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2](https:\u002F\u002Fwww.htb.gov.cn\u002Fu\u002Fcms\u002Fhtbxrmzf\u002F202609\u002F02185835uxvu.jpg)\n\n种养百花齐放解锁，多元增收路径。单一种养已成过往，多元富民产业遍地开花。五年来，呼图壁县依托本土资源优势，摒弃粗放零散的养殖模式，推动畜牧、特色种养产业规模化、标准化发展，闯出一条适配乡村、惠及百姓的共富新路。全县稳定8万亩优质饲草种植基地，培育3家专业化草产品加工主体，为畜牧产业高质量发展筑牢源头根基。\n\n![Image 3](https:\u002F\u002Fwww.htb.gov.cn\u002Fu\u002Fcms\u002Fhtbxrmzf\u002F202609\u002F02185904ct0t.png)\n\n奶业成为县域特色标杆产业，呼图壁县成功创建州级奶业现代农业产业园，依托 西域春乳业 等龙头企业，打造规模化优质奶业产业带。锦华盛业、润泰达万头规模化牛场顺利投产，9个千头奶牛养殖场、1个500头奶牛养殖合作社有序运营，全县奶牛存栏4.7万头，年产鲜奶超19万吨，稳稳扛起自治区奶业核心区招牌。\n\n![Image 4](https:\u002F\u002Fwww.htb.gov.cn\u002Fu\u002Fcms\u002Fhtbxrmzf\u002F202609\u002F02185921otfg.png)\n\n肉牛羊产业提质扩容势头强劲，五工台肉牛肉羊产业园加速成型，汇成肉牛项目正式运营，标准化养殖小区遍布乡镇。五年累计引进优质种畜、完成数十万头只畜禽品种改良，畜禽良种品质大幅升级。目前全县牛羊存栏45万头只，肉产品总产量突破4.7万吨，猪禽产业平稳发展，畜禽养殖已然成为乡村支柱富民产业。\n\n特色种养持续出圈出彩，成为乡村增收新势力。全县3500峰骆驼稳步养殖，驼奶产业化发展有序推进。水产养殖更是实现全州突破性飞跃，成功攻克盐碱地海水养殖技术，填补昌吉州技术空白。7500亩养殖水面活力满满，南美白对虾、中华绒螯蟹、鸭嘴鱼 等高端水产成功扎根盐碱地，年产量超4000吨，让盐碱滩变身致富田。\n\n![Image 5](https:\u002F\u002Fwww.htb.gov.cn\u002Fu\u002Fcms\u002Fhtbxrmzf\u002F202609\u002F02190006htwh.jpg)\n\n农机智慧迭代，解锁全新农耕模式。种地不靠力气丰收全靠科技。这五年，呼图壁县农耕模式发生颠覆性变革，彻底告别“面朝黄土背朝天”的传统劳作，智慧农机、数字农业走进田间地头，新农人轻松实现“坐着机器种地、盯着屏幕管护”。\n\n![Image 6](https:\u002F\u002Fwww.htb.gov.cn\u002Fu\u002Fcms\u002Fhtbxrmzf\u002F202609\u002F0219003260a3.jpg)\n\n呼图壁县持续加码农机惠农政策，五年累计兑付农机购置补贴9673.32万元，助力农户添置4044台套现代化智能农机设备。如今的田野上，自动导航拖拉机精准耕作、无人机凌空植保、智能采棉机 高效采收、番茄采收机快速作业，粮棉种植、管护、采收全流程实现机械化、智能化覆盖。\n\n目前，全县农机总动力达52万千瓦，拥有拖拉机8658台、配套农机具3.6万台套、农用无人机330余架，农业综合机械化率高达98.6%，较全国平均水平高出20个百分点，稳居全疆第一梯队。科技赋能让农耕效率翻倍、成本减半，为现代农业高质量发展插上腾飞翅膀。\n\n![Image 7](https:\u002F\u002Fwww.htb.gov.cn\u002Fu\u002Fcms\u002Fhtbxrmzf\u002F202609\u002F02190059f4dj.png)\n\n农品延链增值，本土好物出圈走红。从田间原生食材到市场爆款好物，农产品完成华丽蜕变。五年来，呼图壁县不再局限于种养产出，全力推进农产品精深加工、品牌塑造，拉长产业链、提升附加值，让本土优质农货走出乡村、热销全疆。\n\n![Image 8](https:\u002F\u002Fwww.htb.gov.cn\u002Fu\u002Fcms\u002Fhtbxrmzf\u002F202609\u002F0219012465sv.jpg)\n\n龙头企业扛起产业升级大旗，中粮八一面粉30万吨生产线顺利投产，西域春乳业、豆宝科技、云龙棉业等本土企业稳步壮大、提质增效。番茄产业摆脱单一原料销售模式，迭代推出番茄沙司、番茄粉、番茄红素等高附加值产品；豆宝食品多款产品成功入选品味新疆优质榜单，本土农产品品牌影响力持续攀升。全县县级以上农业产业化龙头企业达35家，农产品加工业产值从2021年108亿元增长至2025年138亿元，年均增长7%，产业增值成效十分亮眼。\n\n![Image 9](https:\u002F\u002Fwww.htb.gov.cn\u002Fu\u002Fcms\u002Fhtbxrmzf\u002F202609\u002F02190143zizw.png)\n\n特色新业态蓬勃兴起，点亮乡村经济版图。苗木花卉产业领跑全州，本土企业拿下全疆首个苗木出口全流程资质，斩获千万元出口订单，年销售额突破3亿元。新疆农科院育种示范中心落地投用、二十里店村鲜切花温室大棚投产运营，科创赋能现代农业提质升级。1.7万亩特色林果稳产丰产，年产量超6000吨，多元融合的乡村产业体系愈发成熟。\n\n![Image 10](https:\u002F\u002Fwww.htb.gov.cn\u002Fu\u002Fcms\u002Fhtbxrmzf\u002F202609\u002F02190200cb46.jpg)\n\n乡村颜值焕新，绘就宜居幸福画卷。产业旺带动乡村美环境优托起百姓福。五年来，呼图壁县持续推进城乡融合发展，大手笔完善乡村基建、精细化整治人居环境、全方位壮大集体经济，让乡村既有绿水青山的生态颜值，更有安居乐业的民生温度。