[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-1393":3,"related-1393":122},{"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":24,"tags":26,"primary_topic":9,"secondary_topics":31,"classification":32,"search_phrases":90,"slug":93,"view_count":94,"doi":95,"paper":96,"created_at":121},1393,"From vertical farms to healthy food environments: a Public-Health-by-Design framework for controlled environment agriculture in sustainable urban food systems","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1920989","Vertical farming and controlled environment agriculture (CEA) are increasingly promoted as responses to urbanisation, climate instability, water scarcity and the need for more reliable fresh-food supply. Yet high yield, technological sophistication and internal resource efficiency do not by themselves establish public-health value. This conceptual analysis reframes CEA as a conditional component of urban and regional food systems and develops a Public-Health-by-Design framework that links production choices to nutrition, food safety, environmental health, affordability, labour, governance and equity. The analysis draws on a targeted evidence update and interprets comparative findings within their original crop, system and geographic boundaries. The evidence supports a realistic complementary role for CEA in producing selected perishable, high-value and nutrient-dense crops; it does not support the near-term replacement of conventional agriculture for staple cereals, pulses and root crops. Nutritional outcomes vary with cultivar, light, temperature, carbon dioxide, water quality, nutrient formulation, nutrient origin, electrical conductivity, harvest stage and post-harvest handling. Nutrient circularity should therefore be assessed at two levels: recirculation within the facility and substitution of virgin mineral inputs with safe, standardised nutrients recovered from waste streams. Closed-loop systems can reduce water and nutrient losses, but salinity, sodium accumulation, pathogens, residues and final discharge remain material constraints. CEA may reduce selected field-associated hazards, while recirculating water, biofilms, seeds, workers and equipment can also transmit contamination. Beneficial produce-associated microbiota should be included in future food-quality research rather than treating all microorganisms as hazards. Economic competitiveness is similarly contextual because CEA operates within markets shaped by agricultural subsidies, energy prices, finance, procurement and infrastructure. The proposed framework contains an operational pathway from design choices to intermediate outcomes, public-health effects, governance and adaptive learning, while six cross-cutting principles guide decisions at every stage. CEA should consequently be evaluated against explicit comparators, distributional outcomes and transparent indicators. To strengthen operational use, the framework explicitly positioned against six established sustainability, food-system, food-environment, One Health, safe-and-sustainable-by-design, and food-system indicator frameworks. A risk-based microbiome monitoring protocol and a digital-governance module covering IoT, machine learning, computer vision, robotics, predictive analytics and digital twins are also specified.","垂直农业和可控环境农业（CEA）正日益被推广为应对城市化、气候不稳定、水资源短缺以及对更可靠的新鲜食品供应需求的方案。然而，高产、技术先进和内部资源效率本身并不能确立其公共健康价值。本概念性分析将CEA重新定位为城市和区域食品系统中的一个条件性组成部分，并构建了一个“设计即公共健康”（Public-Health-by-Design）框架，将生产选择与营养、食品安全、环境健康、可负担性、劳动力、治理和公平联系起来。该分析基于有针对性的证据更新，并在其原始作物、系统和地理边界内解读比较性发现。证据支持CEA在生产特定易腐、高价值和营养密集型作物方面发挥现实的补充作用；但不支持其在短期内替代传统农业用于主粮谷物、豆类和块根作物。营养结果因品种、光照、温度、二氧化碳、水质、营养液配方、养分来源、电导率、采收阶段和采后处理而异。因此，养分循环性应在两个层面进行评估：设施内的再循环，以及用从废物流中回收的安全、标准化养分替代原始矿物投入。闭环系统可减少水和养分损失，但盐度、钠积累、病原体、残留物和最终排放仍是实质性制约因素。CEA可能减少某些与田间相关的危害，而循环水、生物膜、种子、工人和设备也可能传播污染。有益于产品的相关微生物群应纳入未来的食品质量研究，而非将所有微生物视为危害。经济竞争力同样具有情境依赖性，因为CEA在由农业补贴、能源价格、金融、采购和基础设施所塑造的市场中运作。所提出的框架包含一条从设计选择到中间结果、公共健康效应、治理和适应性学习的可操作路径，同时六项跨领域原则指导每个阶段的决策。因此，CEA应针对明确的比较对象、分配结果和透明指标进行评估。