[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-3636":3,"related-3636":82},{"id":4,"title":5,"url":6,"summary":7,"summary_zh":8,"content":9,"source_name":10,"source_url":8,"published_at":11,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":15,"score_detail":16,"sources":24,"tags":26,"primary_topic":8,"secondary_topics":33,"classification":34,"search_phrases":77,"slug":80,"view_count":50,"doi":8,"paper":8,"created_at":81},3636,"以农业科技创新支撑农业强国建设——人民日报理论版发表中国农业科学院署名文章","https:\u002F\u002Fcaas.cn\u002Fxwzx\u002Ftpxw\u002F76f0e0b59253478d977bb8ed2153f0e7.htm","9月23日第九个中国农民丰收节当天，人民日报理论版'深入学习贯彻习近平新时代中国特色社会主义思想'专栏发表中国农业科学院署名文章《以科技创新支撑农业强国建设》。文章指出：'十五五'规划纲要设置'加快农业农村现代化 扎实推进乡村全面振兴'专篇，要求'强化农业科技和装备支撑'。要把党中央决策部署落到实处，要锚定高水平农业科技自立自强目标，加快提升农业科技创新体系整体效能。我国人口数量占世界比重约17%但耕地资源仅占9%，人均耕地面积不足世界平均水平的40%，丘陵山区占1\u002F3以上，淡水资源只占6%。",null,"习近平总书记指出：“要完善符合科技创新规律的资源配置方式”。当前，随着新一轮科技革命和产业变革加速突破，人工智能、生物制造、新材料、新能源等领域的重大科技成果不断涌现，向农业农村各领域渗透融合，农业科技创新体系整体效能进一步提升，正展现出更强劲的动能。加快推动农业科技创新，必须充分认识和遵循农业科技创新规律，准确把握农业科技的发展趋势和时代要求。\n\n农业科技创新具有研究周期长、系统复杂性强、区域差异突出等特征。农业科技创新以动植物、微生物等生命体为主要研究对象，是围绕生命体开展的多学科交叉融合研究。比如，水稻新品种培育一般需要10年左右，肉牛新品种培育需要40年左右。这决定了农业科技创新必须遵循生命节律、遗传规律、气候地理等自然规律。同时，农业生产是一个开放的复杂系统，作物种植涉及土、肥、水、种、保、管、工等各个方面，畜禽养殖包括种、料、繁、舍、病、管等诸多环节，各方面各环节相互影响、相互制约，具有很强的系统性。农业科研成果应用受气候类型、水土条件、耕作制度等影响十分显著，“橘生淮南则为橘，生于淮北则为枳”就是生动写照。因此，推进农业科技创新既要坚持长期连续投入，还要注重全链条、多区域系统布局。\n\n农业科技创新必须切实保障粮食和重要农产品稳定安全供给。农业科技创新直接关系老百姓的“米袋子”“菜篮子”，是保障人民基本生活需求、保障国家粮食安全的重要支撑。特别是底盘技术、核心种源、关键农机装备等一旦受制于人，将给国家安全带来重大挑战。农业基础研究、关键核心技术攻关等科研活动投入大、周期长、风险高，直接经济效益不明显，但一个突破性品种可能惠及整个产业，一项绿色技术推广可能改善整个区域生态环境，社会收益巨大，具有显著的正外部性和公益属性。因此，在充分发挥市场在创新资源配置中决定性作用的同时，要更好发挥政府作用，确保聚焦国家战略需求，提供有力有效的科技公共产品。\n\n农业科技创新正由单项技术突破加快转向体系化、全链条协同创新。当前，以基因编辑、生物合成为代表的前沿生物技术不断突破，以人工智能、区块链等为代表的新一代信息技术加速演进，推动农业科技创新对象由传统生命体向“生命体+数据+模型”复合系统拓展，带动农业科技创新模式向数据驱动、智能赋能、场景验证一体化转型，数据要素和智能算法正深度嵌入研发、试验、推广全过程。同时，大面积单产提升需求更加迫切，推动农业科技创新由提供单项产品或技术加快转向因地制宜提供定制化、集成化、场景化的系统解决方案。比如，东北粮食主产区需要集成良种、密植、农机、水肥一体化的增产增效技术方案，西南丘陵山区需要轻简适用、机艺结合、抗灾稳产的技术方案。因此，必须加强有组织科研，加强全产业链攻关，加快推动农业科技创新从“单兵突进”向“体系作战”转变。","中国农业科学院（人民日报理论版）2026-09-23","2026-09-23T00:00:00Z","报道",10,true,84,{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":21,"relevant":22,"comment":23},27,20,17,15,5,1,"国家级科研机构在央媒理论版系统阐述农业科技创新规律与体系化转型方向，权威性与政策信号价值突出，但属理论阐释而非新增政策条款，时效性一般。",[25],{"name":10,"url":6},[27,28,29,30,31,32],"智慧农业","粮食安全","生物育种","农业强国","农业科技创新","有组织科研",[],{"status":35,"locked":36,"version":37,"method":38,"evidence":39},"needs_review",false,"2026-10-22.2","rules",{"candidates":40,"agricultural_evidence":14,"reason":76},[41,48,55,61,66,71],{"code":42,"score":43,"supported":14,"title":44,"abstract":45,"tags":47},"J2",16,[30],[30,46],"农业农村现代化",[30,31],{"code":49,"score":50,"supported":14,"title":51,"abstract":52,"tags":54},"H3",3,[],[53],"水资源",[],{"code":56,"score":50,"supported":14,"title":57,"abstract":58,"tags":60},"J4",[],[59],"丰收节",[],{"code":62,"score":22,"supported":36,"title":63,"abstract":64,"tags":65},"A8",[],[],[28],{"code":67,"score":22,"supported":36,"title":68,"abstract":69,"tags":70},"F2",[],[],[29],{"code":72,"score":22,"supported":36,"title":73,"abstract":74,"tags":75},"I1",[],[],[27],"多个产业证据相当，需要确认主归属",[78,79],"中国农业科学院 农业科技创新","人民日报理论版 