[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-2299":3,"related-2299":105},{"id":4,"title":5,"url":6,"summary":7,"summary_zh":8,"content":8,"source_name":9,"source_url":6,"published_at":10,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":14,"score_detail":15,"sources":23,"tags":25,"primary_topic":31,"secondary_topics":37,"classification":50,"search_phrases":84,"slug":87,"view_count":88,"doi":89,"paper":90,"created_at":104},2299,"Causal Effects of Climate-Smart Agriculture Adoption on Smallholder Welfare and Food Security in Zambia: Evidence from Endogenous Switching Regression, Double Machine Learning, and Bayesian Estimation","https:\u002F\u002Fdoi.org\u002F10.21203\u002Frs.3.rs-10994635\u002Fv1","Causal Effects of Climate-Smart Agriculture Adoption on Smallholder Welfare and Food Security in Zambia: Evidence from Endogenous Switching Regression, Double Machine Learning, and Bayesian Estimation。Research Square",null,"Research Square","2026-09-11T00:00:00Z","论文",10,false,67,{"impact":16,"substance":17,"depth":18,"authority":19,"freshness":20,"relevant":21,"comment":22},12,20,18,8,9,1,"方法组合新颖、结论有实证价值，但研究对象为赞比亚小农户，对国内三农实践的直接参考有限，适合作为国际经验类精选。",[24],{"name":9,"url":6},[26,27,28,29,30],"粮食安全","因果推断","气候智慧农业","小农户生计","赞比亚",{"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",[38,44],{"code":39,"slug":40,"name":41,"path":42,"parent_code":43},"G2","farm-services","社会化服务与规模经营","\u002Ftopic\u002Frural-services\u002Ffarm-services","G",{"code":45,"slug":46,"name":47,"path":48,"parent_code":49},"I2","agricultural-ai","农业AI与大模型","\u002Ftopic\u002Fdigital-agriculture\u002Fagricultural-ai","I",{"status":51,"locked":13,"version":52,"method":53,"evidence":54},"classified","2026-10-22.2","rules",{"candidates":55,"agricultural_evidence":57},[56,62,68,74,79],{"code":32,"score":16,"supported":57,"title":58,"abstract":60,"tags":61},true,[59],"food security",[59],[26],{"code":39,"score":63,"supported":57,"title":64,"abstract":66,"tags":67},11,[65],"smallholder",[65],[],{"code":69,"score":63,"supported":57,"title":70,"abstract":72,"tags":73},"I1",[71],"smart agriculture",[71],[],{"code":45,"score":63,"supported":57,"title":75,"abstract":77,"tags":78},[76],"machine learning",[76],[],{"code":80,"score":21,"supported":13,"title":81,"abstract":82,"tags":83},"H7",[],[],[28],[85,86],"气候智慧农业 小农户生计 因果推断 粮食安全","气候智慧农业 小农户生计","气候智慧农业小农户生计因果推断粮食安全-2299",3,"10.21203\u002Frs.3.rs-10994635\u002Fv1",{"doi":89,"openalex_id":91,"authors":92,"venue":9,"cited_by_count":101,"oa_url":6,"card":8,"direction":102,"ingested_from":103},"W7212246566",[93,96,98],{"name":94,"orcid":95},"Evans Kudzai Chinembiri","https:\u002F\u002Forcid.org\u002F0009-0003-7304-0214",{"name":97,"orcid":8},"Munyaradzi Mutenje",{"name":99,"orcid":100},"Nkele D. Malahlela","https:\u002F\u002Forcid.org\u002F0009-0001-1653-7553",0,"智慧农业 \u002F 农业物联网","openalex","2026-09-13T23:30:09.568432Z",{"total":106,"page":21,"page_size":106,"items":107},6,[108,201,310,376,445,519],{"id":109,"title":110,"url":111,"summary":112,"summary_zh":113,"content":8,"source_name":114,"source_url":111,"published_at":115,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":116,"score_detail":117,"sources":120,"tags":122,"primary_topic":126,"secondary_topics":127,"classification":134,"search_phrases":178,"slug":181,"view_count":101,"doi":182,"paper":183,"created_at":200},5478,"Characterisation of Food Security Situation for Smallholder Farmers in Zvimba","https:\u002F\u002Fdoi.org\u002F10.71458\u002Frx0qpm30","This study provides a comprehensive analysis of the food security situation among smallholder farmers (SHFs) in Zvimba District, Zimbabwe. Smallholder agriculture is the bedrock of Zimbabwe's food system, yet it remains highly vulnerable to a complex array of shocks and stressors. Using a mixed-methods approach, this research investigates the prevalence, drivers and lived experiences of food insecurity within this community. A structured survey was administered to 412 randomly selected smallholder households across the district's wards. The quantitative data were supplemented by 12 Focus Group Discussions (FGDs) and 24 Key Informant Interviews (KIIs) with farmers, community leaders and agricultural extension officers to capture qualitative nuances. The study is grounded in the Food Security Theory (FST), which conceptualises food security through its four pillars: food availability, food access, food utilisation and food stability. Findings