Root water uptake (RWU) is influenced not only by instantaneous soil conditions but also by two dynamic processes often neglected in models: stress hysteresis, arising from prior exposure to suboptimal water/salinity conditions, and compensation, whereby roots in favorable zones offset reduced uptake in zones less conducive to RWU. Empirical RWU models, such as the Feddes model (FM), are widely used but typically neglect these dynamic effects. Here, we extended FM by introducing a recovery coefficient to capture stress hysteresis and incorporating either a piecewise or continuous compensation function. Six models were tested: FM, single-process models WM (hysteresis), PM (piecewise compensation), and DM (continuous compensation); and combined-process models-WM-PM and WM-DM. Using data from a greenhouse soil column experiment with winter wheat, we found that both historical stress and spatial heterogeneity in root zone water and salinity strongly influence RWU and transpiration by plants. The coupled models (WM-PM, WM-DM) outperformed FM and single-process models in simulating transpiration dynamics, improvingR2 by 10.1-12.9% and 3.8-29.7% for actual and relative transpiration, while reducing RMSE by 27.6-36.4% and 13.8-41.9%, respectively. The WM-DM showed the highest accuracy attributed to its compensation function incorporating soil hydraulic conductivity, matric potential, and osmotic potential. Coupled with the one-dimensional Richards and convection-dispersion equations, WM-DM successfully reproduced soil water and salinity dynamics in greenhouse soil column experiment and a two-year field study of a winter wheat-summer maize rotation. In addition, model robustness analysis showed that WM-DM exhibited limited sensitivity to most parameters, lower uncertainties for the salinity and recovery stress response parameters than for the water-deficit and compensation stress response parameters, and unavoidable parameter non-uniqueness under simultaneous optimization. These findings highlight the value of accounting for both stress hysteresis and compensation in empirical RWU models for improved irrigation scheduling and salinity management.

Soil biosolarization, which combines organic matter incorporation with solarization, is effective for soil improvement but may generate substantial greenhouse gas (GHG) emissions. Plastic film mulching is a key operational factor in soil biosolarization. However, it remains poorly understood how different mulching strategies regulate soil temperature, moisture, and redox conditions and thereby reshape microbial carbon and nitrogen transformation pathways and GHG emissions. This study compared continuous film mulching (ContFM), no film mulching (NoFM), and intermittent film mulching (IntFM) during soil biosolarization. ContFM produced the highest soil temperature and moisture and likely favored the most persistent O-2-limited microenvironment with prolonged anaerobic conditions, while IntFM showed intermediate and phase-dependent characteristics between ContFM and NoFM. Compared with NoFM, ContFM increased soil temperature and moisture by 18.60% and 58.31%, respectively, suppressed aerobic oxidative metabolism, reduced cumulative CO2 emissions by 52.66%, and increased CH4 emissions by 1.44-fold through enhanced methanogenesis-related potential, especially acetoclastic methanogenesis. In nitrogen cycling, ContFM enhanced dissimilatory nitrate reduction potential, favored NH4+ retention, and strengthened terminal N2O reduction potential, thereby reducing NO3- content by 65.70% and N2O emissions by 95.37%. Consequently, ContFM lowered GWP by 62.40%. However, delayed establishment of O-2-limited conditions in IntFM may have caused a mismatch between upstream N2O-producing processes and terminal N2O reduction, resulting in only a 7.01% reduction in N2O emissions and a 20.10% reduction in GWP relative to NoFM. All treatments achieved high inactivation of F. oxysporum, while ContFM accelerated early-stage pathogen suppression. These findings suggest that ContFM can optimize GHG emission patterns and support cleaner biosolarization.

