[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-1128":3,"related-1128":68},{"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":31,"secondary_topics":37,"classification":38,"search_phrases":62,"slug":65,"view_count":66,"doi":8,"paper":8,"created_at":67},1128,"第十一届APEC粮食安全部长级会议在杭州召开 通过《创新与数字化增强亚太区域粮食体系韧性原则文件》","https:\u002F\u002Fwww.workercn.cn\u002Fpapers\u002Fgrrb\u002F2026\u002F08\u002F27\u002F8\u002Fnews-5.html","8月25日,第十一届APEC粮食安全部长级会议在浙江杭州召开,会议由农业农村部部长张柱主持。会议审议通过《第十一届APEC粮食安全部长级会议联合声明》《创新与数字化增强亚太区域粮食体系韧性原则文件》,后者围绕数据驱动与科学决策、技术创新与全链应用、广泛参与与普惠共享、多元协作与政企携手、系统思维与转型发展5方面原则,规划17项关键行动。FAO总干事屈冬玉强调亚太地区要把科技和AI放在农业粮食系统转型核心,SMART农业:S科学驱动、M机器学习、A人工智能、R韧性、T转型。",null,"本报讯（记者姜雨晴）8月25日，第十一届亚太经合组织（APEC）粮食安全部长级会议在浙江杭州召开。会议通过并发布《创新与数字化增强亚太区域粮食体系韧性原则文件》（以下简称原则文件），呼吁各经济体应用创新成果和人工智能等数字技术，提高粮食体系全链条的决策能力、互联互通水平和响应速度，推动粮食体系更好地预见风险、承受冲击、适应变化和恢复产能，提升运行效率和整体效能。\n\n2026年是APEC“中国年”，我国肩负东道主责任，与各经济体多轮磋商、深入交流，牵头起草该原则文件。8月21日，原则文件经APEC粮食安全政策伙伴关系机制2026年第二次全体会议审议通过后，提交第十一届APEC粮食安全部长级会议审议。\n\n原则文件围绕数据驱动与科学决策、技术创新与全链应用、广泛参与与普惠共享、多元协作与政企携手、系统思维与转型发展等5方面原则，规划了17项关键行动，凝聚各方共识，为今后一个时期深化亚太粮食安全合作提供行动方向。\n\n国家粮食和物资储备局局长刘焕鑫表示，中方愿与APEC各经济体携手，以落实原则文件为契机，秉持开放合作、互利共赢精神，持续开展政策对话，持续推进交往交流，持续深化务实合作，携手建设更具韧性、更有效率、更高质量的亚太粮食体系。","工人日报2026年8月27日","2026-08-25T12:00:00Z","政策",10,true,88,{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":21,"relevant":22,"comment":23},28,22,18,14,6,1,"APEC粮食安全部长级会议通过数字化韧性文件，国家级政策事件，信息具体，权威性高，但时效性稍弱。",[25],{"name":10,"url":6},[27,28,29,30],"数字农业","粮食安全","人工智能","APEC",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},"A8","yield-food-security","单产提升与粮食安全","\u002Ftopic\u002Ffield-crops\u002Fyield-food-security","A",[],{"status":39,"locked":40,"version":41,"method":42,"evidence":43},"classified",false,"2026-10-22.2","rules",{"candidates":44,"agricultural_evidence":14},[45,50,57],{"code":32,"score":46,"supported":14,"title":47,"abstract":48,"tags":49},12,[28],[28],[28],{"code":51,"score":52,"supported":14,"title":53,"abstract":54,"tags":56},"I2",4,[],[55],"机器学习",[29],{"code":58,"score":22,"supported":40,"title":59,"abstract":60,"tags":61},"I1",[],[],[27],[63,64],"人工智能 数字农业 粮食安全 APEC","人工智能 数字农业","人工智能数字农业粮食安全APEC-1128",5,"2026-08-31T00:08:54.562095Z",{"total":21,"page":22,"page_size":21,"items":69},[70,106,189,258,324,384],{"id":71,"title":72,"url":73,"summary":74,"summary_zh":8,"content":75,"source_name":76,"source_url":8,"published_at":77,"category":78,"cover_url":8,"hotness":13,"is_selected":14,"score":15,"score_detail":79,"sources":82,"tags":84,"primary_topic":88,"secondary_topics":89,"classification":90,"search_phrases":101,"slug":104,"view_count":52,"doi":8,"paper":8,"created_at":105},882,"中国在APEC粮食安全高级别政企对话会提出AI保护粮食安全三项倡议","https:\u002F\u002Fwww.toutiao.com\u002Farticle\u002F7676792582709543459","8月20日APEC粮食安全高级别政企对话会在辽宁大连举行，国家粮食和物资储备局局长刘焕鑫代表中方提出三点倡议：第一推动人工智能、数字技术和智能加工在粮食产业全链条规模化应用，促进\"可信数据共享\"，为风险研判、政策制定和应急响应提供依据；强调AI要从田间延伸至收购、仓储、物流、加工、销售乃至政府风险预警系统等\"全链条\"场景。