\n\n乡村基础设施实现提档升级，全县累计投入11.6亿元实施98个乡村振兴重点项目，新改建农村道路344.6公里，新建高标准农田19.99万亩，11个行政村生活污水接入城市管网。县域农村公路通车总里程达1428公里，S101、南山伴行公路顺利通车，“六横五纵”路网骨架全面成型，村民出行便捷通畅。\n\n![Image 11](https:\u002F\u002Fwww.htb.gov.cn\u002Fu\u002Fcms\u002Fhtbxrmzf\u002F202609\u002F02190232p240.jpg)\n\n水利保障能力持续夯实，累计投入18.21亿元建成23个重点水利项目，新增调蓄能力2500万立方米，农业灌溉水有效利用系数提升至0.65，为农田丰产丰收保驾护航。农村人居环境持续优化，卫生厕所普及率提升至66.63%，7个村获评自治区级美丽宜居村。如今的乡村，生活垃圾百分百规范处置，5G网络、快递物流、电力保障全域覆盖，村容整洁、乡风文明。2025年全县村集体经济总收入达1.2亿元，39个村集体收入破百万，二十里店村获评国家乡村治理示范村，群众的幸福感、获得感实实在在。\n\n![Image 12](https:\u002F\u002Fwww.htb.gov.cn\u002Fu\u002Fcms\u002Fhtbxrmzf\u002F202609\u002F02190249g531.png)\n\n改革活水赋能，激活乡村内生动能。改革破难题活水润乡土。五年来，呼图壁县以农村综合改革为抓手，持续盘活土地、资产、资金等沉睡资源，破除乡村发展壁垒，让闲置资源变资产、集体资产变收益、村民群众变股东。\n\n全县54个村（社区）全面完成集体产权制度改革，落地74个经营类资产项目，股权证发放率全覆盖，实现户户持股、人人受益。同时，持续规范农村集体三资管理，圆满化解2.16亿元集体债务，彻底卸下村级发展历史包袱，让乡村发展轻装上阵。依托农村产权交易平台，全县累计完成16.27万亩土地交易，零散闲置土地得到整合利用，有效激活了乡村发展内生动力。\n\n![Image 13](https:\u002F\u002Fwww.htb.gov.cn\u002Fu\u002Fcms\u002Fhtbxrmzf\u002F202609\u002F02190319li1z.png)\n\n风好正是扬帆时策马扬鞭再奋蹄。如今的呼图壁县，田野生机勃勃、产业势头强劲、乡村宜居宜业、群众安居乐业。未来，我县将持续深耕三农沃土、精进产业发展、雕琢乡村风貌、深化改革创新，奋力书写农业强农村美农民富的新时代乡村振兴崭新篇章。","呼图壁县人民政府","2026-09-02T00:00:00Z","报道",70,{"impact":18,"substance":99,"depth":19,"authority":12,"freshness":100,"relevant":21,"comment":101},20,8,"县域农业五年成效综述，数据详实，涵盖粮棉、畜牧、农机等，具参考价值。",[103],{"name":94,"url":91},[26,27,28,105,106,107],"奶业","十四五","棉花机械化",{"code":109,"slug":110,"name":111,"path":112,"parent_code":113},"A6","cash-crops","棉麻糖与特色经作","\u002Ftopic\u002Ffield-crops\u002Fcash-crops","A",[115],{"code":116,"slug":117,"name":118,"path":119,"parent_code":120},"F5","machinery","农机装备与机械化","\u002Ftopic\u002Finputs-equipment\u002Fmachinery","F",{"status":122,"locked":34,"version":35,"method":36,"evidence":123},"classified",{"candidates":124,"agricultural_evidence":13},[125,131,136,142,148,154,158,163,167],{"code":109,"score":126,"supported":13,"title":127,"abstract":129,"tags":130},11,[128],"棉花",[128],[],{"code":116,"score":126,"supported":13,"title":132,"abstract":134,"tags":135},[133],"机械化",[133],[],{"code":137,"score":62,"supported":13,"title":138,"abstract":139,"tags":141},"A2",[],[140],"小麦",[],{"code":143,"score":62,"supported":13,"title":144,"abstract":145,"tags":147},"A3",[],[146],"玉米",[],{"code":149,"score":62,"supported":13,"title":150,"abstract":151,"tags":153},"B1",[],[152],"番茄",[],{"code":40,"score":21,"supported":34,"title":155,"abstract":156,"tags":157},[],[],[28],{"code":159,"score":21,"supported":34,"title":160,"abstract":161,"tags":162},"C2",[],[],[105],{"code":46,"score":21,"supported":34,"title":164,"abstract":165,"tags":166},[],[],[27],{"code":56,"score":21,"supported":34,"title":168,"abstract":169,"tags":170},[],[],[26],[172,173],"棉花机械化 