Moisture plays a critical role in crop growth and development, making accurate, efficient, and non-destructive detection and monitoring of crop water stress essential for advancing crop science research and optimizing production management. Traditional non-destructive methods for monitoring water stress primarily rely on color imaging or partial 2D spectral analysis. However, these methods are limited to two-dimensional features and fail to capture the spatial variability of water stress within the three-dimensional canopy structure of crops. To address this limitation, this study integrates RGB-D cameras and thermal infrared cameras and introduces a method for calculating the 3D spatial distribution characteristics of crop water stress using RGB-D-T fusion analysis. This approach enables high-precision detection and analysis of water stress in strawberry plants. An RGB-D-T acquisition system was designed and implemented to collect RGB images, depth images, and thermal infrared images of strawberries subjected to different moisture gradient treatments. Using the YOLOv8-seg deep learning model, semantic segmentation of the crop canopy and the wet reference surface was performed. The segmentation results were fused with 3D point cloud data to generate a 3D dataset incorporating temperature, color, and semantic information. Subsequently, the three-dimensional distribution characteristics and dynamic changes in the canopy water stress index (CWSI) of strawberry plants were analyzed under varying moisture conditions. The results demonstrated that under low moisture gradients (15%–30%), the CWSI value increased significantly and exhibited a concentrated distribution, indicating severe water stress. Conversely, under high moisture gradients (75%–90%), the CWSI value approached zero, reflecting sufficient water supply and complete stress alleviation. Additionally, the study highlighted the variation in the temperature difference between strawberry leaves and the surrounding air, confirming the sensitivity of strawberries to water stress across different reproductive stages. The response to water deficit was most pronounced during the growth phase. By fusing multi-source data, this study achieves 3D visualization and precise quantification of water stress in strawberries, providing innovative insights and technical support for precision irrigation and crop phenotyping research.

Biodegradable mulch film (BDM) residues in farmland have attracted extensive concern due to their low degradation rate in soil after the service period. However, different reactions of the bacterial and fungal communities to LDPEM and BDM residues have been confusing. A pot experiment was implemented to explore the influences of 0.5% and 2.0% (w/w) LDPEM and BDM residues on soil physicochemical properties and bacterial and fungal communities in the present study. The results indicated that BDM residues significantly increased soil pH and SOC to an increasing degree under the treatment with a higher mulch film residue amount, while LDPEM residues did not. The dissimilarities of the bacterial community between the treatment groups and the control ranged from 0.24 to 0.27, while the dissimilarities of the fungal community were higher, with the variation ranging from 0.43 to 0.46. Higher variations in the internal correlation coefficient were observed in the fungal community than in the bacterial community under the treatment groups. In addition, the modules of the bacterial community network increased from 2 to 3 under the BDM 0.5% and BDM 2.0%. Comparatively, the treatments with BDM residues doubled the modules of the fungal community network from 2 to 4. Structural equation modelling indicated that mulch film residues had a higher negative direct effect on fungal community structure (−0.752) than on bacterial community structure (−0.600). However, soil physicochemical properties had no significant influences on either bacterial or fungal communities. Overall, soil fungi respond more violently to mulch film residues than bacteria do.

