[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-1749":3,"related-1749":80},{"id":4,"title":5,"url":6,"summary":7,"summary_zh":8,"content":9,"source_name":10,"source_url":6,"published_at":11,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":16,"sources":23,"tags":25,"primary_topic":9,"secondary_topics":30,"classification":31,"search_phrases":43,"slug":46,"view_count":21,"doi":47,"paper":48,"created_at":79},1749,"LED lighting as a solution for turf shading: insights from a systemic assessment of Seashore paspalum and Zoysia japonica","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffpls.2026.1936506","Introduction The roof structures of professional enclosed stadiums often cause shading problems on the turf, posing a major challenge to maintaining turf quality and efficient management. Artificial lighting has been applied to address this issue, particularly light-emitting diode (LED). Methods To evaluate the efficacy of LED with a specific wavelength in alleviating the adverse effects of shade stress on turfgrasses, we conducted a systematic and multi-dimensional assessment of Seashore paspalum ( Paspalum vaginatum Sw.) and Zoysia japonica ( Zoysia japonica Steud.) turf under three light conditions: natural lighting, shading, and LED, within a stadium. Results The results demonstrated that LED effectively alleviated shade-induced light limitation. It maintained turf normalized difference vegetation index (NDVI) and chlorophyll content at levels comparable to those under natural light. Furthermore, LED treatment improved physiological responses associated with shade stress, as indicated by enhanced cell membrane stability, reduced membrane lipid peroxidation, and altered antioxidant-related responses, including increased superoxide dismutase (SOD) activity and dynamic changes in peroxidase (POD) activity. Regarding root morphology, LED treatment reduced the shade-induced increases in specific root length (SRL) and specific root surface area (SRA), suggesting a modification of shade-induced root morphological responses. Principal component analysis (PCA) revealed distinct multivariate response patterns associated with different light environments. Correlation analysis further indicated significant associations among NDVI, chlorophyll content, and antioxidant-related traits across different light environments. These associations suggested that turf performance under LED lighting was related to concurrent variation in chlorophyll content and antioxidant-related traits. Discussion In conclusion, applying LED lighting can effectively improve turf recovery-related traits and physiological status through improvements in canopy characteristics, chlorophyll status, antioxidant-related responses, and root morphological traits. This study demonstrated under a real stadium environment that specific LED lighting can serve as an effective supplemental light source for improving turf performance in shaded areas, providing practical guidance for stadium turf management.","引言 专业封闭式体育场的屋顶结构常导致草坪遮荫问题，对维持草坪质量和高效管理构成重大挑战。人工照明已被应用于解决这一问题，尤其是发光二极管（LED）。方法 为评估特定波长的LED在缓解遮荫胁迫对草坪草不利影响方面的效果，我们在体育场内三种光照条件下——自然光照、遮荫和LED——对海滨雀稗（Paspalum vaginatum Sw.）和结缕草（Zoysia japonica Steud.）草坪进行了系统且多维度的评估。结果 结果表明，LED有效缓解了遮荫引起的光照限制。