中方今年担任APEC东道主将\"开放、创新、合作\"确定为优先领域，人工智能放在\"创新\"突出位置。","2026-08-22 17:56·[观察者网](https:\u002F\u002Fwww.toutiao.com\u002Fc\u002Fuser\u002Ftoken\u002FMS4wLjABAAAAjMIvjM9ZCTBrb2fOwv_KpFPQ6MJh6iHm2OlIm9xgyJk\u002F?source=tuwen_detail)\n\n中国今年在APEC重点推进的两条议程，正在越来越明显地交汇到一起：一条是人工智能，另一条是粮食安全。\n\n8月20日，在辽宁大连举行的APEC粮食安全高级别政企对话会上，国家粮食和物资储备局局长刘焕鑫代表中方向APEC各经济体提出三点倡议。其中第一项，就是推动人工智能、数字技术和智能加工在粮食产业全链条规模化应用，并促进“可信数据共享”，为风险研判、政策制定和应急响应提供依据。\n\n![Image 1](https:\u002F\u002Fp3-sign.toutiaoimg.com\u002Ftos-cn-i-axegupay5k\u002F0c9e29924fab4188ae6e26ad445e437d~tplv-tt-origin-web:gif.jpeg?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1788134798&x-signature=%2BRkYKRHCdSRllwkSWYJi0SUuQx8%3D)\n8月20日，亚太经合组织（APEC）粮食安全高级别政企对话会在辽宁省大连市举行国家粮食和物资储备局\n\n这里的关键词不是简单的“智慧农业”，而是“全链条”。\n\n也就是说，AI要进入的不只是田间地头，还包括粮食收购、仓储、物流、加工、销售乃至政府的风险预警系统。粮食安全正在从过去主要依靠增产、库存和贸易渠道，增加一套新的能力——用数据提前发现风险，再用算法提高整个供应链的调度效率。\n\n这恰好接上了中国今年在APEC大力推动的另一项议程。\n\n中国担任2026年APEC东道主，将“开放、创新、合作”确定为三项优先领域，人工智能被放在“创新”的突出位置。7月23日，APEC数字与人工智能部长会议在成都举行并发表《成都声明》，明确继续落实《APEC人工智能倡议（2026—2030年）》；第二天举行的APEC人工智能高级别论坛，又把讨论重点进一步转向AI如何真正进入经济和社会应用场景。\n\n这份五年AI倡议是在2025年韩国庆州APEC会议期间通过的，并非今年才由中国提出。但2026年恰恰是其实施的第一年，中国作为东道主正在把“AI合作”向具体行业推进。\n\n粮食安全就是其中一个非常现实的落点。\n\n原因并不难理解。粮食供应链面对的是一个高度复杂、同时越来越难预测的系统：高温、洪水可能突然影响产量，地缘冲突和出口限制可能改变国际价格，港口和航运中断又可能迅速传导至进口国。APEC秘书处在介绍今年大连会议时，也直接把供应链扰动、极端天气和粮食安全联系在一起。\n\nAI无法凭空多生产粮食，却可以帮助回答几个越来越重要的问题：哪里可能减产、哪里的库存正在下降、哪一段运输线路出现异常、价格是否存在快速上涨风险，以及出现突发情况后，粮食应该从哪里调往哪里。\n\n因此，中方此次特别提出“可信数据共享”，意义可能比单纯推广几个AI应用更大。农业和粮食数据长期分散在政府、企业、农场、仓储和物流体系中。如果不同经济体之间能够逐步建立数据交换、风险预警和技术合作机制，AI才可能真正从单个企业提高效率的工具，升级为区域粮食安全治理的基础设施。\n\n当然，这也是最难的一步。APEC的21个成员经济体在农业规模、数字基础设施和数据规则上的差距非常大，所以中方第二项倡议专门提出帮助小规模生产者、中小微企业和初创企业获得技术、融资和市场机会，第三项则提出推动政府、企业、科研机构和国际组织共同参与。\n\n接下来值得观察的是8月24日至25日在杭州举行的APEC粮食安全部长会议。\n\n如果相关思路进一步进入部长会议成果，那么中国今年推动的APEC人工智能议程，就不再只是围绕大模型、数据和技术规则展开，而开始进入一个更传统、也更现实的领域。\n\nAI竞争的下一阶段，可能不只是比谁的模型更聪明，还要比谁能把算法真正嵌进粮仓、港口和供应链。\n\n**本文系观察者网独家稿件，未经授权，不得转载。**","观察者网 2026-08-22","2026-08-22T00:00:00Z","报道",{"impact":17,"substance":18,"depth":19,"authority":46,"freshness":80,"relevant":22,"comment":81},8,"报道中国在APEC提出AI保护粮食安全倡议，涉及国际政策与产业级影响，内容详实，信源权威，时效性良好。",[83],{"name":76,"url":73},[28,29,30,85,86,87],"可信数据共享","全链条","国家粮食和物资储备局",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":40,"version":41,"method":42,"evidence":91},{"candidates":92,"agricultural_evidence":14},[93,97],{"code":32,"score":46,"supported":14,"title":94,"abstract":95,"tags":96},[28],[28],[28],{"code":51,"score":22,"supported":40,"title":98,"abstract":99,"tags":100},[],[],[29],[102,103],"国家粮食和物资储备局 可信数据共享 人工智能 粮食安全","国家粮食和物资储备局 可信数据共享","国家粮食和物资储备局可信数据共享人工智能粮食安全-882","2026-08-24T00:06:08.726661Z",{"id":107,"title":108,"url":109,"summary":110,"summary_zh":111,"content":8,"source_name":112,"source_url":109,"published_at":113,"category":114,"cover_url":8,"hotness":13,"is_selected":40,"score":115,"score_detail":116,"sources":122,"tags":124,"primary_topic":128,"secondary_topics":129,"classification":130,"search_phrases":163,"slug":166,"view_count":167,"doi":168,"paper":169,"created_at":188},5491,"Analysis