农业强国","中国农业科学院农业科技创新-3636","2026-09-28T00:02:58.534635Z",{"total":83,"page":22,"page_size":83,"items":84},6,[85,162,265,337,408,459],{"id":86,"title":87,"url":88,"summary":89,"summary_zh":90,"content":8,"source_name":91,"source_url":88,"published_at":92,"category":93,"cover_url":8,"hotness":13,"is_selected":36,"score":94,"score_detail":95,"sources":100,"tags":102,"primary_topic":106,"secondary_topics":112,"classification":113,"search_phrases":142,"slug":145,"view_count":146,"doi":147,"paper":148,"created_at":161},5588,"Certified Temporal Fusion of Artificial Intelligence Climate Analytics for Crop Failure Early Warning Under Sparse Agricultural Sensors: Error Bounds and Famine Relief Targeting","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.23545489","Sparse agricultural sensor networks across sub-Saharan Africa leave crop-failure early-warning systems with too little ground observation to support reliable famine relief targeting. The framework treats sensor sparsity as a missing-data problem with a known observation operator and propagates climate-analytics uncertainty through a temporal Kalman-Buys filter whose gain is constrained by a certified risk envelope. Using NASA POWER monthly reanalysis for Accra, Ghana (2000-2023, 312 observations), the analysis establishes a mean temperature of 26.521 C and a warming trend of 0.1622 C per decade, which calibrates the climate-analytics prior. The derived bounds show that relief-targeting error scales with the square root of sensor density and with the Lipschitz constant of the crop-response function, yielding an explicit sensor-placement rule for a target misclassification rate. The contribution is a certified, assumption-explicit bridge between climate analytics and famine relief targeting that states the conditions under which early warning is trustworthy.","撒哈拉以南非洲稀疏的农业传感器网络使得作物歉收预警系统缺乏足够的地面观测数据，难以支撑可靠的饥荒救援目标定位。该框架将传感器稀疏性视为具有已知观测算子的缺失数据问题，并通过时间Kalman-Buys滤波器传播气候分析不确定性，该滤波器的增益受经认证的风险包络约束。利用NASA POWER对加纳阿克拉的月度再分析数据（2000—2023年，312个观测值），分析确定了平均气温为26.521°C、每十年0.1622°C的增暖趋势，据此校准了气候分析先验。推导出的界限表明，救援目标定位误差随传感器密度的平方根以及作物响应函数的Lipschitz常数缩放，从而为目标误分类率给出了明确的传感器布设规则。该研究的贡献在于构建了一个经认证的、假设明确的气候分析与饥荒救援目标定位之间的桥梁，阐明了早期预警可信赖的条件。","Zenodo (CERN European Organization for Nuclear Research)","2026-10-21T00:00:00Z","论文",74,{"impact":96,"substance":97,"depth":98,"authority":96,"freshness":13,"relevant":22,"comment":99},12,22,18,"该研究提出一种带误差界认证的时序融合方法，用于稀疏传感器条件下的作物歉收预警与饥荒救援瞄准，方法新颖、结论明确，但案例局限于加纳阿克拉，产业影响有限，适合作为技术前沿条目收录。",[101],{"name":91,"url":88},[27,103,28,104,105],"农业人工智能","遥感","气候分析",{"code":107,"slug":108,"name":109,"path":110,"parent_code":111},"I2","agricultural-ai","农业AI与大模型","\u002Ftopic\u002Fdigital-agriculture\u002Fagricultural-ai","I",[],{"status":114,"locked":36,"version":37,"method":38,"evidence":115},"classified",{"candidates":116,"agricultural_evidence":14},[117,123,129,133,137],{"code":107,"score":118,"supported":14,"title":119,"abstract":121,"tags":122},9,[120],"artificial intelligence",[],[103],{"code":124,"score":50,"supported":14,"title":125,"abstract":126,"tags":128},"I5",[],[127],"农业传感",[],{"code":62,"score":22,"supported":36,"title":130,"abstract":131,"tags":132},[],[],[28],{"code":72,"score":22,"supported":36,"title":134,"abstract":135,"tags":136},[],[],[27],{"code":138,"score":22,"supported":36,"title":139,"abstract":140,"tags":141},"I3",[],[],[104],[143,144],"NASA POWER 加纳 气候分析","作物歉收 早期预警 