为加强操作性应用，该框架明确对标六项既有的可持续性、食品系统、",null,"Frontiers in Sustainable Food Systems","2026-09-01T00:00:00Z","论文",10,false,80,{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":21,"relevant":22,"comment":23},18,22,20,13,7,1,"提出Public-Health-by-Design框架，系统评估垂直农业的公共健康价值，对可持续城市食物系统有重要参考。",[25],{"name":10,"url":6},[27,28,29,30],"智慧农业","垂直农业","公共健康","食物系统",[],{"status":33,"locked":14,"version":34,"method":35,"evidence":36},"needs_review","2026-10-22.2","rules",{"candidates":37,"agricultural_evidence":41,"reason":89},[38,47,54,60,67,73,79,84],{"code":39,"score":40,"supported":41,"title":42,"abstract":43,"tags":46},"E4",6,true,[],[44,45],"食品安全","food safety",[],{"code":48,"score":40,"supported":41,"title":49,"abstract":50,"tags":53},"I2",[],[51,52],"machine learning","computer vision",[],{"code":55,"score":56,"supported":41,"title":57,"abstract":58,"tags":59},"B7",4,[],[28],[28],{"code":61,"score":62,"supported":41,"title":63,"abstract":64,"tags":66},"G3",3,[],[65],"农业补贴",[],{"code":68,"score":62,"supported":41,"title":69,"abstract":70,"tags":72},"H3",[],[71],"水资源",[],{"code":74,"score":62,"supported":41,"title":75,"abstract":76,"tags":78},"I5",[],[77],"IoT",[],{"code":80,"score":22,"supported":14,"title":81,"abstract":82,"tags":83},"E2",[],[],[30],{"code":85,"score":22,"supported":14,"title":86,"abstract":87,"tags":88},"I1",[],[],[27],"多个产业证据相当，需要确认主归属",[91,92],"公共健康 垂直农业 智慧农业 食物系统","公共健康 垂直农业","公共健康垂直农业智慧农业食物系统-1393",0,"10.3389\u002Ffsufs.2026.1920989",{"doi":95,"openalex_id":97,"authors":98,"venue":10,"cited_by_count":94,"oa_url":112,"card":113,"direction":119,"ingested_from":120},"W7204937036",[99,102,105,108,110],{"name":100,"orcid":101},"Sylvester Chibueze Izah","https:\u002F\u002Forcid.org\u002F0000-0001-5526-006X",{"name":103,"orcid":104},"Matthew Chidozie Ogwu","https:\u002F\u002Forcid.org\u002F0000-0001-6054-1667",{"name":106,"orcid":107},"Vivian Ibienebakabobo Promise","https:\u002F\u002Forcid.org\u002F0000-0001-9837-5676",{"name":109,"orcid":9},"Ebinyo Rebecca Aseibai",{"name":111,"orcid":9},"Esther Ugo Alum","https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fsustainable-food-systems\u002Farticles\u002F10.3389\u002Ffsufs.2026.1920989\u002Fpdf",{"tldr":114,"method":115,"finding":116,"direction":117,"opportunity":118},"提出公共卫生导向设计框架，评估垂直农业在可持续城市食品系统中的条件性作用。","概念分析与证据更新，构建多维度公共卫生设计框架。","垂直农业仅适合特定高价值作物，不能替代主粮，需关注营养循环与安全。","其他","可研究垂直农业与传统农业在营养、经济、环境上的比较评估，以及营养循环与食品安全的具体实现路径。","智慧农业 \u002F 农业物联网","openalex","2026-09-02T23:30:08.179316Z",{"total":40,"page":22,"page_size":40,"items":123},[124,208,289,358,422,523],{"id":125,"title":126,"url":127,"summary":128,"summary_zh":129,"content":9,"source_name":130,"source_url":127,"published_at":131,"category":12,"cover_url":9,"hotness":132,"is_selected":14,"score":133,"score_detail":134,"sources":138,"tags":142,"primary_topic":146,"secondary_topics":151,"classification":152,"search_phrases":190,"slug":193,"view_count":94,"doi":194,"paper":195,"created_at":207},5566,"Accelerated Precision Cultivation of Coffea arabica in a Vertical Hybrid Greenhouse Unit Integrated with Non-Thermal Dielectric Barrier Discharge Plasma Seed Priming","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.23509132","Indoor controlled environment agriculture (CEA) offers substantial opportunities to insulate perennial crops from climate volatility and optimize resource efficiency, yet high-density cultivation of coffee (Coffea arabica) remains constrained by long ontogenetic establishment periods, slow seed germination, and physical root-zone limitations. In this work, we propose, model, and optimize a four-stage Vertical Hybrid Coffee Cultivation Unit (VH-CCU™) coupled with an upstream non-thermal dielectric barrier discharge (DBD) plasma seed conditioning skid. Pre-sowing treatment of Coffea arabica var. Kholani seeds using a 50 W, 10 kHz atmospheric helium DBD reactor induced sub-micron coat etching and accelerated imbibition by 10% to 12%, advancing emergence by approximately two weeks and boosting the Seedling Vigor Index from 