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Artificial intelligence empowering quality agriculture: Advances in intelligent detection and quality assurance of agricultural products AI Introduction
Abstract：To clarify the application basis and future direction of artificial intelligence in quality agriculture， this review summarizes recent advances in intelligent detection and quality assurance of agricultural products. The review focuses on machine vision， near-infrared/hyperspectral spectroscopy， Raman/surface-enhanced Raman spectroscopy， electronic nose/electronic tongue， mass spectrometry-based omics， flexible sensing， the Internet of Things， and knowledge graphs， and analyzes their applications in appearance grading， internal quality evaluation， nutritional and functional component detection， hazard screening， authenticity and origin traceability， storage and processing monitoring， and standardization-based regulation. The results show that current research has shifted from single-modality recognition to multi-source perception， model fusion， explainable analysis， and edge deployment. However， insufficient trustworthy datasets， limited cross-scenario generalization， incomplete evidence chains， and weak linkage with standards still restrict practical application. Future studies should establish a coordinated “data-model-standard-regulation” framework， strengthen trusted data spaces， model explainability， external validation， and standard mapping， and promote the transition of intelligent detection from algorithm verification to quality assurance applications.Keywords：quality agriculture;artificial intelligence;intelligent detection of agricultural products;multimodal fusion;quality assurance;intelligent regulation147|37|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2026-10-09Sustainable in-situ remediation and intelligent regulation scheme for special fish aquaculture water based on “AI+ semiconductor photocatalysis” AI Introduction
Abstract：Facing issues such as water quality fluctuations， empirical medication practices， extensive on-site control， and the simultaneous pressure to meet effluent standards in localized northern breeding of high-value specialty fish from the south， this paper aims at stable control of aquaculture water bodies and green management. Using multi-source data integration， spatiotemporal prediction， constrained decision control， and in-situ semiconductor photocatalytic purification methods， the study investigates water body state identification， risk warning， control decision-making， and pollutant reduction in specialty fish farming. A multi-source database covering water quality， meteorology， and fish growth stages was constructed to perform rolling predictions of dissolved oxygen， ammonia nitrogen， pH， temperature， and residual drug risks. Based on these predictions， control recommendations were generated considering fish physiological thresholds， equipment capacity， medication limits， and operational costs. The results show that： 1） Multi-source sensing improves the continuity and integrity of water quality state identification， compensating for the shortcomings of manual pond inspection and single-point sampling； 2） The CNN-Transformer hybrid model captures short-term water quality fluctuations and medium-to-long-term trends， providing early warnings for low dissolved oxygen， ammonia accumulation， and medication residue risks； 3） Constrained decision-making can translate predictions into recommendations for feeding， oxygenation， water exchange， medication， and operation of purification units， while the broad-spectrum nano-composite photocatalytic network offers a low-energy pathway for reducing antibiotic residues and certain organic pollutants. The study demonstrates that the collaborative application of intelligent prediction， on-site control， and photocatalytic purification can provide technical support for water management and effluent reduction in high-value specialty fish farming.Keywords：smart aquaculture;high-value special fish;aquaculture water in-situ remediation;photocatalysis;cloud-edge-terminal collaboration68|22|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2026-10-09Prediction of the rice blast in Hubei Province based on machine learning and multi-dimensional meteorological features AI Introduction
Abstract：To improve the early warning capability of rice blast in Hubei Province， and stabilize rice yield while mitigating disaster losses， this study takes the incidence rate of rice blast across Hubei Province as the research object. Based on rice’s primary growth stages （May to August）， 48 monthly meteorological indicators are selected from three dimensions： dynamic condition， radiation and thermal condition， and moisture condition. By comparing multiple machine learning approaches， the XGBoost （eXtreme Gradient Boosting） method is selected to build the rice blast prediction model， and the SHAP （SHapley Additive exPlanations） interpretable framework is employed to systematically explore the key meteorological indicators affecting the incidence of rice blast in Hubei Province. The results indicate that： 1） The XGBoost method outperforms traditional machine learning approaches in terms of accuracy， recall， and F1-score. 2） 15 key meteorological indicators affecting rice blast incidence are identified via SHAP analysis， among which the maximum wind gust in May is the critical indicator， contributing 13.19% to the model’s predictive performance. The dominant indicators also vary across different rice growth stages. During the sowing-seedling stage， maximum wind gust and surface pressure are the primary indicators； during the jointing-booting stage， average minimum temperature and surface pressure are the most influential indicators； and during the heading-flowering stage， maximum sustained wind speed and days of rain emerge as the key indicators. 3） Various meteorological indicators exhibit obvious non-linear threshold effects on rice blast incidence， where some indicators （e.g. soil moisture from June to July） exacerbate risk when exceeding thresholds， while others （e.g. surface pressure from May to July） act as negative indicators. 4） Significant interaction effects are revealed among different meteorological indicators on rice blast incidence. For example， strong wind gust in May weaken the inhibitory effect of high surface pressure on disease incidence. This study combined XGBoost with the SHAP interpretable framework for rice blast prediction， which can effectively predict the risk of rice blast in Hubei Province and provide technical support for disease prevention.Keywords：rice blast;disease prediction;machine learning;XGBoost;SHAP68|22|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2026-10-09Key economic issues and prospects of low-altitude technologies enabling smart forestry AI Introduction
Abstract：To reveal the key economic issues triggered by the integration of low-altitude technology into the forestry sector， this study employs a mixed-methods approach combining the characterization of descriptive stylized facts with qualitative mechanism analysis. The empirical foundation relies on two UAV trajectory datasets： 20 987 plant-protection flights and 589 heavy-payload sling-load trajectories in Nanping City， Fujian Province （2020-2025）， alongside 11 048 monitoring flight missions and patrol records from 1 690 forest rangers in Quanzhou City （2023-2025）. These quantitative data is supplemented by semi-structured in-depth interviews with 15 key stakeholders. We conceptualize the entry of low-altitude technology into forestry as a systemic restructuring of factor markets driven by a novel composite factor. Stylized facts are extracted and a research agenda is constructed along three dimensions： factor substitution， factor revaluation， and factor creation. These dimensions correspond respectively to the labor， land， and data factor markets； align with the operational stages of production， circulation， and governance； and reflect the classical economic propositions of the rebound effect and task reorganization， market access， and asset specificity. The main findings are as follows： 1） In the dimension of factor substitution， plant-protection operations expanded synchronously along both extensive and intensive margins. The number of accounting grid cells covered by flights increased from 528 to 4 419， and the annual average adoption days per grid cell rose from 1.61 to 2.18. The spray application volume per unit area under the autonomous flight mode （88.92 L/hm²） was higher than that under manual operation （50.85 L/hm²）. In monitoring tasks， the proportion of labor-substituting tasks decreased from 91.1% to 65.2%， while newly created tasks increased from 6.1% to 25.6%， demonstrating spatially stratified complementarity between UAVs and forest rangers. 