它使草坪归一化植被指数（NDVI）和叶绿素含量维持在接近自然光照条件下的水平。此外，LED处理改善了与遮荫胁迫相关的生理响应，表现为细胞膜稳定性增强、膜脂过氧化降低以及抗氧化相关响应的改变，包括超氧化物歧化酶（SOD）活性升高和过氧化物酶（POD）活性的动态变化。在根系形态方面，LED处理减少了遮荫引起的比根长（SRL）和比根表面积（SRA）的增加，表明其对遮荫诱导的根系形态响应具有调节作用。主成分分析（PCA）揭示了不同光照环境下不同的多变量响应模式。相关性分析进一步表明，在不同光照环境下，NDVI、叶绿素含量和抗氧化相关性状之间存在显著关联。这些关联表明，LED光照下草坪的表现与叶绿素含量和抗氧化相关性状的同步变化有关。讨论 总之，应用LED照明可通过改善冠层特征、叶绿素状态、抗氧化相关响应和根系形态性状，有效提升草坪恢复相关性状和生理状态。本研究在真实体育场环境下证明，特定LED照明可作为遮荫区域改善草坪表现的有效的补充光源，为体育场草坪管理提供了实践指导。",null,"Frontiers in Plant Science","2026-09-04T00:00:00Z","论文",10,false,66,{"impact":17,"substance":18,"depth":18,"authority":19,"freshness":20,"relevant":21,"comment":22},12,18,13,5,1,"针对体育场草坪遮阴问题，系统评估LED补光对两种暖季型草坪的恢复效果，为设施草坪管理提供科学依据。",[24],{"name":10,"url":6},[26,27,28,29],"智慧农业","设施农业","草坪管理","LED补光",[],{"status":32,"locked":14,"version":33,"method":34,"evidence":35},"needs_review","2026-10-22.2","rules",{"candidates":36,"agricultural_evidence":14,"reason":42},[37],{"code":38,"score":21,"supported":14,"title":39,"abstract":40,"tags":41},"I1",[],[],[26],"农业相关性需要复核",[44,45],"智慧农业 草坪管理 设施农业 LED补光","智慧农业 草坪管理","智慧农业草坪管理设施农业LED补光-1749","10.3389\u002Ffpls.2026.1936506",{"doi":47,"openalex_id":49,"authors":50,"venue":10,"cited_by_count":69,"oa_url":70,"card":71,"direction":77,"ingested_from":78},"W7208726798",[51,53,55,57,59,62,64,67],{"name":52,"orcid":9},"Weihao Dou",{"name":54,"orcid":9},"Wan Geng",{"name":56,"orcid":9},"Weisen Sun",{"name":58,"orcid":9},"Jie Xu",{"name":60,"orcid":61},"Wenchao Zhang","https:\u002F\u002Forcid.org\u002F0000-0001-8803-224X",{"name":63,"orcid":9},"Guilong Song",{"name":65,"orcid":66},"Yufeng Chen","https:\u002F\u002Forcid.org\u002F0000-0003-2384-0777",{"name":68,"orcid":9},"Liebao Han",0,"https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fplant-science\u002Farticles\u002F10.3389\u002Ffpls.2026.1936506\u002Fpdf",{"tldr":72,"method":73,"finding":74,"direction":75,"opportunity":76},"研究LED光照对体育场遮荫草坪的缓解效果，评估两种草坪草的多维响应。","在真实体育场设置自然光、遮荫、LED三种光照，系统评估草坪生理和形态指标。","LED光照有效缓解遮荫胁迫，维持NDVI和叶绿素，改善抗氧化和根系形态。","智慧农业 \u002F 农业物联网","可探索LED光配方优化及在多种草坪草和不同遮荫程度下的应用，结合智能调控实现精准补光。","农业人工智能与决策模型","openalex","2026-09-05T23:30:45.430586Z",{"total":81,"page":21,"page_size":81,"items":82},6,[83,147,190,264,320,403],{"id":84,"title":85,"url":86,"summary":87,"summary_zh":9,"content":9,"source_name":88,"source_url":9,"published_at":89,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":90,"score_detail":91,"sources":96,"tags":98,"primary_topic":102,"secondary_topics":108,"classification":114,"search_phrases":134,"slug":137,"view_count":69,"doi":9,"paper":138,"created_at":146},5536,"日光温室番茄全生育期环境特征解析与智能调控决策支持方法","https:\u002F\u002Fpaper.sciencenet.cn\u002Fhtmlpaper\u002F2026\u002F10\u002F20261021145441802156759.shtm","研究解析日光温室番茄全生育期环境特征，发现该类温室气候缓冲能力较强、有效积温与番茄生理需求呈双峰匹配，但相对增益指标揭示单位时间热量供给失衡、深冬热量不足以及光能结构性不足、湿度调控昼夜失衡等问题。作者建议构建温度—光照—湿度耦合的智能闭环控制系统。","Agriculture 