Metal-organic frameworks (MOFs) are attractive for ion separation membranes due to their exceptional molecular sieving precision. However, issues such as poor pore connectivity, insufficient porosity and weak pressure stability continue to impede their practical implementation. Herein, we report an amphoteric polymer-mediated interfacial strategy for the in-situ growth of a ZIF-8 selective layer on a PEEK substrate, enabling the fabrication of continuous, defect-free composite nanofiltration membranes. In this approach, we designed a bifunctional polymer interlayer via UV-initiated copolymerization of acrylic acid and 1-vinylimidazole which plays two critical roles: it templates the oriented growth of a dense ZIF-8 layer and simultaneously undergoes in-situ chemical reconstruction to generate free carboxyl groups that serve as cooperative Mg2+ recognition moieties.The resulting PEEK@ZIF-8 membrane demonstrates an exceptional combination of selectivity and permeability, achieving a record Mg2+/Li+ separation factor of up to 98.44 alongside a high pure water permeability of 18.1 L·m-2·h-1·bar-1, surpassing most reported nanofiltration membranes. Mechanistic studies reveal that the separation performance originates from a cooperative size-sieving and charge-repulsion effect within a rationally designed triple-layer "wide-narrow-wide" architecture. This work provides a versatile and scalable platform for designing stable, high-flux MOF composite membranes, offering a promising solution for energy-efficient lithium extraction and other precise ion-separation applications.

Recycling organic phosphorus (P) sources may reduce dependence on synthetic P fertilizers in sustainable agriculture. However, the overall lack of understanding of the impact of organic P management practices on crop yields and the environment limits further optimization of organic P strategies. Herein, we first executed a global meta-analysis of over 860 paired observations to validate potential indicators for delineating risk zones for organic P fertilizer management. Then, a combination of machine learning tools and global datasets was used to further identify the risk zones for organic P management practices. Finally, an optimal organic P management strategy was developed considering the total P inputs, types of organic P sources, organic P proportions, and organic P management risk zones. Results indicated that the P activation coefficient (PAC) can be used as a potential indicator for delineating risk zones for organic P management. Hypothesis-oriented path analysis suggests that P inputs under low-soil-PAC conditions drive the preferential allocation of P to the occluded and moderately labile P pools and that organic P fertilizer application can positively affect labile P. P inputs under high-soil-PAC conditions have a more balanced effect on various P fractions of soil, and P inputs through organic fertilizers are primarily stored in the organic P pool. Current organic P management practices do not benefit food production in case of low-soil-PAC cropland and may increase the risk of P runoff in case of high-soil-PAC cropland. A combination of optimal organic P management with risk zones achieved a 13.3 % reduction in global P runoff and a 10.7 % increment in global food production compared with the use of synthetic P fertilizers alone. Our study provides a solution for enhancing the efficient use of organic P resources to create more productive, clean, and sustainable food production systems.

Herbicide residues following extensive use of amide herbicides (AHs) have become a major global concern. The present study established a hierarchical evaluation system for AH residual risk using the gray whitening weight function cloud model (gray cloud model). Furthermore, we developed a priority control list for the AH residual risk. Among the herbicides evaluated—pethoxamid, carbetamide, and diphenamid—exhibited higher residual risks. Consequently, these were included in the priority control list and designated as priority control herbicides. Second, a 3D-QSAR model of the AH residual risk index was established using the molecular similarity indices in a comparative analysis method. Notably, the effect value of the AH molecular residual index was considered as the dependent variable and molecular structure as the independent variable. Metolachlor was used as the target molecule for the molecular design of the AH substitutes. Based on the 3D-QSAR and gray cloud models, the residue risk grade of the newly designed molecules was evaluated, and 21 types of metolachlor substitute molecules with reduced residue risk were designed. Among them, the residue risk of one metolachlor substitute was reduced from medium residue risk (III) to low residue risk (II), whereas that of 20 metolachlor substitutes were reduced from medium residue risk (III) to minimal residual risk (I). Based on the human health risk assessment, ecological risk, herbicidal efficacy, and synthesis, seven types of metolachlor substitute molecules were identified with high herbicidal efficacy, safe medication, easy synthesis, and low residual risk. Furthermore, the results of reducing the residual risk before and after the molecular modification of AHs were determined. The present study addresses the issue of pesticide residues resulting from the long-term and large-scale AH application in agricultural production, offering a new basis for AH control and providing theoretical guidance for reducing chemical herbicide residues.