2） In the dimension of factor revaluation， heavy-payload sling-load operations were concentrated within an approximately 600 m radius of road terminals， constituting a marginal extension of the road network rather than a fundamental substitution. The land transfer price of unmanaged bamboo forests rose from approximately 300 CNY/hm² to 600-870 CNY/hm²， with the coexistence of two institutional responses： one-off high-intensity harvesting and property-style proxy management. 3） In the dimension of factor creation， high-precision mapping services exhibited a coexistence of two fee structures with differing property-rights attributions， while the governance of monitoring data bifurcated between self-building and outsourcing models， each facing distinct structural dilemmas. Positioned as an agenda-setting study， this paper proposes a subsequent research agenda focused on three critical directions： causal identification of the rebound effect， welfare evaluation of market access， and systemic examination of governance structures， aiming to provide a robust analytical framework and empirical foundation for economic research on low-altitude technology empowering smart forestry.Keywords：low-altitude technology;smart forestry;unmanned aerial vehicle;rebound effect;market access;asset specificity;data elements35|15|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2026-10-09Impact of intelligent economy on green total factor productivity AI Introduction
Abstract：Against the backdrop of the coordinated advancement of digital transformation and green low-carbon transformation， this study aims to examine the impact of intelligent economy development on green total factor productivity and its underlying mechanisms. Based on the evaluation index system of intelligent economy development， the entropy-weighted TOPSIS method is used to measure the development level of the intelligent economy in 30 Chinese provinces from 2015 to 2024 （The data do not include those of Xizang， Hong Kong， Macao and Taiwan regions. The same below）， Green total factor productivity （GTFP） is measured by the SBM-GML model. On this basis， this study empirically examines the impact of the intelligent economy on GTFP and its underlying mechanisms. The findings are as follows. First， there is a significant U-shaped nonlinear relationship between the intelligent economy and GTFP. Second， mechanism analysis shows that carbon productivity is a transmission channel through which the intelligent economy affects GTFP， and the impact of the intelligent economy on carbon productivity is likewise U-shaped. Third， the green effect of the intelligent economy exhibits significant heterogeneity across regions， human capital， marketization level， and government intervention. The “cost effect–innovation effect” theoretical framework constructed in this paper， together with its empirical conclusions， provides new empirical evidence and policy implications for understanding the green development effect of the intelligent economy and for promoting the intelligent economy to empower the achievement of the “dual carbon” goals.Keywords：intelligent economy;green total factor productivity;carbon productivity;U-shaped relationship;SBM-GML model32|21|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2026-10-09Spatio-temporal pattern of Chinese agriculture and rural digitalization and greening collaboration development and its income-increasing effect AI Introduction
Abstract：To reveal the theoretical logic and development level of agriculture and rural digitalization and greening collaboration（hereinafter referred to as “digitalization-greening collaboration”）， this study constructs a measurement index system based on the internal logic of agriculture and rural digitalization-greening collaborative of “production-management-ecology-innovation-life”， measures the development level of agriculture and rural digitalization-greening collaboration and characterizes its spatio-temporal evolution characteristics by adopting the entropy weight method， improved coupling coordination model， Kernel density estimation and spatial Markov chain transition matrix， and examines the impact of agriculture and rural digitalization-greening collaborative development on rural residents’ income and its spatial spillover effects by constructing fixed effects model and spatial econometric model. The findings indicate that： 1） The development level of agriculture and rural digitalization-greening collaboration across the country and in each province is slowly rising and is still in the basic synergy stage. 2） The development level of agriculture and rural digitalization-greening collaboration shows a development pattern of “high in the east and low in the west”， and the speed of collaborative development shows the evolutionary characteristics of “continuous improvement in the east and rapid catching up in the central and western regions”. 3） Across the country， eastern and western regions， the absolute difference in the development level of agriculture and rural digitalization-greening collaboration is gradually narrowing， with the central region showing an expanding trend， and there is a polarization phenomenon within the region. The spatial transfer direction of the development level of agriculture and rural digitalization-greening collaboration is affected by neighboring provinces. 4） The collaborative development of agriculture and rural digitalization-greening significantly increases rural residents’ income， and there is a significant spatial spillover effect. In the future， efforts should be made to improve rural digital infrastructure， accelerate rural green transformation， promote the balanced development of agricultural and rural digitalization-greening collaboration according to local conditions， and fully release the diffusion effect of agricultural and rural digitalization-greening collaborative development.Keywords：digitalization-greening collaboration;spatio-temporal characteristics;rural residents’ income;space overflow;increase income effect35|18|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2026-10-09- Abstract：To reveal the influence， mechanism and group differences of risk perception on farmers’ green production behaviors， this study investigates the impact， mechanism and differences of risk perception on farmers’ green production behaviors based on 1 254 survey data of citrus growers in Sichuan Province and prospect theory. The Oprobit， mediation and moderation effect models were employed for the empirical test， and the endogeneity was corrected through conditional mixed estimation. The results show that： 1） Farmers’ environmental risk perception has a significant positive impact on their green production behavior， mainly through enhancing their ecological concern and health awareness. Pro-environmental technical operation ability and green production health cognition positively regulated the two pathways， respectively. 2） An interaction exists between environmental risk perception and economic benefit perception， and the two have a significant complementary effect. 3） Young farmers have a stronger understanding of the benefits of green production， technical ability and behavior level. Environmental risk perception has a significant positive impact on the older generation of farmers， but has no significant impact on the younger generation of farmers. Therefore， this study proposes suggestions such as strengthening the publicity and education of environmental risks and green production benefits， enhancing the level of farmers’ ecological concern and health awareness through multiple channels， and differentially cultivating farmers’ technical operation and cognitive abilities， to sustainably promote agricultural green development.Keywords：environmental risk perception;green production behavior;mechanism analysis;complementary effect;heterogeneity analysis28|28|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2026-10-09
- Abstract：To explore the influences of internal and external factors on farmers’ green production transition， based on survey data from 980 Chinese medicinal herb growers in Gansu Province and Ningxia Hui Autonomous Region. The comprehensive index method was used to measure the level of green production transition. The OLS model and moderation effect model were used to explore the effects of rational cognition， environmental regulation， and the interaction on the green production of Chinese herbal medicine growers. The findings revealed that： 1） Rational cognition can significantly promote the green production transition of traditional Chinese medicine growers. 2） Environmental regulations exert a positive impact on the green production transition of traditional Chinese medicine growers. 3） There is an interactive effect exists between environmental regulations and rational cognition. 4） The effects of rational cognition， environmental regulations， and their interaction differ across production rhythms and business entities. Therefore， it is necessary to deepen cognitive cultivation so as to strengthen the endogenous motivation for green production transition， optimize the environmental regulation system to enhance the external driving force of green production transition， reinforce interactive synergy to promote the two-way empowerment between rational cognition and environmental regulation， and implement differentiated regulation to improve the adaptability of policies to heterogeneous groups.Keywords：rational cognition;environmental regulations;green production transition;interaction mechanism33|15|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2026-10-09