Introduction There is limited knowledge about how co-applying organic fertilizer and zeolite influences maize yield and soil greenhouse gas (GHG) emissions in sandy loam soil.Methods In the present study, a 3-year maize field experiment was conducted on a sandy loam soil in the North China Plain with five treatments: no added fertilizer (control, CK), synthetic fertilizer (SF), organic fertilizer replacing 30% synthetic N fertilizer (OF), synthetic fertilizer with zeolite (ZSF), and organic fertilizer with zeolite (ZOF).Results Results showed that, compared with the SF treatment, the ZOF treatment significantly increased yield by 14.72-23.61% in each of the 3 years, ZSF by 13.91-15.59% in 2022 and 2023, and OF by 16.92% in 2023. Compared with ZSF, the cumulative CO2 emission was significantly increased by 4.52% in OF in 2023. Compared with SF, the average N2O emission flux and cumulative (over 2022 and 2023) N2O emissions were significantly reduced by 6.74-8.23% and 6.10-8.79% by OF, 9.29-11.86% and 9.23-10.85% by ZSF, and 7.59-11.24% and 12.27-16.06% by ZOF, respectively. Compared with SF, the total global warming potential (GWP) was significantly lower by 4.78% in ZOF in 2023, the greenhouse gas intensity (GHGI) was significantly lower over the 3 years of trials by 6.45-15.31% and 14.16-21.06% in treatments ZSF and ZOF, respectively, and was significantly lower by 10.53-13.13% in OF in 2022 and 2023. Compared with SF, the levels of available potassium and phosphorus content, dissolved organic carbon content, soil beta-glucosidase activity, and microbial biomass carbon and nitrogen concentration in the ZOF treatment were significantly higher by 7.34, 8.90, 19.48, 9.20, 8.42, and 11.29%, respectively; however, soil NH4+-N and NO3--N were significantly lower by 9.08 and 9.30%, respectively. The beneficial yield effects were due mainly to the enhanced synchronization of nutrient availability, soil moisture, and microbial biomass, while the mitigation of N2O emission was mainly attributed to the decreasing soil NO3- and NH4+ concentrations in response to ZOF.Conclusion Applying both organic fertilizer and zeolite achieved increased maize yield and positive environmental benefits. This strategy could be adopted to improve maize production, mitigate greenhouse effects caused by N2O emissions, and improve soil quality in sandy loam soils.

Straw returning is essential for soil conservation and mitigating wind erosion in semiarid regions bearing black soil areas. Quantitative studies on crop development and soil water-nitrogen dynamics processes under complete straw returning are fundamental for establishing a rational farmland management system. To model crop yields and soil profile water-nitrogen distribution under various fertilization treatments, we used the soil water heat carbon nitrogen simulator (WHCNS), namely CK (no fertilization), T1 (compound fertilizer), T2 (compound fertilizer + straw returning), and T3 (humic acid fertilizer + straw returning). We calibrated and evaluated the performance of the WHCNS model by using soil water content, nitrate nitrogen content, aboveground dry matter mass, and yield data collected from the Meilisi Daur District experimental farm in Qiqihar, Heilongjiang Province, in 2022. We also simulated the effects of different fertilization methods on spring maize field evapotranspiration, crop yield, and water-nitrogen use efficiency. The results indicate that the hydraulic parameters Qs and n significantly impacted the soil water content in the parameter sensitivity analysis. In contrast, SLAmax had the largest impact on soil nitrate nitrogen content among crop parameters, and Ts was the most influential factor on crop yield. The relative root mean square errors of simulated and observed soil water storage, nitrate nitrogen content, and aboveground dry matter mass were all lower than 32%. Consistency indices for the 0-60 cm and 60-100 cm soil layers were greater than or equal to 0.68 and 0.30, respectively. Finally, the Nash coefficients were within reasonable ranges. The evapotranspiration rate under the straw returning treatment (T2) was 6.33% lower than without straw returning (T1). T2 exhibited the highest water-nitrogen use efficiency among all treatments, and compared with T1 and T3, water-nitrogen use efficiency increased by 10.27%, 7.78%, 26.71%, and 48.15%, respectively. These findings suggest that straw returning can effectively reduce evapotranspiration and improve resource utilization efficiency. Overall, the calibrated WHCNS model can reliably simulate the dynamics of soil water- nitrogen movement and crop growth under straw returning in the semiarid regions of northeastern China.