传感器","NASAPOWER加纳气候分析-5588",0,"10.5281\u002Fzenodo.23545489",{"doi":147,"openalex_id":149,"authors":150,"venue":91,"cited_by_count":146,"oa_url":88,"card":153,"direction":159,"ingested_from":160},"W7223111766",[151],{"name":152,"orcid":8},"Fatima-Zahra El Khattabi",{"tldr":154,"method":155,"finding":156,"direction":157,"opportunity":158},"提出带误差界的时间融合框架，在稀疏传感器下用气候分析预警作物歉收。","卡尔曼-布西滤波+NASA POWER再分析数据，风险包络约束增益。","救济瞄准误差随传感器密度平方根和作物响应Lipschitz常数缩放，给出布点规则。","农业遥感与作物表型","可将该认证误差界框架扩展到多作物多区域，结合卫星遥感弥补地面传感器稀疏。","农业人工智能与决策模型","openalex","2026-10-22T11:21:02.682497Z",{"id":163,"title":164,"url":165,"summary":166,"summary_zh":167,"content":8,"source_name":168,"source_url":165,"published_at":169,"category":93,"cover_url":8,"hotness":13,"is_selected":36,"score":170,"score_detail":171,"sources":173,"tags":175,"primary_topic":179,"secondary_topics":185,"classification":190,"search_phrases":244,"slug":247,"view_count":146,"doi":8,"paper":248,"created_at":264},5312,"Agricultural Production under Climate Change in Afghanistan: Impacts, Challenges and Adaptation Options (A Review)","https:\u002F\u002Fesrj.edu.af\u002Fesrj\u002Farticle\u002Fview\u002F123","Climate change poses serious challenges to agriculture in Afghanistan, a country largely dependent on rainfed farming and highly vulnerable to water scarcity, drought, and temperature extremes. Understanding the impacts of climate variability and identifying effective adaptation strategies are essential to sustain agricultural productivity and ensure food security. This systematic review synthesizes empirical, modeling, and review studies on climate change effects on Afghan agriculture, assesses adaptation measures, and integrates regional experiences from Pakistan, Iran, Tajikistan, and Uzbekistan. A structured literature search was conducted using peer-reviewed articles, institutional reports, and regional studies published between 2000 and 2025. Studies were selected based on relevance to Afghan agro-ecological systems, climate stressors, and adaptation strategies. We extracted data using a structured table format following PRISMA guidelines, combining national and regional evidence. Findings indicate that water scarcity, prolonged drought, rising temperatures, and erratic precipitation are the main stressors affecting major crops, including wheat, barley, chickpea, maize, and cotton. Yield reductions ranged from 12% to 25% across provinces. Adaptation strategies such as Climate-Smart Agriculture (CSA), efficient irrigation (drip and sprinkler), rainwater harvesting, mulching, and drought- or heat-tolerant crop varieties were most effective. Regional evidence confirms the transferability of these measures under similar agro-climatic conditions. In conclusion, climate change significantly threatens agricultural productivity in Afghanistan. Evidence-based adaptation strategies, supported by coordinated policy and capacity-building initiatives, can enhance resilience, protect rural livelihoods, and ensure sustainable food security.","气候变化对阿富汗农业构成严峻挑战，该国农业在很大程度上依赖雨养耕作，极易受到水资源短缺、干旱和极端温度的影响。理解气候变异的影响并确定有效的适应策略，对于维持农业生产力和保障粮食安全至关重要。本系统综述综合了关于气候变化对阿富汗农业影响的实证研究、模拟研究和综述研究，评估了适应措施，并整合了巴基斯坦、伊朗、塔吉克斯坦和乌兹别克斯坦的区域经验。采用结构化文献检索方法，检索了2000年至2025年间发表的同行评审论文、机构报告和区域研究。研究依据其与阿富汗农业生态系统、气候胁迫因子和适应策略的相关性进行筛选。我们遵循PRISMA指南，采用结构化表格格式提取数据，综合了国家层面和区域层面的证据。研究结果表明，水资源短缺、持续干旱、气温上升和降水不稳定是影响主要作物（包括小麦、大麦、鹰嘴豆、玉米和棉花）的主要胁迫因子。各省产量降幅在12%至25%之间。