Horizontal measurement, time series evolution and influencing factors analysis of green transformation of feed enterprises AI Introduction
Abstract：To clarify the status and patterns of the green transformation of China’s feed enterprises， and deeply explore its influencing factors， this study conducts comprehensive empirical analysis based on data from A-share listed and NEEQ （National Equities Exchange and Quotations） feed enterprises. The Critic-Topsis method， kernel density estimation， and panel regression models are employed . The results showed that： 1） The overall level of green transformation of feed enterprises fluctuated upward but remained relatively low. The development of green transformation levels among different tiers was uneven， showing obvious differentiation characteristics. 2） The relative gap in the overall green transformation level of feed enterprises continued to narrow， converging toward a medium level. 3） The proportion of high-skilled labor， integration of executives’ environmental experience， and adaptability significantly promoted the green transformation of feed enterprises， whereas the degree of equity checks and balances， public attention-oriented， and market-oriented environmental regulations inhibited the green transformation of enterprises. 4） The proportion of high-skilled labor and equity checks and balances displayed more significant impacts on large-scale enterprises， executives’ environmental experience integration as well as public attention-oriented and market-oriented regulatory tools had more significant impacts on small-scale enterprises； the proportion of high-skilled labor had more significant impacts on central enterprises， environmental regulations had more significant impacts on eastern enterprises， and adaptability had more significant impacts on western enterprises.Keywords：feed enterprise;green transformation;horizontal measurement;temporal evolution;influencing factors32|22|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2026-10-09Impact of urban-rural integration on agricultural carbon emissions: Effects and mechanisms AI Introduction
Abstract：Understanding how urban-rural integration influences agricultural carbon emissions is essential for advancing agricultural and rural modernization and achieving the “dual-carbon” objectives. Based on provincial panel data from 30 Chinese provinces from 2011 to 2023， this study investigates the effects of urban-rural integration on agricultural carbon emissions and their underlying mechanisms. （The data do not include those of Xizang， Hong Kong， Macao and Taiwan regions， the same below）. The key findings are as follows： 1） Urban-rural integration exhibits an inverted U-shaped relationship with agricultural carbon emissions. This pattern， however， is observed only in non-major grain-producing regions and is particularly evident in steep areas. 2） Rural financial agglomeration serves as a nonlinear mediator in the relationship between urban-rural integration and agricultural carbon emissions. Specifically， urban-rural integration has a significant U-shaped effect on rural financial agglomeration， which in turn indirectly affects agricultural carbon emissions， thereby substantiating the existence of a nonlinear mediating mechanism. 3） The influence of urban-rural integration on reducing agricultural carbon emissions is subject to a single threshold effect related to rural human capital. Only when the level of rural human capital exceeds the threshold of 9.304 does the emission-reducing effect become fully effective. 4） Urban-rural integration also demonstrates an inverted U-shaped spatial spillover effect on agricultural carbon emissions， meaning that integration efforts in one region can influence emission levels in neighboring areas. Given these insights， policymakers should tailor strategies according to regional characteristics and developmental stages of urban-rural integration to maximize their potential in mitigating agricultural carbon emissions.Keywords：urban-rural integration;agricultural carbon emissions;nonlinear relationships;rural financial agglomeration;level of human capital in rural areas;spatial spillover effects25|20|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2026-10-09Impact of new quality rural productive forces on the development of agriculture-tourism integration AI Introduction
Abstract：To explore the correlation between new quality rural productive forces and the development of agriculture-tourism integration， this study empirically examines the impact， threshold characteristics and spatial spillover effects of new quality rural productive forces on the development of agriculture-tourism integration based on provincial panel data from 2012 to 2024. The research conclusions are as follows： First， both the development level of new quality rural productive forces and agriculture-tourism integration show an upward trend， accompanied by an obvious regional imbalance. Second， new quality rural productive forces exert a significant driving effect on agriculture-tourism integration， and this conclusion remains valid after endogeneity treatment and multiple robustness tests. Third， the promotional effect of new quality rural productive forces on agriculture-tourism integration presents nonlinear threshold characteristics. The enabling effect rises substantially when the agricultural industrial agglomeration degree exceeds the critical value of 0.869， while the enabling effect decreases slightly when the rural population aging rate is higher than 0.209. Fourth， the boosting effect has significant regional heterogeneity， which is especially prominent in areas east of the Hu Huanyong Line， as well as in plain and hilly regions， and the Yangtze river economic belt. Fifth， while facilitating local agriculture-tourism integration， new quality rural productive forces attract production factors to concentrate in central regions through the spatial siphon effect， generating negative spatial spillovers on adjacent areas and resulting in the emergence of an “agglomeration shadow”. Therefore， we should comprehensively advance the in-depth integration of agricultural and tourism industries by implementing categorized and targeted development policies， advancing the transformation and practical application of technologies， complying with the evolutionary rules of threshold effects， introducing targeted measures tailored to local conditions， and establishing cross-regional coordination mechanisms.Keywords：new quality rural productive forces;development of agriculture-tourism integration;threshold effect;spatial Durbin model;siphon effect37|19|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2026-10-09- Abstract：To explore the effects of local identity and identity formation in cultural heritage tourism within the context of agriculture-culture-tourism integration， this study draws on grammatical analysis theory and employs self-narrative texts of cultural heritage tourism experiences in Shanxi Province collected from self-media platforms as empirical materials. A comprehensive textual analysis is conducted to examine the identity effects of cultural heritage tourism and their underlying driving factors. The findings indicate that cultural heritage tourism effectively stimulates place attachment and territorial identity among both tourists and local residents， and further facilitates the elevation of local identity to national and ethnic identity through the binding force of shared culture. Attribution analysis reveals significant differences in the contribution of three experiential factors to identity-related emotions across different subject groups. For tourists， identity emotions are primarily driven by social comparison experiences， contributing 52.7%， followed by agri-culture integration （25.9%） and aesthetic resonance （21.4%）； For local residents， agriculture-culture-tourism integration experiences serve as the primary driver， with a contribution rate of 49.8%， followed by social comparison （35.9%） and aesthetic resonance （14.3%）. Qualitative textual analysis further demonstrates that tourist identity and resident identity are not mutually isolated but exhibit a two-way interactive and mutually reinforcing emotional amplification mechanism. These findings provide empirical evidence and theoretical reference for scientifically elucidating the patterns of identity effects in cultural heritage tourism under the agriculture-culture-tourism integration framework， as well as for uncovering the generative mechanisms underlying identity-related emotions.Keywords：agriculture-culture-tourism integration;cultural heritage tourism;place identity;self-identity;Shanxi Province41|23|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2026-10-09