of the Impact of Digital Technology on the Resilience of Anhui’s Agricultural Industry Chain: Threshold Effect of Relative Grain Yield","https:\u002F\u002Fdoi.org\u002F10.3390\u002Fsu182010656","Improving the resilience of the agricultural industry chain to frequent external shocks and the intertwined agricultural production risks is critical for ensuring national food security and sustainable agricultural development. Taking the 16 prefecture-level cities in Anhui Province—a major grain-producing region in China—as the research sample, two composite proxy indices were constructed in this study; namely, an agricultural industry chain resilience index built upon aggregate official statistics (rather than direct observed shock-response outcomes) and an index capturing broad rural digital development instead of purely agriculture-specific digital adoption. Based on balanced panel data from 2015 to 2024, two-way fixed-effect, mediation-effect, and panel-threshold models were adopted in this study to examine the association, mediating mechanism, regional heterogeneity, and threshold characteristics conditioned on the relative grain yield. The empirical results show that the rural-oriented digital development index is significantly and robustly positively associated with our composite agricultural industry chain resilience proxy. Although agricultural TFP exhibits a statistically detectable partial mediating pattern in this correlational relationship, the economic magnitude of this indirect channel is extremely modest. As such, this finding indicates a potential theoretical transmission pathway rather than providing definitive empirical evidence for a causal mechanism. The promotion effect exhibits clear regional heterogeneity, with the strongest effect in Northern Anhui, followed by Central Anhui, while the coefficient is positive but insignificant in Southern Anhui. Furthermore, a single-threshold effect of the relative grain yield is identified; that is, the positive association between rural-oriented digital development and resilience proxy cannot be statistically detected when the grain yield remains below the threshold. Only after the agricultural grain yield increases can digital-related rural development release its resilience-related empowering dividends. We note that both composite indices are subject to measurement constraints linked to the local agricultural economic scale and broad rural digital conditions; these limitations are further discussed in the paper. This study provides empirical correlational evidence for the implementation of differentiated digital agriculture policies in major grain-producing provinces.","提升农业产业链对频繁外部冲击与交织叠加的农业生产风险的韧性，对保障国家粮食安全和农业可持续发展至关重要。本研究以中国粮食主产省安徽省的16个地级市为研究样本，构建了两个复合代理指标：一是基于官方统计数据总量（而非直接观测的冲击—响应结果）构建的农业产业链韧性指数，二是刻画农村数字化广泛发展（而非单纯农业领域数字化应用）的指数。