2026-10-21","2026-10-21T00:00:00Z",77,{"impact":92,"substance":93,"depth":94,"authority":19,"freshness":13,"relevant":21,"comment":95},16,21,17,"论文解析日光温室番茄全生育期环境特征并提出温光湿耦合智能调控方案，结论有新意，对设施农业信息化有参考价值。",[97],{"name":88,"url":86},[26,27,99,100,101],"环境调控","温室番茄","智能决策",{"code":103,"slug":104,"name":105,"path":106,"parent_code":107},"B7","protected-horticulture","设施园艺与植物工厂","\u002Ftopic\u002Fhorticulture\u002Fprotected-horticulture","B",[109],{"code":110,"slug":111,"name":112,"path":113,"parent_code":107},"B1","vegetables","蔬菜","\u002Ftopic\u002Fhorticulture\u002Fvegetables",{"status":115,"locked":14,"version":33,"method":34,"evidence":116},"classified",{"candidates":117,"agricultural_evidence":119},[118,124,130],{"code":103,"score":19,"supported":119,"title":120,"abstract":122,"tags":123},true,[121],"温室",[121],[100,99],{"code":110,"score":125,"supported":119,"title":126,"abstract":128,"tags":129},11,[127],"番茄",[127],[],{"code":38,"score":21,"supported":14,"title":131,"abstract":132,"tags":133},[],[],[26],[135,136],"日光温室 番茄 环境调控","温室番茄 智能闭环控制","日光温室番茄环境调控-5536",{"doi":9,"openalex_id":9,"authors":139,"venue":9,"cited_by_count":69,"oa_url":9,"card":140,"direction":75,"ingested_from":145},[],{"tldr":141,"method":142,"finding":143,"direction":75,"opportunity":144},"解析日光温室番茄全生育期环境特征并提出智能调控决策支持方法。","基于全生育期环境监测数据，分析积温匹配与相对增益指标。","温室缓冲力强但深冬热量不足、光能结构性不足、湿度昼夜失衡。","可研发温度—光照—湿度耦合的智能闭环控制算法，并验证其对番茄产量与能耗的协同优化效果。","agent","2026-10-22T00:07:10.129353Z",{"id":148,"title":149,"url":150,"summary":151,"summary_zh":9,"content":152,"source_name":153,"source_url":9,"published_at":154,"category":155,"cover_url":9,"hotness":13,"is_selected":14,"score":156,"score_detail":157,"sources":160,"tags":162,"primary_topic":166,"secondary_topics":167,"classification":168,"search_phrases":185,"slug":188,"view_count":21,"doi":9,"paper":9,"created_at":189},5257,"北京发布《北京市2026年智慧设施(种植)建设指南》分级建设\"数智京园\"","https:\u002F\u002Fk.sina.com.cn\u002Farticle_7517400647_1c0126e4705909clmq.html","北京市农业农村局印发《2026年智慧设施(种植)建设指南》,按基础版、升级版分级建设,适配不同主体不同设施不同生产需求,坚持\"优先选用适用技术,避免过度智能化浪费\";依托\"数智京园\"开展国产化智能控制技术\"赛马制\"验证,目前连栋温室国产系统产量与对照系统逐步齐平、商品果率提升。","设备好不好用，模型能不能适应自家大棚，经营主体更愿意到现场看一看。市场上智慧农业产品种类繁多，质量与售后不一，导致“不会选”。“数智京园”把验证、示范、选型推荐连起来，让农户先看实效再决定。\n\n在示范园区，合作社理事长、家庭农场主走进温室，查看智能调控效果，体验系统操作流程。不少园区在观摩后主动联系，希望接入“数智京园”。和合园作为集成展示点，集中呈现环境感知、卷膜卷被、水肥一体化、高压微雾，以及多光谱表型监测、智能植保、采摘机器人等装备，面向“头雁”、设施产业集群和产业园主体开展观摩，避免盲目跟风买高配、不适配设备。\n\n让农户放心选择，先要把技术的实际能力测清楚。首农翠湖智慧农业创新工场（以下简称“翠湖工场”）使用“数智京园”开展数字化管理，并另行开展连栋温室国产化智能控制技术“赛马制”验证。“验证不仅要看设备能否执行指令，还要看执行得是否及时、调控是否高效。”翠湖工场科技总监王利利介绍，国产系统产量与对照系统逐步齐平、商品果率提升后，园区选用国产系统也更有底气。\n\n让技术在真实场景中经受检验，也是“数智京园”推进应用的重要做法。围绕番茄、草莓、黄瓜、叶菜等作物，以及土壤、基质等栽培方式，在不同区域、不同茬口开展对照验证，检验环境控制、水肥调控的效果，再把成熟技术集成到“数智京园”中，形成可供不同园区选择的方案。2026年，北京市农业农村局印发了《北京市2026年智慧设施（种植）建设指南》，按照基础版、升级版分级建设，适配不同主体、不同设施和不同生产需求，坚持“优先选用适用技术，避免过度智能化浪费”，解决“不会选”。\n\n验证之后，还要让农户看得见、学得会。京郊的示范园区成为现场课堂，经营主体进棚看设备运行、体验农事排产，了解改造投入和生产收益。技术服务人员开展手把手培训，配合图文操作手册，帮助农户掌握使用方法。设备出现异常，通过远程诊断和现场维修处理，减少“坏了没人管”的顾虑。京品码追溯、智能采收秤等把生产、采收、包装数据打通，既方便劳动力考核，也方便消费者扫码看全过程。\n\n从验证到示范，再到推广，“数智京园”正把技术选择、生产应用和后续服务连成一条线。随着这套模式在更多设施大棚落地生根，智能管控将在京郊的一茬茬农事里持续发挥作用，让省下来的人工、节约的水肥和增加的收益，结出更多硕果，为首都乡村全面振兴注入强劲的数字动能。\n\n特别声明：以上文章内容仅代表作者本人观点，不代表新浪网观点或立场。如有关于作品内容、版权或其它问题请于作品发表后的30日内与新浪网联系。","新浪网转载(2026-10-19)","2026-10-19T00:00:00Z","政策",70,{"impact":18,"substance":158,"depth":92,"authority":81,"freshness":13,"relevant":21,"comment":159},20,"省级智慧设施建设指南，含分级建设、验证示范与推广服务链条等实质内容，对设施农业数字化有参考价值，但来源为商业门户转载，权威性一般。",[161],{"name":153,"url":150},[163,26,27,164,165],"数字乡村","北京","建设指南",{"code":103,"slug":104,"name":105,"path":106,"parent_code":107},[],{"status":115,"locked":14,"version":33,"method":34,"evidence":169},{"candidates":170,"agricultural_evidence":119},[171,176,180],{"code":103,"score":172,"supported":119,"title":173,"abstract":174,"tags":175},3,[],[121],[],{"code":38,"score":21,"supported":14,"title":177,"abstract":178,"tags":179},[],[],[26],{"code":181,"score":21,"supported":14,"title":182,"abstract":183,"tags":184},"I6",[],[],[163],[186,187],"北京 