- Abstract：To examine the relationship between rural sports event IP and county-level economic growth， and to analyze its effects on growth momentum and tourism development， this study uses county-level panel data from seven counties and county-level cities in Qiandongnan Prefecture from 2022 to 2024. A regional economic growth momentum index and a simplified event IP index are constructed， and panel regression models are employed for empirical analysis. The robustness of the results is further tested using different fixed-effects specifications and alternative dependent variables. The results show that： 1） Counties with rural sports event IP generally perform better in terms of growth momentum and tourism expansion. The simplified event IP index has a significantly positive effect in the pooled model and the year fixed-effects model. However， after simultaneously controlling county-specific fixed differences and common year shocks， the independent explanatory power of this variable for overall growth momentum weakens， suggesting that the economic effects of event IP are closely related to local culture-tourism foundations， industrial structure， and common year effects. 2） Rural sports event IP shows a clearer positive relationship with the growth rate of total tourism revenue， whereas its effects on tourism development intensity and the growth rate of rural residents’ income are more likely to be realized through indirect transmission and conditional mechanisms. Overall， based on short-panel evidence， this study reveals the possible pathways and conditions through which rural sports events may transform from “activity resources” into “development assets”， providing an empirical basis for future studies to expand county-level samples， improve communication-related variables， and conduct spatial identification.Keywords：rural sports event IP;spatial correlation;county-level economic development;integration of sports， culture and tourism;Qiandongnan region32|24|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2026-10-09
Effects of urease inhibitor combined with optimized nitrogen application on yield and quality of strong‑gluten winter wheat AI Introduction
Abstract：To investigate the effects of urease inhibitor-coordinated nitrogen application on nitrogen use efficiency， yield， grain nutritional quality， and dough and bread processing quality of strong-gluten winter wheat， a field experiment was conducted in Quzhou County， Handan City， Hebei Province from 2023 to 2024. A total of six treatments were established： Conventional nitrogen application of 300 kg/hm² （CONV，nitrogen rate calculated as pure N，the same below）， optimized nitrogen application of 200 kg/hm² （OPT）， as well as reduced nitrogen application of 155 kg/hm² （OPT-） and increased nitrogen application of 245 kg/hm² （OPT+）， optimized nitrogen application combined with urease inhibitor of 200 kg/hm² （OUI）， and no nitrogen application （CK）. The nitrogen uptake and utilization efficiency， dry matter accumulation and remobilization， yield and yield components of wheat， as well as grain protein and wet gluten contents， farinograph parameters， extensibility properties， and bread quality scores were determined. The regulatory relationships among nitrogen application measures， nitrogen utilization， and processing quality were systematically analyzed. The results showed that： 1） Compared with CONV， both OPT and OUI treatments significantly increased nitrogen partial factor productivity， nitrogen agronomic efficiency， post-anthesis dry matter accumulation， and grain yield. Compared with OPT， OUI treatment significantly increased nitrogen partial factor productivity and nitrogen agronomic efficiency by 1.89% and 4.67% （P<0.05）， respectively. OUI treatment also significantly increased spike number by 4.54% （P<0.05）， and post-anthesis dry matter accumulation. Grain yields of OPT and OPT+ treatments were significantly higher than that of OPT- treatment by 10.96% and 11.13%， respectively. 2） Grain protein and wet gluten contents were highest in the OUI treatment， significantly higher than those in all other treatments （OPT-， OPT+， CK， CONV）. Compared with OPT， OUI treatment significantly increased protein content， dough stability， and extensibility by 9.62%， 18.30%， and 6.85% （P<0.05）， respectively. The wet gluten content， protein content， and water absorption of OPT treatment were significantly higher than those of CONV and OPT- treatments. 3） The bread volume， texture， appearance， and structure of winter wheat under the no nitrogen application treatment （CK） were significantly lower than those under all nitrogen application treatments. Among all treatments， OPT treatment exhibited the best bread quality， with the highest bread volume （843.5 mL）， crumb texture （8.3 points）， crumb color （3.3 points）， and overall score （81.1 points）. The overall score of OPT treatment was significantly higher than that of OPT- and OUI treatments by 7.28% and 8.42% （P<0.05）， respectively. In conclusion， for strong-gluten winter wheat production in the North China Plain， controlling nitrogen application rate at 200 to 245 kg/hm² can simultaneously improve wheat yield and nitrogen use efficiency while enhancing grain nutritional quality and processing quality. Among these treatments，the optimized nitrogen application combined with urease inhibitor （OUI） significantly improved grain protein concentration and key dough rheological properties， and is therefore recommended as a fertilization strategy for achieving high yield and quality in this region.Keywords：strong-gluten winter wheat;nitrogen application rate;yield;nitrogen uptake and utilization;dry matter accumulation;quality41|21|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2026-10-09- Abstract：To optimize the utilization of regional climatic resources for rice quality improvement， based on daily meteorological data from 62 stations in the main single cropping mid-season production areas of Anhui Province from 1991 to 2024， combined with a rice grain quality evaluation model based on meteorological factors， this study analyzed the trends in average temperature， solar radiation， diurnal temperature range， and the comprehensive meteorological index during the key quality formation period for single-season indica rice （short for mid-season indica） and single-season japonica rice （short for mid-season japonica） in Anhui Province. Climate trend analysis and significance tests were applied to examine these variables， and the optimal full heading dates for high-quality production under climate change were also determined for both rice types. The results showed that over the past 34 years， the average temperature during the key period for mid-indica rice increased by 0.37 ℃ per decade in the region along the Huai River （short for the Yanhuai region）， and by 0.49 ℃ per decade in both the region between the Yangtze and Huai River （short for the Jianghuai region） as well as the region along the Yangtze River and the region south of Yangtze River （short for the Yanjiang Jiangnan region）. For mid-season japonica rice， the corresponding increases were 0.24， 0.36 and 0.50 ℃ per decade， respectively. Warming trends in the Jianghuai and Yanjiang Jiangnan regions were statistically significant for both varieties （P<0.01）. Solar radiation during the key period for mid-season indica rice exhibited a decreasing trend （-0.01 MJ/（m2·10 a）） in the Yanhuai region but increasing trends in the Jianghuai region （0.16 MJ/（m2·10 a）） and the Yanjiang Jiangnan region （0.19 MJ/（m2·10 a））. For mid-season japonica rice， radiation decreased in the Yanhuai region （-0.21 MJ/（m2·10 a）） and the Jianghuai region （-0.30 MJ/（m2·10 a））， while a slight increase occurred in the Yanjiang Jiangnan region （0.07 MJ/（m2·10 a））. The diurnal temperature range for mid-season indica rice increased across all regions （0.04， 0.16 and 0.18 ℃ per decade for Yanhuai， Jianghuai， and Yanjiang Jiangnan region， respectively）， whereas it decreased for mid-season japonica rice in all regions （-0.15， －0.13 and -0.05 ℃ per decade for the corresponding region ）. The comprehensive meteorological index for both mid-season indica and mid-season japonica rice showed a declining trend， suggesting that climate change is increasingly unfavorable to rice quality formation. For mid-season indica rice， the suitable full heading dates for Anhui Province under climate change are during August 18-22 in most parts of the Yanhuai region， northern and central Jianghuai region， and southern Jiangnan region， and August 23-27 in the southern Jianghuai region and most parts of the eastern Yanjiang Jiangnan region. For mid-season japonica rice， the optimal full heading dates are during August 23-27 in the Huai River region and northern-central Jianghuai region； August 28-September 1 in the southern Jianghuai region and Jiangnan region； and September 2-6 in most parts of the Yanjiang region. Implementing these adjusted heading dates significantly enhanced the proportion of high-quality rice production compared to conventional practices. This study provides a scientific basis for the strategic use of regional climate resources to improve rice quality in Anhui Province.Keywords：single cropping mid-season rice;japonica rice;indica rice;rice quality;climate resource;full heading date;climate change31|53|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2026-10-09