475.9 to 766.6 (+61.1%) at 120 s exposure without generating toxic chemical effluents. Downstream cultivation integrates rooftop agrivoltaics (Stage 1), tiered pyramid micro-droplet fertigation (Stage 2), an engineered shallow volcanic-coir substrate bed (Stage 3), and an enclosed aeroponic sub-chamber (“basement”) for automated, non-destructive root phenotyping via multispectral computer vision (Stage 4). A 46-run Box–Behnken response surface Design of Experiments (DoE) evaluated five design factors across biological, hydraulic, and energetic responses. Multi-objective numerical optimization identified an optimal operating regime (X∗ 1 = 214 s plasma exposure, X∗ 2 = 1.21 L\u002Fplant\u002Fday drip volume, X∗ 3 = 25.5 cm bed depth, X∗ 4 = 16.7 mol\u002Fm2\u002Fday DLI, and X∗ 5 = adaptive edge-vision mist control), which achieved an experimental water-use efficiency of 4.72 g dry biomass\u002FL, compressed time to first bearing from 36–48 months down to 17–18 months, and maintained active root health above 96%. Techno economic modeling reveals that while high specific energy requirements (∼241 kWh\u002Fkg of green coffee) preclude commodity grade scaling, targeted micro-lot specialty production (SCA score 88+) paired with rooftop solar offsets yields a simple payback of 5.1 years and a 10-year Net Present Value of +$169,400. This hybrid framework establishes an empirical basis for the rapid, resource-efficient indoor production of high-grade coffee.","室内受控环境农业（CEA）为多年生作物规避气候波动和优化资源效率提供了重要机遇，但咖啡（Coffea arabica）的高密度栽培仍受限于漫长的个体发育建成期、缓慢的种子萌发以及根区物理空间限制。本研究提出、建模并优化了一种四阶段垂直混合咖啡栽培单元（VH-CCU™），并耦合上游非热介质阻挡放电（DBD）等离子体种子调理装置。采用50 W、10 kHz大气氦气DBD反应器对Kholani品种咖啡种子进行播前处理，诱导了亚微米级种皮刻蚀，使吸胀速率提高10%至12%，出苗提前约两周，在120 s暴露条件下将幼苗活力指数从475.9提升至766.6（+61.1%），且不产生有毒化学废液。下游栽培集成了屋顶农业光伏（第1阶段）、分层金字塔微滴灌施肥（第2阶段）、工程化浅层火山椰糠基质床（第3阶段）以及封闭式气雾栽培地下子室（第4阶段），后者通过多光谱计算机视觉实现自动化非破坏性根系表型分析。通过46组Box–Behnken响应面试验设计（DoE），评估了五个设计因子在生物学、水力学和能量学响应方面的表现。多目标数值优化确定了最优运行方案（X∗1 = 214 s等离子体暴露时间，X∗2 = 1.21 L\u002F株\u002F天滴灌量，X∗3 = 25.5 cm基质床深度，X∗4 = 16.7 mol\u002Fm²\u002F天日光积分，X∗5 = 自适应边缘视觉喷雾控制），实现了4.72 g干生物量\u002FL的实验水分利用效率，将首次结果期从36–48个月缩短至17–18个月，并维持根系健康率在96%以上。技术经济建模表明，尽管高比能耗（约241 kWh\u002Fkg生咖啡）限制了商品级规模化生产，但面向微批次精品生产（SCA评分88+）并配合屋顶太阳能抵消，可实现5.1年简单投资回收期和+$169,400的10年净现值。该混合框架为高等级咖啡的快速、资源高效室内生产奠定了实证基础。","Zenodo (CERN European Organization for Nuclear Research)","2026-10-21T00:00:00Z",25,71,{"impact":135,"substance":18,"depth":17,"authority":13,"freshness":136,"relevant":22,"comment":137},12,9,"方法新颖、数据扎实的室内咖啡栽培论文，但属细分作物与预印本平台，产业影响有限，可作主题聚合而非每日精选头条。",[139,140],{"name":130,"url":127},{"name":130,"url":141},"https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.23527545",[27,28,143,144,145],"设施园艺","咖啡种植","等离子种子处理",{"code":55,"slug":147,"name":148,"path":149,"parent_code":150},"protected-horticulture","设施园艺与植物工厂","\u002Ftopic\u002Fhorticulture\u002Fprotected-horticulture","B",[],{"status":153,"locked":14,"version":34,"method":35,"evidence":154},"classified",{"candidates":155,"agricultural_evidence":41},[156,161,168,175,180,186],{"code":55,"score":13,"supported":41,"title":157,"abstract":159,"tags":160},[158],"greenhouse",[],[28,143],{"code":162,"score":21,"supported":41,"title":163,"abstract":164,"tags":167},"B3",[],[165,166],"咖啡","coffee",[144],{"code":169,"score":40,"supported":41,"title":170,"abstract":171,"tags":174},"F3",[],[172,173],"施肥","fertigation",[],{"code":48,"score":40,"supported":41,"title":176,"abstract":177,"tags":179},[],[178,52],"计算机视觉",[],{"code":181,"score":62,"supported":41,"title":182,"abstract":183,"tags":185},"I3",[],[184],"multispectral",[],{"code":85,"score":22,"supported":14,"title":187,"abstract":188,"tags":189},[],[],[27],[191,192],"Coffea arabica 垂直温室 等离子种子处理","VH-CCU 咖啡 室内栽培","Coffeaarabica垂直温室等离子种子处理-5566","10.5281\u002Fzenodo.23509132",{"doi":194,"openalex_id":196,"authors":197,"venue":130,"cited_by_count":94,"oa_url":127,"card":201,"direction":206,"ingested_from":120},"W7223104009",[198],{"name":199,"orcid":200},"Ahmed