乡村振兴 智慧农业 粮食安全","棉花机械化 乡村振兴","棉花机械化乡村振兴智慧农业粮食安全-1468",2,"2026-09-03T00:06:40.612010Z",{"id":178,"title":179,"url":180,"summary":181,"summary_zh":182,"content":8,"source_name":183,"source_url":180,"published_at":184,"category":185,"cover_url":8,"hotness":12,"is_selected":34,"score":186,"score_detail":187,"sources":191,"tags":193,"primary_topic":197,"secondary_topics":203,"classification":204,"search_phrases":230,"slug":233,"view_count":234,"doi":235,"paper":236,"created_at":249},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":188,"substance":189,"depth":18,"authority":188,"freshness":12,"relevant":21,"comment":190},12,22,"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。",[192],{"name":183,"url":180},[26,194,28,195,196],"农业人工智能","遥感","气候分析",{"code":198,"slug":199,"name":200,"path":201,"parent_code":202},"I2","agricultural-ai","农业AI与大模型","\u002Ftopic\u002Fdigital-agriculture\u002Fagricultural-ai","I",[],{"status":122,"locked":34,"version":35,"method":36,"evidence":205},{"candidates":206,"agricultural_evidence":13},[207,212,217,221,225],{"code":198,"score":20,"supported":13,"title":208,"abstract":210,"tags":211},[209],"artificial intelligence",[],[194],{"code":68,"score":62,"supported":13,"title":213,"abstract":214,"tags":216},[],[215],"农业传感",[],{"code":40,"score":21,"supported":34,"title":218,"abstract":219,"tags":220},[],[],[28],{"code":56,"score":21,"supported":34,"title":222,"abstract":223,"tags":224},[],[],[26],{"code":226,"score":21,"supported":34,"title":227,"abstract":228,"tags":229},"I3",[],[],[195],[231,232],"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":235,"openalex_id":237,"authors":238,"venue":183,"cited_by_count":234,"oa_url":180,"card":241,"direction":247,"ingested_from":248},"W7223111766",[239],{"name":240,"orcid":8},"Fatima-Zahra El Khattabi",{"tldr":242,"method":243,"finding":244,"direction":245,"opportunity":246},"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":251,"title":252,"url":253,"summary":254,"summary_zh":8,"content":255,"source_name":256,"source_url":8,"published_at":184,"category":96,"cover_url":8,"hotness":12,"is_selected":34,"score":257,"score_detail":258,"sources":261,"tags":263,"primary_topic":267,"secondary_topics":271,"classification":272,"search_phrases":288,"slug":291,"view_count":234,"doi":8,"paper":8,"created_at":292},5501,"湖南部署常态化精准帮扶与秋粮收购攻坚战","https:\u002F\u002Fnews.qq.com\u002Frain\u002Fa\u002F20261021A0DV5F00","10月21日湖南省委副书记谢卫江在全省农业农村工作专题会议上要求，今年是推进常态化帮扶的第一年，要落实30个省级乡村振兴重点帮扶县常态化帮扶机制，坚决守牢不发生规模性返贫致贫底线；同时紧盯中晚稻集中上市，加快解决送粮排队、仓容不足、轮换不畅问题，以农民「种粮卖得出」为底线打好秋粮收购攻坚战。","湖南日报10月21日讯（全媒体记者 黄晗）21日，省委副书记谢卫江在长沙主持召开全省农业农村工作专题会议，深入学习贯彻习近平总书记关于“三农”工作的重要论述精神，落实省委工作要求，部署常态化帮扶、秋粮收购等工作。