[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-4109":3,"related-4109":107},{"id":4,"title":5,"url":6,"summary":7,"summary_zh":8,"content":9,"source_name":10,"source_url":6,"published_at":11,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":16,"sources":23,"tags":25,"primary_topic":31,"secondary_topics":37,"classification":38,"search_phrases":85,"slug":88,"view_count":89,"doi":90,"paper":91,"created_at":106},4109,"Hormonal crosstalk at the plant–microbiome interface governing plant immunity under combined biotic and abiotic stresses","https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs11084-026-09767-z","Plant immunity is orchestrated through an intricate network of signaling pathways that enables plants to perceive, respond to, and adapt to a wide range of biotic and abiotic challenges. Increasing evidence indicates that phytohormones not only regulate immune responses but also mediate dynamic interactions between plants and their associated microbiomes, collectively shaping plant health and resilience. Rather than acting independently, hormones such as salicylic acid, jasmonic acid, ethylene, abscisic acid, auxin, cytokinins, gibberellins, brassinosteroids, strigolactones, melatonin, and peptide hormones interact through extensive crosstalk to balance growth, defense, and environmental adaptation. Beneficial microorganisms, including plant growth-promoting rhizobacteria, endophytes, mycorrhizal fungi, and biocontrol agents, further modulate these hormonal networks by producing bioactive metabolites, volatile organic compounds, and signaling molecules that enhance induced systemic resistance (ISR) and stress tolerance. This review provides a comprehensive and current knowledge on the molecular mechanisms underlying hormone-mediated regulation of plant immunity at the plant–microbiome interface. This review highlights how phytohormonal networks coordinate plant immune responses through pattern-triggered immunity, effector-triggered immunity, ISR, and systemic acquired resistance, particularly under combined biotic and abiotic stresses. It summarizes recent advances in multi-omics technologies that have improved our understanding of hormone–microbiome interactions and discusses emerging strategies such as biopriming, synthetic microbial communities, microbiome engineering, genome editing, RNA interference, nano-biopriming, artificial intelligence, and precision agriculture. Finally, the review outlines current knowledge gaps, translational challenges, and future research directions for developing sustainable, climate-resilient crop production systems and strengthening global food security. Graphical abstract","植物免疫通过复杂的信号通路网络进行调控，使植物能够感知、响应并适应多种生物和非生物胁迫。越来越多的证据表明，植物激素不仅调控免疫反应，还介导植物与其相关微生物组之间的动态互作，共同塑造植物健康与韧性。水杨酸、茉莉酸、乙烯、脱落酸、生长素、细胞分裂素、赤霉素、油菜素甾醇、独脚金内酯、褪黑素和肽类激素等并非独立发挥作用，而是通过广泛的交叉对话相互作用，以平衡生长、防御和环境适应。有益微生物，包括植物促生根际细菌、内生菌、菌根真菌和生物防治菌剂，通过产生生物活性代谢物、挥发性有机化合物和信号分子进一步增强诱导系统抗性（ISR）和胁迫耐受性，从而调控这些激素网络。本综述全面梳理了植物–微生物组界面中激素介导的植物免疫调控分子机制的最新知识。本综述重点阐述了植物激素网络如何通过模式触发免疫、效应子触发免疫、ISR和系统获得性抗性协调植物免疫反应，尤其是在生物与非生物胁迫复合条件下。综述总结了多组学技术的最新进展，这些技术增进了我们对激素–微生物组互作的理解，并讨论了生物 priming、合成微生物群落、微生物组工程、基因组编辑、RNA干扰、纳米生物 priming、人工智能和精准农业等新兴策略。最后，本综述概述了当前的知识空白、转化挑战以及未来研究方向，以期为开发可持续、气候韧性作物生产系统和加强全球粮食安全提供支撑。图形摘要",null,"Discover Life","2026-10-02T00:00:00Z","论文",10,false,79,{"impact":17,"substance":18,"depth":17,"authority":19,"freshness":20,"relevant":21,"comment":22},18,22,13,8,1,"该综述系统梳理了植物-微生物组界面激素串扰调控免疫的分子机制，并展望了微生物组工程、基因编辑、AI等前沿策略，学术深度与信息增量突出，对智慧农业与气候韧性作物研究具有参考价值。",[24],{"name":10,"url":6},[26,27,28,29,30],"智慧农业","植物免疫","植物激素","植物微生物组","气候韧性作物",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},"A8","yield-food-security","单产提升与粮食安全","\u002Ftopic\u002Ffield-crops\u002Fyield-food-security","A",[],{"status":39,"locked":14,"version":40,"method":41,"evidence":42},"classified","2026-10-22.2","rules",{"candidates":43,"agricultural_evidence":47},[44,53,60,67,73,79],{"code":45,"score":46,"supported":47,"title":48,"abstract":49,"tags":52},"I1",7,true,[],[50,51],"精准农业","precision agriculture",[26],{"code":32,"score":54,"supported":47,"title":55,"abstract":56,"tags":59},6,[],[57,58],"粮食安全","food