The practical application of metal-organic framework (MOF) membranes is hindered by poor processability and unstable polymer-MOF interfaces. We report a hydrogel-mediated interfacial engineering strategy to fabricate robust MIL-101(Fe)@PEEK nanofiltration membranes via in situ solvothermal growth on a photografted poly(acrylic acid) (PAA) hydrogel layer. The PAA layer serves as both a coordination anchor for Fe3+ and a nucleation platform, enabling the formation of a dense, defect-free MIL-101(Fe) layer with exceptional interfacial integrity. The membrane exhibits ultrahigh water permeance (150.6 L m(-2) h(-1)& centerdot;bar(-1)), a sharp molecular weight cut-off (similar to 376 Da), and a remarkable separation factor of 106.7 for MgCl2/Congo Red mixtures. Molecular dynamics simulations reveal a dual transport mechanism combining size-selective permeation through MOF pores and enhanced interfacial diffusion. Beyond separation, the membrane integrates multifunctional capabilities including efficient dye adsorption, sunlight-driven photocatalytic degradation of antibiotics, and robust self-cleaning with >90% flux recovery. The membrane withstands ultrasonic, mechanical, and high-pressure stresses without performance loss, demonstrating exceptional durability. This work provides a scalable strategy for designing next-generation MOF-based membranes with stable interfaces and synergistic functionalities for sustainable water treatment.

Harvest total shoot phosphorus uptake (TSPU) is difficult to estimate from unmanned aerial vehicle (UAV) canopy imagery because phosphorus (P) accumulation is unevenly distributed among leaves, stems, and grains, whereas UAV observations primarily capture an integrated and stage-dependent canopy signal. Here, we developed a phenology-aware organ-specific multi-temporal UAV framework that shifts maize TSPU estimation from conventional direct regression to organ-aware target construction. Multi-temporal spectral and textural features acquired at the jointing, grain-filling, and milk-ripe stages were integrated to compare three strategies under the same leakage-aware feature-selection and validation framework: direct TSPU prediction (M1), organ-specific uptake decomposition (M2), and concentration–biomass integration (M3). In the Site 1 fixed-split benchmark, M2 with fused spectral–textural inputs achieved the highest validation accuracy, reducing root mean square error (RMSE) by 9.53% and mean absolute error (MAE) by 12.07% relative to M1 with the same inputs. Additional organ-level uncertainty analysis showed that this improvement should not be interpreted as uniformly high predictability of all organ components. The TSPU reconstruction was mainly supported by stem P uptake (SPU) and grain P uptake (GPU) and was primarily controlled by GPU-related uncertainty. Leaf P uptake (LPU) remained weakly observable from canopy-level UAV predictors, indicating that M2 should be interpreted as an organ-specific diagnostic reconstruction framework. By contrast, M3 did not further improve performance, indicating that physiologically explicit intermediate predictions may introduce additional uncertainty when canopy observability is constrained. External-field evaluation showed that local calibration supported TSPU reconstruction at Site 2, with strong agreement in full-sample reconstruction (R2 = 0.87, RMSE = 5.81 kg ha−1, n = 120) and moderate accuracy in fixed-split validation (R2 = 0.61, RMSE = 10.03 kg ha−1, n = 36). The matched validation further confirmed that external-field uncertainty was dominated by GPU-related residuals, which accounted for 81.2% of the total absolute organ-level residuals and 97.4% of the component residual variance, highlighting the need for local recalibration and organ-level residual diagnosis. Field-scale mapping experiments further showed that the finest UAV resolution was not necessarily the most practical for P uptake mapping. In this study, an intermediate resolution of approximately 2.5 m provided a locally suitable compromise between preserving within-field heterogeneity and reducing map fragmentation. These findings demonstrate that organ-specific target construction combined with multi-temporal spectral–textural UAV information can moderately improve maize TSPU estimation under fused inputs and, more importantly, diagnose the organ-level sources of prediction uncertainty, thereby providing practical guidance on local calibration and mapping resolution for field-scale P uptake mapping and potential precision P management.