\n\n谢卫江指出，做好常态化帮扶和秋粮收购工作，事关不发生规模性返贫致贫、维护国家粮食安全“两条底线”。要深学细悟习近平总书记重要指示精神，深刻认识做好这两项工作的特殊重要性、任务艰巨性、时间紧迫性，把这两项工作摆在当前“三农”工作的突出位置抓紧抓好，以实际行动深刻领悟“两个确立”的决定性意义、坚决做到“两个维护”。\n\n谢卫江强调，今年是推进常态化帮扶的第一年。各级各部门要强化答卷意识，压紧压实责任，持续深化去年中央考核评估反馈问题、省级自查督查发现问题整改，严格对照今年中央考核方案做好自查整改，认真落实30个省级乡村振兴重点帮扶县常态化帮扶机制，坚决守牢不发生规模性返贫致贫底线。\n\n谢卫江强调，面对今年粮食收购复杂形势，当前要紧盯中晚稻集中上市，加快解决好送粮排队、仓容不足、轮换不畅等现实问题，坚决打好秋粮收购攻坚战。要处理好立足当前与着眼长远、市场收购与政府托市、促进流通与确保安全、部门工作与群众利益的关系，以农民“种粮卖得出”为底线，以“卖个好价钱”为目标，长短结合、统筹兼顾，坚决扛牢维护国家粮食安全的政治责任。\n\n谢卫江要求，四季度是全年工作冲刺收官的关键期。各级各部门要对账盘点，统筹抓好秋冬农业生产、农业品牌建设、农田水利和高标准农田建设、农业农村重点工作专项整治等工作，确保“十五五”开局之年圆满收官。","湖南日报 2026-10-21",75,{"impact":189,"substance":18,"depth":259,"authority":126,"freshness":20,"relevant":21,"comment":260},15,"省级专题会议部署防返贫与秋粮收购两条底线，政策信号明确、时效性强，但属常规工作部署，信息增量有限。",[262],{"name":256,"url":253},[27,28,264,265,266],"常态化帮扶","秋粮收购","防止返贫",{"code":61,"slug":268,"name":269,"path":270,"parent_code":46},"rural-integration","帮扶与城乡融合","\u002Ftopic\u002Frural-services\u002Frural-integration",[],{"status":122,"locked":34,"version":35,"method":36,"evidence":273},{"candidates":274,"agricultural_evidence":13},[275,280,284],{"code":61,"score":276,"supported":13,"title":277,"abstract":278,"tags":279},5,[],[264],[264,266],{"code":46,"score":41,"supported":13,"title":281,"abstract":282,"tags":283},[],[27],[27],{"code":40,"score":175,"supported":34,"title":285,"abstract":286,"tags":287},[],[],[265,28],[289,290],"湖南 秋粮收购","湖南 常态化帮扶","湖南秋粮收购-5501","2026-10-22T00:06:58.311020Z",{"id":294,"title":295,"url":296,"summary":297,"summary_zh":298,"content":8,"source_name":299,"source_url":296,"published_at":300,"category":185,"cover_url":8,"hotness":12,"is_selected":34,"score":301,"score_detail":302,"sources":305,"tags":307,"primary_topic":311,"secondary_topics":317,"classification":323,"search_phrases":371,"slug":374,"view_count":234,"doi":8,"paper":375,"created_at":391},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":18,"substance":99,"depth":303,"authority":188,"freshness":86,"relevant":21,"comment":304},17,"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。",[306],{"name":299,"url":296},[26,28,308,309,310],"气候变化","适应性策略","水资源短缺",{"code":312,"slug":313,"name":314,"path":315,"parent_code":316},"H7","climate","气候适应与防灾减灾","\u002Ftopic\u002Fenvironment\u002Fclimate","H",[318],{"code":319,"slug":320,"name":321,"path":322,"parent_code":316},"H3","irrigation","水资源与灌溉","\u002Ftopic\u002Fenvironment\u002Firrigation",{"status":122,"locked":34,"version":35,"method":36,"evidence":324},{"candidates":325,"agricultural_evidence":13},[326,333,339,345,350,355,360,365],{"code":312,"score":18,"supported":13,"title":327,"abstract":329,"tags":332},[328],"climate