Plastic film mulching, widely used in agriculture, leads to microplastic (MP) pollution in soils. While biodegradable polybutylene adipate terephthalate (PBAT) films may offer a solution, their impacts on subsurface soils and microorganisms remain unclear. To investigate the effects of conventional non-biodegradable polyethylene (PE) and biodegradable PBAT MPs on the properties of sub-surface soils and microbial communities, MPs were added at varying doses in a field experiment and incubated for 160 days. Physicochemical characteristics, nutrient dynamics, and microbial composition, diversity, and networks of soils were analyzed using standard techniques and 16S rRNA/ITS gene sequencing. Correlations between soil properties and microbes were assessed. Both MP types significantly altered soil characteristics, with PBAT-MP elevating pH and the levels of available phosphorus and potassium more than PE-MP. Microbial composition shifts occurred, with low-addition PBAT-MP promoting plastic-degrading genera. The assessment of α/β-diversity indicated that PBAT-MP predominantly influenced fungi while PE-MP impacted bacteria. An examination of microbial co-occurrence networks highlighted that PE-MP primarily disrupted fungal interactions, whereas PBAT-MP streamlined network complexity. Correlation analyses revealed that PBAT-MP promoted fungal diversity/network resilience correlating to nutrients. PE-MP and PBAT-MP significantly altered native soil/microbe relationships. PBAT-MP may exert greater, yet unknown, impacts over time through its biodegradation into newer and smaller fragments. Future research needs to integrate multi-omics and stable isotope science to elucidate the deep mechanistic impacts of degraded film-derived MPs on microbial ecological functions and biogeochemical cycles. Attention should also be paid to the long-term accumulation/transport of MPs in agricultural soils. Overall, this work deepens the impact and understanding of MPs from plastic film on sub-surface soil ecology. Furthermore, it provides a theoretical foundation for managing ‘white pollution’ in the film-covered farmlands of arid and semi-arid regions in China.

Biodegradable film mulching is increasingly used to replace polyethylene in agriculture, but effects on soil respiration (SR) and components remain unclear, especially during degradation. This study investigated biodegradable mulching’s regulation of SR, root-derived respiration (RDR), and non-root-derived respiration (NRDR) under varying phases. A two-year field experiment was conducted in a rainfed maize system in northern China, comparing conventional tillage with biodegradable film mulching (BM), conventional tillage with polyethylene film mulching (PM), and conventional tillage without mulching (CT). Continuous measurements of soil CO₂ concentration (SCC), temperature, water content, and respiration components were used to assess dynamic responses. Results showed that BM enhanced SR and shifted peak timing, with the SR peaking at 106 days after sowing (DAS) under BM, 91.8 DAS under PM, and 91.2 DAS under CT, mainly through a more sustained RDR (BM peak at 103 DAS with a broader peak and greater cumulative RDR than PM and CT). As the biodegradable plastic film degraded, NRDR was higher during the degradation phase, consistent with a priming-like response. These phase-dependent effects suggest that BM first facilitates root growth then serves as a microbial substrate. Moreover, elevated SCC was positively associated with both RDR and NRDR, indicating that CO₂ may function as a regulatory signal rather than a passive byproduct of respiration. These findings reveal distinct temporal mechanisms by which BM influences soil carbon fluxes and offer mechanistic insights into the sustainable application of biodegradable film mulching. Future research should evaluate long-term effects on microbial community composition, soil carbon balance, and potential trade-offs with crop productivity and environmental risks.

Real-time monitoring of cotton moisture status and determination of appropriate irrigation thresholds are essential for achieving precision irrigation. Currently employed diagnostic methods based on physiological indicators, remote sensing, or soil moisture measurements typically present limitations including cumbersome procedures, high labor intensity, requirements for specialized technical expertise, and delayed results. To address these challenges, this study investigated the relationship between plant water content and leaf RGB color values (red, green, and blue color values measured using LScolor technology) during the bud, flowering, and boll development stages, with the objective of establishing a predictive model for rapid, real-time moisture status monitoring. Given that leaf position and color values (R, G, and B) of different functional leaves may influence the relationship between leaf color and plant water content, and this relationship varies across different temporal periods, a two-year experiment was conducted. In 2023, leaf color data from the top five functional leaves were measured at five time points daily throughout the irrigation cycle. In 2024, the following four irrigation treatments were established: one conventional irrigation control treatment (CK) and three irrigation treatments at 72% (T1), 70% (T2), and 68% (T3) plant water content thresholds. Results demonstrated that the following: (1) plant water content initially declined during the day and subsequently showed slight recovery, indicating cotton’s particular susceptibility to water stress between 2:30 p.m. and 7:00 p.m.; (2) plant water content continuously decreased across five measurement periods following irrigation during the bud, flowering, and boll development stages, with R and G color values of the five functional leaves showing declining trends between 2:30 p.m. and 7:00 p.m., while B color values exhibited no consistent pattern; (3) correlation analysis revealed significant positive correlations between plant water content and R and G color values of the five functional leaves during the 2:30 p.m. to 5:00 p.m. period, with highly significant correlations observed for the third and fourth leaves from the apex; (4) univariate and bivariate linear regression models were successfully established between cotton water content and R and G color values of the third and fourth leaves from the top; and (5) under 72% plant water content conditions, cotton achieved the highest yield and Irrigation Water Use Efficiency, indicating that 72% represents the optimal irrigation threshold. In conclusion, integrating leaf color–plant water content relationships with the 72% irrigation threshold enables rapid, non-destructive, large-scale diagnosis of cotton moisture status, providing a robust foundation for implementing effective precision irrigation strategies.