security",[],{"code":61,"score":62,"supported":47,"title":63,"abstract":64,"tags":66},"A4",3,[],[65],"油菜",[],{"code":68,"score":62,"supported":47,"title":69,"abstract":70,"tags":72},"F4",[],[71],"生物防治",[],{"code":74,"score":62,"supported":47,"title":75,"abstract":76,"tags":78},"H2",[],[77],"根际",[],{"code":80,"score":62,"supported":47,"title":81,"abstract":82,"tags":84},"I2",[],[83],"artificial intelligence",[],[86,87],"植物微生物组 激素调控 植物免疫","植物微生物组 气候韧性作物 智慧农业 植物免疫","植物微生物组激素调控植物免疫-4109",0,"10.1007\u002Fs11084-026-09767-z",{"doi":90,"openalex_id":92,"authors":93,"venue":10,"cited_by_count":89,"oa_url":6,"card":99,"direction":103,"ingested_from":105},"W7216135601",[94,96],{"name":95,"orcid":9},"Seada Yassin Ahmed",{"name":97,"orcid":98},"Azamal Husen","https:\u002F\u002Forcid.org\u002F0000-0002-9120-5540",{"tldr":100,"method":101,"finding":102,"direction":103,"opportunity":104},"综述植物激素与微生物组互作调控植物在生物与非生物复合胁迫下免疫的机制及前沿策略。","整合多组学、激素信号网络与微生物组工程等文献证据进行系统综述。","激素网络与有益微生物协同调控PTI、ETI、ISR和SAR，提升复合胁迫下植物韧性。","农业人工智能与决策模型","可探索AI驱动的激素-微生物组互作预测模型，用于设计合成菌群与精准田间调控策略。","openalex","2026-10-03T23:30:53.236460Z",{"total":54,"page":21,"page_size":54,"items":108},[109,189,279,362,417,487],{"id":110,"title":111,"url":112,"summary":113,"summary_zh":114,"content":9,"source_name":115,"source_url":112,"published_at":116,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":117,"score_detail":118,"sources":123,"tags":125,"primary_topic":128,"secondary_topics":129,"classification":142,"search_phrases":169,"slug":172,"view_count":21,"doi":173,"paper":174,"created_at":188},5308,"Geopolitics and food security: A comprehensive review of emerging risks and responses","https:\u002F\u002Fdoi.org\u002F10.51200\u002Fjsffs.v2i2.7666","This review paper examines the relationship between geopolitics and food security through a Systematic Literature Review guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses framework. A total of 15 peer-reviewed journal articles published between 2015 and 2026 were reviewed to identify emerging geopolitical risks and responses affecting global food systems. The study synthesizes literature on armed conflicts, trade restrictions, climate change, supply chain disruptions, energy market instability, and technological transformation in agriculture. The findings identified four major themes. First, geopolitical conflicts and protectionist trade policies significantly disrupt global food supply chains and increase food price volatility. Second, climate-related shock such as droughts, floods, and extreme weather events intensifies food insecurity, particularly in import-dependent and developing economies. Third, weaknesses in global logistics and energy dependence expose food systems to external shocks and market instability. Fourth, technological innovations, including smart farming, precision agriculture, and digital monitoring systems, play an increasingly important role in strengthening agricultural productivity, improving resource efficiency, and enhancing resilience against geopolitical and environmental uncertainties. The policy implications of this study include strengthening regional food reserves, diversifying import sources, investing in climate-resilient agriculture, promoting the adoption of smart farming technologies, and enhancing institutional cooperation between governments and international organizations. The relevance of smart farming is increasingly evident, as precision agriculture, Internet of Things (IoT)-based monitoring systems, and data-driven farming technologies play a critical role in improving productivity, reducing resource inefficiency, and enhancing food system resilience under geopolitical stress. The study contributes to a broader understanding of how geopolitical dynamics shape food security and provides recommendations for building sustainable, resilient, and technology-driven food systems in an increasingly uncertain global environment.","本文通过遵循系统评价与荟萃分析首选报告条目（Preferred Reporting Items for Systematic Reviews and Meta-Analyses）框架的系统文献综述，考察地缘政治与粮食安全之间的关系。共 review 了2015年至2026年间发表的15篇同行评审期刊论文，以识别影响全球粮食系统的新兴地缘政治风险与应对措施。本研究综合了关于武装冲突、贸易限制、气候变化、供应链中断、能源市场不稳定以及农业技术转型的文献。