气候智慧型农业（CSA）、高效灌溉（滴灌和喷灌）、雨水收集、覆盖栽培以及耐旱或耐热作物品种等适应策略最为有效。区域证据证实了这些措施在相似农业气候条件下的可推广性。总之，气候变化显著威胁阿富汗的农业生产力。以协调政策和能力建设举措为支撑的循证适应策略能够增强韧性、保护农村生计并确保可持续的粮食安全。","ESRJ","2026-10-16T00:00:00Z",73,{"impact":98,"substance":18,"depth":19,"authority":96,"freshness":83,"relevant":22,"comment":172},"系统综述整合2000-2025年证据，量化减产12%-25%并提出可迁移的适应策略，对区域农业气候韧性研究有参考价值，但非国内三农政策或产业事件，时效性一般。",[174],{"name":168,"url":165},[27,28,176,177,178],"气候变化","适应性策略","水资源短缺",{"code":180,"slug":181,"name":182,"path":183,"parent_code":184},"H7","climate","气候适应与防灾减灾","\u002Ftopic\u002Fenvironment\u002Fclimate","H",[186],{"code":49,"slug":187,"name":188,"path":189,"parent_code":184},"irrigation","水资源与灌溉","\u002Ftopic\u002Fenvironment\u002Firrigation",{"status":114,"locked":36,"version":37,"method":38,"evidence":191},{"candidates":192,"agricultural_evidence":14},[193,200,205,211,218,225,232,238],{"code":180,"score":98,"supported":14,"title":194,"abstract":196,"tags":199},[195],"climate change",[176,197,195,198],"干旱","drought",[176],{"code":49,"score":118,"supported":14,"title":201,"abstract":202,"tags":204},[],[203,53,187],"灌溉",[],{"code":62,"score":206,"supported":14,"title":207,"abstract":208,"tags":210},7,[],[28,209],"food security",[28],{"code":212,"score":83,"supported":14,"title":213,"abstract":214,"tags":217},"A2",[],[215,216],"小麦","wheat",[],{"code":219,"score":83,"supported":14,"title":220,"abstract":221,"tags":224},"A3",[],[222,223],"玉米","maize",[],{"code":226,"score":83,"supported":14,"title":227,"abstract":228,"tags":231},"A6",[],[229,230],"棉花","cotton",[],{"code":72,"score":233,"supported":14,"title":234,"abstract":235,"tags":237},4,[],[236],"smart agriculture",[27],{"code":239,"score":50,"supported":14,"title":240,"abstract":241,"tags":243},"H6",[],[242],"农业生态",[],[245,246],"阿富汗 气候变化","气候智慧型农业 灌溉","阿富汗气候变化-5312",{"doi":8,"openalex_id":249,"authors":250,"venue":168,"cited_by_count":146,"oa_url":165,"card":257,"direction":263,"ingested_from":160},"W7222907396",[251,253,255],{"name":252,"orcid":8},"Mohammad Shafiq Faieq",{"name":254,"orcid":8},"Mustafa Abid",{"name":256,"orcid":8},"Abdul khalil Afghani",{"tldr":258,"method":259,"finding":260,"direction":261,"opportunity":262},"系统综述气候变化对阿富汗农业的影响、挑战与适应策略。","按PRISMA检索2000-2025年文献，整合阿富汗及周边四国区域证据。","水资源短缺与干旱致主要作物减产12%-25%，气候智慧型农业与节水灌溉最有效。","农业绿色发展与碳","可研究气候智慧型农业措施在阿富汗及周边干旱区的本地化适配与推广机制。","智慧农业 \u002F 农业物联网","2026-10-19T23:30:11.285828Z",{"id":266,"title":267,"url":268,"summary":269,"summary_zh":270,"content":8,"source_name":271,"source_url":268,"published_at":272,"category":93,"cover_url":8,"hotness":13,"is_selected":36,"score":273,"score_detail":274,"sources":277,"tags":279,"primary_topic":283,"secondary_topics":288,"classification":294,"search_phrases":318,"slug":321,"view_count":22,"doi":322,"paper":323,"created_at":336},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":98,"substance":18,"depth":19,"authority":275,"freshness":118,"relevant":22,"comment":276},13,"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。",[278],{"name":271,"url":268},[27,280,28,281,282],"农业供应链","精准农业","地缘政治",{"code":62,"slug":284,"name":285,"path":286,"parent_code":287},"yield-food-security","单产提升与粮食安全","\u002Ftopic\u002Ffield-crops\u002Fyield-food-security","A",[289,290],{"code":180,"slug":181,"name":182,"path":183,"parent_code":184},{"code":124,"slug":291,"name":292,"path":293,"parent_code":111},"agricultural-iot","物联网传感与边缘计算","\u002Ftopic\u002Fdigital-agriculture\u002Fagricultural-iot",{"status":114,"locked":36,"version":37,"method":38,"evidence":295},{"candidates":296,"agricultural_evidence":14},[297,301,307,311],{"code":62,"score":20,"supported":14,"title":298,"abstract":299,"tags":300},[209],[28,209],[28],{"code":72,"score":302,"supported":14,"title":303,"abstract":304,"tags":306},11,[],[27,281,305],"precision