基于2015—2024年平衡面板数据，本研究采用双向固定效应模型、中介效应模型和面板门槛模型，考察二者之间的关联、中介机制、区域异质性以及以相对粮食产量为条件变量的门槛特征。实证结果表明，农村导向的数字化发展指数与本研究的农业产业链韧性复合代理指标之间存在显著且稳健的正向关联。尽管农业全要素生产率在这一相关关系中呈现出统计上可检测的部分中介模式，但该间接渠道的经济量级极为有限。因此，这一发现指示的是一种潜在的理论传导路径，而非为因果机制提供确凿的实证证据。其促进效应表现出明显的区域异质性，皖北效应最强，皖中次之，皖南系数为正但不显著。此外，还识别出相对粮食产量的单一门槛效应，即当粮食产量低于门槛值时，农村导向的数字化发展与韧性代理指标之间的正向关联在统计上无法被检测到；只有在农业粮食产量提高之后，数字相关农村发展才能释放其韧性赋能红利。我们注意到，两个复合指数均受到与地方农业经济规模和农村数字化总体状况相关的测度约束；这些局限性在文中进一步讨论。本研究为粮食主产省实施差异化数字农业政策提供了实证相关性证据。","Sustainability","2026-10-20T00:00:00Z","论文",74,{"impact":117,"substance":118,"depth":119,"authority":120,"freshness":80,"relevant":22,"comment":121},16,20,17,13,"基于安徽16市面板数据的实证研究，方法规范、结论有区域异质性价值，但属省级学术论文，公共影响有限，适合作为主题页聚合素材而非头条精选。",[123],{"name":112,"url":109},[27,125,28,126,127],"数字乡村","农业产业链韧性","安徽农业",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":40,"version":41,"method":42,"evidence":131},{"candidates":132,"agricultural_evidence":14},[133,139,144,151,158],{"code":32,"score":134,"supported":14,"title":135,"abstract":136,"tags":138},7,[],[28,137],"food security",[28],{"code":58,"score":134,"supported":14,"title":140,"abstract":141,"tags":143},[],[27,142],"digital agriculture",[27],{"code":145,"score":21,"supported":14,"title":146,"abstract":147,"tags":150},"G",[],[148,149],"农村发展","rural development",[],{"code":152,"score":153,"supported":14,"title":154,"abstract":155,"tags":157},"J1",3,[],[156],"农业政策",[],{"code":159,"score":22,"supported":40,"title":160,"abstract":161,"tags":162},"I6",[],[],[125],[164,165],"安徽 农业产业链韧性 数字技术","安徽 粮食产量 数字乡村","安徽农业产业链韧性数字技术-5491",0,"10.3390\u002Fsu182010656",{"doi":168,"openalex_id":170,"authors":171,"venue":112,"cited_by_count":167,"oa_url":109,"card":181,"direction":185,"ingested_from":187},"W7223005655",[172,175,177,179],{"name":173,"orcid":174},"Lan Ma","https:\u002F\u002Forcid.org\u002F0000-0003-2468-9917",{"name":176,"orcid":8},"Yuyan Li",{"name":178,"orcid":8},"张国亮",{"name":180,"orcid":8},"Yaoyao Li",{"tldr":182,"method":183,"finding":184,"direction":185,"opportunity":186},"以安徽16市面板数据检验农村数字发展对农业产业链韧性的影响及粮食产量门槛效应。","2015—2024年安徽16市平衡面板，双向固定效应、中介效应与面板门槛模型。","数字发展显著提升产业链韧性，存在粮食相对产量单门槛，且皖北效应最强、皖南不显著。","数字乡村与农业信息化","可细化数字技术指标、引入真实冲击响应韧性测度，并探究门槛形成机制与皖南失效原因。","openalex","2026-10-21T23:30:29.219265Z",{"id":190,"title":191,"url":192,"summary":193,"summary_zh":8,"content":8,"source_name":194,"source_url":8,"published_at":8,"category":114,"cover_url":8,"hotness":195,"is_selected":40,"score":196,"score_detail":197,"sources":201,"tags":206,"primary_topic":210,"secondary_topics":211,"classification":212,"search_phrases":241,"slug":244,"view_count":21,"doi":245,"paper":246,"created_at":257},4969,"Digital technology, agricultural resilience, and food security: A mini review","https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fsustainable-food-systems\u002Farticles\u002F10.3389\u002Ffsufs.2026.2002109\u002Ffull","Shen在《Frontiers in Sustainable Food Systems》(2026)发表的综述综合了国际数字农业文献与中国'数字经济—农业经济韧性'研究两条主线。