研究结果识别出四大主题。第一，地缘政治冲突和保护主义贸易政策显著扰乱全球粮食供应链并加剧粮食价格波动。第二，干旱、洪水和极端天气事件等气候相关冲击加剧粮食不安全，尤其是在依赖进口的经济体和发展中经济体中。第三，全球物流的薄弱环节和能源依赖使粮食系统暴露于外部冲击和市场不稳定之中。第四，包括智慧农业、精准农业和数字监测系统在内的技术创新，在增强农业生产力、提高资源效率以及增强应对地缘政治和环境不确定性的韧性方面发挥着日益重要的作用。本研究的政策启示包括加强区域粮食储备、多元化进口来源、投资气候韧性农业、促进智慧农业技术的采用，以及加强政府与国际组织之间的制度合作。智慧农业的相关性日益明显，因为精准农业、基于物联网（IoT）的监测系统和数据驱动农业技术在提高生产力、减少资源低效以及增强地缘政治压力下粮食系统韧性方面发挥着关键作用。本研究有助于更广泛地理解地缘政治动态如何塑造粮食安全，并为在日益不确定的全球环境中构建可持续、有韧性且技术驱动的粮食系统提供建议。","Journal of Smart Farming and Food Security","2026-10-19T00:00:00Z",77,{"impact":17,"substance":119,"depth":120,"authority":19,"freshness":121,"relevant":21,"comment":122},20,17,9,"系统综述梳理地缘政治与粮食安全风险，并强调智慧农业的韧性价值，具政策与产业参考意义，但属综述性论文，非突破性成果。",[124],{"name":115,"url":112},[26,126,57,50,127],"农业供应链","地缘政治",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[130,136],{"code":131,"slug":132,"name":133,"path":134,"parent_code":135},"H7","climate","气候适应与防灾减灾","\u002Ftopic\u002Fenvironment\u002Fclimate","H",{"code":137,"slug":138,"name":139,"path":140,"parent_code":141},"I5","agricultural-iot","物联网传感与边缘计算","\u002Ftopic\u002Fdigital-agriculture\u002Fagricultural-iot","I",{"status":39,"locked":14,"version":40,"method":41,"evidence":143},{"candidates":144,"agricultural_evidence":47},[145,150,155,162],{"code":32,"score":146,"supported":47,"title":147,"abstract":148,"tags":149},15,[58],[57,58],[57],{"code":45,"score":151,"supported":47,"title":152,"abstract":153,"tags":154},11,[],[26,50,51],[26,50],{"code":131,"score":121,"supported":47,"title":156,"abstract":157,"tags":161},[],[158,159,160],"气候变化","干旱","climate change",[],{"code":137,"score":121,"supported":47,"title":163,"abstract":164,"tags":168},[],[165,166,167],"物联网","internet of things","IoT",[],[170,171],"地缘政治 粮食安全","智慧农业 粮食系统韧性","地缘政治粮食安全-5308","10.51200\u002Fjsffs.v2i2.7666",{"doi":173,"openalex_id":175,"authors":176,"venue":115,"cited_by_count":89,"oa_url":112,"card":182,"direction":186,"ingested_from":105},"W7222902031",[177,179],{"name":178,"orcid":9},"Parameswaran Mahendran",{"name":180,"orcid":181},"Wong Sing Yun","https:\u002F\u002Forcid.org\u002F0000-0001-5776-8852",{"tldr":183,"method":184,"finding":185,"direction":186,"opportunity":187},"系统综述地缘政治风险对粮食安全的影响及应对，强调智慧农业的韧性作用。","按PRISMA框架系统综述2015-2026年15篇同行评议文献。","冲突、贸易限制、气候与能源冲击威胁粮食安全，智慧农业可提升韧性与效率。","智慧农业 \u002F 农业物联网","可量化研究物联网与精准农业在地缘政治冲击下对粮食系统韧性的实证贡献。","2026-10-19T23:30:07.850994Z",{"id":190,"title":191,"url":192,"summary":193,"summary_zh":194,"content":9,"source_name":195,"source_url":192,"published_at":196,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":197,"score_detail":198,"sources":200,"tags":202,"primary_topic":207,"secondary_topics":208,"classification":214,"search_phrases":258,"slug":261,"view_count":89,"doi":262,"paper":263,"created_at":278},4488,"Harnessing Indigenous Knowledge for Climate-Smart Agri-Food Systems: A Review of Adaptation Strategies, Food Security, Ecosystem Services, Governance, and Digital Innovation in Sub-Saharan Africa","https:\u002F\u002Fdoi.org\u002F10.3390\u002Fconservation6040120","Sub-Saharan Africa (SSA) faces escalating climate challenges that threaten agricultural productivity, food security, ecosystem sustainability, and rural livelihoods. Indigenous knowledge (IK), developed through generations of interaction with local environments, offers context-specific and culturally embedded solutions for climate adaptation and resilient agri-food systems. This scoping review synthesizes evidence on the role of indigenous knowledge in advancing climate-smart agriculture (CSA) and resilient agri-food systems across SSA. Guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR), the review analyzed 17 studies published between 2000 and 2026. The findings reveal that indigenous knowledge contributes significantly to climate resilience through traditional weather forecasting, crop diversification, indigenous seed preservation, agroforestry, water harvesting, soil fertility management, and community-based natural resource governance. These practices enhance food security, livelihood resilience, biodiversity conservation, and ecosystem service provision while strengthening adaptive capacity among smallholder farmers. The