Hala","https:\u002F\u002Forcid.org\u002F0000-0002-7749-2299",{"tldr":202,"method":203,"finding":204,"direction":119,"opportunity":205},"提出并优化等离子体种子预处理+四阶段垂直混合温室单元，加速咖啡室内栽培。","50W氦DBD等离子体处理种子，Box-Behnken响应面试验与多目标优化建模","出苗提前约两周，活力指数增61.1%，首果期缩至17-18个月，水分利用效率4.72g\u002FL。","等离子体种子预处理与室内垂直栽培耦合可拓展至其他多年生高值作物，并需验证规模化能耗经济性。","农业遥感与作物表型","2026-10-22T11:20:31.314461Z",{"id":209,"title":210,"url":211,"summary":212,"summary_zh":213,"content":9,"source_name":214,"source_url":211,"published_at":215,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":216,"score_detail":217,"sources":221,"tags":223,"primary_topic":227,"secondary_topics":228,"classification":229,"search_phrases":259,"slug":262,"view_count":22,"doi":263,"paper":264,"created_at":288},4984,"A Comparative Review of Soilless Precision Agriculture Techniques and Emerging Smart Farming Technologies","https:\u002F\u002Fdoi.org\u002F10.38094\u002Fjastt721251","The rapidly diminishing arable land, uncertain climatic conditions, and lack of ample natural resources are worsening the urgency for adopting sustainable agricultural systems. Soilless cultivation methods promote enhanced resource utilization and better productivity. These methods, like aeroponics, hydroponics, and aquaponics, are evolving as smart farming techniques, providing notable advantages over traditional farming methods, enhancing water conservation, resource utilization, and enabling cultivation in places with reduced area and less water. The concept of soilless cultivation provides multifold advantages over traditional cultivation methods by further making provision for cultivating in the closest proximity to urban farmers, like residential rooftops. A bibliometric analysis is also conducted to highlight the recent trends in smart precision farming technologies and the choice of substrate for each technique. In this article, various methods of soilless smart precision agriculture are identified and compared with traditional cultivation methods. Moreover, aspects like economic sustainability and recent research trends are analyzed to obtain insight into the three basic classes of soilless cultivation, namely aeroponics, aquaponics, and hydroponics. Furthermore, the study also focuses on briefly analyzing the economics of soilless techniques. The study concludes by outlining the major challenges and possible future enhancements in this domain that can lead to the evolution of smart, efficient, and resilient agricultural systems.","可耕地迅速减少、气候条件不稳定以及充足自然资源的匮乏，正日益加剧采用可持续农业体系的紧迫性。无土栽培方法促进了资源利用率的提高和生产力的提升。气雾栽培、水培和鱼菜共生等方法正演变为智慧农业技术，相较传统耕作方式具有显著优势，能够增强节水能力、提高资源利用率，并使得在面积有限、水资源匮乏的地区进行种植成为可能。无土栽培的概念相较传统栽培方法具有多重优势，还能进一步满足在城市农户附近（如住宅屋顶）进行种植的需求。本文还进行了文献计量分析，以揭示智慧精准农业技术的最新趋势以及每种技术对基质的选择。本文识别了多种无土智慧精准农业方法，并将其与传统栽培方法进行比较。此外，还分析了经济可持续性和近期研究趋势等方面，以深入了解无土栽培的三大基本类别，即气雾栽培、鱼菜共生和水培。进一步地，本研究还着重简要分析了无土栽培技术的经济性。研究最后概述了该领域的主要挑战及可能的未来改进方向，这些改进有望推动智慧、高效且具有韧性的农业体系的发展。","Journal of Applied Science and Technology Trends","2026-10-14T00:00:00Z",76,{"impact":17,"substance":19,"depth":218,"authority":20,"freshness":219,"relevant":22,"comment":220},17,8,"系统比较无土栽培三类技术与智慧农业趋势，含文献计量分析，对设施农业与都市农业有参考价值。",[222],{"name":214,"url":211},[27,224,28,225,226],"精准农业","水培","无土栽培",{"code":55,"slug":147,"name":148,"path":149,"parent_code":150},[],{"status":153,"locked":14,"version":34,"method":35,"evidence":230},{"candidates":231,"agricultural_evidence":41},[232,238,242,249,253],{"code":85,"score":233,"supported":41,"title":234,"abstract":236,"tags":237},19,[235],"precision agriculture",[27,224,235],[27,224],{"code":55,"score":40,"supported":41,"title":239,"abstract":240,"tags":241},[],[226],[28,226,225],{"code":243,"score":40,"supported":41,"title":244,"abstract":245,"tags":248},"I7",[],[246,247],"文献计量","bibliometric",[],{"code":68,"score":62,"supported":41,"title":250,"abstract":251,"tags":252},[],[71],[],{"code":254,"score":62,"supported":41,"title":255,"abstract":256,"tags":258},"H8",[],[257],"可持续农业",[],[260,261],"无土栽培 智慧农业 技术对比","水培 气雾培 鱼菜共生 