Straw return is an effective agricultural strategy for incorporating organic carbon into soil organic matter pools through microbial decomposition. This process modifies soil physicochemical properties, thereby altering microbial habitats and resource availability, which can influence the structure and function of soil microbial communities. However, the changes of soil physicochemical properties and microbial communities under different straw incorporation forms remain poorly understood. And how these straw return materials alter soil physicochemical properties and microbial communities within a single cycle. In this study, we conducted straw returning experiments in a maize-producing region of Jilin Province, China, comparing the impact of two distinct maize-derived residues (crushed maize straw and crushed corncob) on soil quality and microbial communities. Our results demonstrated that corncob return more effectively improved key soil physicochemical properties compared to maize straw return. While neither residue significantly alters microbial alpha diversity, both induced shifts in beta diversity. We identified distinct correlations between dominant microbial taxa and key soil physicochemical parameters. Furthermore, KEGG and GO analyses revealed that both of the residues altered microbial functional hierarchies, with corncob return inducing more pronounced changes than maize straw return. These findings provide a mechanistic basis for optimizing straw management strategies to enhance microbial-mediated soil fertility.

Covalent organic networks (CONs) membranes show unprecedented potential for the separation of organic small molecules owing to their adjustable structure and surface properties. Despite the variety of methodologies available for synthesizing CONs membranes, the preparation of CONs membranes by interfacial polymerization (IP) at 25 degrees C in a shorter period of time remains a great challenge. In this work, a highly anti-fouling EDA-TPA CONs composite nanofiltration (NF) membrane with adjustable structure was constructed by rapid IP of amine (ethylenediamine, EDA) and aldehyde (terephthalaldehyde, TPA) at 25 degrees C for 3 h. EDA-TPA CONs composite membranes showed good selectivity for most common organic small molecules, achieving a permeance of 35 L h- 1 m- 2 bar- 1. Moreover, with respect to anti-fouling properties, the EDA-TPA CONs composite membranes exhibited a 96 % flux recovery ratio (FRR) during bovine serum albumin (BSA) filtration, reflecting an 81 % improvement compared to the control membranes (hydrolyzed polyacrylonitrile, HPAN). In addition, the EDATPA CONs composite membranes displayed robust comprehensive stability after continuous operation of 480 min, 5 times of cyclic testing, 180 min of continuous ultrasound at 16 kHZ and 24 h of mechanical agitation at 100 rpm. After these extensive evaluations, the EDA-TPA CONs composite membranes still retained their original separation efficacy. This study provides a fast and mild preparation process to fabricate the high performance CONs composite membranes with good anti-fouling performance and stability for treatment of organic small molecules in wastewater.

Highly permeable polyamide (PA) membranes with precise molecular sieving capabilities are crucial for energy-efficient chemical separations. There is a critical need to design solvent-stabilized membranes with enhanced permeance to improve separation efficiency. In this work, we propose a novel anhydrous interfacial polymerization (IP) method, where flexible polyethyleneimine (PEI) and rigid p-phenylenediamine (PPD) are uniquely dissolved in isopropanol (IPA) and subsequently crosslinked with trimethyl chloride (TMC) in situ to fabricate high-performance PA membranes. Notably, the use of IPA as a solvent represents a significant advancement in membrane fabrication. This approach resulted in PA membranes with a relatively loose selective layer compared to traditional PA membranes, allowing for exceptionally high solvent permeance while maintaining strong rejection performance in organic solvent nanofiltration (OSN). The obtained PEI+PPD/TMC PA membranes demonstrated outstanding ethanol (EtOH) permeance of 46.44 L m-2 h-1 bar-1 in the organic solvent system, along with good rejection for small organic molecules, such as 93.84% for Eriochrome Black T (EBT, 461.38Da). In addition, the performance of the PEI+PPD/TMC PA membranes remained at a high level even during 510 min of continuous cross-flow filtration, under high pressure (5 bar) testing, and after 6 cycles of separation, which demonstrated their good stability in long-term service. This work establishes a robust foundation for employing anhydrous IP reactions and innovative solvent systems, such as IPA, to develop high-permeance PA membranes.

