This study aimed to explore the combined effects of micro-nano bubble water drip irrigation and different phosphorus (P) application rates (P0: 0 kg·hm⁻²; P1: 86 kg·hm⁻²; P2: 172 kg·hm⁻²; P3: 258 kg·hm⁻²) on maize growth, soil phosphorus dynamics, and phosphorus use efficiency to optimize irrigation and P fertilizer use efficiency. Through a field column experiment, the impact of micro-nano bubble water drip irrigation on maize plant height, stem diameter, leaf SPAD values, biomass, and yield was evaluated. The results showed that (1) irrigation methods significantly affected maize growth indicators such as plant height, stem diameter, and root dry weight. Micro-nano bubble water drip irrigation consistently promoted growth during all growth stages, especially under higher P application. (2) P application significantly increased the dry weight and P concentration in maize roots, stems, leaves, ears, and grains. Under micro-nano bubble water drip irrigation, the P concentrations in roots and grains increased by 59.28% to 92.59%. (3) Micro-nano bubble water drip irrigation significantly enhanced P uptake efficiency, partial factor productivity of P, and agronomic P use efficiency. Particularly under P1 and P2 treatments, the increases were 134.91% and 45.42%, respectively. Although the effect on apparent P recovery efficiency was relatively small, micro-nano bubble water drip irrigation still improved P utilization under moderate P levels. (4) Structural equation modeling indicated that P supply under micro-nano bubble water drip irrigation primarily regulated alkaline protease and alkaline phosphatase, enhancing soil P availability, which in turn promoted maize P accumulation and increased yield. In conclusion, this study demonstrated that the combination of micro-nano bubble water drip irrigation and appropriate P application can effectively promote maize growth and nutrient utilization, providing a theoretical basis for optimizing irrigation and fertilization strategies in maize production.

The contradiction between increased irrigation demand and water scarcity in arid regions has become more acute for crops as a result of global climate change. This highlights the urgent need to improve crop water use efficiency. In this study, four irrigation volumes were established for drip-irrigated maize under plastic mulch: 2145 m³ ha⁻¹ (W1), 2685 m³ ha⁻¹ (W2), 3360 m³ ha⁻¹ (W3), and 4200 m³ ha⁻¹ (W4). The effects of these volumes on soil moisture, maize growth, water consumption, crop coefficients, and yield were analyzed. The results showed that increasing the irrigation volume led to a 2.86% to 8.71% increase in soil moisture content, a 24.56% to 47.41% increase in water consumption, and a 3.43% to 35% increase in the crop coefficient. Maize plant height increased by 16.34% to 42.38%, ear height by 16.85% to 51.01%, ear length by 2.43% to 28.13%, and yield by 16.96% to 39.24%. Additionally, soil temperature was reduced by 1.67% to 5.67%, and the maize bald tip length decreased by 6.62% to 48%. The irrigation water use efficiency improved by 6.57% to 28.89%. A comprehensive evaluation using the TOPSIS method demonstrated that 3360 m³ ha⁻¹ of irrigation water was an effective irrigation strategy for increasing maize yield under drip irrigation with plastic mulch in the southern border area. Compared to 4200 m³ ha⁻¹, this strategy saved 840 m³ ha⁻¹ of irrigation water, increased the irrigation water use efficiency by 23.96%, and resulted in only a 0.84% decrease in yield. The findings of this study provide a theoretical foundation for optimizing production benefits in the context of limited water resources.

This study aimed to investigate the effects of planting density, irrigation volume, and nitrogen application on the resistance of rapeseed to lodging and yield and to provide technical support for achieving high yield and lodging resistance. We employed an L₉ (3⁴) orthogonal array, different planting densities, irrigation levels, and nitrogen applications to investigate their impact on rapeseed lodging and yield. The results showed the following: (1) Irrigation had the greatest effect on rapeseed lodging. This effect was most pronounced for the combination (A3B3C2), which exhibited the most severe lodging phenomenon (90%). Planting density had the greatest effect on yield, and the optimal combination was A2B2C3, which reached 3744 kg/hm² in 2023 and 3420 kg/hm² in 2024. (2) The agronomic practices increased the content of lignin, cellulose, hemicellulose, crude fiber, pectin, and soluble sugar fractions in the stalks by enhancing their flexural, puncture, and stress resistance. This led to the highest yield while reducing the rate of lodging. This emphasizes the importance of agricultural practices for rapeseed lodging and yield, providing critical insights into rapeseed cultivation in the Aksu region of Xinjiang.