Accurate groundwater depth (GWD) prediction is pivotal for designing effective drainage systems and formulating water management strategies, particularly in coastal regions where groundwater can impact soil water/solute transport and plant growth. This study introduces an innovative hybrid model for estimating GWD combining physical process-based and data-driven approaches. The process-based DRAINMOD model was employed to simulate GWD driven by water balance, while a data-driven model featuring nonlinear autoregressive networks with exogenous inputs (NARXε) was used to estimate and rectify the daily absolute error (ε) of the simulated GWD by DRAINMOD. An experiment was conducted in a coastal drained field encompassing two winter wheat-summer maize rotation cropping seasons from 2019 to 2021 in China's Yellow River Delta. DRAINMOD, NRAXGWD (to estimate GWD using NRAX) and a hybrid DRAINMOD-NARXε model were evaluated for simulating GWD under designed scenarios including varied drainage system parameters (drainage ditch depth and spacing) and data from the literature for an adjacent cotton field. The hybrid model significantly outperformed DRAINMOD and NRAXGWD in predicting daily GWD across a variety of periods with different initial groundwater levels and simulation time intervals during two rotation cropping seasons. The determination coefficient (R2) increased 6.7% and 10.2%, and normalized root mean squared error (NRMSE) reduced 47.9% and 17.0% when comparing the hybrid model to DRAINMOD and NRAX, respectively. More importantly, potential inaccuracies in GWD prediction due to irrational estimation of ε by NRAXε, were found to be manageable and controllable. The hybrid model inherited DRAINMOD's ability to extrapolate to other drainage management conditions, and provided the best prediction of monthly mean GWD in the adjacent cotton field. The hybrid model emerges as a reliable and promising method to predict groundwater level dynamics in coastal drained fields, and should be beneficial to field drainage system and water management strategy design.

The AquaCrop model has been extensively utilized to simulate the growth and yield of various crops across diverse environments, with transpiration-driven water consumption serving as a critical variable. While AquaCrop's treatment of root water uptake (RWU) and transpiration are relatively simplistic, improvement has recently been proposed via the inclusion of the effects of previous water stress, nonlinear characteristics of root distribution, and the relative distribution between soil water and roots. The objectives of this study were to compare and assess the RWU model utilized in AquaCrop (RWU-AC) against a revised RWU model (RWU-RE) using data from two greenhouse column experiments on winter wheat, and to integrate the revised RWU model into AquaCrop and assess its performance relative to the original model in simulating soil-plant water dynamics and crop growth. The column experiments encompassed loam and sandy soils, surface and subsurface irrigation, and different irrigation levels. Compared to the RWU-AC model, the RWU-RE model significantly improved the simulation accuracy of transpiration and soil water dynamics under various water supply conditions in a soilwheat system, with 44 % and 57 % average increase of determination coefficient (R2), and 62 % and 71 % average decrease of normalized root mean squared error (NRMSE), respectively. The RWU-RE model was subsequently incorporated into AquaCrop to investigate its simulation performance using data from a two-year field experiment on spring maize. Results indicated that the revised AquaCrop markedly improved the accuracy of the simulation for soil water distribution, transpiration, canopy cover, aboveground biomass, and grain yield, with R2 increased by 87 %, 18 %, 27 %, 7 %, and 10 %, and NRMSE reduced by 66 %, 52 %, 49 %, 44 %, and 69 %, respectively. The incorporation of the improvements in root-water-uptake and transpiration in AquaCrop makes it a more reliable tool for studying a wide range of crop responses to water, and hence helpful for optimizing irrigation strategies.

The study aims to elucidate the therapeutic mechanism of Baicalin (BAI) in alleviating cartilage injury in osteoarthritic (OA) rat models, concentrating on its regulation of the miR-766-3p/AIFM1 axis. An OA rat model was developed with unilateral anterior cruciate ligament transection (ACLT). Interventions comprised of BAI treatment and intra-articular administration of miR-766-3p inhibitor. For evaluation, histopathological staining was conducted to investigate the pathological severity of knee cartilage injury. The levels of oxidative stress (OS) indicators including MDA, SOD, and GSH-Px, were quantified using colorimetric assays. Inflammatory factors (IFs; TNF-α, IL-1β, and IL-6) in knee joint lavage fluids were assessed using ELISA, while RT-PCR was employed to quantify miR-766-3p expression. TUNEL apoptosis staining was utilized to detect chondrocyte apoptosis, and western blotting examined autophagy-related markers (LC3, Beclin, p62), extracellular matrix (ECM) synthesis-associated indices (COL2A, ACAN, MMP13), and apoptosis-inducing factor mitochondrion-associated 1 (AIFM1). Histological examination revealed a marked amelioration of cartilage injury in the BAI-treated OA rat models compared to controls. BAI treatment significantly reduced inflammation and OS of knee joint fluid, activated autophagy, and decreased chondrocyte apoptosis and ECM degradation. Interestingly, the inhibitory effects of BAI on these pathological markers were significantly decreased by the miR-766-3p inhibitor. Further assessment revealed that BAI efficiently promoted miR-766-3p expression while inhibiting AIFM1 protein expression. BAI potentially mitigates articular cartilage injury in OA rats, likely through modulation of miR-766-3p/AIFM1 axis.