提出三点发现:一是数字技术通过不同机制强化食物安全的四个维度——可获得性(生产力与投入效率)、可及性(市场信息与数字金融)、稳定性(溯源、预警与保险)、利用性(溯源、营养信息与移动支付);二是准自然实验证据显示数字基础设施、数字金融和人工智能主要通过社会化服务、土地流转、产业融合、人力资本而非仅'采纳'提升粮食生产与价值链韧性;三是收益分布不均,空间溢出方向取决于吸收能力、市场整合与要素流动性。","Frontiers in Sustainable Food Systems 2026",25,77,{"impact":18,"substance":198,"depth":19,"authority":20,"freshness":199,"relevant":22,"comment":200},21,2,"核心期刊综述，系统梳理数字技术强化粮食安全四维度的机制与准自然实验证据，兼具国际文献与中国经验，但发布日期不明、时效性偏弱，适合作为主题页深度聚合素材。",[202,203],{"name":194,"url":192},{"name":204,"url":205},"Frontiers in Sustainable Food Systems","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.2002109",[27,28,207,208,209],"农业韧性","空间溢出","数字金融",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":40,"version":41,"method":42,"evidence":213},{"candidates":214,"agricultural_evidence":14},[215,220,227,231,236],{"code":32,"score":216,"supported":14,"title":217,"abstract":218,"tags":219},9,[137],[],[28],{"code":221,"score":21,"supported":14,"title":222,"abstract":223,"tags":226},"G2",[],[224,225],"土地流转","社会化服务",[],{"code":58,"score":52,"supported":14,"title":228,"abstract":229,"tags":230},[],[27],[27],{"code":232,"score":22,"supported":40,"title":233,"abstract":234,"tags":235},"G3",[],[],[209],{"code":237,"score":22,"supported":40,"title":238,"abstract":239,"tags":240},"I4",[],[],[208],[242,243],"Frontiers in Sustainable Food Systems 数字农业","数字技术 农业韧性 粮食安全","FrontiersinSustainableFoodSystems数字农业-4969","10.3389\u002Ffsufs.2026.2002109\u002Ffull",{"doi":245,"openalex_id":247,"authors":248,"venue":204,"cited_by_count":167,"oa_url":205,"card":252,"direction":185,"ingested_from":187},"W7223134273",[249],{"name":250,"orcid":251},"Yang Shen","https:\u002F\u002Forcid.org\u002F0000-0002-6781-6915",{"tldr":253,"method":254,"finding":255,"direction":185,"opportunity":256},"综述数字技术通过多机制强化食物安全四维度并提升农业韧性，但收益分布不均。","综合国际数字农业文献与中国数字经济—农业经济韧性研究两条主线。","数字技术经社会化服务、土地流转等提升韧性，收益不均且空间溢出取决于吸收能力。","可探究数字技术收益不均的成因及吸收能力、市场整合对空间溢出方向的调节机制。","2026-10-15T00:06:08.890950Z",{"id":259,"title":260,"url":261,"summary":262,"summary_zh":263,"content":8,"source_name":264,"source_url":261,"published_at":265,"category":114,"cover_url":8,"hotness":13,"is_selected":40,"score":266,"score_detail":267,"sources":269,"tags":271,"primary_topic":275,"secondary_topics":276,"classification":277,"search_phrases":307,"slug":310,"view_count":22,"doi":311,"paper":312,"created_at":323},4600,"Optimization model of agricultural economic structure based on LSTM","https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs42452-026-09594-x","With the development of artificial intelligence (AI) and agricultural big data, the adjustment of agricultural economic structure has shifted from empirical judgment to data-driven decision-making. This study uses the provincial panel data of agricultural economy in Hubei Province from 2010 to 2023 to construct a comprehensive framework of prediction and optimization. The forecasting layer uses the Long Short-Term Memory (LSTM) model to capture the dynamic