review further highlights the importance of inclusive governance frameworks, knowledge co-production, and policy support for integrating indigenous knowledge into climate adaptation and agricultural development strategies. Emerging digital technologies and innovation platforms also present opportunities for documenting, preserving, and scaling indigenous agricultural knowledge. However, challenges related to weak policy recognition, inadequate documentation, knowledge erosion, and limited digital infrastructure continue to constrain its effective utilization. The study concludes that integrating indigenous knowledge with scientific innovation is essential for building inclusive, sustainable, and climate-resilient agri-food systems in SSA.","撒哈拉以南非洲（Sub-Saharan Africa, SSA）面临日益加剧的气候挑战，威胁着农业生产力、粮食安全、生态系统可持续性和农村生计。土著知识（Indigenous Knowledge, IK）经由世代与当地环境的互动而积累，为气候适应和韧性农业食品系统提供了契合具体情境且深植于文化的解决方案。本范围综述综合了关于土著知识在推动撒哈拉以南非洲气候智慧型农业（Climate-Smart Agriculture, CSA）和韧性农业食品系统中作用的证据。在系统综述和荟萃分析首选报告条目扩展版——范围综述（PRISMA-ScR）的指导下，本综述分析了2000年至2026年间发表的17项研究。研究结果表明，土著知识通过传统天气预报、作物多样化、土著种子保存、农林业、集水、土壤肥力管理和社区为基础的自然资源治理，对气候韧性作出了显著贡献。这些实践增强了粮食安全、生计韧性、生物多样性保护和生态系统服务供给，同时强化了小农户的适应能力。本综述进一步强调了包容性治理框架、知识共同生产以及政策支持对于将土著知识纳入气候适应和农业发展战略的重要性。新兴数字技术和创新平台也为记录、保存和推广土著农业知识提供了机遇。然而，政策认可薄弱、记录不足、知识流失和数字基础设施有限等挑战持续制约着其有效利用。研究结论认为，将土著知识与科学创新相结合，对于在撒哈拉以南非洲构建包容、可持续且具有气候韧性的农业食品系统至关重要。","Conservation","2026-10-08T00:00:00Z",76,{"impact":17,"substance":119,"depth":120,"authority":19,"freshness":20,"relevant":21,"comment":199},"系统综述揭示本土知识与数字创新融合路径，对气候适应型农业与农业信息化有参考价值，但属区域研究、非国内政策事件。",[201],{"name":195,"url":192},[26,203,57,204,205,206],"撒哈拉以南非洲","气候智慧型农业","本土知识","数字创新",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[209],{"code":210,"slug":211,"name":212,"path":213,"parent_code":135},"H6","biodiversity","生态保护与生物多样性","\u002Ftopic\u002Fenvironment\u002Fbiodiversity",{"status":39,"locked":14,"version":40,"method":41,"evidence":215},{"candidates":216,"agricultural_evidence":47},[217,221,228,234,241,247,253],{"code":32,"score":146,"supported":47,"title":218,"abstract":219,"tags":220},[58],[57,58],[57],{"code":210,"score":121,"supported":47,"title":222,"abstract":223,"tags":227},[],[224,225,211,226],"生物多样性","生态系统服务","ecosystem service",[],{"code":131,"score":46,"supported":47,"title":229,"abstract":230,"tags":233},[],[231,232],"气候适应","climate resilience",[204],{"code":235,"score":54,"supported":47,"title":236,"abstract":237,"tags":240},"G2",[],[238,239],"小农户","smallholder",[],{"code":74,"score":54,"supported":47,"title":242,"abstract":243,"tags":246},[],[244,245],"土壤","soil",[],{"code":45,"score":248,"supported":47,"title":249,"abstract":250,"tags":252},4,[],[251],"smart agriculture",[26],{"code":254,"score":21,"supported":14,"title":255,"abstract":256,"tags":257},"J3",[],[],[203],[259,260],"撒哈拉以南非洲 本土知识 气候智慧型农业","撒哈拉以南非洲 气候智慧型农业 数字创新 智慧农业","撒哈拉以南非洲本土知识气候智慧型农业-4488","10.3390\u002Fconservation6040120",{"doi":262,"openalex_id":264,"authors":265,"venue":195,"cited_by_count":89,"oa_url":192,"card":272,"direction":186,"ingested_from":105},"W7220921430",[266,269],{"name":267,"orcid":268},"Adetomiwa Kolapo","https:\u002F\u002Forcid.org\u002F0000-0002-0808-1293",{"name":270,"orcid":271},"Wale Ayojimi","https:\u002F\u002Forcid.org\u002F0000-0003-0038-3462",{"tldr":273,"method":274,"finding":275,"direction":276,"opportunity":277},"综述撒哈拉以南非洲本土知识在气候智慧型农业与食物系统中的作用与挑战。","PRISMA-ScR范围综述，分析2000-2026年17项研究。","本土知识通过传统预报、作物多样化等提升气候韧性，但政策认可与数字化不足制约其应用。","数字乡村与农业信息化","可研究本土知识与数字技术协同的知识共生产机制，及适配小农的低成本数字化记录与传播工具。","2026-10-09T23:30:07.725864Z",{"id":280,"title":281,"url":282,"summary":283,"summary_zh":9,"content":284,"source_name":285,"source_url":9,"published_at":286,"category":287,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":288,"sources":293,"tags":295,"primary_topic":299,"secondary_topics":304,"classification":306,"search_phrases":357,"slug":360,"view_count":89,"doi":9,"paper":9,"created_at":361},4460,"中国农科院资划所牵头智慧农作体系观摩会在山东桓台举行 千亩玉米单产提升8%—12%","https:\u002F\u002Fwww.stdaily.com\u002Fweb\u002Fgdxw\u002F2026-10\u002F03\u002Fcontent_591573.html","中国农业科学院农业资源与农业区划研究所牵头粮食作物精准智慧化生产管理关键技术与集成示范项目黄淮海麦玉轮作主产区智慧农作体系应用示范观摩会在山东桓台中化MAP桓台农场举行；项目构建以多源感知为基础、智能诊断为核心、农机精准执行为保障、数据平台为中枢的智慧农作技术体系，千亩示范方玉米单产较周边常规种植对照提升8%—12%，优质品率稳定在88%以上，化肥、农药、灌溉用水量较常规种植分别减少10%—15%、8%—10%、12%—18%。","![Image 