To explore the effects of micro-nano aeration and oxygenation irrigation on soil characteristics and cotton growth in cotton fields in arid areas, this study was conducted at the National Soil Quality Aksu Observation and Experiment Station in Baicheng County, Xinjiang. “Xinluzao 78” cotton was used as the experimental material, and the soil column cultivation method was adopted. Four nitrogen concentration gradients (N0: 0 kg·hm⁻², NL: 112.5 kg·hm⁻², NM: 225 kg·hm⁻², and NH: 337.5 kg·hm⁻²) and two irrigation methods (micro-nano aeration and oxygenation irrigation Y: DO15 mg/L, conventional irrigation C: DO7.6 mg/L) were set up to systematically analyze the total nitrogen content of the soil, enzyme activity, microbial community structure, and the response characteristics of cotton growth and yield. The results show that aeration treatment significantly increases the total nitrogen content in the soil. The total nitrogen content in the 0–15 cm and 15–30 cm soil layers treated with YNM (aeration + local conventional nitrogen application rate) increased by 9.14% and 8.53%, respectively, compared with CNM. YNM treatment significantly increased the activities of soil urease, sucrase, and β-glucosidase, among which total nitrogen had the strongest correlation with the activity of β-glucosidase. Oxygenation significantly increased the richness of soil microorganisms. The Chao1 index of YNM-treated bacteria was 75.7% higher than that of CNM-treated bacteria. YNM treatment increased cotton yield by 26.73% compared with CNM treatment. Moreover, the number of bells formed per plant and the weight of the bells increased by 44.44% and 29.6%, respectively. In conclusion, micro-nano aeration and oxygenation irrigation effectively increase cotton yield. By optimizing the activities of soil enzymes and microorganisms, micro-nano aeration and oxygenation irrigation enhance the ability of cotton to utilize and transform nitrogen, and alleviate the impact of insufficient nitrogen utilization by cotton in arid areas.

Using multi-depth continuous observations from nine farmland sites in the Bachu irrigation district, Xinjiang (November 2024–April 2026), this study developed a two-layer conditional prediction model to test whether predicted soil-moisture trajectories improve apparent electrical conductivity (EC) prediction beyond a persistence benchmark. Four prediction windows (0–1, 1–3, 3–7, and 7–15 d) were evaluated using time-forward validation under observed ERA5 forcing, paired ablation, SHAP, and post-hoc meteorological-deficit linkage analysis. For EC₂₀, the R² values were 0.978, 0.923, 0.727, and −1.376, with corresponding Skill values of −0.001, 0.277, 0.540, and 0.635; absolute performance at 7–15 d remained unreliable. EC₄₀ achieved R² of 0.943–0.987, with Skill of 0.029–0.325, and EC₆₀ achieved R² of 0.737–0.974, with Skill of 0.065–0.177. Ablation showed the clearest gain for EC₂₀ at 3–7 d (ΔR² = 0.193; ΔSkill = 0.325), whereas most other combinations showed no consistent improvement. At 0–1 d, SHAP contributions of predicted moisture trajectories to EC₂₀, EC₄₀, and EC₆₀ were 39.2%, 37.6%, and 26.8%, respectively. Meteorological-deficit linkage responses varied by depth and horizon but were generally limited. Overall, trajectory benefits were depth- and horizon-dependent and reflected model dependence rather than causal water–salt mechanisms. The framework is currently applicable mainly to monitored, unfrozen post-irrigation periods without additional wetting recharge.