Characterizing the effects of previous water and salinity stresses is critical for the evaluation of plant water status, which, in turn, is essential for understanding soil-plant water relations and optimizing irrigation schemes. Recent research has found that hysteresis of plant response following water stress alone can be described by an exponential function of the stress degree on the previous day. To explore and quantify the effects of hysteresis concerning salinity stress and combined water-salinity stress, a hydroponic experiment and a soil column experiment on winter wheat, and a field experiment on cotton were conducted. Like water stress, previous salinity stress and combined water-salinity stress also resulted in hysteretic effects on root-water-uptake. Leaf stomatal conductance and plant transpiration rate of stressed crops could only recover gradually from a previous stressed status after re-watering. When stress was mild, compensatory recovery was found, while incomplete recovery occurred when stress was severe. Although the recovery process was closely related to stress history and type, a recovery coefficient was quantified universally with an exponential function of the stress extent on the previous day (with a coefficient of determination R2 >= 0.60). Consideration of hysteresis for water and salinity stresses with a mathematical model led to significant improvement in the simulation of both relative transpiration rate (R2 = 0.94, root mean squared error RMSE = 0.04, maximal absolute error MAE = 0.12) and soil water content (R2 = 0.90, RMSE = 0.01 cm3 cm-3, MAE = 0.03 cm3 cm-3), especially during the recovery periods severely affected by historical stress. Consideration of hysteresis is expected to benefit regulation of soil water and salinity and thus enhance water use efficiency. However, the mechanisms underlying hysteresis, especially the compensatory recovery mechanisms, still need to be further investigated.

Accurate monitoring and evaluation of root-zone soil salt content (SSC) are critical for sustainable development of irrigated agriculture in arid and semi-arid areas. Based on soil-crop water relations and farmland evapotranspiration (ET) fused through remote sensing data, this study developed an inversion method to estimate root-zone SSC using a case study from cotton fields under film mulched drip irrigation (CFFMDI) in the Manas River Basin (MRB) over 21 years (2000–2020). Two hypotheses were set as: (1) relative transpiration can be approximated by relative ET; and (2) the soil water stress response function is linearly proportional to the ratio of relative water supply. Measured data from a field experiment and collected data from regional survey and literature retrieval were used to optimize parameters and verify the hypotheses and method. The method was then applied to analyze the spatial and temporal distribution characteristics and cumulative effects of root-zone SSC. Results showed that the hypotheses and the method were reasonable and reliable in estimating root-zone SSC (with coefficient of determination R2 > 0.50). Along with the popularization of film-mulched drip irrigation and the expansion of CFFMDI over the past 21 years, regional-scale root-zone SSC declined significantly with an annual attenuation rate of about 0.09 g kg−1. Due to the gradual reduction of irrigation amount per unit area, the decline was more rapid before 2011 (0.18 g kg−1), but slightly slowed down or even reversed at the end of the second decade (2015–2020). By 2020, the mean regional root-zone SSC reached 3.93 g kg−1. At the beginning of this century, MRB was mainly composed of mildly- (59.8%) and moderately-salinized CFFMDI (39.9%). However, by 2020, non- (69.7%) and mildly-salinized cotton field (28.2%) dominated the basin. The inversion method of root-zone SSC fully considers the water consumption mechanism of soil-crop system, thus shows great potential in effective planning and management of soil and water resources in arid salinized areas such as MRB.

