyme activities (ACP, ALP, DP, NAG, BG, AG, CB) led to decreases in organic carbon turnover and utilization. Intercropping altered soil microbial community diversity and composition due to changes in soil properties and enzyme activities. These findings suggest that no-tilled cereal–legume intercropping is a sustainable cropping practice for improving soil properties and enhancing microbial (archaea, bacterial, eukaryota) diversity, but the persistence is not conducive to rapid turnover of soil nutrients due to limited enzyme activities.

The current study evaluated the canopy cover competition for light and heat in a jujube–cotton intercropping system to measure the growth and yield performance of cotton, and the optimal cotton planting configuration. In this study, a two-year field experiment (2020 and 2021) was studied with different spacing configuration modes designed as follows: two rows of cotton (CM1) planted 1.4 m apart, four rows of cotton (CM2) planted 1.0 m apart, and six rows of cotton (CM3) planted 0.5 m apart, spacing intercropped jujube trees, respectively. The control treatment consisted of monocultured cotton (CK). The light-response curve was plotted using an LI-6400 XT photosynthesis instrument. Based on the modified rectangular hyperbola model, the photosynthetic characteristics were fitted, and the dry matter distribution characteristics and yield were compared. The results showed that with the increase in photosynthetically active radiation, the net photosynthetic rate (Pn) of each growth phase decreased first and then increased rapidly in the range of 0–200 μmol·m⁻²·s⁻¹ and then decreased slightly after the inflection point (light saturation point). The light-response curves of stomatal conductance and transpiration rate showed a linear relationship. The trend in the intercellular CO₂ concentration response curve was opposite to that of Pn. The maximum Pn (Pmax) of intercropped cotton was significantly impacted by configuration modes, of which CM2 treatment generated 1.8% and 22.8% higher Pmax than the CM1 and CM3 treatments. The cotton yield in the two years ranked as CK > CM3 > CM2 > CM1, and the average land equivalent ratio of CM2 was significantly higher than that of CM3 (22.4%) and CM1 (95.9%). The six-row configuration resulted in greater competition with the trees, which affected the accumulation of below-ground dry matter, while the four-row configuration formed a reasonable canopy structure, which ensured that more photosynthetic substances were distributed to the generative organs. The reasonable four-rows configuration mode may improve the photosynthetic efficiency of intercropped cotton economic yield.