精准农业","无土栽培智慧农业技术对比-4984","10.38094\u002Fjastt721251",{"doi":263,"openalex_id":265,"authors":266,"venue":214,"cited_by_count":94,"oa_url":211,"card":283,"direction":119,"ingested_from":120},"W7221762528",[267,270,273,275,278,281],{"name":268,"orcid":269},"Monica Dutta","https:\u002F\u002Forcid.org\u002F0000-0002-6235-9794",{"name":271,"orcid":272},"Deepali Gupta","https:\u002F\u002Forcid.org\u002F0000-0002-6771-2534",{"name":274,"orcid":9},"Walaa Jamal Alharthi",{"name":276,"orcid":277},"Mohammad Zubair Khan","https:\u002F\u002Forcid.org\u002F0000-0002-2409-7172",{"name":279,"orcid":280},"Adnan Nadeem","https:\u002F\u002Forcid.org\u002F0000-0001-9622-150X",{"name":282,"orcid":9},"Sapna Juneja",{"tldr":284,"method":285,"finding":286,"direction":119,"opportunity":287},"综述无土精准农业技术，比较气雾培、水培和鱼菜共生，并分析智能农业趋势。","文献综述与文献计量分析，比较无土栽培技术、基质选择及经济可持续性。","无土栽培在节水、资源利用和城市近郊种植上优于传统农业，但经济性和技术挑战仍存。","可研究无土栽培与物联网、AI决策模型的深度融合，优化基质选择和能耗经济性。","2026-10-15T23:30:08.336176Z",{"id":290,"title":291,"url":292,"summary":293,"summary_zh":294,"content":9,"source_name":295,"source_url":292,"published_at":296,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":297,"score_detail":298,"sources":303,"tags":305,"primary_topic":309,"secondary_topics":310,"classification":311,"search_phrases":327,"slug":330,"view_count":56,"doi":331,"paper":332,"created_at":357},3976,"Model-based optimization of dynamic photon allocation for maximizing biomass production under a fixed total light integral in vertical farming","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.compag.2026.112489","Model-based optimization of dynamic photon allocation for maximizing biomass production under a fixed total light integral in vertical farming。Computers and Electronics in Agriculture","基于模型的动态光子分配优化，以在垂直农业固定总光积分下最大化生物量生产。","Computers and Electronics in Agriculture","2026-10-01T00:00:00Z",78,{"impact":299,"substance":300,"depth":17,"authority":301,"freshness":136,"relevant":22,"comment":302},16,21,14,"核心期刊论文，提出固定光积分下动态光子分配模型优化方法，对垂直农业光环境精准调控有参考价值，但属细分领域方法研究，产业影响有限。",[304],{"name":295,"url":292},[27,306,28,307,308],"农业人工智能","作物模型","光环境调控",{"code":55,"slug":147,"name":148,"path":149,"parent_code":150},[],{"status":153,"locked":14,"version":34,"method":35,"evidence":312},{"candidates":313,"agricultural_evidence":41},[314,318,323],{"code":55,"score":56,"supported":41,"title":315,"abstract":316,"tags":317},[],[28],[28],{"code":48,"score":319,"supported":14,"title":320,"abstract":321,"tags":322},2,[],[],[307,306],{"code":85,"score":22,"supported":14,"title":324,"abstract":325,"tags":326},[],[],[27],[328,329],"垂直农业 光积分 生物量","动态光子分配 模型优化","垂直农业光积分生物量-3976","10.1016\u002Fj.compag.2026.112489",{"doi":331,"openalex_id":333,"authors":334,"venue":295,"cited_by_count":94,"oa_url":9,"card":351,"direction":355,"ingested_from":120},"W7215104938",[335,338,341,343,346,348],{"name":336,"orcid":337},"Eunjeong Lim","https:\u002F\u002Forcid.org\u002F0009-0008-2621-8602",{"name":339,"orcid":340},"Da-Seul Choi","https:\u002F\u002Forcid.org\u002F0009-0008-3239-9817",{"name":342,"orcid":9},"Hyeonjee Kim",{"name":344,"orcid":345},"Taewon Moon","https:\u002F\u002Forcid.org\u002F0000-0002-1593-7870",{"name":347,"orcid":9},"Myung-min Oh",{"name":349,"orcid":350},"Tae In Ahn","https:\u002F\u002Forcid.org\u002F0000-0001-5939-7450",{"tldr":352,"method":353,"finding":354,"direction":355,"opportunity":356},"在固定总光照积分下，用模型优化垂直农业中动态光子分配以最大化生物量。","基于作物生长模型的优化方法，模拟不同光子分配策略。","动态光子分配策略可提升固定光积分下的生物量产量。","农业人工智能与决策模型","可结合实时传感与作物状态反馈，发展自适应光配方优化，并验证多作物多场景泛化性。","2026-10-02T23:30:02.603545Z",{"id":359,"title":360,"url":361,"summary":362,"summary_zh":363,"content":9,"source_name":130,"source_url":361,"published_at":364,"category":12,"cover_url":9,"hotness":132,"is_selected":14,"score":365,"score_detail":366,"sources":368,"tags":372,"primary_topic":375,"secondary_topics":376,"classification":377,"search_phrases":406,"slug":409,"view_count":22,"doi":410,"paper":411,"created_at":421},3821,"Transforming Agriculture Through Technology And Smart Farming Innovations","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.23036819","Abstract In the