The soil ecosystem has been severely damaged because of the increasingly severe environmental problems caused by excessive application of phosphorus (P) fertilizer, which seriously hinders soil fertility restoration and sustainable farmland development. Shoot P uptake (SPU) is an important parameter for monitoring crop growth and health and for improving field nutrition management and fertilization strategies. Achieving on-site measurement of large-scale data is difficult, and effective nondestructive prediction methods are lacking. Improving spatiotemporal SPU estimation at the regional scale still poses challenges. In this study, we proposed a combination prediction model based on some representative samples. Furthermore, using the experimental area of Henan Province, as an example, we explored the potential of the hyperspectral prediction of maize SPU at the canopy scale. The combination model comprises predicted P uptake by maize leaves, stems, and grains. Results show that (1) the prediction accuracy of the combined prediction model has been greatly improved compared with simple empirical prediction models, with accuracy test results of R2 = 0.87, root mean square error = 2.39 kg/ha, and relative percentage difference = 2.71. (2) In performance tests with different sample sizes, two-dimensional correlation spectroscopy i.e., first-order differentially enhanced two-dimensional correlation spectroscopy (1Der-2DCOS) and two-trace 2DCOS of enhanced filling and milk stages (filling-milk-2T2DCOS)) can effectively and robustly extract spectral trait relationships, with good robustness, and can achieve efficient prediction based on small samples. (3) The hybrid model constrained by the Newton-Raphson-based optimizer’s active learning method can effectively filter localized simulation data and achieve localization of simulation data in different regions when solving practical problems, improving the hybrid model’s prediction accuracy. The practice has shown that with a small number of representative samples, this method can fully utilize remote sensing technology to predict SPU, providing an evaluation tool for the sustainable use of agricultural P. Therefore, this method has good application prospects and is expected to become an important means of monitoring global soil P surplus, promoting sustainable agricultural development.

This study leverages a traditional in-situ growth method to prepare covalent organic frameworks (COFs) membranes that can effectively treat oil/water mixtures, especially challenging oil-water emulsions. We construct bionic functional layers of COFs in situ on the fiber surface, that feature a mechanically robust, strong interfacial adhesion, unique hydrophilicity, reduce pore clogging and improve the specific surface area, which facilitates adsorption. Tightly weaving these fibers and COFs produces Eucommia ulmoides gum (EUG)@TAPB-PDA-COF membranes, the separation efficiency up to 99 % or more. Gravity-driven separation is employed to effectively treat n-hexane-in-water emulsion, attaining a flux of up to 2597 ± 14 L·m-2·h-1. The EUG@TAPB-PDA-COF demonstrate outstanding chemical stability, maintaining structural integrity when exposed to strong acids, bases, high-concentration saline solutions, and various organic solvents. The EUG@TAPB-PDA-COF show superior adsorption capacity for organic dyes, achieving removal efficiencies exceeding 93 % for crystalline violet. These excellent properties make EUG@TAPB-PDA-COF an ideal candidate for the treatment of oily water waste streams and the removal of dyes.

Remote sensing technology and machine learning methods are being scaled up globally to predict nutrient content based on spectral data. However, there is a lack of rigorous comparison of co-benefit delivery across different factors, which leads to unstable accuracy of the final model owing to insufficient analysis of the factors influencing the prediction model. In particular, for nutrients (e.g. phosphorus), visual symptoms are not obvious or have a certain lag. Therefore, a Three-Level Meta-Analysis model was proposed in this study to extract and analyse a large number of studies, delving into the analysis of various influencing factors and filling the current knowledge gap. Through global synthesis, a Three-Level Meta-Analysis was applied to seven validated datasets of field observations from multispectral remote sensing, including 32 effect sizes, and 46 datasets of field observations from hyperspectral remote sensing, including 630 effect sizes. We thoroughly explored the heterogeneity of a Three-Level Meta-Analysis using the new machine learning method Meta-Forest, while also using Meta-Cart to explore the interaction effects between moderating variables. Through a comprehensive analysis of the literature published over the past 25 years, we determined the importance of matching preprocessing and regression methods for predicting plant phosphorus spectral responses. The combination of pretreatment and regression methods is particularly important for regional-scale phosphorus concentration prediction. Baseline calibration is effective in removing background noise at the regional scale; however, it cannot solve the problem of redundancy between hyperspectral data. It is necessary to combine a regression method that can effectively deal with redundancy between data to improve the accuracy of the model. Nonlinear non-parametric regression can better deal with the complex nonlinear relationship between phosphorus concentration and spectral data and can resist the influence of the quantity and quality of the data itself and the heterogeneity of the study area; therefore, it has excellent prediction ability. The type of spectrometer is crucial for predicting regional phosphorus concentrations using multispectral data, especially when collecting data using drones. This study provides guidance for fully utilising spectral data and establishing a fast, efficient, and non-destructive prediction model for plant P concentrations, revealing the optimal selection of data preprocessing and regression methods.