relationship among agricultural GDP growth rate, main crop output, rural employment structure, agricultural product price index, financial subsidies and agricultural infrastructure investment. The optimization layer uses the prediction results as parameters. It defines three objectives. overall agricultural benefit, structural deviation and food security risk. It also includes restrictions on cultivated land area, budget, labor supply and food security. Based on these backgrounds, the adjustment scheme of agricultural economic structure was formulated. The results show that the Mean Absolute Error (MAE), Root Mean Square Error (RMSE) and r of LSTM model are 0.32, 0.45 and 0.91 respectively. Its prediction performance is better than autoregressive moving average (ARIMA), back propagation neural network (BPNN), support vector regression (SVR) and random forest (RF). These findings show that the combination of multivariate collaborative forecasting and structural optimization constraints can improve the efficiency of agricultural resource allocation. This method also provides quantitative support for rural revitalization, food security and digital agriculture policy design.","随着人工智能（AI）与农业大数据的发展，农业经济结构调整已从经验判断转向数据驱动决策。本研究利用2010—2023年湖北省农业经济省级面板数据，构建了预测与优化的综合框架。预测层采用长短期记忆（LSTM）模型，捕捉农业GDP增长率、主要作物产量、农村就业结构、农产品价格指数、财政补贴与农业基础设施投资之间的动态关系。优化层以预测结果作为参数，设定三个目标：农业整体效益、结构性偏差与粮食安全风险，并纳入耕地面积、预算、劳动力供给与粮食安全等约束条件。在此基础上，制定农业经济结构调整方案。结果表明，LSTM模型的平均绝对误差（MAE）、均方根误差（RMSE）与r分别为0.32、0.45和0.91，其预测性能优于自回归移动平均（ARIMA）、反向传播神经网络（BPNN）、支持向量回归（SVR）与随机森林（RF）。这些发现表明，多变量协同预测与结构优化约束的结合能够提高农业资源配置效率。该方法也为乡村振兴、粮食安全与数字农业政策设计提供了量化支持。","Discover Applied Sciences","2026-10-09T00:00:00Z",75,{"impact":117,"substance":118,"depth":119,"authority":120,"freshness":216,"relevant":22,"comment":268},"基于湖北省级面板数据构建LSTM预测与多目标优化框架，方法对比充分、结论有量化支撑，对数字农业与乡村振兴政策设计具参考价值。",[270],{"name":264,"url":261},[27,272,28,273,274],"农业人工智能","农业经济结构","LSTM预测",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":40,"version":41,"method":42,"evidence":278},{"candidates":279,"agricultural_evidence":14},[280,284,288,293,298,303],{"code":32,"score":134,"supported":14,"title":281,"abstract":282,"tags":283},[],[28,137],[28],{"code":58,"score":134,"supported":14,"title":285,"abstract":286,"tags":287},[],[27,142],[27],{"code":51,"score":52,"supported":14,"title":289,"abstract":290,"tags":292},[],[291],"artificial intelligence",[272],{"code":145,"score":153,"supported":14,"title":294,"abstract":295,"tags":297},[],[296],"乡村振兴",[],{"code":159,"score":153,"supported":14,"title":299,"abstract":300,"tags":302},[],[301],"农业大数据",[],{"code":152,"score":153,"supported":14,"title":304,"abstract":305,"tags":306},[],[156],[],[308,309],"湖北 农业经济结构 LSTM","农业经济结构 优化模型","湖北农业经济结构LSTM-4600","10.1007\u002Fs42452-026-09594-x",{"doi":311,"openalex_id":313,"authors":314,"venue":264,"cited_by_count":167,"oa_url":261,"card":317,"direction":185,"ingested_from":187},"W7221088951",[315],{"name":316,"orcid":8},"Xue