[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-3651":3,"related-3651":126},{"id":4,"title":5,"url":6,"summary":7,"summary_zh":8,"content":8,"source_name":9,"source_url":8,"published_at":10,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":14,"score_detail":15,"sources":22,"tags":24,"primary_topic":30,"secondary_topics":36,"classification":37,"search_phrases":110,"slug":113,"view_count":114,"doi":8,"paper":115,"created_at":125},3651,"[预印本] 蒙特卡洛事前评估AI驱动智慧农业平台绿色效益——以海南热带农业为例","https:\u002F\u002Farxiv.org\u002Fhtml\u002F2609.06737v1","以整合大语言模型问答、多模态病虫害诊断、物联网土壤湿度传感、NASA GIBS卫星遥感与闭环田间记录系统的热带农业AI决策平台为对象，构建覆盖农药化肥生产、田间N2O、灌溉电力与稻田CH4的'摇篮到农场大门'农业碳核算模型。在三个海南代表性场景（芒果园、冬季蔬菜、稻\u002F南繁育种田，按面积40%：30%：30%加权）下，通过蒙特卡洛模拟参数不确定性传播：在完全采纳试点情景下，化学农药使用减少23.5%（90%置信区间15.0%–33.2%），化肥施用减少21.0%（13.8%–28.9%），灌溉水减少16.5%（10.9%–23.5%），碳强度降低21.5%（16.1%–27.2%）。达成化肥减量≥15%与碳强度明确下降的概率分别为90.6%与98.1%，而总节水≥20%的概率仅约20%，表明应采用场景化表述。",null,"arXiv 2609.06737v1 (2026-09)","2026-09-15T00:00:00Z","论文",10,false,76,{"impact":16,"substance":17,"depth":16,"authority":18,"freshness":19,"relevant":20,"comment":21},18,22,12,6,1,"预印本以蒙特卡洛量化AI平台在海南三类场景的减药减肥与碳减排概率，方法新颖、数据具体，但尚未经同行评审，属细分领域进展。",[23],{"name":9,"url":6},[25,26,27,28,29],"智慧农业","农业人工智能","农药减量","农业碳核算","海南热带农业",{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},"F4","crop-protection","农药与绿色防控","\u002Ftopic\u002Finputs-equipment\u002Fcrop-protection","F",[],{"status":38,"locked":13,"version":39,"method":40,"evidence":41},"classified","2026-10-22.2","rules",{"candidates":42,"agricultural_evidence":46},[43,50,56,63,69,75,81,87,93,99,105],{"code":44,"score":45,"supported":46,"title":47,"abstract":48,"tags":49},"I1",9,true,[25],[],[25],{"code":31,"score":51,"supported":46,"title":52,"abstract":53,"tags":55},4,[],[54],"农药",[27],{"code":57,"score":58,"supported":46,"title":59,"abstract":60,"tags":62},"A1",3,[],[61],"稻田",[],{"code":64,"score":58,"supported":46,"title":65,"abstract":66,"tags":68},"B1",[],[67],"蔬菜",[],{"code":70,"score":58,"supported":46,"title":71,"abstract":72,"tags":74},"B2",[],[73],"芒果",[],{"code":76,"score":58,"supported":46,"title":77,"abstract":78,"tags":80},"H2",[],[79],"土壤",[],{"code":82,"score":58,"supported":46,"title":83,"abstract":84,"tags":86},"H3",[],[85],"灌溉",[],{"code":88,"score":58,"supported":46,"title":89,"abstract":90,"tags":92},"H4",[],[91],"农业碳",[],{"code":94,"score":58,"supported":46,"title":95,"abstract":96,"tags":98},"I3",[],[97],"遥感",[],{"code":100,"score":58,"supported":46,"title":101,"abstract":102,"tags":104},"I5",[],[103],"物联网",[],{"code":106,"score":20,"supported":13,"title":107,"abstract":108,"tags":109},"I2",[],[],[26],[111,112],"海南 热带农业 AI平台","蒙特卡洛 农业碳核算","海南热带农业AI平台-3651",2,{"doi":8,"openalex_id":8,"authors":116,"venue":8,"cited_by_count":117,"oa_url":8,"card":118,"direction":122,"ingested_from":124},[],0,{"tldr":119,"method":120,"finding":121,"direction":122,"opportunity":123},"用蒙特卡洛模拟评估AI智慧农业平台在海南热带农业中的绿色减排效益。","构建摇篮到农场大门碳核算模型，结合蒙特卡洛模拟参数不确定性。","完全采纳下碳强度降21.5%，化肥减量达标概率90.6%，但总节水≥20%概率仅20%。","农业绿色发展与碳","可延伸研究AI平台在不同作物场景下的节水短板及多目标优化策略。","agent","2026-09-28T00:03:02.301756Z",{"total":19,"page":20,"page_size":19,"items":127},[128,259,313,392,446,506],{"id":129,"title":130,"url":131,"summary":132,"summary_zh":133,"content":8,"source_name":134,"source_url":131,"published_at":135,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":136,"score_detail":137,"sources":139,"tags":141,"primary_topic":144,"secondary_topics":150,"classification":157,"search_phrases":213,"slug":216,"view_count":58,"doi":217,"paper":218,"created_at":258},1325,"Changing