It is of great significance to explore the strategy of regulated deficit irrigation (RDI) under mulched drip irrigation to stabilize tomato yield and improve quality and efficiency. This experimental study was conducted on a drip-irrigated greenhouse in two consecutive years (2020 and 2021). Three deficit levels were set for the flowering and fruit development stage (Stage I), and three were set for the fruit-ripening stage (Stage II). As a combination evaluation method, the fuzzy Borda model was used to optimize the RDI strategy of greenhouse tomato. The results showed that the net photosynthetic rate, stomatal conductance, transpiration rate, and total shoot biomass of tomato decreased with an increase in the water deficit, while the intercellular CO₂ concentration had an opposite trend. The mild and moderate water deficit at Stage I reduced tomato yield by 16–24% and 30–40% compared to full irrigation. The water deficit at Stage II was able to improve various quality parameters and the water-use efficiency of tomato; the irrigation water-use efficiency (32.8–33.9 kg/m³) and leaf water-use efficiency (3.2–3.6 μmol/mmol) were the highest when the soil water content was 70–90% θ_f (field capacity) at Stage I and 40–60% θ_f at Stage II (T3). Based on the fuzzy Borda combination evaluation model, T3 was determined as the treatment with stable yield, high quality, and efficient irrigation under the experimental conditions. The irrigation regime was as follows: irrigating 20–25 mm in the transplanting stage, no irrigation in the seedling stage, irrigating 193.2–220.8 mm at Stage I, and then irrigating 27.6 mm at Stage II.

Agricultural producers in China are presently confronting the challenge of “white pollution” caused by the continuous expansion of plastic film area coverage. The main objective of this research is to address the increasing interest in the effects of film residual on tomato growth, yield, and quality under drip irrigation. To reveal the effects of film residual on tomato physiology, field trials were conducted with five levels of film residual treatment applied in two consecutive cropping seasons from 2019 to 2020. Soil water content, plant height, stem diameter, photosynthetic characteristics, yield, soluble sugar content (SSC), organic acid (OA), vitamin C (VC), and nitrate content (NC) were measured; furthermore, four analysis methods were used to assess the comprehensive tomato quality. The results showed that film residuals significantly affected soil water content in 2019 and 2020 and inhibited tomato plant height and stem diameter. The variations in photosynthetic rate and stomatal conductance showed practically the same trend, increasing with an increase in the film residual at the seedling stage. The maximum yields were observed at 94.02 ton/hm² and 84.44 ton/hm² in 2019 and 2020, respectively, and tomato yield exhibited a shape reduction with increasing amounts of film residual in all years. SSC, VC, and NC showed an increasing trend with increasing amounts of film residual. The best tomato comprehensive quality was observed when the amount of film residual was lower than 200 kg/hm² and declined with an increasing amount of film residual. Overall, the soil water content, tomato growth, and fruit quality changed significantly under the influence of film residual. These results not only deepen our understanding of the harm caused by film residual to tomato growth and fruit quality but also provide reasonable advice to establish a management system for residual pollution on cultivated land.

Seed germination is a crucial stage in plant development, intricately regulated by various environmental stimuli. Understanding these interactions is essential for optimizing planting and seedling management but remains challenging due to the trade-off effects of environmental factors on the germination process. We proposed a new conceptual model by viewing seed germination as a dynamic process in a physiological dimension, with the influence of environmental factors and seed heterogeneity characterized by a germination speed and a dispersion coefficient. To validate the model, we conducted field experiments by drilling wheat seeds at different dates to establish a temperature gradient and in different plots to create a soil water content gradient. Comparisons with our experimental data and literature results show the model accurately reproduces all germination patterns and the subsequent seedling tillering, with R ² > 0.95. Our results reveal that within suboptimal temperature range, the seed germination increases asymptotically with temperature, and that as soil water content increases, the germination speed increases initially before decreasing, illustrating the trade-off effect of soil water on bioavailability of water and oxygen. Introducing a physiological dimension enables seed germination and the subsequent tillering process to be modelled as a continuous physiological process, providing deeper insight into plant growth dynamics.