Fabrication of crystalline, robust graphene oxide (GO) OSN membranes is promising yet highly challenging. Herein, we prepare a SPEEK@GO/PEEK solvent-resistant composite membrane by novel weaving strategies. Among the process, SPEEK is seen as the "line", repaired of broken small pieces of GO. This facile weaving can significantly improve the separation performance and the whole stability of the membrane and effectively remove small dyes in organic solvents. The stable composite membrane exhibited excellent performance and high solvent permeance for organic solvents (DMF, 22.71 L·m-2·h-1·bar-1; acetone, 121.77 L·m-2·h-1·bar-1). The rejection rate of Acid fuchsin (AF,585 Da) exceeded 92% in DMF. The membranes exhibited excellent stability. Even after ultrasound, solvent immersion, high temperature treatment, fouling by BSA, and a long operation process, the composite membrane still maintains its original microstructure and separation performance. Taken together, this work may provide considerations in designing high performance and robust GO membranes with a stable interface.

The production of methane from straw lignocellulose is limited by its structure. It is necessary to break the complex structure and prevent the loss of cellulose/hemicellulose by lignin-removing pretreatment. This paper designed bidirectional selective hydrolases based on laccase of Pleurotus ostreatus (Q6RYA4) and Bacillus subtilis (E7EDN4), established Scenario 1 (6 % H2SO4 and E7EDN4-2) and Scenario 2 (5 % NaOH and E7EDN4-12), significantly enhancing lignin hydrolysis while minimizing cellulose/hemicellulose hydrolysis using homology modeling, molecular docking and molecular dynamics. The suitable environmental conditions for the scenarios were determined through L9 Taguchi orthogonal. Resveratrol was found to enhance enzyme activity in an acidic environment, while rhamnolipid in an alkaline environment. The enhanced mechanism of lignin hydrolysis was elucidated through the hotspots amino acids, root mean square fluctuation, and enzyme adsorption-desorption process. Subsequently, the deep learning algorithm was employed to conduct the enzyme turnover numbers of new hydrolases, quantifying lignin hydrolysis rate and theoretical methane yield. Compared with E7EDN4, the lignin hydrolysis rate in Scenario 1 and 2 increased by 208.16 % and 272.49 %, while the theoretical methane yields were increased by 98.23 % and 97.96 % under suitable environmental condition of appropriate concentration of exogenous substances (rhamnolipid or resveratrol). This study constituted an advanced technology for the high-efficiency utilization of cellulose/hemicellulose, which offered novel insights and approaches for the biological enhancement of the pretreatment of lignocellulose.

In this study, an innovative strategy of fabricating Janus hollow fiber membrane to produce microbubbles for enhancing CO2 removal was proposed. The polyvinylidene difluoride (PVDF) hollow fiber membrane was prepared using two different hydrophilic dopes followed by modification with 1H, 1H, 2H, 2H-perfluorodecyltriethoxysilane (FAS). The contact angle of the Janus hollow fiber membrane was 37 degrees for the outer layer and 122 degrees for the inner layer. Attenuated total reflectance Fourier transform infrared spectrometer (ATR-FTIR) and Xray photoelectron spectroscopy (XPS) were employed to verify the grafting of FAS onto the inner layer of membrane. The unique morphology showing a progressive transition from sponge-like to finger-like pores, extending from the inner to the outer layer, was examined using a scanning electron microscope (SEM); this morphology helped reduce mass transfer resistance. Microbubbles were produced by the prepared Janus hollow fiber membrane at high and consistent fluxes. The CO2 mass transfer flux reached 5.0 x 10-3mol m-2 s-1 under the gas-liquid pressure difference of 0.10 MPa. The average size of microbubbles was 75 mu m and the CO2 removal rate was nearly 100 % in CO2 removal experiments. The Janus hollow fiber membrane developed in this study exhibited good aeration property and application potential in post-combustion CO2 capture.