contemporary agricultural landscape, a significant paradigm shift is taking place as farmers across the globe increasingly adopt advanced technologies and innovative farming practices. This transformation highlights the profound impact of modern agricultural technologies and the key trends shaping the future of food production. A central component of this revolution is the integration of precision agriculture, wherein farmers utilize cutting-edge tools such as GPS systems, sensors, and drones to optimize resource allocation. This approach enhances crop management efficiency, reduces resource wastage, and improves overall productivity. The rise of smart farming has introduced data-driven decision-making processes, enabling farmers to monitor, analyze, and manage crops with remarkable accuracy. In addition, advancements in biotechnology and genetic engineering have facilitated the development of genetically modified crops with improved resilience, enhanced nutritional value, and greater resistance to pests and diseases. These innovations not only increase agricultural output but also promote sustainability and environmentally responsible farming practices. Moreover, the emergence of vertical farming and controlled-environment agriculture marks a significant departure from conventional farming methods. By employing hydroponic and aeroponic systems in vertically structured environments, crops can be cultivated efficiently with minimal land use and optimized resource consumption. This method is particularly advantageous in urban areas where arable land is limited, offering a sustainable solution to growing food demands. Furthermore, robotics and automation are reshaping agricultural operations. Technologies such as autonomous tractors, robotic harvesters, and drone-assisted planting systems are reducing reliance on manual labor while enhancing operational efficiency. These advancements help address labor shortages and strengthen the overall resilience and sustainability of the agricultural sector.","在当代农业格局中，随着全球农民日益采用先进技术和创新耕作方式，正在发生重大的范式转变。这一变革凸显了现代农业技术的深远影响以及塑造未来粮食生产的关键趋势。这场革命的核心组成部分是精准农业的整合，农民利用GPS系统、传感器和无人机等前沿工具来优化资源配置。这种方法提高了作物管理效率，减少了资源浪费，并提升了整体生产力。智慧农业的兴起引入了数据驱动的决策过程，使农民能够以极高的精度监测、分析和管理作物。此外，生物技术和基因工程的进步促进了转基因作物的开发，这些作物具有更强的适应力、更高的营养价值和更强的抗病虫害能力。这些创新不仅提高了农业产量，还促进了可持续性和环境友好的耕作方式。此外，垂直农业和受控环境农业的出现标志着对传统耕作方式的重大突破。通过在垂直结构中采用水培和气培系统，作物可以在最少的土地利用和优化的资源消耗下高效种植。这种方法在城市地区尤为有利，因为那里可耕地有限，为日益增长的粮食需求提供了可持续的解决方案。此外，机器人技术和自动化正在重塑农业作业。自主拖拉机、机器人收割机和无人机辅助种植系统等技术正在减少对人工劳动的依赖，同时提高作业效率。这些进步有助于应对劳动力短缺问题，并增强农业部门的整体韧性和可持续性。","2026-09-30T00:00:00Z",65,{"impact":17,"substance":301,"depth":135,"authority":135,"freshness":136,"relevant":22,"comment":367},"Zenodo 平台上的智慧农业综述性论文，覆盖面广但缺乏新数据与具体案例，可作为主题聚合素材而非每日精选。",[369,370],{"name":130,"url":361},{"name":130,"url":371},"https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.23036818",[27,373,374,224,28],"农业机器人","生物育种",{"code":55,"slug":147,"name":148,"path":149,"parent_code":150},[],{"status":153,"locked":14,"version":34,"method":35,"evidence":378},{"candidates":379,"agricultural_evidence":41},[380,385,390,396,401],{"code":85,"score":381,"supported":41,"title":382,"abstract":383,"tags":384},11,[],[27,224,235],[27,224],{"code":55,"score":21,"supported":41,"title":386,"abstract":387,"tags":389},[],[28,388],"hydroponic",[28],{"code":391,"score":62,"supported":41,"title":392,"abstract":393,"tags":395},"F5",[],[394],"收割机",[],{"code":397,"score":22,"supported":14,"title":398,"abstract":399,"tags":400},"F2",[],[],[374],{"code":402,"score":22,"supported":14,"title":403,"abstract":404,"tags":405},"F6",[],[],[373],[407,408],"农业机器人 垂直农业 智慧农业 生物育种","农业机器人 