数智京园 建设指南","北京 智慧设施 种植 分级建设","北京数智京园建设指南-5257","2026-10-19T00:07:31.752116Z",{"id":191,"title":192,"url":193,"summary":194,"summary_zh":195,"content":9,"source_name":196,"source_url":193,"published_at":197,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":198,"score_detail":199,"sources":203,"tags":205,"primary_topic":209,"secondary_topics":215,"classification":216,"search_phrases":238,"slug":241,"view_count":172,"doi":242,"paper":243,"created_at":263},4108,"Visión artificial para la detección de plagas en cultivos de tomate: revisión sistemática de la literatura","https:\u002F\u002Fdoi.org\u002F10.36825\u002Friti.14.34.010","Phytosanitary monitoring is an essential activity for reducing production losses caused by pests in tomato crops grown under protected agriculture conditions. In recent years, computer vision and deep learning methods have gained relevance as tools capable of automating agricultural image detection and analysis processes. Despite these advances, there is still a need to determine which techniques have been used, under what conditions they have been evaluated, and what performance they have reported, particularly in protected agriculture and small-scale production contexts. This study aims to examine research published on these technologies and assess their potential incorporation into participatory agricultural monitoring schemes. To this end, a systematic review of scientific literature published between 2020 and 2026 was conducted following the methodological guidelines proposed by Kitchenham. The review was developed through the stages of planning, study search and selection, and information synthesis, considering previously established inclusion and exclusion criteria. As a result, fifty studies related to image processing, artificial intelligence, and phytosanitary monitoring were selected and analyzed. Among the main findings of the review, several studies reported high-performance levels for deep learning models in tasks involving the automatic identification of symptoms associated with pests and other crop-related conditions. The synthesis identified the main techniques, data, application contexts, and reported performance levels, providing reference elements for assessing their potential incorporation into participatory agricultural monitoring schemes.","植物检疫监测是减少保护地番茄种植中由有害生物造成的产量损失的一项重要活动。近年来，计算机视觉和深度学习方法作为能够自动化农业图像检测与分析流程的工具而日益受到重视。尽管取得了这些进展，但仍需明确已采用了哪些技术、这些技术在何种条件下进行了评估，以及它们报告了怎样的性能，尤其是在保护地农业和小规模生产情境下。本研究旨在考察已发表的关于这些技术的研究，并评估其纳入参与式农业监测方案的潜力。为此，按照Kitchenham提出的方法学指南，对2020年至2026年间发表的科学文献进行了系统综述。该综述通过规划、研究检索与筛选以及信息综合等阶段展开，并依据事先确立的纳入与排除标准。结果共筛选并分析了50项与图像处理、人工智能和植物检疫监测相关的研究。在综述的主要发现中，多项研究报告了深度学习模型在自动识别与有害生物相关的症状及其他作物相关状况的任务中具有高性能水平。