change",[308,330,328,331],"干旱","drought",[308],{"code":319,"score":20,"supported":13,"title":334,"abstract":335,"tags":338},[],[336,337,320],"灌溉","水资源",[],{"code":40,"score":340,"supported":13,"title":341,"abstract":342,"tags":344},7,[],[28,343],"food security",[28],{"code":137,"score":86,"supported":13,"title":346,"abstract":347,"tags":349},[],[140,348],"wheat",[],{"code":143,"score":86,"supported":13,"title":351,"abstract":352,"tags":354},[],[146,353],"maize",[],{"code":109,"score":86,"supported":13,"title":356,"abstract":357,"tags":359},[],[128,358],"cotton",[],{"code":56,"score":41,"supported":13,"title":361,"abstract":362,"tags":364},[],[363],"smart agriculture",[26],{"code":366,"score":62,"supported":13,"title":367,"abstract":368,"tags":370},"H6",[],[369],"农业生态",[],[372,373],"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":376,"authors":377,"venue":299,"cited_by_count":234,"oa_url":296,"card":384,"direction":390,"ingested_from":248},"W7222907396",[378,380,382],{"name":379,"orcid":8},"Mohammad Shafiq Faieq",{"name":381,"orcid":8},"Mustafa Abid",{"name":383,"orcid":8},"Abdul khalil Afghani",{"tldr":385,"method":386,"finding":387,"direction":388,"opportunity":389},"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":393,"title":394,"url":395,"summary":396,"summary_zh":397,"content":8,"source_name":398,"source_url":395,"published_at":399,"category":185,"cover_url":8,"hotness":12,"is_selected":34,"score":400,"score_detail":401,"sources":404,"tags":406,"primary_topic":410,"secondary_topics":414,"classification":420,"search_phrases":442,"slug":445,"view_count":21,"doi":446,"paper":447,"created_at":460},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":18,"substance":99,"depth":303,"authority":402,"freshness":20,"relevant":21,"comment":403},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。",[405],{"name":398,"url":395},[26,407,28,408,409],"农业供应链","精准农业","地缘政治",{"code":40,"slug":411,"name":412,"path":413,"parent_code":113},"yield-food-security","单产提升与粮食安全","\u002Ftopic\u002Ffield-crops\u002Fyield-food-security",[415,416],{"code":312,"slug":313,"name":314,"path":315,"parent_code":316},{"code":68,"slug":417,"name":418,"path":419,"parent_code":202},"agricultural-iot","物联网传感与边缘计算","\u002Ftopic\u002Fdigital-agriculture\u002Fagricultural-iot",{"status":122,"locked":34,"version":35,"method":36,"evidence":421},{"candidates":422,"agricultural_evidence":13},[423,427,432,436],{"code":40,"score":259,"supported":13,"title":424,"abstract":425,"tags":426},[343],[28,343],[28],{"code":56,"score":126,"supported":13,"title":428,"abstract":429,"tags":431},[],[26,408,430],"precision