agriculture",[27,281],{"code":180,"score":118,"supported":14,"title":308,"abstract":309,"tags":310},[],[176,197,195],[],{"code":124,"score":118,"supported":14,"title":312,"abstract":313,"tags":317},[],[314,315,316],"物联网","internet of things","IoT",[],[319,320],"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":322,"openalex_id":324,"authors":325,"venue":271,"cited_by_count":146,"oa_url":268,"card":331,"direction":263,"ingested_from":160},"W7222902031",[326,328],{"name":327,"orcid":8},"Parameswaran Mahendran",{"name":329,"orcid":330},"Wong Sing Yun","https:\u002F\u002Forcid.org\u002F0000-0001-5776-8852",{"tldr":332,"method":333,"finding":334,"direction":263,"opportunity":335},"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。","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":338,"title":339,"url":340,"summary":341,"summary_zh":342,"content":8,"source_name":343,"source_url":344,"published_at":345,"category":93,"cover_url":8,"hotness":13,"is_selected":36,"score":346,"score_detail":347,"sources":351,"tags":353,"primary_topic":356,"secondary_topics":357,"classification":358,"search_phrases":391,"slug":394,"view_count":50,"doi":395,"paper":396,"created_at":407},5085,"AgriSense: IoT-Driven Precision Agriculture for National Food Sustainability and Development","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.23335305","Precision agriculture integrates digital technologies to improve agricultural resource management, productivity, and sustainability, while the Internet of Things (IoT) enables real-time monitoring of soil and environmental conditions through connected sensors. In Nigeria, inefficient water and fertilizer use, declining soil health, climate variability, and limited access to timely agricultural information constrain sustainable food production. This study presents AgriSense, an IoT-driven precision agriculture platform designed to support data-informed farm management under Nigerian agricultural conditions. The study adopts a mixed-method research framework incorporating descriptive, experimental, and analytical approaches, with proposed data sources including IoT sensor measurements, farmer surveys and interviews, field observations, and relevant weather information. The AgriSense platform integrates soil-moisture, nitrogen-phosphorus-potassium (N-P-K), soil-pH, temperature, and humidity monitoring with farm and field management, sensor-status tracking, automated alerts, agronomic recommendations, and reporting functions. The demonstrated interface represents agricultural fields and crops across Asaba Demonstration Farm, Jos Highland Farm, and Sokoto Smart Farm. Its threshold-based alerts identify conditions associated with low soil moisture, low nitrogen, acidic soil, high temperature, and sensor connectivity faults, linking selected conditions to recommended management actions. The