Gong",{"tldr":318,"method":319,"finding":320,"direction":321,"opportunity":322},"用LSTM预测湖北农业经济指标，并构建多目标优化模型调整农业结构。","LSTM预测2010-2023年湖北面板数据，结合多目标优化与约束条件。","LSTM预测精度优于ARIMA、BPNN等，优化方案可提升农业资源配置效率。","农业人工智能与决策模型","可探索将LSTM与多目标优化耦合框架推广至其他省份或作物类型，并引入实时数据流。","2026-10-10T23:30:34.807708Z",{"id":325,"title":326,"url":327,"summary":328,"summary_zh":329,"content":8,"source_name":330,"source_url":327,"published_at":331,"category":114,"cover_url":8,"hotness":13,"is_selected":40,"score":332,"score_detail":333,"sources":335,"tags":337,"primary_topic":340,"secondary_topics":341,"classification":342,"search_phrases":361,"slug":364,"view_count":153,"doi":365,"paper":366,"created_at":383},1746,"Digitization in Agriculture and Food Security in Sub-Saharan Africa: A Systematic Review","https:\u002F\u002Fdoi.org\u002F10.70382\u002Fajbar.v13i1.032","Digitization is increasingly recognized as a transformative force in Sub-Saharan Africa’s (SSA) agricultural sector, with significant implications for productivity enhancement and food security improvement. This systematic review examines the role of digital technologies in agriculture, focusing on their contributions to food availability, accessibility, utilization, and stability across SSA. The study adopts a systematic literature review (SLR) methodology, drawing evidence from peer-reviewed journals and reports published by institutions such as the World Bank, FAO, IFAD, and the African Development Bank between 2015 and 2025. Findings reveal that digital agriculture interventions, including mobile advisory systems, precision agriculture tools, digital financial services, and e-market platforms, significantly improve agricultural productivity, reduce transaction costs, strengthen market integration, and enhance farmers’ access to financial services. However, adoption remains uneven due to infrastructural deficits, digital illiteracy, gender inequality, and weak institutional frameworks. The review concludes that while digitization holds strong potential to transform food systems in SSA, its effectiveness depends on enabling environments such as infrastructure development, inclusive policies, and capacity building. The study recommends strengthening digital infrastructure, improving literacy programs, and expanding public–private partnerships to accelerate inclusive digital transformation in agriculture.","数字化日益被视为撒哈拉以南非洲（SSA）农业部门的变革性力量，对提高生产力和改善粮食安全具有重大意义。本系统综述考察了数字技术在农业中的作用，重点关注其对撒哈拉以南非洲粮食可得性、可及性、利用和稳定性的贡献。研究采用系统文献综述（SLR）方法，借鉴了2015年至2025年间同行评审期刊以及世界银行、联合国粮农组织（FAO）、国际农业发展基金（IFAD）和非洲开发银行等机构发布的报告中的证据。研究结果表明，包括移动咨询系统、精准农业工具、数字金融服务和电子市场平台在内的数字农业干预措施，显著提高了农业生产力，降低了交易成本，加强了市场整合，并增强了农民获取金融服务的机会。然而，由于基础设施不足、数字文盲、性别不平等和制度框架薄弱，数字技术的采用仍不均衡。本综述得出结论：尽管数字化在改变撒哈拉以南非洲粮食系统方面具有巨大潜力，但其有效性取决于有利环境，如基础设施发展、包容性政策和能力建设。