reveal a precarious food security situation. Quantitatively, 78.4% of households were found to be food insecure, with an average Hunger Months Index of 4.7 months per year. The study identifies a significant disconnect between maize production, the national staple and household consumption, with over 65% of households failing to produce enough maize to meet their annual requirements. Qualitative data illuminated the multi-faceted drivers of this insecurity. Key points to note include climate change whereby erratic rainfall and prolonged mid-season dry spells were consistently reported as the primary production challenges, limited access to farming inputs whereby high costs and unreliable supplies of certified seeds, fertilizers and agro[1]chemicals constrain productivity. Morelso, socio-economic factors such as poverty, lack of viable alternative livelihoods and limited access to formal credit perpetuate a cycle of vulnerability. In addition, institutional weaknesses, for example, challenges with agricultural extension services and market inefficiencies, exacerbate the situation. The study concludes that food insecurity in Zvimba is not merely a problem of food production, but is deeply rooted in structural issues affecting food access, food utilisation, as well as food stability. Recommendations are proposed for a multi-sectoral approach, including promoting Climate-Smart Agriculture (CSA) and drought-resistant crops, strengthening input support systems and rural finance, diversifying livelihood strategies and enhancing the capacity of extension services. This research contributes to a deeper understanding of the localised dynamics of food security and provides evidence-based guidance for policymakers, development practitioners and the farmers of Zvimba themselves.","本研究对津巴布韦兹维姆巴区小农户（smallholder farmers, SHFs）的粮食安全状况进行了全面分析。小农农业是津巴布韦粮食体系的基石，但仍极易受到一系列复杂冲击和压力的影响。本研究采用混合方法，考察了该社区粮食不安全的普遍程度、驱动因素及生活体验。研究对该区各选区随机抽取的412户小农户进行了结构化问卷调查。定量数据辅以12次焦点小组讨论（FGDs）和24次关键知情人访谈（KIIs），访谈对象包括农民、社区领袖和农业推广人员，以捕捉定性层面的细微差异。本研究以粮食安全理论（Food Security Theory, FST）为基础，该理论通过四大支柱界定粮食安全：粮食可供性、粮食获取、粮食利用和粮食稳定性。研究结果揭示了严峻的粮食安全形势。定量数据显示，78.4%的家庭存在粮食不安全，年均饥饿月份指数为4.7个月。研究发现，玉米产量——该国主粮——与家庭消费之间存在显著脱节，超过65%的家庭生产的玉米不足以满足其年度需求。定性数据揭示了这一不安全状况的多重驱动因素。值得注意的要点包括：气候变化，即降雨不稳定和持续的中期干旱被一致报告为主要生产挑战；农业投入品获取受限，即认证种子、化肥和农用化学品成本高昂且供应不可靠，制约了生产力。此外，贫困、缺乏可行的替代生计以及正规信贷获取受限等社会经济因素使脆弱性循环持续存在。此外，制度薄弱环节，例如农业推广服务面临的挑战和市场效率低下，加剧了这一状况。研究得出结论，兹维姆巴的粮食不安全不仅仅是粮食生产问题，而是深深植根于影响粮食获取、粮食利用以及粮食稳定性的结构性问题。研究提出了采取多部门方法的建议，包括推广气候智能型农业（Climate-Smart Agriculture, CSA）和抗旱作物、加强投入品支持体系和农村金融、多样化生计策略以及增强","Ngenani The Zimbabwe Ezekiel Guti Journal of Community Engagement and Societal Transformations","2026-10-20T00:00:00Z",55,{"impact":19,"substance":18,"depth":118,"authority":106,"freshness":19,"relevant":21,"comment":119},15,"基于412户调查与混合方法的扎实实证研究，但属津巴布韦地方性案例，公共影响与信源权威度有限，可作参考而非每日精选。",[121],{"name":114,"url":111},[26,123,28,124,125],"小农户","农业推广","津巴布韦",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[128,129],{"code":39,"slug":40,"name":41,"path":42,"parent_code":43},{"code":80,"slug":130,"name":131,"path":132,"parent_code":133},"climate","气候适应与防灾减灾","\u002Ftopic\u002Fenvironment\u002Fclimate","H",{"status":51,"locked":13,"version":52,"method":53,"evidence":135},{"candidates":136,"agricultural_evidence":57},[137,141,145,153,160,167,174],{"code":32,"score":118,"supported":57,"title":138,"abstract":139,"tags":140},[59],[26,59],[26],{"code":39,"score":118,"supported":57,"title":142,"abstract":143,"tags":144},[65],[123,65],[123],{"code":80,"score":12,"supported":57,"title":146,"abstract":147,"tags":152},[],[148,149,150,151],"气候变化","干旱","climate change","drought",[28],{"code":154,"score":155,"supported":57,"title":156,"abstract":157,"tags":159},"G1",7,[],[124,158],"agricultural extension",[124],{"code":161,"score":106,"supported":57,"title":162,"abstract":163,"tags":166},"A3",[],[164,165],"玉米","maize",[],{"code":168,"score":106,"supported":57,"title":169,"abstract":170,"tags":173},"G3",[],[171,172],"农村金融","rural finance",[],{"code":69,"score":88,"supported":57,"title":175,"abstract":176,"tags":177},[],[71],[],[179,180],"Zvimba 小农户 粮食安全","津巴布韦 小农 玉米","Zvimba小农户粮食安全-5478","10.71458\u002Frx0qpm30",{"doi":182,"openalex_id":184,"authors":185,"venue":114,"cited_by_count":101,"oa_url":8,"card":194,"direction":102,"ingested_from":103},"W7223029383",[186,189,192],{"name":187,"orcid":188},"Casper Myambo","https:\u002F\u002Forcid.org\u002F0009-0007-8625-7526",{"name":190,"orcid":191},"Chipo