As a critical factor influencing crop productivity in agricultural ecosystems, phosphorus (P)-fertilizer application can significantly alter soil physicochemical properties. However, the relative efficiencies of different types of spatially stratified P fertilizers and their underlying biological mechanisms remain insufficiently elucidated. In this study, an 8-year field experiment was conducted in a black soil region of Northeast China to compare the effects of five P-fertilization regimes: CK (without P application), FP (100% as basal fertilizer), APP (20% as starter fertilization by ammonium polyphosphate), MAP (20% as starter fertilization by monoammonium phosphate), and CMP (20% as starter fertilization by calcium magnesium phosphate). We systematically investigated the effects of spatially stratified P fertilization on soil physical properties, nutrient accumulation, maize yield performance, and bacterial and fungal community structure. CMP demonstrated the best performance in improving soil aeration and enhancing water infiltration capacity. MAP significantly increased the soil total P content by 18.62% and the soil Olsen-P content by 81.46% compared to those of FP. Both MAP and CMP promoted P uptake in various parts of maize plants, including the roots, straw, and grains. All tested starter P fertilizers improved P use efficiency. Compared to that of FP, the soil P surplus was reduced by 7.52%, 14.74%, and 13.04% under APP, MAP, and CMP, respectively. MAP demonstrated the most pronounced yield-increasing effect. Based on amplicon sequencing (16S rRNA for bacteria, interspacer region for fungi) and microbiome profiling, this study confirms that fungi are more susceptible than bacteria to variations in fertilizer types and application methods. Furthermore, the relative abundance of Tausonia was most significantly influenced by MAP. By enhancing the relative abundance of P-cycling functional genes (gph, phoU), MAP modulated the abundance of dominant microbial taxa such as Acidobacteria and Proteobacteria, thereby significantly improving maize yield. Therefore, in maize cropping systems in the black soil region of Northeast China, optimized P fertilizer selection and application methods can effectively reduce soil P surplus and modulate microbial community structure and functional diversity while maintaining stable crop yields.

Covalent organic frameworks (COFs) are a novel materials platform that combines covalent connectivity, structural regularity, and molecularly precise porosity. However, COFs usually form insoluble aggregates, which limits their wide application in separation membranes. Here, we adopted "reaction-separation-assembly" strategy to produce continuous and uniform COFs membranes with controllable thickness. Our experimental data showed that the strategy can manipulate colloidal COFs suspensions to create tailored selective layer. The obtained membranes exhibited high pure water flux of 150 L m (-2) h(-1) bar(-1), good salt/dyes separation factor and superior molecular sieving ability (> 90 % for active pharmaceutical ingredients, >97 % for dyes molecules), which is substantially higher than that of commercial NF1. In addition, the prepared composite membranes showed superior stability, especially under harsh conditions such as strong acids (4 mol L-1 HCl) and strong bases (2 mol L-1 NaOH). Overall, this work provides a promising approach for highly permeable and stable COFs membranes, and facilitates rapid recycling of small organic molecules such as active pharmaceutical ingredients and dyes.

Fabrication of high crystalline, robust and continuous covalent organic frameworks (COFs) nanofiltration membranes based on green solvents is promising yet highly challenging. Here, we prepared robust COFs membranes by facile microwave-assisted technique using water as the solvent involved in the reaction. Initially, we prepared TbPa-SO3H COFs suspensions containing cetyltrimethylammonium bromide (CTAB) by Schiff base reaction. Subsequently, using household microwave-assisted solvent evaporation technology, the TbPa-SO3H suspension could be deposited on the polyacrylonitrile (PAN) support membrane to form high crystalline TbPaSO3H separation layer in just a few minutes, thus transforming it from amorphous to crystalline state. Due to its high crystallinity, the obtained TbPa-SO3H membranes exhibited high rejection for common dyes (96% for Congo red, MW 696.5 Da), low salts rejection (1.21% for NaCl) and high pure water flux (109 L m- 2h- 1bar- 1). To our surprise, the obtained COFs membranes remained their original structure after numerous cycles of use, continuous filtration and high pressure (7 bar) operating conditions. Microwave-assisted preparation of COFs membranes strategy lays a solid foundation for a new generation of crystalline membrane materials and precise separation.