该综合识别了主要技术、数据、应用情境及所报告的性能水平，为评估其纳入参与式农业监测方案的潜力提供了参考要素。","Revista de Investigación en Tecnologías de la Información","2026-10-02T00:00:00Z",63,{"impact":17,"substance":18,"depth":200,"authority":13,"freshness":201,"relevant":21,"comment":202},15,8,"系统综述梳理2020-2026年计算机视觉与深度学习在番茄病虫害检测中的应用，方法规范、结论有参考价值，但属细分领域综述，公共影响有限。",[204],{"name":196,"url":193},[26,206,27,207,208],"农业人工智能","番茄种植","病虫害监测",{"code":210,"slug":211,"name":212,"path":213,"parent_code":214},"I2","agricultural-ai","农业AI与大模型","\u002Ftopic\u002Fdigital-agriculture\u002Fagricultural-ai","I",[],{"status":115,"locked":14,"version":33,"method":34,"evidence":217},{"candidates":218,"agricultural_evidence":119},[219,228,234],{"code":210,"score":13,"supported":119,"title":220,"abstract":221,"tags":227},[],[222,223,224,225,226],"深度学习","计算机视觉","deep learning","artificial intelligence","computer vision",[206],{"code":110,"score":229,"supported":119,"title":230,"abstract":231,"tags":233},7,[],[127,232],"tomato",[207],{"code":38,"score":21,"supported":14,"title":235,"abstract":236,"tags":237},[],[],[26],[239,240],"计算机视觉 番茄 病虫害检测","深度学习 设施农业 植保监测","计算机视觉番茄病虫害检测-4108","10.36825\u002Friti.14.34.010",{"doi":242,"openalex_id":244,"authors":245,"venue":196,"cited_by_count":69,"oa_url":193,"card":258,"direction":77,"ingested_from":78},"W7216085028",[246,248,251,254,256],{"name":247,"orcid":9},"Jesús Alberto Alarcón Luna",{"name":249,"orcid":250},"María Salomé Alejandre Apolinar","https:\u002F\u002Forcid.org\u002F0009-0008-0232-8217",{"name":252,"orcid":253},"Hugo Amores Pérez","https:\u002F\u002Forcid.org\u002F0009-0009-0260-4872",{"name":255,"orcid":9},"Jacel Adame García",{"name":257,"orcid":9},"María Angélica Cerdán",{"tldr":259,"method":260,"finding":261,"direction":77,"opportunity":262},"系统综述2020-2026年计算机视觉与深度学习在番茄设施栽培虫害检测中的研究。","遵循Kitchenham指南系统检索筛选50篇文献，归纳技术、数据与性能。","深度学习模型在虫害症状自动识别任务中普遍报告高性能，但多限于特定条件。","面向设施农业与小规模生产的轻量化模型及参与式监测集成仍属研究空白。","2026-10-03T23:30:53.163959Z",{"id":265,"title":266,"url":267,"summary":268,"summary_zh":269,"content":9,"source_name":270,"source_url":267,"published_at":197,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":271,"score_detail":272,"sources":277,"tags":279,"primary_topic":9,"secondary_topics":283,"classification":284,"search_phrases":293,"slug":296,"view_count":69,"doi":297,"paper":298,"created_at":319},4047,"CEA SiteScout: application of a data-driven screening tool for controlled environment agriculture site selection and resource estimation in U.S. communities","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1891079","Controlled Environment Agriculture (CEA) is expanding rapidly, but selecting suitable sites for new facilities remains a complex challenge due to the interplay of climate, infrastructure, logistics, economic, policy, and other factors. We present CEA SiteScout, an interactive decision-support tool that integrates multiple public datasets to generate site-specific overviews and energy analyses for screening purposes, providing the critical foundation for data-driven CEA site evaluation in the US. By aggregating national and, for selected spotlight communities, regional environmental, social, and economic datasets into one intuitive platform, CEA SiteScout helps users visualize nearby resources and constraints relevant to site selection. Underpinned by a simplified, validated energy-water model ( Hodson et al., 2026 ), this tool also provides order-of-magnitude estimates of resource consumption for a variety of representative CEA configurations. We demonstrate the application of CEA SiteScout in five spotlight U.S. communities: York