利用咸水或微咸水进行农田灌溉是缓解中国新疆地区农业水资源供需矛盾从而保障当地棉花产业可持续发展的主要途径之一.为了明确不同咸水灌溉措施对棉花产量及经济效益的影响,该研究通过2 a的棉花膜下滴灌大田试验和文献检索获取了新疆9个不同试验地点的土壤、作物及灌溉等数据资料,评估作物产量-水盐胁迫响应分析模型(ANalytical Salt WatER,ANSWER)在新疆棉花产量评估中的适用性和可靠性,并结合经济收支平衡方法,模拟分析不同咸水灌溉措施(包括不同灌溉定额和灌溉水电导率的组合)对棉花产量与经济效益的影响.采用决定系数(R2)、均方根误差(root mean squared error,RMSE)、相对均方根误差(relative root mean squared error,RRMSE)评价模型精度.结果表明,在9个不同试验地点,ANSWER模型均可较准确地估算棉花的相对产量,其估算值与实测值之间的R2≥0.54,RMSE≤0.14,RRMSE≤0.16;不同试验地点,优化获得的各个模型生物参数(与棉花根系吸水的水盐胁迫响应相关的参数)差异较小,变异系数的绝对值处于0.08～0.37之间;基于不同试验地点优化的各生物参数均值估算各地的棉花相对产量,其与实测值仍然吻合良好(R2为0.59,RMSE为0.06,RRMSE为0.07);此外,当灌溉水电导率一定时,棉花净收益随灌溉定额增加呈先增后降的趋势,净收益达到峰值所需的灌溉定额随灌溉水电导率升高而迅速增加;当灌溉水电导率不大于10 dS/m时,通过加大供水量均可获得与淡水灌溉相当的净收益.研究可为新疆地区棉花产量与效益评估以及咸水资源合理开发利用提供理论依据.

Delineating root-water-uptake (RWU) under conditions with augmented CO2 concentrations is very important for scheduling irrigation to contend with climate change. Responses of plant growth to elevated CO(2)concentration (e[CO2]) have been widely reported, while the effects of e[CO2] on RWU has hardly been studied. A hydroponic experiment of wheat (Triticum aestivum L.) with five NO -3-N concentrations (Exp. 1) was conducted to investigate and quantify the effects of e[CO2] on RWU activity. Another experiment growing wheat in soil columns with four combinations of water and N supply levels (Exp. 2) was conducted to validate the results obtained in Exp. 1, establishing a macroscopic RWU model to simulate soil water dynamics under e[CO2]. Although CO2 acclimation was observed in both experiments, plant canopy and root growth were generally stimulated under e[CO2], while transpiration consumption was not synchronously enhanced due to decreased stomatal conductance, indicating an increase in water use efficiency while a decrease in RWU activity. Potential transpiration was found more linearly related to root nitrogen mass (RNM) than root length under various CO2 concentrations, regardless of wheat growth stage, water and N supply level. Consequently, RNM density was used to drive the RWU model. The results from Exp. 1 indicated that the effects of e[CO2] on water uptake coefficient per RNM could be quantified by a recently proposed nonlinear stomatal conductance response model (R-2 = 0.84, RMSE = 0.55 cm(3 )mg(-1) d(-1)). The RWU model reliably simulated the dynamics of soil water transport and wheat transpiration under e[CO2] in Exp. 2 with the RMSE and relative errors mostly less than 0.03 cm(3) cm(-3) and 10 %, respectively. Practical application of the established RWU model for any other specific conditions is expected to benefit from optimization of parameters following choice of most appropriate stomatal conductance response model.