研究建议加强数字基础设施建设，改善扫盲计划，并扩大公私伙伴关系，以加速农业领域的包容性数字化转型。","Journal of Biotechnology and Agricultural Research","2026-09-04T00:00:00Z",70,{"impact":19,"substance":118,"depth":19,"authority":46,"freshness":199,"relevant":22,"comment":334},"系统综述非洲数字农业对粮食安全的影响，证据扎实，但时效性低，适合精选。",[336],{"name":330,"url":327},[27,338,28,339],"系统综述","非洲农业",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":40,"version":41,"method":42,"evidence":343},{"candidates":344,"agricultural_evidence":14},[345,350,356],{"code":32,"score":346,"supported":14,"title":347,"abstract":348,"tags":349},15,[137],[28,137],[28],{"code":58,"score":13,"supported":14,"title":351,"abstract":352,"tags":355},[],[353,27,354,142],"精准农业","precision agriculture",[27],{"code":357,"score":22,"supported":40,"title":358,"abstract":359,"tags":360},"J3",[],[],[339],[362,363],"数字农业 粮食安全 系统综述 非洲农业","数字农业 粮食安全","数字农业粮食安全系统综述非洲农业-1746","10.70382\u002Fajbar.v13i1.032",{"doi":365,"openalex_id":367,"authors":368,"venue":330,"cited_by_count":167,"oa_url":327,"card":378,"direction":185,"ingested_from":187},"W7208759473",[369,372,374,376],{"name":370,"orcid":371},"Funso O. Alabuja","https:\u002F\u002Forcid.org\u002F0000-0002-7579-1041",{"name":373,"orcid":8},"Ejiofor D. Chukwubuike",{"name":375,"orcid":8},"Lateefah O. Lama-Abdul",{"name":377,"orcid":8},"Olabiyi Fatimah Adebisi",{"tldr":379,"method":380,"finding":381,"direction":185,"opportunity":382},"系统综述撒哈拉以南非洲农业数字化对粮食安全的影响，发现其提升生产力但采用不均。","系统文献综述，分析2015-2025年同行评审文献及国际机构报告。","数字农业提高生产力、降低交易成本，但受基础设施、数字素养等制约。","可研究数字农业采用不均的驱动因素，如性别差异、制度障碍，探索包容性数字化路径。","2026-09-05T23:30:35.595189Z",{"id":385,"title":386,"url":387,"summary":388,"summary_zh":8,"content":8,"source_name":389,"source_url":8,"published_at":390,"category":78,"cover_url":8,"hotness":13,"is_selected":14,"score":15,"score_detail":391,"sources":393,"tags":395,"primary_topic":399,"secondary_topics":400,"classification":401,"search_phrases":412,"slug":415,"view_count":153,"doi":8,"paper":8,"created_at":416},943,"刘国中出席第十一届亚太经合组织粮食安全部长级会议开幕式并致辞","https:\u002F\u002Fszb.farmer.com.cn\u002Fnmrb\u002Fhtml\u002F2026\u002F20260826\u002F20260826_1\u002Fnmrb_20260826_13388_1_2092322241576538120.html","新华社杭州8月25日电：第十一届亚太经合组织(APEC)粮食安全部长级会议8月25日在浙江杭州召开，中共中央政治局委员、国务院副总理刘国中出席开幕式并致辞。刘国中提出4点建议：聚焦产能提升、强化创新驱动、畅通贸易循环、坚持普惠包容，共同构建更加稳固的亚太粮食安全体系。本次会议以「建设亚太共同体，促进共同繁荣」为主题，来自APEC经济体、秘书处和有关国际组织代表近200人参会。中方在会议期间重申「以我为主、立足国内、确保产能、适度进口、科技支撑」的粮食安全战略，并与越南、新西兰等多国部长展开双边会谈。","农民日报 2026-08-26 第1版","2026-08-26T00:00:00Z",{"impact":17,"substance":118,"depth":346,"authority":346,"freshness":13,"relevant":22,"comment":392},"国家级粮食安全会议，政策导向明确，信息权威且时效性强。",[394],{"name":389,"url":387},[28,396,397,30,398],"国际合作","刘国中","杭州",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":40,"version":41,"method":42,"evidence":402},{"candidates":403,"agricultural_evidence":14},[404,408],{"code":32,"score":46,"supported":14,"title":405,"abstract":406,"tags":407},[28],[28],[28],{"code":357,"score":22,"supported":40,"title":409,"abstract":410,"tags":411},[],[],[396],[413,414],"国际合作 粮食安全 刘国中 杭州","国际合作 粮食安全","国际合作粮食安全刘国中杭州-943","2026-08-26T00:09:29.372868Z"]