4](https:\u002F\u002Fstatics.kjrb.com.cn\u002Fresource\u002Fkjw\u002Findex\u002Fimages\u002Fshare_logo.jpg)\n\n[![Image 5](https:\u002F\u002Fstatics.kjrb.com.cn\u002Fresource\u002Fkjw\u002Findex\u002Fimages\u002Flogo.png)](http:\u002F\u002Fwww.stdaily.com\u002F)\n\n*   [时政](https:\u002F\u002Fwww.stdaily.com\u002Fweb\u002Fszxw\u002Fnode_357.html)\n*   [热点](https:\u002F\u002Fwww.stdaily.com\u002Fweb\u002Frdxw\u002Fnode_327.html)\n*   [政务](https:\u002F\u002Fwww.stdaily.com\u002Fweb\u002Fzwxw\u002Fnode_362.html)\n*   [深瞳](https:\u002F\u002Fwww.stdaily.com\u002Fweb\u002Fstbd\u002Fnode_434.html)\n*   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马爱平\n\n近日，由中国农业科学院农业资源与农业区划研究所牵头的“粮食作物精准智慧化生产管理关键技术与集成示范”项目黄淮海麦玉轮作主产区智慧农作体系应用示范观摩会，在山东桓台中化MAP桓台农场举行。\n\n与会人员实地观摩项目针对黄淮海小麦—玉米轮作精准智慧生产现实需求，围绕麦玉种、肥、水、药管理关键环节研发的作物表型监测、精量播种、养分诊断与变量追肥、精准灌溉、病虫害监测与变量喷施等系列新技术、新装备，现场考察了集实时监测、智能诊断、定量调控、变量作业于一体，农艺农机信息深度融合的区域智慧农作技术体系及示范成效。\n\n![Image 8](https:\u002F\u002Fwww.stdaily.com\u002Fweb\u002Fgdxw\u002Fpic\u002F2026-10\u002F03\u002F591573_4296d9a8-883a-4a2a-98e1-7290f3adff4fcopy.jpg)\n\n据中化MAP桓台农场负责人介绍，这套数字技术解决方案通过精准播种、变量施肥和智能灌溉等核心环节的优化，实现千亩示范方玉米单产较周边常规种植对照提升8%—12%，优质品率稳定在88%以上；同时，实现农业资源的节约，化肥、农药和灌溉用水量较常规种植分别减少10%—15%、8%—10%、12%—18%，资源利用效率得到显著提升，目前已形成面向周边普通农户和新型经营主体的技术培训、推广和辐射服务能力。\n\n![Image 9](https:\u002F\u002Fwww.stdaily.com\u002Fweb\u002Fgdxw\u002Fpic\u002F2026-10\u002F03\u002F591573_e7499078-dee9-4a40-bf66-504e09cef576copy.jpg)\n\n项目首席科学家吴文斌研究员表示，玉米是我国种植面积最大、产量最高的粮食作物。但长期以来，我国玉米种植生产管理整体偏粗放。播种质量参差不齐，关键农情信息获取滞后，水肥药施用多依赖传统经验，不仅造成玉米单产与先进国家相比有较大差距，也带来农业资源浪费、农田生态压力加大等问题。为此，项目组联合中化MAP团队，选择灌溉条件完善、机械化基础扎实的MAP桓台农场作为核心基地，打造玉米生产方式数字化转型升级示范区。该项目构建一套以多源感知为基础、智能诊断为核心、农机精准执行为保障、数据平台为中枢的智慧农作技术体系，实现玉米种植全过程的数据驱动和精准管控。\n\n（中国农业科学院农业资源与农业区划研究所供图）\n\n责任编辑：陈可轩\n\n相关稿件：\n\n![Image 10](https:\u002F\u002Fstatics.kjrb.com.cn\u002Fresource\u002Fkjw\u002Fimages\u002Fpinglun.png)网友评论\n\n评论\n\n最热评论\n\n没有更多评论了\n\n[热点](https:\u002F\u002Fwww.stdaily.com\u002Fweb\u002Frdxw\u002Fnode_327.html)\n\n[![Image 11](https:\u002F\u002Fwww.stdaily.com\u002Fweb\u002Fgdxw\u002Fpic\u002F2026-10\u002F08\u002F592769_1df74a15-67d5-4910-aece-debcc638606a_1009x6734106423copy.JPG)](https:\u002F\u002Fwww.stdaily.com\u002Fweb\u002Fgdxw\u002F2026-10\u002F08\u002Fcontent_592769.html)\n\n[国庆假期服务消费旺盛 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[京公网安备11010802036145号](http:\u002F\u002Fwww.beian.gov.cn\u002Fportal\u002FregisterSystemInfo?recordcode=11010802036145)\n\n[![Image 24](https:\u002F\u002Fwww.stdaily.com\u002Fresource\u002FtemplateRes\u002F\u002F202408\u002F19\u002F345\u002Fimages\u002Fclose.png)](https:\u002F\u002Fwww.stdaily.com\u002Fweb\u002Fgdxw\u002F2026-10\u002F03\u002Fcontent_591573.html)\n\n#### 抱歉，您使用的浏览器版本过低或开启了浏览器兼容模式，这会影响您正常浏览本网页\n\n### 您可以进行以下操作:\n\n## 1.将浏览器切换回极速模式\n\n![Image 25](https:\u002F\u002Fwww.stdaily.com\u002Fresource\u002FtemplateRes\u002F\u002F202408\u002F19\u002F345\u002Fimages\u002F360tip.png)\n\n## 2.点击下面图标升级或更换您的浏览器\n\n[![Image 26](https:\u002F\u002Fwww.stdaily.com\u002Fresource\u002FtemplateRes\u002F\u002F202408\u002F19\u002F345\u002Fimages\u002Ffirefox.jpg)](http:\u002F\u002Fwww.firefox.com.cn\u002Fdownload\u002F)[![Image 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2026-10-03","2026-10-03T00:00:00Z","报道",{"impact":18,"substance":289,"depth":290,"authority":291,"freshness":54,"relevant":21,"comment":292},21,16,14,"国家级科研机构牵头、有明确增产与节本数据的智慧农作示范报道，专业性与信息增量俱佳，值得进入每日精选。",[294],{"name":285,"url":282},[26,296,50,297,298],"农业遥感","水肥一体化","玉米单产提升",{"code":300,"slug":301,"name":302,"path":303,"parent_code":36},"A3","maize","玉米","\u002Ftopic\u002Ffield-crops\u002Fmaize",[305],{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},{"status":39,"locked":14,"version":40,"method":41,"evidence":307},{"candidates":308,"agricultural_evidence":47},[309,314,319,325,330,336,342,347,352],{"code":300,"score":310,"supported":47,"title":311,"abstract":312,"tags":313},12,[302],[302],[298],{"code":32,"score":121,"supported":47,"title":315,"abstract":317,"tags":318},[316],"单产提升",[],[298],{"code":320,"score