现代的温室是一个复杂的环境系统,其中土壤、作物和微气候三个子系统间各种生物和非生物现象时常发生.农业数学模型可以用来模拟和预测温室内微气候和植物生长的变化,从而推荐最优化的生产管理策略.本文对国内外温室气候模型和温室作物生长模型进行了综述,温室气候动态模型可以预测关键气候因子,分为机械模型和黑箱模型.机械模型基于物理方程构建,它描述了基于过程的知识模拟的系统;黑箱模型属于经验模型,更多地用于温室系统控制、优化和设计的应用.作物生长模型是基于科学原理和数学关系的一种定量化工具,可以评估温室内土壤、微气候、水分和管理因素对作物生长发育的影响程度,预测作物生长状况.作物生长模型主要包括两类:描述性模型和解释性模型.温室作物模型是基于露地作物建立的最早的作物生长模型,并在几十年发展过程中对原来各功能模块进行修正、扩展和升级而来.功能-结构植物模型(functional–structural plant modeling,FSPM)是基于植物建筑学并结合气候和作物模块而形成,可以模拟单个植物的生长、形态以及它们与其生长环境的相互作用.最后指出未来趋势是利用数字技术、人工智能结合FSP模型,利用云数据储存计算分析.

Plastic film mulching and organic fertilisation result in the coexistence of mulch film residues of multiple sizes and antibiotic resistance genes (ARGs) in farmlands. However, the differential effects of large and small low-density polyethylene mulch film (LDPEM) and biodegradable mulch film (BDM) residues on ARGs have not yet been studied. In this study, we investigated the dynamic variations in soil ARGs induced by organic fertiliser application under treatments with different LDPEM and BDM residue sizes. The results indicated that the target ARGs could be divided into six clusters according to their variation characteristics with sampling time. The reduction rates of most target ARGs, including ermC, aadA-01, qacEdelta1-01, sul1, sul2, tetM-01, tetM-02 and tetPA in treatments with large mulch film residues were lower than those with small mulch film residues for both LDPEM and BDM, which resulted from the higher average degree and positive correlation ratio in the networks between the soil bacterial community and ARGs. The results of structural equation modelling indicated that soil bacterial communities directly affected soil ARGs, with a path coefficient of −0.6428. Soil physicochemical properties and soil enzyme activities affected soil ARGs through the soil bacterial community with path coefficients of 0.24 and 0.28, respectively. The results of the present study emphasise that the environmental impact of large mulch film residues should not be ignored.

The combined pollution of microplastics (MPs) and Cd can affect plant growth and development and Cd accumulation, with most studies focusing on dryland soil. However, the effects of polyurethane (PU) controlled-release fertiliser coated MPs (PU MPs), which widely exist in rice systems, coupled with Cd on plant growth and Cd accumulation under flooding conditions are still unknown. Therefore, in the present study, in situ techniques were used to systematically study the effects of PU MPs and Cd coupling on the physiological and biochemical performance, metabolomics characteristics, rhizosphere bacterial community, and Cd bioavailability of rice in different soil types (red soil/cinnamon soil). The results showed that the effects of PU MPs on rice growth and Cd accumulation were concentration-dependent, especially in red soil. High PU concentration (1 %) inhibited rice root growth significantly (44 %). The addition of PU MPs inhibited photosynthetically active radiation, net photosynthesis, and transpiration rate of rice, mainly with low concentration (0.1 %) in red soil and high concentration (1 %) in cinnamon soil. PU MPs can enhance the expression of Cd resistance genes (cadC and copA) in soil, enhance the mobility of Cd, and affect the metabolic pathways of metabolites in the rhizosphere soil (red soil: fatty acid metabolism; cinnamon soil: amino acid degradation, heterobiodegradation, and nucleotide metabolism) to promote Cd absorption in rice. Especially in red soil, Cd accumulation in the root and aboveground parts of rice after the addition of high concentration PU (1 %) was 1.7 times and 1.3 times, respectively, that of the control (p < 0.05). Simultaneously, microorganisms can affect rice growth and Cd bioavailability by affecting functional bacteria related to carbon, iron, sulfur, and manganese. The results of the present study provide novel insights into the potential effects of PU MPs coupled with Cd on plants, rhizosphere bacterial communities, and Cd bioavailability.