available demonstration establishes the platform’s integrated monitoring and decision-support functionality. However, because the interface identifies its environment as a live simulation, the displayed information does not independently establish improvements in crop yield, input-use efficiency, soil health, or farmer income. The study provides a technological foundation for subsequent field validation of IoT-enabled precision agriculture and its potential contribution to sustainable food security in Nigeria.","精准农业（precision agriculture）融合数字技术，以改善农业资源管理、生产力和可持续性，而物联网（Internet of Things, IoT）则通过互联传感器实现对土壤和环境条件的实时监测。在尼日利亚，水资源和肥料利用效率低下、土壤健康状况下降、气候多变以及难以及时获取农业信息等因素制约了可持续粮食生产。本研究提出AgriSense——一个由物联网驱动的精准农业平台，旨在支持尼日利亚农业条件下的数据驱动型农场管理。本研究采用混合方法研究框架，融合描述性、实验性和分析性方法，拟采用的数据来源包括物联网传感器测量数据、农民问卷调查与访谈、田间观察以及相关天气信息。AgriSense平台将土壤湿度、氮磷钾（N-P-K）、土壤pH值、温度和湿度监测与农场及田块管理、传感器状态追踪、自动警报、农艺建议和报告功能集成在一起。所展示的界面呈现了阿萨巴示范农场（Asaba Demonstration Farm）、乔斯高原农场（Jos Highland Farm）和索科托智慧农场（Sokoto Smart Farm）的农田和作物。其基于阈值的警报可识别与土壤湿度低、氮含量低、土壤酸性、高温和传感器连接故障相关的情况，并将选定情况与建议的管理措施相关联。现有演示验证了该平台的集成监测与决策支持功能。然而，由于该界面将其环境标识为实时模拟，所显示的信息并不能独立证明作物产量、投入品使用效率、土壤健康或农民收入方面的改善。本研究为后续对物联网赋能精准农业及其对尼日利亚可持续粮食安全潜在贡献的田间验证提供了技术基础。","Tech-Sphere Journal for Pure and Applied Sciences","https:\u002F\u002Fstem.techspherejournals.com\u002Findex.php\u002Ftsjpas\u002Farticle\u002Fview\u002F80","2026-10-13T00:00:00Z",56,{"impact":348,"substance":43,"depth":349,"authority":118,"freshness":118,"relevant":22,"comment":350},8,14,"论文提出面向尼日利亚的IoT精准农业平台AgriSense，集成土壤水分、N-P-K、pH等监测与阈值预警，但界面为模拟环境，尚未验证增产增效，属技术原型阶段，参考价值有限。",[352],{"name":343,"url":344},[27,354,28,281,355],"农业物联网","土壤墒情监测",{"code":124,"slug":291,"name":292,"path":293,"parent_code":111},[],{"status":114,"locked":36,"version":37,"method":38,"evidence":359},{"candidates":360,"agricultural_evidence":14},[361,365,369,373,380,387],{"code":124,"score":98,"supported":14,"title":362,"abstract":363,"tags":364},[316],[314,315,316],[354],{"code":72,"score":43,"supported":14,"title":366,"abstract":367,"tags":368},[305],[281,305],[27,281],{"code":62,"score":206,"supported":14,"title":370,"abstract":371,"tags":372},[],[28,209],[28],{"code":374,"score":83,"supported":14,"title":375,"abstract":376,"tags":379},"F3",[],[377,378],"肥料","fertilizer",[],{"code":381,"score":83,"supported":14,"title":382,"abstract":383,"tags":386},"H2",[],[384,385],"土壤","soil",[],{"code":49,"score":50,"supported":14,"title":388,"abstract":389,"tags":390},[],[53],[],[392,393],"AgriSense 物联网 精准农业","尼日利亚 智慧农业 平台","AgriSense物联网精准农业-5085","10.5281\u002Fzenodo.23335305",{"doi":395,"openalex_id":397,"authors":398,"venue":343,"cited_by_count":146,"oa_url":344,"card":402,"direction":263,"ingested_from":160},"W7221676154",[399],{"name":400,"orcid":401},"Innocent Uzougbo Onwuegbuzie","https:\u002F\u002Forcid.org\u002F0000-0002-1582-1739",{"tldr":403,"method":404,"finding":405,"direction":263,"opportunity":406},"提出AgriSense物联网精准农业平台，用于尼日利亚农田监测与决策支持。","混合方法框架，集成土壤水分、N-P-K、pH、温湿度传感器与阈值告警。","平台实现监测与决策支持功能，但界面为模拟，尚未验证产量与效益提升。","可开展真实田间验证，量化IoT精准农业对产量、投入效率和土壤健康的影响。","2026-10-16T23:30:14.088827Z",{"id":409,"title":410,"url":411,"summary":412,"summary_zh":8,"content":413,"source_name":414,"source_url":8,"published_at":345,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":415,"score_detail":416,"sources":420,"tags":422,"primary_topic":426,"secondary_topics":431,"classification":432,"search_phrases":453,"slug":456,"view_count":457,"doi":8,"paper":8,"created_at":458},4952,"我国杂交水稻再获重要突破 '一系法'制种技术阶段性突破","http:\u002F\u002Fwww.nmgsjw.cn\u002Fkx\u002F202610\u002Ft20261013_42892.html","10月11日,杂交水稻无融合生殖('一系法'杂交水稻)现场观摩评议会在湖南生物育种基地举行。