Reconciling high crop productivity with reduced resource inputs is a primary challenge for sustainable agriculture in water-scarce regions. This study evaluated the feasibility of reducing nitrogen (N) fertilizer application for winter wheat under limited micro-sprinkler irrigation in the Huang-Huai-Hai Plain, China. A field experiment compared five treatments: a non-fertilized and non-irrigated control (CK), conventional flood irrigation with standard N (FI), and limited micro-sprinkler irrigation (80 mm) with standard N (MI), a 20% N reduction (MI1), and a 40% N reduction (MI2). We analyzed grain yield, water and N use efficiency (WUE and NUE) and the apparent soil N balance. WUE in this study was expressed as grain yield per seasonal evapotranspiration (ET), and NUE was evaluated using agronomic indices. The results showed that the MI1 treatment maintained a high grain yield that was not significantly different from the high-input FI and MI treatments. This high yield was sustained by a compensatory mechanism involving enhanced post-anthesis N assimilation and increased extraction of deep soil water, which offset the reduced inputs. Consequently, MI1 significantly improved WUE, irrigation water use efficiency (IWUE), and NUE, while reducing the apparent soil N surplus by 74.5% compared to FI. In contrast, the greater N reduction (MI2) led to a significant yield penalty. In conclusion, a moderate (20%) reduction in N top-dressing under limited micro-sprinkler irrigation presents a viable strategy to maintain high wheat yield, simultaneously enhance resource-use efficiency, and markedly reduce environmental N losses.

To accurately understand and investigate carbon fluxes in cropland ecosystems, this study adopted a machine learning ensemble model for estimation. Focusing on the Jinzhou station of the ChinaFLUX, we integrated eddy covariance carbon flux observations with multi-source satellite remote sensing data to construct a machine learning-based cropland carbon flux estimation model. For environmental driver selection, a strategy combining correlation analysis with ecological mechanism understanding was employed to screen LST, NDVI, and NDMI as model input variables, effectively avoiding multicollinearity issues. Using footprint-weighted integrated data from 2005 to 2014 for model training and validation, a Stacking ensemble model was constructed with the RF model serving as the meta-learner to stack the predictions of RF, CART, and GBM. The ensemble model further reduced the prediction error (RMSE = 39.82), maintaining an R² > 0.9 in most years and effectively improving predictive performance during anomalous years where single models underperformed. Based on these findings, the model was applied to analyze the spatiotemporal evolution of NEE in Jinzhou croplands from 2005 to 2014. The analysis revealed that while the region functioned overall as a carbon sink, it exhibited significant spatiotemporal heterogeneity. Spatially, the distribution followed a pattern of “strong intensity in the northeast and center, and weak intensity in the northwest and southwest.” Temporally, the sink intensity underwent significant interannual oscillations characterized by a “strengthening–weakening–re-strengthening–declining” trajectory. The high-precision prediction method proposed in this study is of great significance for revealing spatiotemporal variations in carbon sources/sinks, guiding green agricultural development, and supporting relevant policy formulation.

Conventional irrigation practices, characterized by excessive water application, have diminished water use efficiency (WUE) and intensified agricultural water consumption. Optimizing irrigation schedules and moderately reducing water input are therefore essential for enhancing WUE while safeguarding stable yields. Micro-sprinkler irrigation, which integrates the benefits of both drip and sprinkler systems, represents a promising technology with substantial water-saving potential. However, its effects on root development and crop yield remain inadequately investigated. Here, we established three micro-sprinkler irrigation regimes—MS20 (20 mm), MS30 (30 mm), and MS40 (40 mm)—alongside flood irrigation (FI) and rainfed (RF) controls, to systematically assess their impacts on soil water content, root growth traits, dry matter accumulation, yield, and WUE. Compared with FI, MS treatments decreased profile soil water content at jointing but increased it in specific layers during grain filling, albeit to varying extents. MS treatments enhanced total root length density (TRLD) and total root dry weight density (TRDD) relative to FI, with MS20 significantly increasing both parameters in the 20–100 cm soil layer. Moreover, MS20 increased pre-flowering dry matter translocation (PDMT) by 9.69% on average and post-flowering dry matter accumulation (PFDMA) by 15.04% during the 2022–2023 season. Yield and WUE under MS treatments exceeded those under FI by 3.46–6.53% and 4.42–21.21%, respectively. Among the MS treatments, MS20 achieved the highest average WUE. No significant yield or WUE differences were observed between MS20 and MS30, with MS30 producing the numerically maximum average yield. MS40 did not significantly affect yield in 2021–2022; however, it substantially reduced both yield and WUE relative to MS20 and MS30 in 2022–2023. A comprehensive TOPSIS analysis identified the combination of micro-sprinkler irrigation with total seasonal irrigation amounts of 80 mm or 120 mm as the optimal strategy for winter wheat production in the eastern Henan region of the North China Plain (NCP).