Plaxedes Mubaya","https:\u002F\u002Forcid.org\u002F0000-0002-4123-0238",{"name":193,"orcid":8},"Patience Mutopo",{"tldr":195,"method":196,"finding":197,"direction":198,"opportunity":199},"调查津巴布韦Zvimba小农户粮食安全状况，分析其普遍性、成因与实际体验。","混合方法：412户问卷、12场焦点小组、24个关键人物访谈，基于粮食安全四支柱理","78.4%家庭粮食不安全，年均饥饿月4.7个月，主因是气候、投入、社会经济与制度等结构性问题。","数字乡村与农业信息化","可探索用移动端问卷与遥感产量监测构建小农户粮食安全动态预警与精准干预系统。","2026-10-21T23:30:08.937079Z",{"id":202,"title":203,"url":204,"summary":205,"summary_zh":206,"content":8,"source_name":207,"source_url":204,"published_at":208,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":209,"score_detail":210,"sources":214,"tags":216,"primary_topic":219,"secondary_topics":220,"classification":223,"search_phrases":291,"slug":294,"view_count":101,"doi":295,"paper":296,"created_at":309},5185,"When the rains are too much: El Niño, Smallholder Farmers and Food Security in Western Kenya","https:\u002F\u002Fdoi.org\u002F10.18697\u002Fajfand.155.ed182","When the rains are too much: El Niño, Smallholder Farmers and Food Security in Western Kenya For generations, farmers in Western Kenya have watched the skies carefully. The arrival, duration, and distribution of rainfall have traditionally provided important signals about when to prepare land, plant, weed, and harvest. But these signals are becoming increasingly difficult to read. Climate change is altering rainfall patterns, while increasingly frequent extreme weather events are making farming more uncertain. The current outlook for the October–December 2026 season brings this challenge sharply into focus. The IGAD Climate Prediction and Applications Centre (ICPAC) forecasts a wetter-than-normal season across much of the Greater Horn of Africa. The Lake Victoria Basin, which includes large parts of Western Kenya, is among the areas with a high likelihood of receiving more than 400 mm of seasonal rainfall. ICPAC reports that El Niño has developed and is expected to strengthen, while a positive Indian Ocean Dipole is also expected—climate conditions that are commonly associated with enhanced rainfall in the region, and is likely to run into February of 2027. But what does this mean for the smallholder farmer? The first point is that more rainfall does not necessarily mean more food. For a farmer whose livelihood depends almost entirely on rain-fed agriculture, abundant rainfall can be a blessing. It can replenish streams and water sources, improve soil moisture, restore pasture and create favourable conditions for crop production. If well distributed, the rains could contribute to improved harvests and household food supplies. The problem arises when rainfall is too intense, too concentrated or poorly distributed. A farmer may receive a great deal of rain in a few days and then experience a dry spell. Another farmer a few kilometres away may receive considerably less. Heavy downpours can cause flooding, waterlogging and soil erosion. Seeds may be washed away soon after planting. Young crops can be submerged or damaged. Valuable topsoil and nutrients can be carried away, reducing the productivity of land in subsequent seasons. This is particularly important in Western Kenya, where many households depend on small parcels of land for both food and income. A failed or damaged crop is not simply an agricultural loss. It can mean less food in the household, less money for school fees and health care, and fewer resources to purchase nutritious foods. The food-security paradox We must, therefore, look beyond agricultural production to food and nutrition security. A household may produce enough maize yet still have a poor diet if vegetables, legumes, fruits, milk, eggs or other foods are unavailable or unaffordable. Climate shocks can reduce this diversity. When crops are damaged, families may depend more heavily on whatever staple food remains available. This is why climate resilience must also be nutrition-sensitive. Western Kenya has a rich agricultural tradition and considerable potential for diversified food production. Farmers grow cereals, legumes, vegetables and root crops and keep livestock and poultry. Such diversity is not merely an agricultural advantage; it is a nutritional resource. It can provide different foods, spread risk and generate income at different times of the year. Climate adaptation should, therefore, not encourage farmers simply to produce more of one crop. It should help them