County, Pennsylvania; Riverside, California; Augusta and surrounding rural areas, Georgia; Kaua'i, Hawai'i; and the Western Lake Erie Region, Ohio and Michigan. Results from these communities illustrate how diverse regional contexts influence the suitability of different technologies, resource demands, and policy opportunities. This work highlights how integrated screening tools can reduce early-stage risk for growers, investors, and policymakers, filling a gap in current siting analyses, which often lack comprehensive, accessible, and stakeholder-informed approaches.","受控环境农业（Controlled Environment Agriculture, CEA）正在迅速扩张，但为新设施选择合适场址仍是一项复杂挑战，原因在于气候、基础设施、物流、经济、政策等多重因素相互交织。我们提出CEA SiteScout，这是一款交互式决策支持工具，整合了多个公共数据集，可生成特定场址概览和能源分析，用于筛选目的，为美国数据驱动的CEA场址评估提供了关键基础。通过将全国性以及针对选定焦点社区的区域性环境、社会和经济数据集汇聚到一个直观平台中，CEA SiteScout帮助用户可视化与场址选择相关的周边资源和约束条件。该工具以经过验证的简化能源-水模型（Hodson et al., 2026）为支撑，还可为多种代表性CEA配置提供资源消耗的数量级估算。我们展示了CEA SiteScout在美国五个焦点社区的应用：宾夕法尼亚州约克县；加利福尼亚州里弗赛德；佐治亚州奥古斯塔及周边农村地区；夏威夷州考艾岛；以及俄亥俄州和密歇根州西部伊利湖地区。这些社区的结果表明，不同的区域背景如何影响不同技术的适宜性、资源需求和政策机遇。这项工作凸显了集成筛选工具如何降低种植者、投资者和政策制定者的早期风险，填补了当前选址分析中的空白——这些分析往往缺乏全面、易获取且纳入利益相关者意见的方法。","Frontiers in Sustainable Food Systems",81,{"impact":18,"substance":273,"depth":18,"authority":274,"freshness":275,"relevant":21,"comment":276},22,14,9,"美国受控环境农业选址决策支持工具，方法新颖、数据整合度高，对国内设施农业选址与资源评估有借鉴价值。",[278],{"name":270,"url":267},[26,27,280,281,282],"选址评估","能源水耗","决策支持工具",[],{"status":285,"locked":14,"version":33,"method":34,"evidence":286},"unclassified",{"candidates":287,"agricultural_evidence":119,"reason":292},[288],{"code":38,"score":21,"supported":14,"title":289,"abstract":290,"tags":291},[],[],[26],"缺少足够的主题证据",[294,295],"CEA SiteScout 设施农业 选址","受控环境农业 能源水模型","CEASiteScout设施农业选址-4047","10.3389\u002Ffsufs.2026.1891079",{"doi":297,"openalex_id":299,"authors":300,"venue":270,"cited_by_count":69,"oa_url":267,"card":313,"direction":317,"ingested_from":78},"W7215860000",[301,303,306,309,311],{"name":302,"orcid":9},"Arian Aghajanzadeh",{"name":304,"orcid":305},"Tyler Huntington","https:\u002F\u002Forcid.org\u002F0000-0002-3213-0382",{"name":307,"orcid":308},"Abigayle Hodson","https:\u002F\u002Forcid.org\u002F0009-0005-7453-9687",{"name":310,"orcid":9},"Robinson Negron-Juarez",{"name":312,"orcid":9},"Jennifer Stokes-Draut",{"tldr":314,"method":315,"finding":316,"direction":317,"opportunity":318},"开发CEA SiteScout工具，整合公共数据为美国社区筛选受控环境农业选址并估算资源消耗。","整合多源公共数据集与简化能量-水模型，构建交互式决策支持平台。","在五个美国社区验证，表明区域差异显著影响技术适宜性、资源需求与政策机会。","数字乡村与农业信息化","可扩展至更多地区并耦合实时物联网数据，提升选址模型的动态性与普适性。","2026-10-03T23:30:07.693778Z",{"id":321,"title":322,"url":323,"summary":324,"summary_zh":325,"content":9,"source_name":270,"source_url":323,"published_at":326,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":327,"score_detail":328,"sources":330,"tags":332,"primary_topic":336,"secondary_topics":342,"classification":343,"search_phrases":374,"slug":377,"view_count":378,"doi":379,"paper":380,"created_at":402},4000,"Assessing upper bounds for solar-powered controlled environment agriculture on existing cropland","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1945186","Controlled environment agriculture (CEA) has been proposed as a way of limiting cropland expansion and extending growing seasons, but these systems demand substantial amounts of energy, and