agriculture",[26,408],{"code":312,"score":20,"supported":13,"title":433,"abstract":434,"tags":435},[],[308,330,328],[],{"code":68,"score":20,"supported":13,"title":437,"abstract":438,"tags":441},[],[71,439,440],"internet of things","IoT",[],[443,444],"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":446,"openalex_id":448,"authors":449,"venue":398,"cited_by_count":234,"oa_url":395,"card":455,"direction":390,"ingested_from":248},"W7222902031",[450,452],{"name":451,"orcid":8},"Parameswaran Mahendran",{"name":453,"orcid":454},"Wong Sing Yun","https:\u002F\u002Forcid.org\u002F0000-0001-5776-8852",{"tldr":456,"method":457,"finding":458,"direction":390,"opportunity":459},"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":462,"title":463,"url":464,"summary":465,"summary_zh":466,"content":8,"source_name":467,"source_url":468,"published_at":10,"category":185,"cover_url":8,"hotness":12,"is_selected":34,"score":469,"score_detail":470,"sources":473,"tags":475,"primary_topic":478,"secondary_topics":479,"classification":480,"search_phrases":513,"slug":516,"view_count":62,"doi":517,"paper":518,"created_at":529},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",56,{"impact":100,"substance":471,"depth":19,"authority":20,"freshness":20,"relevant":21,"comment":472},16,"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。",[474],{"name":467,"url":468},[26,476,28,408,477],"农业物联网","土壤墒情监测",{"code":68,"slug":417,"name":418,"path":419,"parent_code":202},[],{"status":122,"locked":34,"version":35,"method":36,"evidence":481},{"candidates":482,"agricultural_evidence":13},[483,487,491,495,502,509],{"code":68,"score":18,"supported":13,"title":484,"abstract":485,"tags":486},[440],[71,439,440],[476],{"code":56,"score":471,"supported":13,"title":488,"abstract":489,"tags":490},[430],[408,430],[26,408],{"code":40,"score":340,"supported":13,"title":492,"abstract":493,"tags":494},[],[28,343],[28],{"code":496,"score":86,"supported":13,"title":497,"abstract":498,"tags":501},"F3",[],[499,500],"肥料","fertilizer",[],{"code":503,"score":86,"supported":13,"title":504,"abstract":505,"tags":508},"H2",[],[506,507],"土壤","soil",[],{"code":319,"score":62,"supported":13,"title":510,"abstract":511,"tags":512},[],[337],[],[514,515],"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":517,"openalex_id":519,"authors":520,"venue":467,"cited_by_count":234,"oa_url":468,"card":524,"direction":390,"ingested_from":248},"W7221676154",[521],{"name":522,"orcid":523},"Innocent Uzougbo Onwuegbuzie","https:\u002F\u002Forcid.org\u002F0000-0002-1582-1739",{"tldr":525,"method":526,"finding":527,"direction":390,"opportunity":528},"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"]