build diverse and resilient farming systems. Women carry a large part of the burden The impact of erratic and excessive rainfall also has a gender dimension. Women in smallholder households are often deeply involved in food production, processing, preparation and household nutrition. When harvests fail, or food prices rise, women frequently have to find ways of stretching limited household resources to feed the family. When roads become impassable or markets are disrupted, women may have greater difficulty accessing food and agricultural inputs. When water sources are contaminated or damaged, household responsibilities can become even more demanding. Climate adaptation must therefore deliberately include women—not simply as beneficiaries, but as decision-makers, innovators, farmers and leaders. Young people must also be part of the solution There is another group that deserves greater attention: young people. Western Kenya cannot build climate-resilient agriculture while treating agriculture as an occupation of the past. Young people need to see opportunities in modern farming, agro-processing, food safety, climate information services, irrigation, digital agriculture and agricultural entrepreneurship. The increasing unpredictability of climate may actually provide an opportunity to make agriculture more innovative. Young people can help introduce new technologies, improve access to climate information, develop value-added products and create businesses around food production and processing. From forecasting to action The availability of a climate forecast is useful only if it reaches the people who need it in time. Farmers need information that answers practical questions: When should I plant? Which crops or varieties are appropriate? How can I protect my soil? What should I do if rainfall becomes excessive? How can I protect harvested food? Where can I obtain reliable seed and other inputs? Seasonal forecasts should, therefore, be translated into local, practical agricultural advice. ICPAC itself emphasizes that seasonal forecasts should be used together with weekly and monthly forecasts and national meteorological information. This requires stronger links between meteorological services, agricultural extension officers, researchers, county governments, farmer organizations and communities. We should also strengthen simple but important measures: water harvesting, drainage, terracing and soil conservation; planting crops and varieties suited to local conditions; maintaining vegetation cover; diversifying crops and livestock; improving storage facilities; and protecting food from moisture and contamination. Prepare before the rain comes The greatest lesson from the current El Niño outlook is perhaps that preparedness must begin before the first heavy rains arrive. Governments and development partners should not wait for floods, damaged roads, destroyed crops or food shortages before responding. Early warning should lead to early action. Farmers should be supported to prepare their farms, protect livestock, secure seed and inputs, strengthen food storage and identify alternative routes to markets. This is particularly important because the same season can produce both opportunities and losses. ICPAC notes that enhanced rainfall can support agricultural production and replenish water resources, but can simultaneously increase the risk of flooding, flash floods and landslides in vulnerable areas. A changing climate requires a different agricultural mindset Perhaps the most important change we need is in the way we think about farming. For too long, agricultural planning has often assumed that rainfall will behave according to a familiar calendar. That assumption is becoming increasingly unsafe. Farmers now have to manage not only too little rain, but also too much rain, rain at the wrong time and rain in the wrong place. The challenge is, therefore, not simply to produce more food. It is to build food systems that can continue providing adequate, diverse, safe and nutritious food under increasingly uncertain climatic conditions. Western Kenya's smallholder farmers should not be left alone to carry this burden. They need science that responds to their realities, extension services that reach them, climate information they can understand and use, financial services that help them manage risk, markets that function during difficult seasons, and policies that recognize