Evaluation of yield performance and stability of foxtail millet varieties based on combined AMMI model and BLUP method AI Introduction
Abstract：To accurately evaluate the yield performance， stability， and adaptability of foxtail millet varieties under different ecological conditions and identify superior varieties suitable for regional deployment， this study analyzed the yield data from multi-location trials of 17 foxtail millet varieties conducted at 20 test sites across 9 provinces in 2023. A randomized block design was designed. The additive main effects and multiplicative interaction model （AMMI） was used to dissect genotype × environment interaction， and best linear unbiased prediction （BLUP）， weighted average of absolute scores from the BLUP of genotype-by-environment interaction effects （WAASB）， and weighted average of absolute scores and yield performance from the BLUP model were integrated for comprehensive evaluation and regional recommendation of the tested varieties. The results showed that the effects of genotypic， environmental， and genotype × environment interaction on foxtail millet yield were all highly significant （P<0.001）， accounting for 7.6%， 31.0%， and 24.4% of the total variation， respectively， with the environmental effect being the major source of yield variation. The genotype × environment interaction was divided into eleven interaction principal component axes， and the first two interaction principal component axes explained 42.0% of the genotype × environment interaction （GEI） variation， and the first four axes explained 66.9%， indicating substantial environmental differences among test sites and marked differentiation in varietal responses to environments. The mean yield across the 20 test sites was 5 690.6 kg/hm2， and the site mean yields ranged from 4 603.7 to 7 129.3 kg/hm2. The BLUP model exhibited the lowest prediction error and the highest predictive accuracy. Based on across-environment BLUP predicted values， ‘K281-2H’， ‘K175-1H’， and ‘JZG10’ exhibited high yield potential. The WAASBY evaluation further indicated that ‘K175-1H’， ‘JZG10’， and ‘K281-2H’ combined high yield performance with good stability and could therefore be considered priority high-yielding and stable varieties. Analysis of genotype × site interaction effects showed that superior varieties differed among test sites. ‘YG56’ and ‘K281-2H’ were suitable for cultivation at Gongzhuling in Jilin Province and showed significant positive interaction effects compared with other varieties， whereas ‘K175-1H’ and ‘JG4’ performed significantly better than other varieties at Xuanhua in Hebei Province. In conclusion， the yield performance of foxtail millet varieties was jointly affected by genotype， environment， and genotype × environment interaction. The integrated evaluation combining AMMI and BLUP can improve the accuracy of assessing yield performance， stability， and regional adaptability.Keywords：genotype × environment interaction;AMMI model;BLUP method;stability index;simultaneous selection index37|26|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2026-10-09Effects of fulvic acid on fatty acid composition and membrane function of oat leaf thylakoids under drought stress AI Introduction
Abstract：To investigate the effects of fulvic acid （FA） on fatty acid composition and thylakoid membranes function in oat leaves under drought stress， two cultivars， ‘Yanke 2’ （drought-resistant） and ‘Bayou 9’ （drought-sensitive）， were used as experimental materials. A pot experiment was conducted using randomized block design. Three water gradients were set up： Normal water supply （75% of field capacity， D0）， mild drought stress （60% of field capacity， D1）， and severe drought stress （45% of field capacity， D2）. Under each water gradient， two treatments were applied at the jointing， heading， and grain-filling stages： Foliar spraying of 600 mg/L （FA） and spraying of an equal amount of water （CK）. A total of 12 treatments were set up. The following parameters of flag leaves were measured： Thylakoid membrane fatty acid composition， thylakoid lamellar structure， Hill reaction activity， H⁺-ATPase activity， photosynthetic pigment content， net photosynthetic rate （Pn）， grain yield and its components. Additionally， correlation analysis was also performed. The results showed that： 1） Spraying FA significantly increased the proportion of unsaturated fatty acids and unsaturated fatty acid index （IUFA） in oat thylakoid membrane under drought stress， stabilized the structure of the membrane， and enhanced the Hill reaction activity and H+-ATPase activity. Compared with CK， the proportions of unsaturated fatty acids （linolenic acid and linoleic acid） and IUFA in thylakoid membranes of both cultivars were significantly increased under FA treatment. The thylakoid lamellar structure became more compact， while Hill reaction activity and H⁺-ATPase activity were also significantly increased. Under D1， for ‘Yanke 2’ and ‘Bayou 9’， linolenic acid increased by 7.89% and 6.08%， linoleic acid increased by 17.98% and 22.06%， IUFA increased by 17.15% and 20.64%， Hill reaction activity increased by 10.02% and 14.05%， and H⁺-ATPase activity increased by 12.92% and 17.01%， respectively. Under D2， the corresponding increases were 14.80% and 15.82%， 19.96% and 27.77%， 19.59% and 26.95%， 13.27% and 18.13%， and 14.48% and 24.00%. 2） FA significantly increased photosynthetic pigment content， net photosynthetic rate （Pn）， spikelet number per spike， 1 000-grain weight and grain yield of both cultivars under drought stress. 3） Correlation analysis showed that IUFA was significantly positively correlated with Hill reaction activity， H⁺-ATPase activity， photosynthetic pigment content， Pn and grain yield. In conclusion， fulvic acid alleviated the inhibition of photosynthesis and increased grain yield in oat under drought stress by increasing the proportion of unsaturated fatty acids in thylakoid membranes， maintaining lamellar structural integrity， and increasing Hill reaction activity and H⁺-ATPase activity. Its mitigation effect on severe drought was better than that under mild drought， and its effect on drought-sensitive variety ‘Bayou 9’ was better than that on drought-resistant variety ‘Yanke 2’.Keywords：oat;fulvic acid;drought stress;fatty acid composition;hill reaction activity;H⁺-ATPase activity37|24|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2026-10-09Effects of intercropping on rhizosphere microorganisms and root metabolites of soybean and maize AI Introduction
Abstract：To reveal the complex interaction relationship between root metabolites and rhizosphere microorganisms of soybean and maize under intercropping systems， field experiments were established with planting patterns including soybean monoculture， maize monoculture， and soybean and maize intercropping. During grain-filling stage of soybean （corresponding to the tasseling stage of maize）， high-throughput detection technologies including 16S and ITS amplicon and non-targeted metabolomics were employed to analyze the effects of intercropping on the rhizosphere microbial diversity and relative abundance of soybean and maize under different planting patterns. The main differential metabolites in the root of soybean and maize under planting patterns including intercropping and monoculture were screened， and the interaction relationship between rhizosphere microorganisms and root metabolites was analyzed through correlation analysis. The results showed： 1） soybean and maize intercropping significantly increased bacteria α-diversity index including Shannon， Simpson， Chao1 and ACE in soybean rhizosphere （P<0.01）， and reduced relative abundance of Bradyrhizobium and Fusarium in soybean rhizosphere（P<0.001）. 