崖州湾实验室牵头,协同中国农业科学院作物科学研究所、中国水稻研究所、湖南省农业科学院、安徽省农业科学院、袁隆平农业高科技股份有限公司和安徽荃银高科种业股份有限公司等优势团队开展联合攻关。中国科学院院士钱前介绍,团队首次将蒲公英孤雌生殖基因ToPAR引入水稻,在部分水稻材料中实现同一株系克隆率达100%、结实率达93.54%。","“一系法”杂交水稻制种技术攻关取得阶段性重要突破。10月11日，杂交水稻无融合生殖（“一系法”杂交水稻）现场观摩评议会在湖南生物育种基地举行。记者从会上获悉，随着“一系法”杂交水稻多品种、多生态区验证和配套技术研究的持续推进，人工无融合生殖有望为水稻优良杂交组合的连续繁殖提供新的技术路径，降低杂交水稻种子生产成本与风险，为保障粮食安全和推动种业创新提供重要支撑。\n\n![Image 1](http:\u002F\u002Fpic1.nmgnews.com.cn\u002F003\u002F011\u002F304\u002F00301130409_236751ec.png)\n\n从三系法到两系法，我国杂交水稻品种不断迭代升级，为保障国家粮食安全作出了重大贡献。但传统杂交水稻制种存在制种工作较繁琐，制种投入大、风险较高的问题，在一定程度上制约了优良杂交水稻组合在更大范围内的推广。如何固定水稻的杂种优势，使优良杂交品种能通过种子实现连续繁殖，是杂交水稻育种家长期追求的重大科学目标。\n\n1987年，中国工程院院士袁隆平提出了杂交稻由“三系法”向“两系法”，最终向“一系法”发展的伟大战略构想。“一系法”的核心便是固定杂种优势，使优良杂交种能通过自身种子连续繁殖，实现“一次杂交、代代可用”。人工无融合生殖是一种通过重新设计植物生殖过程，使杂交种产生与自身遗传组成基本一致的克隆种子，为实现这一战略目标提供了新的技术路径。一旦能实现稳定产业化应用，该方法有望从根本上简化杂交稻种子生产体系，降低制种成本和风险，推动杂交稻向固定和连续繁殖优良杂合基因型转变。\n\n![Image 2](http:\u002F\u002Fpic1.nmgnews.com.cn\u002F003\u002F011\u002F304\u002F00301130410_12de709f.png)\n\n据此，崖州湾实验室牵头，协同中国农业科学院作物科学研究所、中国水稻研究所、湖南省农业科学院、安徽省农业科学院、袁隆平农业高科技股份有限公司和安徽荃银高科种业股份有限公司等优势团队，针对水稻克隆效率、结实能力、遗传背景适用性和田间稳定性等关键问题启动联合攻关。团队将生殖调控研究、材料创制、多代繁殖和田间评价相衔接，在“一系法”杂交水稻制种技术这一颠覆性原始创新攻关中取得了从高效克隆到多品种、多生态区应用验证的系列进展。\n\n中国科学院院士钱前介绍，团队首次将蒲公英孤雌生殖基因ToPAR引入水稻，与减数分裂改造技术相结合，在部分水稻材料中实现了同一株系克隆率达100%、结实率达93.54%，兼顾了水稻的高效克隆与正常结实能力。在此基础上，团队以嘉丰优3号为背景创制的L3材料完成了连续五代跟踪验证，为优良杂交组合遗传组成的跨世代传递提供了重要依据。\n\n为检验该技术的适用范围，团队对中国、南亚和东南亚具有代表性的20个杂交稻组合开展了验证，涵盖三系籼型、三系籼粳型和两系籼型，均获得了相应的无融合生殖材料，其中18个组合的克隆率超过90%。\n\n今年，团队进一步在北京、合肥、长沙、杭州和三亚等地生物育种专区布局了全国多生态区正季田间试验，在覆盖从北方稻区、长江中下游稻区到华南热带稻区的不同生态环境下，团队布局无融合生殖材料，考察不同纬度、光温条件和稻作生态环境下的材料表现，推动技术评价从单一材料向多遗传背景、多生态区拓展。\n\n结果表明，人工无融合生殖正在从“单个材料能够实现克隆繁殖”，向“不同优良组合能够转化、不同生态区能够验证”的方向推进。未来有望将经过多年生产验证的成熟杂交品种直接转化为能连续繁殖的“一系法”材料，显著缩短技术进入产业的周期，提高成熟杂交品种向“一系法”升级的效率。\n\n此次观摩会现场，团队示范设置了单本、二本、三本等栽插方式，将分子育种与栽培调控相结合，探索改善群体稳定性的配套措施。在所展示的栽培条件下，相关材料表现出了良好的群体长势和农艺性状。\n\n崖州湾实验室主任、中国科学院院士李家洋称，固定杂种优势是杂交水稻育种的重要研究方向，当前研究进展展现出了其良好的应用潜力。但与此同时，阶段性成果距离真正大规模生产应用还有诸多现实难题亟待攻克。环境对无融合生殖性状的影响、不同遗传背景下表现的稳定性、长期多代繁育的可靠性、配套栽培技术体系等问题还需持续系统研究。他建议下一步持续深化基础机理研究，进一步做实多生态、多代跟踪验证，力争形成一套稳定、可重复、适合生产应用的技术体系。","内蒙古科协 2026 年 10 月 13 日",91,{"impact":417,"substance":418,"depth":98,"authority":349,"freshness":348,"relevant":22,"comment":419},28,23,"袁隆平战略构想下的颠覆性育种突破，多生态区验证与院士背书信息扎实，值得进入每日精选。",[421],{"name":414,"url":411},[423,28,29,424,425],"种业振兴","杂交水稻","无融合生殖",{"code":427,"slug":428,"name":429,"path":430,"parent_code":287},"A1","rice","水稻","\u002Ftopic\u002Ffield-crops\u002Frice",[],{"status":114,"locked":36,"version":37,"method":38,"evidence":433},{"candidates":434,"agricultural_evidence":14},[435,439,445,449],{"code":427,"score":96,"supported":14,"title":436,"abstract":437,"tags":438},[429],[429],[424],{"code":440,"score":233,"supported":14,"title":441,"abstract":442,"tags":444},"F1",[],[443],"种业",[423],{"code":67,"score":233,"supported":14,"title":446,"abstract":447,"tags":448},[],[29],[29],{"code":62,"score":22,"supported":36,"title":450,"abstract":451,"tags":452},[],[],[28],[454,455],"一系法 杂交水稻 无融合生殖","崖州湾实验室 水稻 