the central role of smallholder agriculture in national food and nutrition security, and partners who are willing to appreciate and make use of indigenous knowledge. El Niño should, therefore, be viewed neither simply as a disaster nor automatically as a blessing. It is a climate event whose consequences will depend greatly on our preparedness. The question before us is not merely, “Will the rains come?” They probably will. The more important question is: Will our farmers, food systems and institutions be ready when they do? That is where climate resilience—and ultimately food and nutrition security—will be tested. Prof. Ruth Khasaya Oniang'o Founder and Editor-in-Chief, AJFAND ORCiD: https:\u002F\u002Forcid.org\u002F0009-0005-8344-9093","当雨水过多时：厄尔尼诺现象、小农户与肯尼亚西部的粮食安全\n\n世代以来，肯尼亚西部的农民一直密切关注着天空。降雨的到来、持续时间和分布，传统上为何时整地、播种、除草和收获提供了重要信号。但这些信号正变得越来越难以解读。气候变化正在改变降雨模式，而日益频繁的极端天气事件使农业变得更加不确定。当前对2026年10月至12月季节的展望使这一挑战凸显出来。政府间发展组织气候预测与应用中心（ICPAC）预测，大非洲之角大部分地区将迎来高于正常水平的湿润季节。维多利亚湖流域——包括肯尼亚西部的大部分地区——属于极有可能获得超过400毫米季节性降雨的区域之一。ICPAC报告称，厄尔尼诺现象已经形成并预计将增强，同时预计还将出现正印度洋偶极子——这些气候条件通常与该地区降雨增强相关，并可能持续到2027年2月。但这对小农户意味着什么？首先，更多降雨并不必然意味着更多粮食。对于生计几乎完全依赖雨养农业的农民来说，充沛的降雨可能是福。它可以补充溪流和水源、改善土壤湿度、恢复牧场，并为作物生产创造有利条件。如果分布良好，降雨可能有助于改善收成和家庭粮食供应。问题出现在降雨过于猛烈、过于集中或分布不均的时候。一个农民可能在几天内获得大量降雨，随后又经历一段干旱期。几公里外的另一个农民可能获得的降雨少得多。暴雨可能引发洪水、渍涝和土壤侵蚀。种子可能在播种后不久被冲走。幼苗可能被淹没或受损。宝贵的表土和养分可能被带走，降低土地在后续季节的生产力。这在肯尼亚西部尤为重要，因为许多家庭依赖小块土地获取食物和收入。作物歉收或受损不仅仅是农业损失。它可能意味着家庭食物减少、用于学费和医疗的钱减少，以及购买营养食品的资源减少。粮食安全……","African Journal of Food Agriculture Nutrition and Development","2026-10-16T00:00:00Z",75,{"impact":18,"substance":17,"depth":211,"authority":212,"freshness":19,"relevant":21,"comment":213},16,13,"核心期刊评论文章，结合El Niño预测讨论小农户气候适应与粮食营养安全，有实质分析与行动建议，但属区域案例、非信息化技术突破。",[215],{"name":207,"url":204},[217,26,123,28,218],"肯尼亚","气候预警",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[221,222],{"code":39,"slug":40,"name":41,"path":42,"parent_code":43},{"code":80,"slug":130,"name":131,"path":132,"parent_code":133},{"status":51,"locked":13,"version":52,"method":53,"evidence":224},{"candidates":225,"agricultural_evidence":57},[226,230,234,240,247,251,257,263,269,275,281,285],{"code":32,"score":118,"supported":57,"title":227,"abstract":228,"tags":229},[59],[26,59],[26],{"code":39,"score":118,"supported":57,"title":231,"abstract":232,"tags":233},[65],[123,65],[123],{"code":80,"score":12,"supported":57,"title":235,"abstract":236,"tags":239},[],[148,149,150,237,238],"climate resilience","waterlogging",[28],{"code":241,"score":106,"supported":57,"title":242,"abstract":243,"tags":246},"H2",[],[244,245],"土壤","soil",[],{"code":161,"score":88,"supported":57,"title":248,"abstract":249,"tags":250},[],[165],[],{"code":252,"score":88,"supported":57,"title":253,"abstract":254,"tags":256},"B4",[],[255],"月季",[],{"code":258,"score":88,"supported":57,"title":259,"abstract":260,"tags":262},"C",[],[261],"livestock",[],{"code":264,"score":88,"supported":57,"title":265,"abstract":266,"tags":268},"C3",[],[267],"poultry",[],{"code":270,"score":88,"supported":57,"title":271,"abstract":272,"tags":274},"E4",[],[273],"food safety",[],{"code":276,"score":88,"supported":57,"title":277,"abstract":278,"tags":280},"F4",[],[279],"除草",[],{"code":154,"score":88,"supported":57,"title":282,"abstract":283,"tags":284},[],[158],[],{"code":286,"score":88,"supported":57,"title":287,"abstract":288,"tags":290},"H3",[],[289],"irrigation",[],[292,293],"El Niño 小农户 粮食安全","ICPAC 季节预报 肯尼亚","ElNiño小农户粮食安全-5185","10.18697\u002Fajfand.155.ed182",{"doi":295,"openalex_id":297,"authors":298,"venue":207,"cited_by_count":101,"oa_url":302,"card":303,"direction":198,"ingested_from":103},"W7222630373",[299],{"name":300,"orcid":301},"Ruth Khasaya Oniang'o","https:\u002F\u002Forcid.org\u002F0009-0005-8344-9093","https:\u002F\u002Fajfand.net\u002FVolume26\u002FNo8\u002FEditorialVol26No8.pdf",{"tldr":304,"method":305,"finding":306,"direction":307,"opportunity":308},"分析厄尔尼诺导致肯尼亚西部降雨过量对小农粮食安全的影响","基于ICPAC季节气候预测与厄尔尼诺、印度洋偶极子分析","降雨过多且分布不均会引发洪涝、土壤侵蚀，反而威胁小农粮食安全","农业绿色发展与碳","可结合遥感与农户调查，量化极端降雨时空分布对小农产量与粮食安全的非线性影响","2026-10-17T23:30:36.130973Z",{"id":311,"title":312,"url":313,"summary":314,"summary_zh":8,"content":8,"source_name":315,"source_url":8,"published_at":316,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":317,"score_detail":318,"sources":322,"tags":324,"primary_topic":328,"secondary_topics":329,"classification":332,"search_phrases":363,"slug":366,"view_count":101,"doi":8,"paper":367,"created_at":375},4735,"干旱区农技社会化服务试点政策对县域粮食生产的激励效应——基于双重机器学习因果推断","http:\u002F\u002Fwww.qikanvip.com\u002Fqkml\u002F176878.html","基于2015至2023年200县面板,采用双重差分与双重机器学习方法评估2021年农业社会化服务试点政策。