their associated environmental impacts remain unclear. Here, we developed a framework to compare global crop area and production (reference year 2020) with an idealized, upper-bound scenario consisting of high-tech greenhouses or vertical farms powered by stand-alone photovoltaics (PV) for wheat, soybeans, potatoes, and tomatoes. The CEA energy calculation was combined with land-use, crop mapping, and PV energy datasets to compare CEA capacity with 2020 global crop production values. Of the 420 Mha of cropland area included in this study, hypothetical high-tech greenhouses and vertical farms powered by stand-alone PV arrays could match 2020 production levels on 313 Mha (74.5% aggregated across the four crops on the studied cropland area) and 275 Mha (65.4%), respectively, in the optimistic upper bound scenario. The modelled potential was greatest in parts of North and South America, South Asia, East Asia, West Africa, the Mediterranean, and Central Asia. These results reflect an idealized comparison, and implementing sustainable CEA at scale would face substantial technical, economic, and societal challenges. However, the framework does illustrate the locations where land and PV energy constraints would be least restrictive for CEA implementation.","受控环境农业（CEA）被视为限制耕地扩张和延长生长季的一种方式，但这些系统需要大量能源，其相关环境影响仍不明确。在此，我们开发了一个框架，将全球作物面积和产量（参考年份2020年）与一个理想化的上限情景进行比较，该情景由独立光伏（PV）供电的高科技温室或垂直农场组成，针对小麦、大豆、马铃薯和番茄。CEA能源计算与土地利用、作物制图和光伏能源数据集相结合，以将CEA产能与2020年全球作物产量值进行比较。在本研究纳入的420 Mha耕地面积中，由独立光伏阵列供电的假设高科技温室和垂直农场在乐观上限情景下，可分别在313 Mha（在研究耕地面积上四种作物合计占74.5%）和275 Mha（65.4%）上匹配2020年产量水平。模拟潜力在南北美洲部分地区、南亚、东亚、西非、地中海和中亚最大。这些结果反映的是一种理想化比较，大规模实施可持续CEA将面临重大技术、经济和社会挑战。然而，该框架确实说明了在哪些地点，土地和光伏能源约束对CEA实施限制最小。","2026-10-01T00:00:00Z",80,{"impact":18,"substance":273,"depth":18,"authority":19,"freshness":275,"relevant":21,"comment":329},"该研究以全球尺度和2020年基准数据量化了光伏驱动设施农业替代耕地的理论上限，方法新颖、数据规模大，对智慧农业与设施农业布局有参考价值，但属理想化情景模拟，落地挑战明显。",[331],{"name":270,"url":323},[26,27,333,334,335],"垂直农场","光伏农业","农业碳中和",{"code":337,"slug":338,"name":339,"path":340,"parent_code":341},"A2","wheat","小麦","\u002Ftopic\u002Ffield-crops\u002Fwheat","A",[],{"status":115,"locked":14,"version":33,"method":34,"evidence":344},{"candidates":345,"agricultural_evidence":119},[346,350,354,360,366,370],{"code":337,"score":81,"supported":119,"title":347,"abstract":348,"tags":349},[],[339,338],[],{"code":103,"score":20,"supported":119,"title":351,"abstract":352,"tags":353},[],[121],[334,333],{"code":355,"score":172,"supported":119,"title":356,"abstract":357,"tags":359},"A4",[],[358],"大豆",[],{"code":361,"score":172,"supported":119,"title":362,"abstract":363,"tags":365},"A5",[],[364],"马铃薯",[],{"code":110,"score":172,"supported":119,"title":367,"abstract":368,"tags":369},[],[127],[],{"code":38,"score":21,"supported":14,"title":371,"abstract":372,"tags":373},[],[],[26],[375,376],"光伏温室 垂直农场 作物产量","可控环境农业 太阳能 耕地","光伏温室垂直农场作物产量-4000",2,"10.3389\u002Ffsufs.2026.1945186",{"doi":379,"openalex_id":381,"authors":382,"venue":270,"cited_by_count":69,"oa_url":323,"card":396,"direction":400,"ingested_from":78},"W7215116626",[383,385,387,389,391,394],{"name":384,"orcid":9},"S. A. Roberts",{"name":386,"orcid":9},"K. Winkler",{"name":388,"orcid":9},"M. D. A. Rounsevell",{"name":390,"orcid":9},"A. Saxena",{"name":392,"orcid":393},"L.F.M. Marcelis","https:\u002F\u002Forcid.org\u002F0000-0002-8088-7232",{"name":395,"orcid":9},"R. Fuchs",{"tldr":397,"method":398,"finding":399,"direction":400,"opportunity":401},"构建框架评估现有农田上光伏驱动可控环境农业替代全球作物生产的理论上限。","结合CEA能耗、土地利用、作物制图与光伏数据，对2020年四种作物做理想化情景模","乐观上限下，高科技温室和垂直农场分别可在313和275 