":62,"supported":47,"title":321,"abstract":322,"tags":324},"A7",[],[323],"轮作",[],{"code":68,"score":62,"supported":47,"title":326,"abstract":327,"tags":329},[],[328],"农药",[],{"code":331,"score":62,"supported":47,"title":332,"abstract":333,"tags":335},"F5",[],[334],"农机",[],{"code":337,"score":62,"supported":47,"title":338,"abstract":339,"tags":341},"H3",[],[340],"灌溉",[],{"code":45,"score":343,"supported":14,"title":344,"abstract":345,"tags":346},2,[],[],[26,50],{"code":348,"score":21,"supported":14,"title":349,"abstract":350,"tags":351},"F3",[],[],[297],{"code":353,"score":21,"supported":14,"title":354,"abstract":355,"tags":356},"I3",[],[],[296],[358,359],"中国农科院资划所 智慧农作 桓台","中化MAP 玉米 单产提升","中国农科院资划所智慧农作桓台-4460","2026-10-09T00:04:56.174089Z",{"id":363,"title":364,"url":365,"summary":366,"summary_zh":9,"content":9,"source_name":367,"source_url":9,"published_at":368,"category":287,"cover_url":9,"hotness":13,"is_selected":14,"score":369,"score_detail":370,"sources":373,"tags":375,"primary_topic":380,"secondary_topics":385,"classification":387,"search_phrases":412,"slug":415,"view_count":62,"doi":9,"paper":9,"created_at":416},3956,"福建2026年福州市闽清县水稻单产提升高素质农民培训班开班——省农科院水稻所参训","https:\u002F\u002Fjxcg.ngx.net.cn\u002Fjypx\u002Fjnpx\u002F202609\u002Ft20260928_247261.html","9月24日，2026年福州市闽清县水稻单产提升高素质农民培训班开班，为期7天，吸引50名从事或有意愿从事粮油生产、经营、服务的农民和返乡人员参加。培训班由闽清县农业农村局主办，福州市金昕职业培训学校有限公司承办，安排有4天田间实践教学，学员们先后前往福建省农科院水稻研究所、福州市长乐区雪美农业开发有限公司、福清市相思岭农创农业发展有限公司等实训基地，实地学习水稻育种设施、稻米加工技术、农机与智慧农业平台协同作业等。","中国农村远程教育网·2026年09月28日","2026-09-28T03:16:00Z",41,{"impact":20,"substance":310,"depth":20,"authority":20,"freshness":371,"relevant":21,"comment":372},5,"县级高素质农民培训动态，含智慧农业平台与田间实训内容，但层级与信息增量有限，属常规地方报道。",[374],{"name":367,"url":365},[26,376,377,378,379],"水稻单产提升","高素质农民","田间实训","福建闽清",{"code":381,"slug":382,"name":383,"path":384,"parent_code":36},"A1","rice","水稻","\u002Ftopic\u002Ffield-crops\u002Frice",[386],{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},{"status":39,"locked":14,"version":40,"method":41,"evidence":388},{"candidates":389,"agricultural_evidence":47},[390,395,399,403,407],{"code":381,"score":291,"supported":47,"title":391,"abstract":392,"tags":394},[383],[383,393],"稻米",[],{"code":32,"score":310,"supported":47,"title":396,"abstract":397,"tags":398},[316],[316],[376],{"code":45,"score":248,"supported":47,"title":400,"abstract":401,"tags":402},[],[26],[26],{"code":331,"score":62,"supported":47,"title":404,"abstract":405,"tags":406},[],[334],[],{"code":408,"score":21,"supported":14,"title":409,"abstract":410,"tags":411},"G1",[],[],[377],[413,414],"闽清县 水稻单产提升 培训班","福建省农科院水稻所 实训","闽清县水稻单产提升培训班-3956","2026-10-02T11:53:12.917292Z",{"id":418,"title":419,"url":420,"summary":421,"summary_zh":422,"content":9,"source_name":423,"source_url":420,"published_at":424,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":425,"score_detail":426,"sources":428,"tags":430,"primary_topic":433,"secondary_topics":434,"classification":435,"search_phrases":470,"slug":473,"view_count":343,"doi":474,"paper":475,"created_at":486},3826,"From Dry Fields To Smart Resilience: Climate-Smart Agriculture, Digital Early-Warning Systems And Household Food Security In Chivi District, Zimbabwe","https:\u002F\u002Fdoi.org\u002F10.36923\u002Fsq.v3i1.435","This paper examines how climate-smart agriculture (CSA) and digital early-warning systems can jointly support household food-security resilience in Chivi District, a drought-prone area of south-eastern Zimbabwe dominated by rain-fed smallholder agriculture. Using a structured qualitative evidence synthesis with a district-centred case orientation, the study reviews 47 academic, policy and institutional sources published from 2021 to 14 September 2026. The study prioritises direct Chivi evidence, while using Zimbabwean, southern African, and wider African evidence comparatively where district-specific studies are limited. The synthesis identifies six interrelated themes concerning climate shocks, CSA adoption, small grains and water management, digital early warning, gender and institutional capacity, and integrated resilience. The findings indicate that CSA can strengthen food security