结果显示政策显著促进县域粮食产量,但呈短期脉冲效应,中等收入地区呈倒U型,主要依赖规模扩张而非效率扩张路径","干旱区资源与环境 2026-10-08","2026-10-08T00:00:00Z",78,{"impact":18,"substance":319,"depth":18,"authority":320,"freshness":106,"relevant":21,"comment":321},22,14,"基于200县面板与双重机器学习的因果推断，方法新颖、数据扎实，对评估社会化服务试点政策有实质参考价值。",[323],{"name":315,"url":313},[26,27,325,326,327],"县域农业","农业社会化服务","试点政策",{"code":39,"slug":40,"name":41,"path":42,"parent_code":43},[330,331],{"code":45,"slug":46,"name":47,"path":48,"parent_code":49},{"code":80,"slug":130,"name":131,"path":132,"parent_code":133},{"status":51,"locked":13,"version":52,"method":53,"evidence":333},{"candidates":334,"agricultural_evidence":57},[335,340,345,350,354,358],{"code":39,"score":16,"supported":57,"title":336,"abstract":338,"tags":339},[337],"社会化服务",[337],[326],{"code":45,"score":63,"supported":57,"title":341,"abstract":343,"tags":344},[342],"机器学习",[342],[],{"code":346,"score":20,"supported":57,"title":347,"abstract":348,"tags":349},"I7",[27],[],[27],{"code":80,"score":19,"supported":57,"title":351,"abstract":352,"tags":353},[149],[],[],{"code":32,"score":21,"supported":13,"title":355,"abstract":356,"tags":357},[],[],[26],{"code":359,"score":21,"supported":13,"title":360,"abstract":361,"tags":362},"G4",[],[],[325],[364,365],"农业社会化服务试点 县域粮食产量","双重机器学习 粮食生产","农业社会化服务试点县域粮食产量-4735",{"doi":8,"openalex_id":8,"authors":368,"venue":8,"cited_by_count":101,"oa_url":8,"card":369,"direction":198,"ingested_from":374},[],{"tldr":370,"method":371,"finding":372,"direction":198,"opportunity":373},"评估干旱区农技社会化服务试点政策对县域粮食产量的因果效应。","2015-2023年200县面板，双重差分与双重机器学习因果推断。","政策显著增产但为短期脉冲效应，中等收入地区呈倒U型，靠规模扩张而非效率提升。","可探究政策长期效应衰减机制及如何转向效率提升型服务模式。","agent","2026-10-12T00:11:14.975039Z",{"id":377,"title":378,"url":379,"summary":380,"summary_zh":381,"content":8,"source_name":382,"source_url":379,"published_at":383,"category":11,"cover_url":8,"hotness":384,"is_selected":13,"score":385,"score_detail":386,"sources":389,"tags":396,"primary_topic":398,"secondary_topics":399,"classification":401,"search_phrases":424,"slug":427,"view_count":88,"doi":428,"paper":429,"created_at":444},1825,"Do productivity and income gains from climate-smart agriculture practices translate into food security? Evidence from smallholder farmers in central Malawi","https:\u002F\u002Fdoi.org\u002F10.6084\u002Fm9.figshare.33441414","Climate-smart agriculture (CSA) is widely promoted to improve smallholder livelihoods under increasing climate risks, yet evidence on impacts beyond productivity, particularly multidimensional food security, remains limited. This study examines determinants of adoption of selected CSA practices and their effects on maize productivity, farm income, food expenditure share, and dietary diversity among 510 smallholder households in Kasungu District, central Malawi. Using 2023 cross-sectional survey data, we employ a multinomial endogenous switching regression model to address potential selection bias across eight mutually exclusive adoption options based on three CSA practices. Gender of the household head, extension participation, and cooperative membership are significantly associated with adoption, with female-headed households more likely to adopt multiple-practice combinations. Average treatment effect on the treated (ATT) estimates indicate significant maize-yield and farm-income gains for certain options relative to the estimated non-adoption counterfactual. However, no practice option shows a statistically significant ATT estimate for dietary diversity measured by the Food Consumption Score, indicating a disconnect between estimated farm-income gains and dietary outcomes. The findings suggest that CSA may support productivity and income, but complementary nutrition-sensitive interventions may be needed to achieve multidimensional food security.","气候智能型农业（CSA）被广泛推广以在日益加剧的气候风险下改善小农户生计，然而关于其超越生产力层面影响（尤其是多维粮食安全）的证据仍然有限。本研究考察了马拉维中部卡松古区510户小农户采纳特定CSA实践的决定因素及其对玉米生产力、农场收入、食品支出份额和膳食多样性的影响。利用2023年横截面调查数据，我们采用多项内生转换回归模型，以解决基于三种CSA实践形成的八种互斥采纳选项中的潜在选择偏差。户主性别、推广参与和合作社成员身份与采纳行为显著相关，其中女性户主家庭更倾向于采纳多种实践组合。处理组平均处理效应（ATT）估计表明，相对于估计的非采纳反事实情景，某些选项在玉米产量和农场收入方面具有显著增益。然而，没有任何实践选项在食品消费得分衡量的膳食多样性方面显示出统计显著的ATT估计值，这表明估计的农场收入增益与膳食结果之间存在脱节。