克隆种子","一系法杂交水稻无融合生殖-4952",2,"2026-10-15T00:06:02.966709Z",{"id":460,"title":461,"url":462,"summary":463,"summary_zh":8,"content":464,"source_name":465,"source_url":8,"published_at":466,"category":12,"cover_url":8,"hotness":13,"is_selected":36,"score":170,"score_detail":467,"sources":470,"tags":472,"primary_topic":477,"secondary_topics":482,"classification":483,"search_phrases":520,"slug":523,"view_count":146,"doi":8,"paper":8,"created_at":524},4942,"江苏省农科院打造农业高新技术群 双链融合跑出加速度","http:\u002F\u002Fwww.macrochina.com.cn\u002Fnews_speed\u002Fhgjj\u002F20260807125282.shtml","基因快速甄别与编辑、田间多功能机器人、果蔬无害保鲜、低升糖糯玉米、高瘦肉湖羊等新技术新产品,在江苏省农科院成批涌现。江苏省农科院种质资源与生物技术研究所所长赵涵介绍,生物育种过去主要靠眼睛看、秤称和尺子量,现在利用AI+无人机+基因测序,一次精准鉴定上百份样本。新一代低GI南粳大米正加速从实验室走向餐桌。今年新投用的江苏农业种质资源综合基因库,能保存55万份种质资源,满足江苏未来30年的农业科技创新需求。","基因快速甄别与编辑、田间多功能机器人、果蔬无害保鲜、低升糖糯玉米、高瘦肉湖羊……这些科技感十足又与餐桌紧密相连的新技术新产品，正在江苏省农业科学院成批涌现。 \n通过引入生物育种、大数据应用、全自动生产等前沿技术，江苏省农科院加速打造农业前沿技术集群，同时加快技术成果从“展示品”到“大田标配”转化。\n\n基因层级研发链条初步成形\n\n“现在做生物育种试验，利用基因测序图信息，结合大数据分析，能够更快发现那些有重要价值的基因。”江苏省农科院种质资源与生物技术研究所所长赵涵表示。\n\n赵涵所说的基因测序、表型分析和基因编辑等工作，正在省农科院基因库、粮食作物研究所、畜牧研究所等科研机构广泛开展。\n\n畜牧研究所副所长王慧利介绍，湖羊是太湖流域特有的地方绵羊品种，具有繁殖力强、肉质鲜美等优良特性，现已成为我国肉羊产业的当家母本，但肉用性能有待进一步提升。团队靶向抑制肌肉生长的关键基因MSTN，通过精准基因编辑技术进行定向敲除，大幅提升了肉用性能。相关技术已辐射新疆、甘肃、青海等西部肉羊产区。\n\n畜牧研究所针对部分人群牛奶不耐受的问题，聚焦主要致敏原β-乳球蛋白，通过单碱基编辑技术，创制可生产低致敏牛奶的奶牛新种质。“十四五”以来，畜牧研究所承担国家生物育种重大专项及国家重点研发计划等课题，取得系列突破。\n\n赵涵介绍，生物育种过去主要靠眼睛看、秤称和尺子量，每次只能界定少量种子样本，找到关键基因像大海捞针。现在利用AI+无人机+基因测序，一次精准鉴定上百份样本，筛查效率大大提升。\n\n“这些年江苏南粳大米热销全国，但是初代南粳从1999年引进并改良，直至2008年才试验成功。随着基因技术进步，现在培育新品种已压缩到3年。”江苏省农科院副院长李爱宏说，新一代低GI南粳大米正加速从实验室走向餐桌。\n\n基因库又称“种子银行”。记者现场看到，江苏省农科院今年新投用的江苏农业种质资源综合基因库，除了庞大的种子低温保藏库外，还配备了立体无人仓储系统，以及基因测序与编辑、功能验证、靶点筛选等十几个实验室。这里能保存55万份种质资源，满足江苏未来30年的农业科技创新需求。\n\n赵涵表示，随着工业化、城镇化推进，以及气候环境变化，一些野生动植物资源和传统老品种正在以惊人速度消失。“我们近6年行程16.8万公里，成功收集了大批散落民间的珍贵种质资源，如黄金小玉米、溧阳白芹等地方特色、珍稀、濒危资源3446份。现在每年免费向社会提供上千份种质资源。”\n\n双链融合跑出加速度\n\n既不扯断藤蔓，也不碰伤果实，搭载了“智能眼睛”与“数字大脑”的双臂番茄采摘机器人，不仅能精准判断番茄的成熟度，还能快速完成采摘作业。这是记者在江苏省农科院番茄示范基地所见。\n\n江苏省农科院农业信息研究所所长任妮介绍，信息所历经6年开发出3代农业机器人，在搬运、巡检、采摘等领域均有突破。农业生产场景远比工厂复杂，主要表现在土地不平、农作物标准不一、果实成熟度不同等多方面。信息所通过构建高质量数据集，已积累番茄全生长季近50种数据指标、40多亿组数据量。目前，采摘一个番茄从最初的15秒降到9秒，机器人成本从60万元降至20万元以下。2025年，信息所获得全国遥感高分领域竞赛第一名，采摘机器人获得雄安智慧农业大赛二等奖。\n\n今年初，农业农村部正式批准建设智能采收机器人重点实验室。该实验室由集萃智能公司联合江苏省农科院等共同打造，未来多种农业机器人将迎来大面积产业化应用。\n\n“我国生鲜农产品在流通过程中的损耗率一直高达25%-30%，而发达国家普遍小于5%。”江苏省农科院农业设施与装备研究所副所长李鹏霞介绍，蔬菜瓜果夏季采摘后若不能及时预冷，很容易氧化腐烂。团队经过攻关，已经实现果蔬保鲜期从5天延长至15天以上。\n\n如今，装备所的新技术推广到江苏、上海、广西等地21个市县，近5年累计保鲜蔬菜6万多吨，平均减少蔬菜产后损耗12%以上。新技术累计增加销售额75.4亿元，累计新增利润22.5亿元。\n\n近期，李鹏霞领衔的冷链流通技术成功通过美国加州大学戴维斯分校（UC Davis）采后研究与推广中心评估，正式上线其全球权威的Product Fact Sheets平台。这一重要突破标志李鹏霞团队的生鲜农产品采后技术打破了国外长期主导的格局。\n\n锻造科技服务队伍助农增收\n\n在江苏广袤的田野，江苏省农科院通过构建“亚夫科技服务体系”，长期培养科技服务队伍，将先进的农业科技成果精准送达田间地头，被农民亲切称为致富好帮手。\n\n江苏省农科院成果转化处处长顾军介绍，亚夫工作站核心职能是遴选科技特派员下乡服务，要求每年至少180天到田间地头服务农民。这种机制有效提升了农业科技转化率。\n\n在涟水高沟镇，李春宏研究员在当地常年无法种植农作物的盐碱地一待就是6年，通过引进国内优质高粱品种，高沟镇一带高粱种植面积从2020年的1000亩，扩大到如今的5万余亩，亩均增效300多元。\n\n宿豫新庄工作站站长于红梅引入草莓脱毒种苗和水旱轮作技术，帮助当地草莓产业从零发展到5000亩，亩均净利润超8000元。沛县鹿楼工作站站长赵伟引进全舍饲生态高效种鸭养殖新模式，减排污水95%以上。\n\n在丰县大沙河畔，科技特派员朱伟指导农户种植“徐稻9号”，将昔日的荒滩地变成了亩产超1200斤的高产稻田。在盱眙，张家宏研究员通过筛选“高富帅”水稻品种和研发专用缓释肥，解决了稻虾共生中的技术难题。示范户袁洪江稻前虾亩产突破300斤，每亩纯利润达7500元。\n\n截至目前，江苏省农科院已先后选派科技特派员140名，在全省建设亚夫工作站92个，体系累计服务超19.1万人次，示范推广新品种、新技术、新模式、新装备，辐射推广面积近8500万亩。\n\n“未来我们将持续优化科研布局，分层培育各类人才，紧扣江苏农业产业链痛点攻关，聚力攻坚生物育种、智慧农业、绿色农业等现代农业前沿领域，建设高水平农业科研院所。”江苏省农科院党委书记王克华表示。（邓华宁 经济参考报）\n\n中宏网责任编辑：文懿铎","中宏网 2026 年 8 月 7 日(10 月 15 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