2）A total of 534 differentially expressed metabolites （DEMs） were identified in soybean roots （194 up-regulated and 340 down-regulated） and 604 DEMs in maize roots （284 up-regulated and 320 down-regulated） were identified between intercropping and monocultures. DEMs in soybean root were mainly enriched in pathways such as amino acid biosynthesis， ABC transporters， and D-amino acid metabolism. DEMs in maize root are mainly enriched in pathways such as secondary metabolite biosynthesis， tryptophan metabolism and flavonoid biosynthesis. 3）The relative abundance of Bradyrhizobium was significantly positively correlated （P<0.05） with relative abundance of all DEMs in the soyMets Cluster Ⅰ group except for 1-｛［3-（3，4-dihydroxyphenyl）acryloyl］oxy｝-3，5-dihydroxycyclohexane-1-carboxylic acid， and showed an extremely significant negative correlation （P<0.01） with relative abundance of all DEMs in the soyMets Cluster Ⅱ group except for 1-palmitoyl-2-（archidonoyl）-sn-glycero-3-phosphoethanolamine in soybean root. The relative abundance of Purpureocillium， Saitozyma and Badarisama showed a significant negative correlations （P<0.05） with the relative abundance of DEMs in the mazMets Cluster Ⅰ group such as 2，3，4-trihydroxy-4-ethoxybenzophenone， showed a significant positive correlation （P<0.05） with relative abundance of DEMs in the mazMets Cluster Ⅱ group such as Thr-Ala-Phe-Lys， in maize root. In conclusion， soybean and maize intercropping significantly increased bacteria diversity in soybean rhizosphere， significantly decreased the relative abundance of Bradyrhizobium and Fusarium in soybean rhizosphere. The relative abundance of Bradyrhizobium in the soybean rhizosphere was significantly related to DEMs in soybean root， while Purpureocillium， Saitozyma and Badarisama in the maize rhizosphere were significantly related to DEMs in maize roots.Keywords：intercropping;soybean;maize;bacteria;fungus;root metabolites33|21|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2026-10-09- Abstract：To optimize irrigation and fertilizer management in the Ordos irrigation area on the south bank of the Yellow River， maize and sunflower were selected as the research subjects. A multi-objective optimization framework integrating the AquaCrop model with the Non-dominated Sorting Genetic Algorithm Ⅱ （NSGA-Ⅱ） was adopted， with the maximization of crop yield， irrigation water use efficiency， and nitrogen partial factor productivity as collaborative objectives， to investigate the optimization of water and fertilizer regimes under mulched drip irrigation conditions. The results indicated that the AquaCrop model effectively simulated crop growth and yield responses in the study area， demonstrating strong applicability. Based on the meteorological conditions of specific hydrological years， the multi-objective optimization identified the optimal water and nitrogen application rates for maize in a typical normal year as 1 280-1 520 m3/hm2 and 212.8-243.6 kg/hm2， respectively. For sunflower in a typical dry year， the optimal ranges were 900-1 100 m3/hm2 for water and 232.5-273.75 kg/hm2 for nitrogen. Compared with traditional optimization schemes focusing solely on maximizing yield， the proposed framework resulted in yield losses of only 9% for maize and 6% for sunflower， while significantly enhancing water and fertilizer use efficiency by 21% and 14%， respectively. In conclusion， the simulation-optimization coupling framework developed in this study provides a robust tool for mitigating agricultural non-point source pollution and promoting ecological protection and high-quality agricultural development in the Yellow River Basin.Keywords：AquaCrop model;NSGA-Ⅱ optimization algorithm;water and nitrogen optimization;maize;sunflower33|22|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2026-10-09
- Abstract：To address the difficult detection of latent infection and the challenge of early control in Chinese chive gray mold， non-targeted metabolomics combined with physiological and biochemical indicators were employed to systematically analyze the metabolic reprogramming process of Chinese chives at different stages following Botrytis cinerea inoculation. The results indicated that phenylpropanoid biosynthesis， flavonoid biosynthesis， and sphingolipid metabolism pathways were rapidly activated during the latent phase. Phenylalanine ammonia-lyase （PAL） activity was approximately twice that of the control， and peroxidase （POD） activity was approximately 4.3 times that of the control. Phenolic and sphingolipid metabolism remained active in the mid-to-late stages to maintain membrane integrity and signaling homeostasis. Based on the linear support vector machine algorithm， this study identified and validated a biomarker panel consisting of feruloyl-O-methyldopamine， 2，4-dihydroxybenzoic acid， and salicylic acid， which demonstrated exceptional discriminatory performance （AUC=0.956）. The research results provide metabolic targets for the early diagnosis and precise control of gray mold.Keywords：Allium tuberosum;gray mold;untargeted metabolomics;phenylpropanoid metabolism;sphingolipid metabolism;early diagnosis36|17|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2026-10-09
Quality of red pitaya juice fermented by Lactobacillus gasseri AI Introduction
Abstract：To investigate the effects of Lactobacillus gasseri L-SS fermentation on the quality of red-fleshed dragon fruit juice and explore its potential application in plant-based functional beverage development， a systematic study was conducted on the quality changes of red-fleshed dragon fruit juice before and after fermentation using rheological measurements， physicochemical analysis， electronic tongue and nose detection， and gas chromatography-mass spectrometry （GC-MS）. The results indicated： 1） Rheological measurements revealed both pre- and post-fermented juices exhibited pseudoplastic fluid characteristics， with fermentation significantly reducing viscosity （P<0.05）； Physicochemical analysis showed fermentation decreased juice pH by 0.79 and increased titratable acidity by 16.99 g/L. High-performance liquid chromatography （HPLC） further indicated that fermentation significantly promoted the accumulation of certain organic acids and free amino acids. Specifically， the mass concentrations of lactic acid and acetic acid increased by 1 419.18 and 162.32 mg/L， respectively， while glycine content rose by 53.97 μg/mL （P<0.05）. 2） The analysis of electronic tongue and nose revealed that fermentation enhanced sourness， sweetness， and umami while reducing astringency， resulting in a more harmonious overall taste profile. 3） A total of 26 compounds were detected in the analysis of flavor compounds. Fermentation significantly increased aromatic compounds phenethyl alcohol and benzaldehyde （11.8 times and 5.7 times， respectively， P<0.05）， while reducing irritant components such as furfural and hexanal， making the aroma more harmonious and tich. In summary， Lactobacillus gasseri L-SS fermentation can significantly enhance the nutritional value and flavor quality of red-fleshed dragon fruit juice， providing theoretical foundations and technical references for developing plant-based functional beverages.Keywords：Hylocereus polyrhizus;Lactobacillus gasseri;probiotic fermentation;flavor substances;sensory evaluation26|15|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2026-10-09Screening of key circRNAs and analysis of the ceRNA network in the interaction between bovine skeletal muscle cells and intramuscular adipocytes AI Introduction
Abstract：To investigate the effect of bovine skeletal muscle cells on the circular RNA （circRNA） expression profile in intramuscular adipocytes under co-culture conditions， and to elucidate the potential regulatory mechanisms of circRNA in intramuscular fat deposition， this study established a Transwell co-culture model of bovine skeletal muscle cells and intramuscular adipocytes. Meanwhile， circRNA sequencing was performed on intramuscular adipocytes cultured separately as the control group and those co-cultured with skeletal muscle cells as the experimental group. Differential expression analysis was conducted using edgeR software， with a threshold of |log₂FC|≥1 andP<0.05 to identify differentially expressed circRNAs. GO and KEGG enrichment analyses were performed for the host genes of these circRNAs. A circRNA-miRNA-mRNA ceRNA regulatory network was constructed using the OmicShare online platform to further screen key regulatory factors. The results showed that： 1） A total of 10 081 circRNAs were identified， including 3 881 unique to the control group， 3 465 unique to the co-culture group， and 2 735 shared by both groups. 2） A total of 51 differentially expressed circRNAs were identified， including 16 upregulated and 35 downregulated in the co-culture group compared to the control group. 3） The differentially expressed circRNAs derived genes were mainly enriched in GO terms such as histone methyltransferase activity and signaling pathways such as ECM-receptor interaction. 4） A total of 42 potential ceRNA regulatory pairs were identified， with novel_circ_002953 occupying a central position in the network. 