研究结果表明，CSA可能有助于提高生产力和收入，但实现多维粮食安全可能需要补充营养敏感型干预措施。","Figshare","2026-09-06T00:00:00Z",40,64,{"impact":16,"substance":319,"depth":18,"authority":12,"freshness":387,"relevant":21,"comment":388},2,"研究揭示CSA增产增收但未改善膳食多样性，对政策制定有参考价值。",[390,391,394],{"name":382,"url":379},{"name":392,"url":393},"Cogent Food & Agriculture","https:\u002F\u002Fdoi.org\u002F10.1080\u002F23311932.2026.2725385",{"name":382,"url":395},"https:\u002F\u002Fdoi.org\u002F10.6084\u002Fm9.figshare.33441414.v1",[397,26,123,28],"非洲",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[400],{"code":39,"slug":40,"name":41,"path":42,"parent_code":43},{"status":51,"locked":13,"version":52,"method":53,"evidence":402},{"candidates":403,"agricultural_evidence":57},[404,408,412,416,420],{"code":32,"score":118,"supported":57,"title":405,"abstract":406,"tags":407},[59],[26,59],[26],{"code":39,"score":118,"supported":57,"title":409,"abstract":410,"tags":411},[65],[123,65],[123],{"code":69,"score":63,"supported":57,"title":413,"abstract":414,"tags":415},[71],[71],[],{"code":161,"score":106,"supported":57,"title":417,"abstract":418,"tags":419},[],[164,165],[],{"code":80,"score":21,"supported":13,"title":421,"abstract":422,"tags":423},[],[],[28],[425,426],"气候智慧农业 粮食安全 小农户 非洲","气候智慧农业 粮食安全","气候智慧农业粮食安全小农户非洲-1825","10.6084\u002Fm9.figshare.33441414",{"doi":428,"openalex_id":430,"authors":431,"venue":382,"cited_by_count":101,"oa_url":379,"card":438,"direction":102,"ingested_from":103},"W7210263968",[432,434,436],{"name":433,"orcid":8},"Jinwon Suh",{"name":435,"orcid":8},"Seongtae Ji",{"name":437,"orcid":8},"Tabitha C. Nindi-Chigwe",{"tldr":439,"method":440,"finding":441,"direction":442,"opportunity":443},"研究气候智能农业对马拉维小农户粮食安全的影响，发现其提升产量和收入但未改善膳食多样性。","使用2023年横截面调查数据，采用多项式内生转换回归模型分析510户农户。","气候智能农业提高玉米产量和农场收入，但对膳食多样性无显著影响，需营养敏感干预。","农业人工智能与决策模型","可探索将营养指标纳入CSA推广评估，或设计结合营养干预的农业技术组合，以弥合收入与膳食鸿沟。","2026-09-07T23:30:08.624334Z",{"id":446,"title":447,"url":448,"summary":449,"summary_zh":450,"content":8,"source_name":451,"source_url":448,"published_at":452,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":453,"score_detail":454,"sources":456,"tags":458,"primary_topic":463,"secondary_topics":464,"classification":472,"search_phrases":502,"slug":505,"view_count":88,"doi":506,"paper":507,"created_at":518},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":16,"substance":18,"depth":211,"authority":106,"freshness":19,"relevant":21,"comment":455},"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。",[457],{"name":451,"url":448},[459,460,26,461,462],"智慧农业","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},[465,471],{"code":466,"slug":467,"name":468,"path":469,"parent_code":470},"E1","food-processing","加工与食品制造","\u002Ftopic\u002Ffood-supply\u002Ffood-processing","E",{"code":45,"slug":46,"name":47,"path":48,"parent_code":49},{"status":51,"locked":13,"version":52,"method":53,"evidence":473},{"candidates":474,"agricultural_evidence":57},[475,480,487,491,497],{"code":466,"score":63,"supported":57,"title":476,"abstract":478,"tags":479},[477],"food manufacturing",[477],[],{"code":45,"score":12,"supported":57,"title":481,"abstract":482,"tags":486},[],[483,342,484,485],"深度学习","artificial intelligence","decision support",[460],{"code":32,"score":20,"supported":57,"title":488,"abstract":489,"tags":490},[59],[],[26],{"code":69,"score":492,"supported":57,"title":493,"abstract":494,"tags":496},4,[],[495],"数字孪生",[459],{"code":270,"score":88,"supported":57,"title":498,"abstract":499,"tags":501},[],[500],"食品安全",[],[503,504],"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":506,"openalex_id":508,"authors":509,"venue":451,"cited_by_count":101,"oa_url":512,"card":513,"direction":102,"ingested_from":103},"W7214295236",[510],{"name":511,"orcid":8},"Atif Maqbool Syed","https:\u002F\u002Fwww.irejournals.com\u002Fformatedpaper\u002F1723457.pdf",{"tldr":514,"method":515,"finding":516,"direction":442,"opportunity":517},"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",{"id":520,"title":521,"url":522,"summary":523,"summary_zh":524,"content":8,"source_name":525,"source_url":522,"published_at":526,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":527,"score_detail":528,"sources":532,"tags":534,"primary_topic":537,"secondary_topics":538,"classification":540,"search_phrases":560,"slug":563,"view_count":21,"doi":564,"paper":565,"created_at":584},3143,"Underutilised indigenous crop adoption and household food security: evidence from a cross-sectional study of smallholder farmers in South Africa","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1939658","Introduction