The assessment of soil health relies on key parameters such as soil aggregates and organic matter content. Therefore, examining the impact of irrigation water ion composition and variations in salinity on soil aggregates and organic matter is imperative, which is key to developing a theoretical basis for the sustainable utilization of saline water resources, particularly in extremely arid regions. This experiment was conducted to investigate the impact of different irrigation water salinity treatments (T3: 3 g/L, T5: 5 g/L, and T7: 7 g/L) on the root zone soil of cotton fields. Each salinity treatment included three variations of the sodium adsorption ratio (SAR) at S10: 10 (mmol/L)^1/2, S15: 15 (mmol/L)^1/2, and S20: 20 (mmol/L)^1/2. Local freshwater irrigation served as the control, resulting in a total of 10 treatments. Our findings show that the soil Ca²⁺ and Mg²⁺ content increased with higher irrigation water salinity but decreased with increasing irrigation water SAR. The relative macroaggregate stability and the content of water-stable macroaggregates and soil organic matter (SOM) decreased as the irrigation water salinity and SAR increased. In comparison to T3S20, T5S10 did not improve the soil Na⁺ content but significantly increased the soil Ca²⁺ content by 147.76%, while the water-stable aggregate and SOM saw a notable increase of 7.66% and 9.86%, respectively. Reducing the SAR in brackish water lessens its negative impact on soil aggregates in cotton fields. This is primarily because Ca²⁺ counteracts the dispersive effect of high Na⁺ concentrations and promotes aggregate formation. Irrigation water with a salinity of 3 g/L and an SAR of 10 (mmol/L)^1/2 positively affected the stabilization of soil aggregates and organic matter.

Plastic mulching is widely used in arid and semi-arid cotton systems to improve soil hydrothermal conditions and water–nutrient use efficiency. However, residual mulch and its potential contribution to microplastic inputs pose growing environmental and soil-quality risks, highlighting the need for high-resolution and automated approaches to support plastic waste management, targeted retrieval, and precision field operations. Taking a mulched cotton field in Alar, Xinjiang, as the study area, this study proposes a novel plastic mulch extraction method that integrates Unmanned Aerial Vehicle (UAV)-based hyperspectral imagery with deep learning semantic segmentation. The Jeffries–Matusita (JM) distance was employed to select highly separable optimal bands and their combinations for discriminating plastic mulch, bare soil, and cotton canopy, which were then used to drive UNet, DeepLabV3+, and PSPNet models for plastic mulch mapping. The results indicate that the PSPNet model driven by the 402 nm single-band reflectance, Normalized Difference Index (NDI) (861 nm, 410 nm), and NDI (757 nm, 676 nm) achieved the best performance for plastic mulch identification (Intersection over Union (IoU) = 80.28%), significantly outperforming the RGB-based model (IoU = 76.51%). This study enables accurate, spatially explicit assessments of residual mulch, providing actionable evidence for plastic waste monitoring and management, while supporting sustainable agriculture and precision farmland management.

Mulching and irrigation are key practices for improving cotton yield and soil conditions, especially in Xinjiang, China. This study investigated the combined effects of mulching width and irrigation depth on cotton growth and rhizosphere microorganisms. Two mulching widths—conventional (M1) and ultra-wide (M2)—and three irrigation depths, 0.8 ETc (W1), 1.0 ETc (W2), and 1.2 ETc (W3), were tested. The impacts on cotton growth, soil environment, and rhizosphere microbial communities were analyzed. Results showed that under the same irrigation depth, M2 significantly increased soil moisture and reduced salt accumulation. Soil temperature under M2 was higher than M1, with increases of 0.55 °C and 1.65 °C during the budding and flowering–boll stages. M2 also increased root length (3.52–10.72%) and root surface area (5.8–7.51%). The beneficial fungus Cladosporium was enriched, while the pathogen Fusarium was suppressed under M2. With the same mulching width, increasing irrigation improved soil moisture, reduced electrical conductivity, and decreased soil temperature. Root diameter and volume increased by 7.67–47% and 9.43–10.36%, respectively. Mulching width and irrigation depth significantly affected bacterial α-diversity. M2W3 showed the highest microbial richness and functional diversity. This study offers guidance for efficient cotton cultivation in southern Xinjiang.