5） Novel_circ_002953 may affect the expression of adipogenic differentiation-related genes such as PSAP and DHCR24 by sponging novel-m0002-3p. Novel_circ_002953 and novel_circ_006185 may regulate the expression of lipid metabolism key genes， including WNT5A and ZBTB16， by sponging novel-m0108-3p. In summary， the co-culture environment can alter the circRNA expression profile of bovine intramuscular adipocytes. This study provides novel candidate circRNA molecules for dissecting the skeletal muscle-adipose interaction regulatory network.Keywords：bovine;intramuscular adipocytes;skeletal muscle cells;co-culture;circRNA;ceRNA network24|24|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2026-10-09- Abstract：To investigate the antimicrobial resistance profiles and prevalence of resistance genes among enterococci along the chicken production supply chain （including hatcheries， farms， slaughterhouses， and supermarkets） in Shihezi City， Xinjiang， a total of 316 samples were collected to isolate and identify Enterococcus faecalis and Enterococcus faecium. The minimum inhibitory concentrations （MICs） of 9 antimicrobial agents were determined by agar dilution method， and 11 antimicrobial resistance genes were detected by PCR. The results were as follows：1）A total of 258 enterococcal strains were isolated， with isolation rates of 66.8% （211/316） for E. faecalis and 14.9% （47/316） for E. faecium. Among them， the isolation rate of E. faecalis exceeded 80.0% in both hatcheries （91.8%） and supermarkets （80.7%）， while E. faecium showed the highest isolation rate （20.9%） in slaughterhouses. 2）The severity of antimicrobial resistance in Enterococcus isolates from different production stages was in the order of hatchery > farm > slaughterhouse > supermarket. Enterococcus isolates from the hatchery exhibited 100.0% resistance to florfenicol， erythromycin， tetracycline， and linezolid. In addition， both E. faecalis and E. faecium showed high resistance rates to tetracycline， florfenicol， and erythromycin， with resistance rates of 99.1%， 95.3%， and 93.4% for E. faecalis， and 95.7%， 100.0%， and 76.6% for E. faecium， respectively. All isolates were fully susceptible to tigecycline and vancomycin. 3）Multidrug resistance （MDR） analysis showed that E. faecalis isolates along the chicken supply chain were predominantly resistant to 4–6 antimicrobials （91.0%）， with more than 60.0% of strains resistant to 6 agents in hatcheries and slaughterhouses. For E. faecium， resistance to 5 antimicrobials （62.5%） was dominant in farm isolates， whereas resistance to 3 antimicrobials （57.1%） was most common in isolates from supermarkets. 4）Detection of resistance genes revealed that the tetracycline resistance gene tetM was detected in more than 85.0% of both E. faecalis （94.8%） and E. faecium （85.1%）， and a positive correlation was observed between phenotypic resistance to tetracycline and the presence of tetM. The detection rate of the oxazolidinone resistance gene optrA in E. faecalis （56.0%） was slightly lower than that in E. faecium （62.0%）， while the poxtA gene was more prevalent in E. faecium （19.2%）. The cfr and vanA genes were not detected in any isolate. In conclusion， E. faecalis and E. faecium isolated from the chicken production supply chain in Shihezi City display severe antimicrobial resistance and carry multiple resistance genes. Standardized antimicrobial usage at the farm level and enhanced biosecurity control during slaughter and processing are recommended to reduce the risk of transmission of drug-resistant bacteria and resistance genes along the food chain.Keywords：supply chain;Enterococcus;antimicrobial resistance;resistance gene;multidrug resistance40|14|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2026-10-09
Risk perception, risk attitude and farmers’ risk management behavior: A case study of beef cattle vaccination AI Introduction
Abstract：To reveal the mechanisms through which risk perception and risk attitude affect beef cattle farmers’ risk management behaviors， and to enrich micro-level evidence on preventive risk management behavior， this study examines the vaccination behavior of 256 beef cattle farmers in Heilongjiang， Jilin， and Shaanxi provinces by using factor analysis， an ordered Probit model， and hierarchical regression. The results show that： 1） Both risk perception and risk attitude significantly promote farmers’ risk management behavior. Farmers with higher levels of risk perception and stronger risk-averse attitudes are more likely to adopt preventive control measures such as vaccination. 2） Risk attitude plays a significant positive moderating role between risk perception and risk management behavior； that is， a risk-averse attitude strengthens the positive effect of risk perception on risk management behavior. 3） The risk cognition mechanism exhibits heterogeneity. Livelihood structure significantly moderates the transmission strength from risk perception to vaccination， while the direct effect of risk attitude remains generally stable across different livelihood structures. Meanwhile， participation in training changes， to some extent， the marginal effects of risk perception and risk attitude on vaccination behavior. In conclusion， this study recommends adopting an “information-incentive-capacity” policy package to increase farmers’ ex ante investment in epidemic prevention， improve the provision of actionable risk information， provide supporting incentives and convenient immunization services， optimize training through procedural and on-site implementation， and implement differentiated resource allocation according to the functional positioning of different regions within the live cattle circulation chain， thereby enhancing policy operability and national applicability.Keywords：risk perception;risk attitude;risk management;moderating effect;beef cattle farmers22|23|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2026-10-09New quality productive forces in animal husbandry: Level measurement, dynamic evolution and driving factors AI Introduction
Abstract：To investigate the development status of new quality productive forces in China’s animal husbandry sector and reveal its dynamic evolution characteristics and driving factors， the entropy-weighted TOPSIS method was employed to measure the development levels of new quality productive forces in animal husbandry across 30 provinces nationwide from 2013 to 2022（The data do not include those of Xizang， Hong Kong， Macao and Taiwan regions. The same below）. The regional disparities， dynamic evolution， and driving factors were analyzed by using the Dagum Gini coefficient， Markov chains， an obstacle factor diagnostic model， and geographic detectors. The results indicate that： 1） From 2013 to 2022， China’s new quality productive forces in animal husbandry showed an overall steady upward trend， through the overall development level remained at a relatively low. Regionally， a decreasing pattern emerged from east to west， followed by central， western， and northeastern regions. 2） Significant regional disparities persist in the development level of new quality productive forces in animal husbandry with a widening trend driven primarily by intra-regional differences. 3） The dynamic evolution of new quality productive forces in animal husbandry exhibits stability， slowness， and an upward shift tendency. 4） The development and innovation of digital technologies constitute a major obstacle to the advancement of new quality productive forces in animal husbandry. Marketization levels， economic development levels， industrial structures， government investment intensity， household meat-egg-dairy consumption levels， and urbanization levels all serve as major driving factors. The dominant factors influencing development are shifting from relatively singular to increasingly diverse. Accordingly， future strategies should strengthen regional coordination， implement targeted measures to narrow regional disparities， concentrate on overcoming weak links hindering digital development in modern animal husbandry， and cultivate diverse driving entities.Keywords：new quality productive forces in animal husbandry;level measurement;spatiotemporal evolution patterns;constraint factors;driving mechanisms22|17|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2026-10-09- Abstract：To systematically understand the generation of agricultural waste and the trends in its resource utilization， a systematic literature search was conducted based on Web of Science （WOS） core collection and the China National Knowledge Infrastructure （CNKI） database. Both Chinese and English keywords were employed， including straw， vegetable， fruit， waste， livestock， poultry， manure， and resource utilization. Based on the obtained relevant research papers， the generation of agricultural waste and its resource utilization technologies were systematically reviewed and summarized from the perspectives of waste yield， characteristics， spatial-temporal distribution， and resource utilization technologies. The results show that： 1） Promoting the efficient resource utilization of agricultural waste became an important task for agricultural development in China during the 15th Five-Year Plan period. 2） The agricultural waste in China is primarily composed of livestock and poultry manure， followed by crop straw and vegetable waste， and the spatial distribution of the three categories differs significantly. 3） The resource utilization of agricultural waste is predominantly fertilizer-based， supplemented by feed， energy， substrate， and material utilization， which can realize the efficient resource recycling of agricultural waste. In summary， while significant progress has been made in the resource utilization of agricultural waste， challenges persist， including insufficient marketization and inadequate institutional support systems. Future efforts should focus on developing high-value utilization technologies and optimizing policy support measures to promote the green， low-carbon， and sustainable development of agricultural production.Keywords：agricultural waste;crop straw;vegetable waste;livestock and poultry manure;circular agriculture;resource utilization32|20|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2026-10-09