Underutilised indigenous crops (UICs) are increasingly recognised in South Africa as a potential component of resilient and nutrition-sensitive agricultural systems. However, policy recognition has not been matched by sufficient household-level evidence on the extent and distribution of UIC adoption, the factors associated with adoption, or the relationship between UIC adoption and household food access insecurity among smallholder farming households in South Africa. Methods A quantitative, cross-sectional observational design was used among 205 smallholder farming households in KwaZulu-Natal and the Eastern Cape. Household food-access insecurity was measured using the Household Food Insecurity Access Scale (HFIAS). Logistic regression, ordinary least squares regression, propensity-score matching, chi-square tests, and descriptive analysis were used to examine adoption patterns, associated factors, and food-access security outcomes. Results UIC adoption was reported by 70.2% of respondents, with pumpkin, cowpeas, and amaranth among the most widely cultivated crops. Adopting households had lower mean HFIAS scores than non-adopting households and were less likely to be classified as severely food insecure. In the OLS model, adoption was negatively associated with HFIAS scores ( β = −2.10, p = 0.007). Propensity-score matching also estimated a lower HFIAS score among adopters than among matched non-adopters (ATT = −2.15, p = 0.006). Water sufficiency, group membership, extension contact, education, and household size were associated with food-access security. Discussion The findings indicate that UIC adoption is associated with better household food-access security, but the cross-sectional observational design does not establish a causal effect. Promoting UICs may contribute to nutrition-sensitive agricultural development when accompanied by enabling conditions such as reliable water access, extension support, social capital, and productive resources.","引言 在南非，未被充分利用的本土作物（underutilised indigenous crops, UICs）日益被视为具有韧性和营养敏感性的农业系统的潜在组成部分。然而，政策层面的认可与充分的家庭层面证据之间仍存在差距，这些证据涉及UIC采用的程度与分布、与采用相关的因素，以及UIC采用与南非小农家庭食物获取不安全状况之间的关系。方法 本研究采用定量、横断面观察性设计，在夸祖鲁-纳塔尔省和东开普省的205个小农家庭中开展调查。家庭食物获取不安全状况采用家庭食物不安全获取量表（Household Food Insecurity Access Scale, HFIAS）进行测量。研究运用逻辑回归、普通最小二乘回归、倾向得分匹配、卡方检验和描述性分析，考察采用模式、相关因素及食物获取安全结果。结果 70.2%的受访者报告采用了UIC，其中南瓜、豇豆和苋菜是种植最广泛的作物。采用UIC的家庭HFIAS平均得分低于未采用家庭，且被归类为严重食物不安全的可能性更低。在OLS模型中，采用UIC与HFIAS得分呈负相关（β = −2.10，p = 0.007）。倾向得分匹配也估计出采用者的HFIAS得分低于匹配后的非采用者（ATT = −2.15，p = 0.006）。水资源充足性、群体成员身份、推广接触、教育程度和家庭规模与食物获取安全相关。讨论 研究结果表明，UIC采用与更好的家庭食物获取安全相关，但横断面观察性设计无法确立因果效应。在具备可靠水资源获取、推广支持、社会资本和生产性资源等有利条件的情况下，推广UIC可能有助于营养敏感型农业发展。","Frontiers in Sustainable Food Systems","2026-09-21T00:00:00Z",71,{"impact":16,"substance":529,"depth":530,"authority":212,"freshness":19,"relevant":21,"comment":531},21,17,"以南非205户小农为样本的实证研究，方法规范、数据具体，但属区域案例，对国内三农信息化参考价值有限。",[533],{"name":525,"url":522},[26,123,124,535,536],"南非农业","本土作物",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[539],{"code":39,"slug":40,"name":41,"path":42,"parent_code":43},{"status":51,"locked":13,"version":52,"method":53,"evidence":541},{"candidates":542,"agricultural_evidence":57},[543,547,551,556],{"code":39,"score":16,"supported":57,"title":544,"abstract":545,"tags":546},[65],[65],[123],{"code":32,"score":20,"supported":57,"title":548,"abstract":549,"tags":550},[59],[],[26],{"code":286,"score":88,"supported":57,"title":552,"abstract":553,"tags":555},[],[554],"水资源",[],{"code":154,"score":21,"supported":13,"title":557,"abstract":558,"tags":559},[],[],[124],[561,562],"南非 小农户 本土作物","KwaZulu-Natal 粮食安全","南非小农户本土作物-3143","10.3389\u002Ffsufs.2026.1939658",{"doi":564,"openalex_id":566,"authors":567,"venue":525,"cited_by_count":101,"oa_url":522,"card":579,"direction":198,"ingested_from":103},"W7213867432",[568,570,573,576],{"name":569,"orcid":8},"Glen Themba Mendi",{"name":571,"orcid":572},"Jan Willem Swanepoel","https:\u002F\u002Forcid.org\u002F0000-0002-0812-2657",{"name":574,"orcid":575},"Siphe Zantsi","https:\u002F\u002Forcid.org\u002F0000-0001-9787-3913",{"name":577,"orcid":578},"Oluwasogo David Olorunfemi","https:\u002F\u002Forcid.org\u002F0000-0002-3524-4262",{"tldr":580,"method":581,"finding":582,"direction":198,"opportunity":583},"研究南非小农户采用未充分利用本土作物与家庭食物安全的关系。","对205户小农户横截面调查，用HFIAS、逻辑回归和倾向得分匹配分析。","70.2%农户采用本土作物，采用者食物不安全评分显著更低。","可结合数字推广与遥感监测，评估本土作物采用对食物安全的长期因果效应。","2026-09-22T23:30:07.989696Z"]