when extension, inputs, finance, and markets support conservation agriculture, crop diversification, small grains, soil-fertility management, and water harvesting. However, digital early-warning information contributes to resilience only when it is timely, trusted, localised and translated into feasible action. Accordingly, the paper's principal contribution is an integrated smart-resilience framework centred on an information-to-action pathway: climate information can influence household food-security resilience only when farmers have viable adaptation options and the material, social and institutional capacity to act. The paper therefore treats digital information, agronomic adaptation, gender, household resources and local institutions as interdependent rather than separate interventions.","本文考察气候智慧型农业（climate-smart agriculture, CSA）与数字预警系统如何共同支撑津巴布韦东南部干旱易发区奇维（Chivi）地区以雨养小农农业为主的家庭粮食安全韧性。研究采用以地区为中心的案例导向结构化定性证据综合方法，梳理了2021年至2026年9月14日期间发表的47份学术、政策与机构文献。研究优先采用奇维地区的直接证据，在地区性专门研究有限时，则比较性地参考津巴布韦、南部非洲及更广泛非洲的证据。该综合识别出六个相互关联的主题，涉及气候冲击、气候智慧型农业采纳、小粒谷物与水资源管理、数字预警、性别与制度能力，以及综合韧性。研究结果表明，当推广服务、投入品、金融和市场支持保护性农业、作物多样化、小粒谷物、土壤肥力管理和集水时，气候智慧型农业能够增强粮食安全。然而，数字预警信息只有在及时、可信、本地化并转化为可行行动时，才能促进韧性。因此，本文的主要贡献在于提出了一个以信息到行动路径为核心的综合智慧韧性框架：气候信息只有在农民拥有可行的适应选项以及采取行动所需的物质、社会和制度能力时，才能影响家庭粮食安全韧性。据此，本文将数字信息、农艺适应、性别、家庭资源和地方制度视为相互依存的干预措施，而非彼此分离的干预措施。","Sustainability Quest","2026-09-29T00:00:00Z",56,{"impact":20,"substance":17,"depth":290,"authority":54,"freshness":20,"relevant":21,"comment":427},"以津巴布韦Chivi区为案例的定性证据综述，提出信息到行动的气候智慧农业韧性框架，对数字预警落地条件有参考价值，但属区域案例研究，公共影响有限。",[429],{"name":423,"url":420},[26,57,238,431,432],"气候智慧农业","数字预警",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":14,"version":40,"method":41,"evidence":436},{"candidates":437,"agricultural_evidence":47},[438,442,446,451,455,459,464],{"code":32,"score":146,"supported":47,"title":439,"abstract":440,"tags":441},[58],[57,58],[57],{"code":45,"score":310,"supported":47,"title":443,"abstract":444,"tags":445},[251],[251],[26],{"code":131,"score":46,"supported":47,"title":447,"abstract":448,"tags":450},[],[159,449],"drought",[431],{"code":74,"score":54,"supported":47,"title":452,"abstract":453,"tags":454},[],[244,245],[],{"code":235,"score":248,"supported":47,"title":456,"abstract":457,"tags":458},[],[239],[238],{"code":337,"score":62,"supported":47,"title":460,"abstract":461,"tags":463},[],[462],"水资源",[],{"code":465,"score":62,"supported":47,"title":466,"abstract":467,"tags":469},"H8",[],[468],"conservation agriculture",[],[471,472],"气候智慧农业 数字预警 智慧农业 粮食安全","气候智慧农业 数字预警","气候智慧农业数字预警智慧农业粮食安全-3826","10.36923\u002Fsq.v3i1.435",{"doi":474,"openalex_id":476,"authors":477,"venue":423,"cited_by_count":89,"oa_url":420,"card":481,"direction":186,"ingested_from":105},"W7214743351",[478],{"name":479,"orcid":480},"Victor Madziyauswa","https:\u002F\u002Forcid.org\u002F0000-0002-6122-6666",{"tldr":482,"method":483,"finding":484,"direction":276,"opportunity":485},"综述津巴布韦Chivi地区气候智慧农业与数字预警系统如何共同提升家庭粮食安全韧性。","结构化定性证据综合，分析47份2021-2026年学术、政策与机构文献。","数字预警须及时、可信、本地化并转化为可行行动，且需配套适应选项与能力才能提升韧性。","可实证检验“信息—行动”路径，研究数字预警与农户适应能力、性别和制度条件的交互机制。","2026-09-30T23:30:09.849166Z",{"id":488,"title":489,"url":490,"summary":491,"summary_zh":492,"content":9,"source_name":493,"source_url":490,"published_at":494,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":495,"score_detail":496,"sources":498,"tags":500,"primary_topic":504,"secondary_topics":505,"classification":516,"search_phrases":546,"slug":549,"view_count":62,"doi":550,"paper":551,"created_at":562},3613,"AI-Assisted Demand Forecasting and Production Scheduling for High-Volume Food Manufacturing in Saudi Arabia: A Food Security Framework for Vision 2030","https:\u002F\u002Fdoi.org\u002F10.64388\u002Firev10i3-1723457","High-volume food manufacturing in Saudi Arabia is increasingly exposed to volatile demand, short product life cycles, promotion-driven peaks, imported input dependencies, capacity bottlenecks, and the operational consequences of seasonal and religious events. These conditions make demand forecasting and production scheduling inseparable rather than sequential planning tasks. This review synthesizes research published