垂直农业","农业机器人垂直农业智慧农业生物育种-3821","10.5281\u002Fzenodo.23036819",{"doi":410,"openalex_id":412,"authors":413,"venue":130,"cited_by_count":94,"oa_url":361,"card":416,"direction":119,"ingested_from":120},"W7214716174",[414],{"name":415,"orcid":9},"R.L. Poonguzhali",{"tldr":417,"method":418,"finding":419,"direction":119,"opportunity":420},"综述精准农业、智慧农业、生物技术、垂直农业与机器人自动化如何重塑未来粮食生产。","文献综述，整合GPS、传感器、无人机、基因工程、水培气培及自动化技术案例。","技术融合可提升效率、减少浪费、促进可持续，并应对劳动力短缺与耕地限制。","可量化评估垂直农业与机器人系统在中小农场的经济可行性及碳足迹，填补实证空白。","2026-09-30T23:30:09.413038Z",{"id":423,"title":424,"url":425,"summary":426,"summary_zh":427,"content":9,"source_name":428,"source_url":425,"published_at":429,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":430,"score_detail":431,"sources":434,"tags":436,"primary_topic":440,"secondary_topics":445,"classification":446,"search_phrases":492,"slug":495,"view_count":62,"doi":496,"paper":497,"created_at":522},2775,"Digital-enabled life cycle thinking for sustainable food systems: aligning with sustainable development goals","https:\u002F\u002Fdoi.org\u002F10.1038\u002Fs41598-026-63273-w","The increasing complexity of global food systems, coupled with climate change, resource scarcity, and socio-economic pressures, necessitates advanced sustainability assessment approaches. While life cycle thinking (LCT) provides a comprehensive framework, its practical application is constrained by data limitations, methodological uncertainty, and the limited ability of conventional models to capture dynamic operational conditions. This study proposes a digitally integrated LCT framework that combines artificial intelligence (AI), blockchain, internet of things (IoT), and remote sensing to enhance data accuracy, transparency, and real-time decision-making in food supply chains. A key contribution of this research is the introduction of two novel constructs, the digital trust index (DTI) and proof-of-climate impact (PCI) which quantify stakeholder trust and provide verifiable evidence linking digital interventions to measurable environmental outcomes. The DTI is conceptualized as a composite measure of stakeholder trust, integrating both digital infrastructure capabilities and governance-based trust mechanisms. Scenario analysis demonstrates that integrated digital and governance systems can achieve up to 34% climate impact reduction (CIR), while Monte Carlo simulation results indicate an average CIR of approximately 20%, confirming the robustness of the framework under uncertainty. The study reveals that SDG 12 (23%) and SDG 9 (20%) dominate digital LCT research in food systems, followed by SDG 2 and SDG 13, while biodiversity-focused goals (SDG 14 & SDG 15) receive less attention. The proposed SDG oriented framework integrates digital technologies across LCT phases, enabling real-time and transparent sustainability assessment while enhancing the monitoring of biodiversity impacts. The findings highlight that digitalization, when coupled with governance and sustainable development goal-oriented metrics, enables more transparent, adaptive, and impact-driven sustainability assessment in food systems.","全球粮食系统日益复杂，加之气候变化、资源稀缺和社会经济压力，迫切需要先进的可持续性评估方法。尽管生命周期思维（LCT）提供了全面的框架，但其实际应用受到数据限制、方法学不确定性以及传统模型捕捉动态运行条件能力有限的制约。本研究提出了一种数字化集成的LCT框架，将人工智能（AI）、区块链、物联网（IoT）和遥感相结合，以提升食品供应链中的数据准确性、透明度和实时决策能力。本研究的一项关键贡献是引入了两个新颖构念——数字信任指数（DTI）和气候影响证明（PCI），用以量化利益相关者信任，并提供可验证的证据，将数字干预与可衡量的环境成果相联系。DTI被概念化为利益相关者信任的综合度量，整合了数字基础设施能力和基于治理的信任机制。情景分析表明，集成的数字与治理系统可实现高达34%的气候影响减排（CIR），而蒙特卡洛模拟结果显示平均CIR约为20%，证实了该框架在不确定性下的稳健性。研究揭示，SDG 12（23%）和SDG 9（20%）在食品系统中的数字LCT研究中占主导地位，其次是SDG 2和SDG 13，而聚焦生物多样性的目标（SDG 14和SDG 15）受到的关注较少。所提出的面向SDG的框架将数字技术整合到LCT各阶段，实现实时、透明的可持续性评估，同时增强对生物多样性影响的监测。研究结果表明，数字化在与治理和面向可持续发展目标的指标相结合时，能够在食品系统中实现更透明、更具适应性和以影响为导向的可持续性评估。","Scientific Reports","2026-09-15T00:00:00Z",86,{"impact":18,"substance":432,"depth":233,"authority":301,"freshness":219,"relevant":22,"comment":433},23,"提出数字信任指数与气候影响证明等新构念，量化数字技术对食物系统可持续性的减排贡献，方法新颖、结论可靠，对农业信息化与绿色转型具有较强参考价值。",[435],{"name":428,"url":425},[27,306,437,438,439,30],"农业遥感","可持续发展","区块链溯源",{"code":74,"slug":441,"name":442,"path":443,"parent_code":444},"agricultural-iot","物联网传感与边缘计算","\u002Ftopic\u002Fdigital-agriculture\u002Fagricultural-iot","I",[],{"status":153,"locked":14,"version":34,"method":35,"evidence":447},{"candidates":448,"agricultural_evidence":41},[449,455,461,468,475,480,484,488],{"code":74,"score":136,"supported":41,"title":450,"abstract":451,"tags":454},[],[452,453,77],"物联网","internet