The impact of excessive rainfall or waterlogging on maize growth and yield have been widely studied, but the effects of planting density and N management under waterlogging remain unknown. We observed the changes in maize yield caused by excessive rainfall via a short-term experiment (2017 to present) in Changchun (125 degrees 14.231 '-125 degrees 14.914 ' E, 43 degrees 56.603 '-43 degrees 57.274 ' N), China. The experiment was conducted at four planting densities (45,000, 60,000, 75,000 and 90,000 plants/ha) and three nitrogen (N) rates (120, 180, and 240 kg/ha). The objective was to explore the effect of excessive precipitation on maize yield through changes in maize growing conditions, and the uptake, allocation, and utilization of N under different planting densities and N rates from 2019 to 2022. The precipitation during the whole growth period of maize in 2019 (542.9 mm) and 2020 (560.0 mm) was normal, while it was excessive in 2021 (829.10 mm) and 2022 (953.56 mm), especially during the vegetative stage from V12 to VT (355.60-482.10 mm). Excessive rainfall negatively affected the growth, photosynthetic characteristics (Pn: -20.00 %, SPAD: -50.50 %), absorption (-56.86 %), distribution (-15.83 %), N utilization efficiency (NUE: -29.69 %), and grain yield (-44.67 %) of maize. Our results indicate that yield loss was minimized (-22.88 %) when the planting density was appropriately reduced (from 75,000 to 60,000 plants/ha) and the N rate was increased from 180 to 240 kg/ha. The effect of different waterlogging durations on yield exhibited a significantly negative linear relation (R-2 > 0.80). This study revealed the physiological mechanism of the sustained effects of excessive rainfall on maize growth and yield. Waterlogging significantly affected the SPAD of maize (p < 0.01, R2 = 0.04), resulting in insufficient kernel N content (p < 0.001, R2 = 0.16) and decreased NUE (p < 0.001, R2 = 0.48). These factors significantly affected yield and exerted a significant negative correlation with planting density (p < 0.05). Our findings improved understanding of planting density and N management for growth and yield of maize under excessive rainfall conditions in midhigh latitude agriculture areas of the world.

Urban landscapes are high phosphorus (P) consumption areas and consequently generate substantial P-containing urban solid waste (domestic kitchen wastes, animal bones, and municipal sludge), due to large population. However, urbanization can also trap P through cultivated land loss and urban solid waste disposal. Trapped urban P is an overlooked and inaccessible P stock. Here, we studied how urbanization contributes to trapped urban P and how it affects the P cycle. We take China as a case study. Our results showed that China generated a total of 13 (+/- 0.9) Tg urban trapped P between 1992-2019. This amounts to 6 (+/- 0.5) % of the total consumed P and 9 (+/- 0.6) % of the chemical fertilizer P used in China over that period. The loss of cultivated land accounted for 15% of the trapped urban P, and half of this was concentrated in three provinces: Shandong, Henan, and Hebei. This is primarily since nearly one-third of the newly expanded urban areas are located within these provinces. The remaining 85% of trapped urban P was associated with urban solid waste disposal. Our findings call for more actions to preserve fertile cultivated land and promote P recovery from urban solid waste through sound waste classification and recycling systems to minimize P trapped in urban areas.

The primary goal of this investigation was to formulate an ecologically sustainable alternative to amide herbicides (AHs) characterized by robust herbicidal effectiveness, minimal corn phytotoxicity, and commendable pharmaceutical safety. We employed comparative molecular similarity index analysis (CoMSIA), a threedimensional quantitative structure-activity relationship (3D-QSAR) model, which systematically outlined parameters such as herbicidal effectiveness, corn phytotoxicity, and AHs biodegradability. Subsequently, after thorough evaluation, we carefully selected a group of fourteen stable AH-substitute compounds known for their safety and environmental compatibility, considering aspects like pharmacokinetics, toxicokinetics, functional properties, and environmental friendliness. This resulted in a significant increase in herbicidal effectiveness, ranging from 21.64% to 34.07%, alongside a decrease in corn phytotoxicity within the range of 12.19-20.87%. Furthermore, we achieved an improvement in biodegradability, measured within the spectrum of 4.92-9.40%. Importantly, these changes also correlated with the reduction of hepatotoxicity, mutagenicity, and cutaneous health risks. Finally, we delved into the mechanisms underlying the improved herbicidal effectiveness, reduced corn phytotoxicity, and enhanced biodegradability of AHs substitutes through molecular docking and analysis of amino acid interactions. The investigation concluded that non-covalent forces governing the interaction between AHs substitutes and receptor proteins are crucial in determinin g herbicidal effectiveness, corn phytotoxicity, and biodegradability. Specifically, Van der Waals and electrostatic forces emerged as key factors governing the binding affinities of AH molecules with receptor proteins, both before and after modification. In summary, this study introduces innovative approaches in the field of agricultural chemical weeding technology and provides a theoretical framework for the environmentally responsible management of AHs herbicides.