between 2020 and 2025 on artificial intelligence-assisted demand forecasting, perishable-product planning, finite-capacity scheduling, digital-twin-enabled decision support, and food supply-chain resilience. The study develops an integrated framework in which demand sensing produces probabilistic forecasts that are translated into production decisions through capacity, shelf-life, sanitation, changeover, labour, inventory, and service constraints. Evidence indicates that machine-learning and deep-learning methods can improve forecast accuracy when promotions, weather, calendar events, regional variation, and censored demand are represented appropriately, while optimization models can convert these signals into feasible schedules that reduce changeovers, waste, shortages, and unstable resource use [1-8]. The review also identifies a persistent implementation gap: forecasting studies often stop at predictive accuracy, whereas scheduling studies frequently assume demand inputs are fixed and reliable. The proposed framework closes this gap by linking forecast uncertainty, rolling-horizon scheduling, execution feedback, and food-security outcomes. For Saudi manufacturers, the value of this integration lies not only in lower cost, but also in improving product availability, freshness, localized processing capacity, shock recovery, and evidence-based management under Vision 2030. The paper concludes with a staged implementation roadmap and research priorities for explainability, cross-site scheduling, event-aware forecasting, data governance, and resilient planning.","沙特阿拉伯的大规模食品制造日益面临需求波动、产品生命周期短、促销驱动的峰值、进口原料依赖、产能瓶颈以及季节性和宗教事件的运营影响。这些条件使得需求预测与生产调度成为不可分割的任务，而非顺序规划任务。本文综述了2020年至2025年间发表的相关研究，涵盖人工智能辅助需求预测、易腐产品规划、有限产能调度、数字孪生赋能的决策支持以及食品供应链韧性。研究构建了一个集成框架，其中需求感知产生概率预测，并通过产能、保质期、卫生、换产、劳动力、库存和服务约束转化为生产决策。证据表明，当促销、天气、日历事件、区域差异和截尾需求得到适当表征时，机器学习和深度学习方法能够提高预测精度，而优化模型可将这些信号转化为可行的调度方案，从而减少换产、浪费、缺货和不稳定的资源使用[1-8]。本综述还指出了一个持续存在的实施缺口：预测研究往往止步于预测精度，而调度研究则常常假设需求输入是固定且可靠的。所提出的框架通过将预测不确定性、滚动时域调度、执行反馈和食品安全结果联系起来，弥合了这一缺口。对于沙特制造商而言，这种集成的价值不仅在于降低成本，还在于改善产品可得性、新鲜度、本地化加工能力、冲击恢复能力以及“2030愿景”下的循证管理。本文最后提出了分阶段实施路线图以及可解释性、跨厂区调度、事件感知预测、数据治理和韧性规划方面的研究优先事项。","Iconic Research and Engineering Journals","2026-09-25T00:00:00Z",60,{"impact":310,"substance":17,"depth":290,"authority":54,"freshness":20,"relevant":21,"comment":497},"综述性论文，提出AI需求预测与生产排程整合框架，对智慧农业与粮食安全有参考价值，但属境外研究且期刊权威性一般。",[499],{"name":493,"url":490},[26,501,57,502,503],"农业人工智能","供应链韧性","生产调度",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[506,512],{"code":507,"slug":508,"name":509,"path":510,"parent_code":511},"E1","food-processing","加工与食品制造","\u002Ftopic\u002Ffood-supply\u002Ffood-processing","E",{"code":80,"slug":513,"name":514,"path":515,"parent_code":141},"agricultural-ai","农业AI与大模型","\u002Ftopic\u002Fdigital-agriculture\u002Fagricultural-ai",{"status":39,"locked":14,"version":40,"method":41,"evidence":517},{"candidates":518,"agricultural_evidence":47},[519,524,531,535,540],{"code":507,"score":151,"supported":47,"title":520,"abstract":522,"tags":523},[521],"food manufacturing",[521],[],{"code":80,"score":13,"supported":47,"title":525,"abstract":526,"tags":530},[],[527,528,83,529],"深度学习","机器学习","decision support",[501],{"code":32,"score":121,"supported":47,"title":532,"abstract":533,"tags":534},[58],[],[57],{"code":45,"score":248,"supported":47,"title":536,"abstract":537,"tags":539},[],[538],"数字孪生",[26],{"code":541,"score":62,"supported":47,"title":542,"abstract":543,"tags":545},"E4",[],[544],"食品安全",[],[547,548],"沙特阿拉伯 食品制造 需求预测","Vision 2030 粮食安全","沙特阿拉伯食品制造需求预测-3613","10.64388\u002Firev10i3-1723457",{"doi":550,"openalex_id":552,"authors":553,"venue":493,"cited_by_count":89,"oa_url":556,"card":557,"direction":186,"ingested_from":105},"W7214295236",[554],{"name":555,"orcid":9},"Atif Maqbool Syed","https:\u002F\u002Fwww.irejournals.com\u002Fformatedpaper\u002F1723457.pdf",{"tldr":558,"method":559,"finding":560,"direction":103,"opportunity":561},"综述2020-2025年AI需求预测与生产调度研究，提出沙特食品制造整合框架以保障Vision 20","文献综述2020-2025年AI预测、易腐品规划、有限产能调度与数字孪生研究。","预测研究止于精度、调度研究假设需求固定，整合框架可弥合实施鸿沟并提升粮食安全。","可研究事件感知预测与滚动调度耦合、跨工厂协同及可解释AI在食品供应链韧性中的应用。","2026-09-27T23:30:14.516185Z"]