of things",[],{"code":181,"score":21,"supported":41,"title":456,"abstract":457,"tags":460},[],[458,459],"遥感","remote sensing",[437],{"code":462,"score":40,"supported":41,"title":463,"abstract":464,"tags":467},"H6",[],[465,466],"生物多样性","biodiversity",[],{"code":469,"score":40,"supported":41,"title":470,"abstract":471,"tags":474},"H7",[],[472,473],"气候变化","climate change",[],{"code":48,"score":56,"supported":41,"title":476,"abstract":477,"tags":479},[],[478],"artificial intelligence",[306],{"code":80,"score":22,"supported":14,"title":481,"abstract":482,"tags":483},[],[],[30],{"code":39,"score":22,"supported":14,"title":485,"abstract":486,"tags":487},[],[],[439],{"code":85,"score":22,"supported":14,"title":489,"abstract":490,"tags":491},[],[],[27],[493,494],"农业人工智能 区块链溯源 可持续发展 农业遥感","农业人工智能 区块链溯源","农业人工智能区块链溯源可持续发展农业遥感-2775","10.1038\u002Fs41598-026-63273-w",{"doi":496,"openalex_id":498,"authors":499,"venue":428,"cited_by_count":94,"oa_url":515,"card":516,"direction":119,"ingested_from":120},"W7213239181",[500,502,505,507,509,512],{"name":501,"orcid":9},"S. U. Parvathy",{"name":503,"orcid":504},"Vysakh Kani Kolil","https:\u002F\u002Forcid.org\u002F0000-0003-2035-3439",{"name":506,"orcid":9},"Raghu Raman",{"name":508,"orcid":9},"Nripendra P. Rana",{"name":510,"orcid":511},"Sasangan Ramanathan","https:\u002F\u002Forcid.org\u002F0000-0002-7459-0934",{"name":513,"orcid":514},"Krishnashree Achuthan","https:\u002F\u002Forcid.org\u002F0000-0003-2618-0882","https:\u002F\u002Fwww.nature.com\u002Farticles\u002Fs41598-026-63273-w_reference.pdf",{"tldr":517,"method":518,"finding":519,"direction":520,"opportunity":521},"提出融合AI、区块链、物联网与遥感的数字生命周期思维框架，用于食品系统可持续性评估。","整合AI、区块链、IoT与遥感，构建数字信任指数和气候影响证明，用情景分析与蒙特","数字与治理结合可使气候影响降低最高34%，平均约20%；SDG12和SDG9主导相关研究。","农业绿色发展与碳","可探索数字信任指数与气候影响证明在农业食品供应链中的实证验证及生物多样性目标监测。","2026-09-17T23:30:15.308110Z",{"id":524,"title":525,"url":526,"summary":527,"summary_zh":9,"content":9,"source_name":528,"source_url":9,"published_at":529,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":430,"score_detail":530,"sources":533,"tags":535,"primary_topic":9,"secondary_topics":539,"classification":540,"search_phrases":562,"slug":565,"view_count":56,"doi":9,"paper":566,"created_at":574},2108,"《AI in Agriculture: Transforming the Food System from Data to Decisions to Action》 美国密西西比州立CAST论文","https:\u002F\u002Fpublications.cast-science.org\u002FCAST\u002Fen\u002Farticle\u002Fview\u002F245","密西西比州立大学农业自主研究所所长Thomasson发表CAST评论,系统论述AI正成为美国食物系统的基础技术,深度嵌入田间装备、生产系统、食物加工、供应链与自然资源管理。引入\"物理AI\"概念——能在生物变异性与环境不确定性下感知、推理、行动的AI系统,农业是其最严苛的试验场。生成式AI被视为让先进分析民主化的力量。约束AI负责任采用的核心不是技术,而是制度——数据质量、田间验证、推荐透明度、网络安全与互操作性。","Council for Agricultural Science and Technology (CAST)","2026-09-08T00:00:00Z",{"impact":531,"substance":18,"depth":17,"authority":301,"freshness":219,"relevant":22,"comment":532},24,"CAST权威评论系统提出物理AI概念并指出制度而非技术是负责任采用的核心约束，观点新颖、信息增量大，值得进入每日精选。",[534],{"name":528,"url":526},[27,306,536,30,537,538],"数据治理","物理AI","生成式AI",[],{"status":541,"locked":14,"version":34,"method":35,"evidence":542},"unclassified",{"candidates":543,"agricultural_evidence":41,"reason":561},[544,548,552,556],{"code":80,"score":22,"supported":14,"title":545,"abstract":546,"tags":547},[],[],[30],{"code":85,"score":22,"supported":14,"title":549,"abstract":550,"tags":551},[],[],[27],{"code":48,"score":22,"supported":14,"title":553,"abstract":554,"tags":555},[],[],[306],{"code":557,"score":22,"supported":14,"title":558,"abstract":559,"tags":560},"I6",[],[],[536],"缺少足够的主题证据",[563,564],"农业人工智能 数据治理 智慧农业 食物系统","农业人工智能 数据治理","农业人工智能数据治理智慧农业食物系统-2108",{"doi":9,"openalex_id":9,"authors":567,"venue":9,"cited_by_count":94,"oa_url":9,"card":568,"direction":355,"ingested_from":573},[],{"tldr":569,"method":570,"finding":571,"direction":355,"opportunity":572},"系统论述AI正成为美国食物系统基础技术，提出物理AI概念并强调制度约束。","CAST评论文章，基于田间装备、供应链等应用场景的系统分析。","约束AI负责任采用的核心是制度而非技术，如数据质量与互操作性。","物理AI在生物变异与环境不确定性下的感知推理行动机制，及制度适配研究。","agent","2026-09-11T00:04:22.740798Z"]