Mha农田上匹配2020年产量。","农业绿色发展与碳","可研究真实技术经济约束下CEA的可行区域，并评估其全生命周期环境与碳足迹。","2026-10-02T23:30:10.316478Z",{"id":404,"title":405,"url":406,"summary":407,"summary_zh":9,"content":408,"source_name":409,"source_url":9,"published_at":410,"category":411,"cover_url":9,"hotness":13,"is_selected":14,"score":412,"score_detail":413,"sources":415,"tags":417,"primary_topic":9,"secondary_topics":421,"classification":422,"search_phrases":448,"slug":451,"view_count":20,"doi":9,"paper":9,"created_at":452},3943,"广东省委副书记、省长孟凡利到省农业科学院调研：以产业链思维发展现代农业","https:\u002F\u002Fwww.gdaas.cn\u002Fywzx\u002Fcontent\u002Fpost_1339884.html","9月29日，广东省委副书记、省长孟凡利到广东省农业科学院围绕科技支撑重要农林牧渔产品种植、养殖及增产提质增收工作进行专题调研。孟凡利强调要强化科技赋能，以产业链思维发展现代农业，加快形成强大的农林牧渔产品生产能力，鼓励科研人员在育种、种植养殖技术、农机装备、耕地保护、疫病防控、智慧农业等领域加强科研攻关；要积极推动发展设施农业，改良改进种植技术，大力推广科学化、精细化、智能化种养方式。","### **孟凡利到省农业科学院调研时强调 强化科技赋能 以产业链思维发展现代农业 加快形成强大的农林牧渔产品生产能力**\n\n时间：2026-09-30 09:30 来源：广东新闻联播、南方日报【字体：大 中 小】\n\n（视频来源：广东新闻联播）\n\n9月29日，省委副书记、省长孟凡利到广东省农业科学院，围绕科技支撑重要农林牧渔产品种植、养殖及增产提质增收工作进行专题调研，强调要认真学习贯彻习近平总书记关于“三农”工作的重要论述，深入实施“百县千镇万村高质量发展工程”，坚持目标导向、问题导向、结果导向，强化科技赋能，以产业链思维发展现代农业，加快形成强大的农林牧渔产品生产能力，积极推动量质齐升，为建设农业强省提供更大支撑。\n\n在省农业科学院，孟凡利详细了解了研发创新、成果转化、科技服务、人才培养等方面的工作情况，与科研人员深入交流，鼓励他们在育种、种植养殖技术、农机装备、耕地保护、疫病防控、智慧农业等领域加强科研攻关，推动更多成果转化为产品、实现产业化，更好服务农林牧渔业增产增收。\n\n孟凡利强调，**要**立足我省资源禀赋和产业基础，统筹抓好种植业、林业、畜牧业、渔业，深入落实藏粮于地、藏粮于技的要求，强化科技创新对农业的支撑和赋能作用，支持农业领域加强产学研合作，加快人工智能等新技术推广应用，推动各类主要农林牧渔业产品产能、产量和产值都有更大增长，确保粮食安全和重要农产品稳定供应。**要**解放思想、大胆创新，在关键育种技术上加强科技攻关，精心选育更多更好适应市场需求、抗病能力强、经济效益好的优良品种，为水稻、果蔬、茶叶、生猪、家禽、水产品等各类农产品扩产提质夯实基础。**要**积极推动发展设施农业，改良改进种植技术，大力推广科学化、精细化、智能化种养方式，加强农机装备和动植物药物的研发、制造、应用和推广，加快建设现代化海洋牧场，不断提升农业综合生产能力和质量效益。**要**大力培养农业科技人才，健全职务科技成果产权制度，把人才培养、科技创新与解决产业实际需求紧密结合起来，为农业高质量发展提供人才智力保障。**要**强化全产业链发展思维，在做大产能产量的基础上，全面拓展农产品精深加工、仓储流通、市场销售、品牌打造等全链条，充分挖掘地理标志产品价值，积极面向全国全球做好推广和营销，促进农业更好向二三产延伸，加快把农业建成现代化大产业。\n\n省领导陈良贤参加调研。\n\n（文字来源：南方日报，链接：[https:\u002F\u002Fm.itouchtv.cn\u002Farticle\u002F321234fc1a5f3b81197ac910e4e97fba?shareId=-siXlOJE](https:\u002F\u002Fm.itouchtv.cn\u002Farticle\u002F321234fc1a5f3b81197ac910e4e97fba?shareId=-siXlOJE)）","广东省农业科学院·2026年09月29日","2026-09-29T00:00:00Z","报道",71,{"impact":273,"substance":92,"depth":274,"authority":17,"freshness":229,"relevant":21,"comment":414},"省级主要领导专题调研，明确科技赋能与全产业链发展路径，对智慧农业、设施农业等方向有政策指向意义，但属常规政务报道，信息增量有限。",[416],{"name":409,"url":406},[26,27,418,419,420],"种业振兴","农业科技","产业链思维",[],{"status":32,"locked":14,"version":33,"method":34,"evidence":423},{"candidates":424,"agricultural_evidence":119,"reason":447},[425,430,436,442],{"code":38,"score":426,"supported":119,"title":427,"abstract":428,"tags":429},4,[],[26],[26],{"code":431,"score":172,"supported":119,"title":432,"abstract":433,"tags":435},"F5",[],[434],"农机",[],{"code":437,"score":172,"supported":119,"title":438,"abstract":439,"tags":441},"H1",[],[440],"耕地保护",[],{"code":443,"score":21,"supported":14,"title":444,"abstract":445,"tags":446},"F1",[],[],[418],"多个产业证据相当，需要确认主归属",[449,450],"广东省农业科学院 孟凡利 调研","智慧农业 产业链 现代农业","广东省农业科学院孟凡利调研-3943","2026-10-02T11:53:11.981406Z"]