Conservation of natural resources, off-farm employment and rural household well-being AI Introduction
Abstract：This study develops a comprehensive evaluation index system for rural residents’ well-being， using survey data of 494 households from national nature reserves in Jiangxi Province. The analysis employs ordinary least squares （OLS） regression and mediation effect models to uncover the underlying mechanisms. The findings are as follows： 1） Natural resource conservation contributes an additional 3.20% to the well-being of rural residents within nature reserves， with this increase primarily attributed to significant contributions from the dimensions of “freedom of choice” and “ecological environmental quality”. 2） Mechanism analysis reveals that natural resource protection facilitates off-farm employment participation among residents living near protected areas， which in turn enhances their well-being. 3） Heterogeneity analysis shows that the positive effect of natural resource protection on rural residents’ well-being is more pronounced among those at the 25th percentile （Q25） of well-being， those in southern Jiangxi Province， and those with relatively high income levels. Based on these findings， we propose promoting the sound co-construction and collaborative governance of natural resource protection areas， implementing targeted and categorized assistance programs， vigorously developing under-forest industries， and expanding off-farm employment opportunities.Keywords：resource protection;nature reserves;residents’ well-being;off-farm employment;mediation effect25|13|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2026-10-09- Abstract：Landscape classification and suitability assessment are key methods for supporting agricultural production space reconstruction， and their effective integration is a critical prerequisite for refined spatial diagnosis. This study couples agricultural production landscape classification with natural suitability assessment， constructing a “landscape classification-suitability assessment-reconstruction strategy” and conducting diagnostic analysis and scheme formulation based on landscape units. Taking Miaoxia Village in Guiyang County， Hunan Province as a case study， a three-level classification system was developed integrating geomorphological， land use， and soil indicators. It was divided into 5 landscape classes， 8 landscape subclasses， and 43 landscape types， revealing a concentric “core-transition-edge” spatial pattern shaped by terrain-soil coupling. By using a composite evaluation model， limiting factor model， and suitability matching method with 13 indicators， this study identified 9 constraint factor types along with their spatial correspondence to landscape units， and units were classified into four suitability grades. Differentiated reconstruction strategies were proposed based on constraint factor diagnosis. This study achieves a methodological linkage from pattern identification to functional diagnosis to reconstruction strategy， providing support for agricultural production space reconstruction in village planning， with reference value for similar villages in hilly areas of southern China.Keywords：agricultural landscape restructuring;agricultural production landscape;landscape classification;agricultural landscape evaluation;southern Hunan region26|18|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2026-10-09
Individual rationality, policy context and farmers’ behavior of recultivating abandoned farmland AI Introduction
Abstract：This study aims to explore the effects of individual rationality and policy context on farmers’ behavior of recultivating abandoned farmland. Based on micro-level survey data collected in 2023 from farm households in five provinces of China， and employing an extended “attitude-behavior-context” analytical framework together with a latent variable interaction effect model， the study analyzes and tests the decision-making mechanism and influencing factors underlying farmers’ recultivation behavior of abandoned farmland from the perspective of individual rationality. The results indicate that： 1） Farmers prioritize economic rationality in their decision-making regarding the recultivation of abandoned farmland， followed by social rationality， and lastly survival rationality. Economic rationality has a significant negative impact on farmers’ intention to recultivate abandoned farmland， while survival rationality and social rationality have a significant positive impact. 2） The economic policy contexts mitigate the negative impact of economic rationality on farmers’ intention to recultivate abandoned farmland， while the regulatory policy contexts weaken the promotion effect of survival rationality. Compared with the regulatory policy contexts， farmers prefer the economic policy contexts. 3） The recultivation of abandoned farmland brings positive effect perception to farmers， but this effect perception is not enough to significantly improve their intention to recultivate abandoned farmland. In conclusion， to effectively reduce farmland abandonment， the government should respond differently to the various levels of rational needs involved in farmers’ decisions to recultivate abandoned farmland， improve a policy system for recultivation that gives priority to economic incentives while being complemented by regulatory measures， and enhance farmers’ perceived benefits of recultivating abandoned farmland.Keywords：recultivating abandoned farmland;behavioral decision-making;individual rationality;policy context;structural equation model25|12|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2026-10-09- Abstract：In order to further optimize the entrepreneurial performance of young people returning to their hometowns and promote their sustainable development， based on 490 rural entrepreneurship financing questionnaire survey data from 12 provinces （autonomous regions） across the country， this study investigates the impact of digital competence and social capital on the entrepreneurial performance of returning youth. The results show that：1）Both digital competence and social capital will have a positive impact on the business performance of youth groups returning home to start businesses， with alleviating financing constraints and improving the availability of formal financial services as a key mediating role in this relationship. 2） According to the operational structure and development stage of different entrepreneurial organizations， the impact of digital competence and social capital on performance is heterogeneous： both are effective in pure production and shrinking or maintaining organizations， while only social capital plays a significant role in non-production organizations， while neither comprehensive nor expanding organizations shows a significant role in promoting performance. 3） There is a significant complementary effect between digital competence and social capital， that is， the performance effect of one is conditional on the high level of the other， and the two complement each other and mutually promote. Based on these findings， it is recommended to implement precise support policies that emphasize both digital empowerment and social connectivity， broaden composite financing channels based on digital credit systems and community trust mechanisms， and implement differentiated growth support systems for entrepreneurial organizations based on different strategies.Keywords：returning home for entrepreneurship;digital competence;social capital;business performance31|16|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2026-10-09