pest dynamics and pesticide use in cotton: Challenges and sustainable management","https:\u002F\u002Fdoi.org\u002F10.14719\u002Fpst.16195","Cotton (Gossypium spp.) is one of the world’s most important fibre crops, yet its sustainability is increasingly challenged by evolving pest complexes, intensified pesticide use, climate change and climate variability. The evidence indicates current knowledge on pest dynamics, pesticide dependence and ecological interactions in cotton agroecosystems, highlighting the shift from bollworm-dominated pest complexes to the increasing prevalence of secondary pests following the widespread adoption of Bacillus thuringiensis (Bt) cotton. Although Bt (Cry toxin)-based transgenic cotton technology initially reduced insecticide use against the bollworm complex, primarily lepidopteran species, the emergence of resistance among bollworms and the upsurge of certain sucking pests in recent decades have reinstated insecticide dependence for pest management. This has led to ecological imbalance, non-target toxicity, the decline of pollinator populations and natural enemy communities, biodiversity loss, environmental contamination, accumulation of residues in products and yield challenges, in addition to increased production costs. The review emphasises the critical role of integrated pest management (IPM) strategies that integrate biological control, habitat diversification, resistant cultivars and threshold-based pesticide applications to restore ecological stability. Alternative approaches such as botanical pesticides, nanoformulations and plant volatile-mediated pest regulation are highlighted as promising tools for sustainable pest control. Advances in precision agriculture, including artificial intelligence (AI), machine learning and unmanned aerial vehicle (UAV)-based pesticide delivery systems, have the potential to improve pest surveillance and reduce chemical inputs. Supply-chain procurement, certification, traceability and consumer demand can encourage lower-pesticide production, although these mechanisms require fair price incentives to avoid transferring compliance costs to smallholders. Sustainable cotton therefore requires region-specific, climate-resilient, evidence-based IPM supported by extension, market incentives, resistance monitoring and coordinated policy.","棉花（Gossypium spp.）是全球最重要的纤维作物之一，然而其可持续性正日益受到害虫群落演变、农药使用强度增加、气候变化及气候变率等因素的挑战。现有证据表明，当前对棉花农业生态系统中害虫动态、农药依赖及生态互作的认识，凸显了自苏云金芽孢杆菌（Bacillus thuringiensis, Bt）棉花广泛推广以来，害虫群落从以棉铃虫为主向次生害虫日益增多的转变。尽管基于Bt（Cry毒素）的转基因棉花技术最初减少了对棉铃虫复合体（主要为鳞翅目害虫）的杀虫剂使用，但近几十年来棉铃虫抗药性的出现及某些刺吸式害虫的激增，重新导致害虫管理对杀虫剂的依赖。这引发了生态失衡、非靶标毒性、传粉昆虫种群及天敌群落减少、生物多样性丧失、环境污染、产品中残留物积累及产量挑战，同时增加了生产成本。本综述强调了综合害虫管理（IPM）策略的关键作用，该策略整合生物防治、生境多样化、抗性品种及基于阈值的农药施用，以恢复生态稳定性。植物源农药、纳米制剂及植物挥发物介导的害虫调控等替代方法，被强调为可持续害虫防治的有前景工具。精准农业的进展，包括人工智能（AI）、机器学习及基于无人机（UAV）的农药施用系统，有望改善害虫监测并减少化学投入。供应链采购、认证、可追溯性及消费者需求可促进低农药生产，但这些机制需辅以公平价格激励，以避免将合规成本转嫁给小农户。因此，可持续棉花生产需要区域特异性、气候韧性、基于证据的IPM，并辅以推广服务、市场激励、抗性监测及协调政策支持。","Plant Science Today","2026-08-31T00:00:00Z",72,{"impact":16,"substance":17,"depth":16,"authority":18,"freshness":114,"relevant":20,"comment":138},"综述性论文，系统分析棉花害虫动态与农药依赖问题，提出IPM与精准农业等可持续路径，对农业绿色发展有参考价值。",[140],{"name":134,"url":131},[25,26,142,27,143],"棉花","病虫害防治",{"code":145,"slug":146,"name":147,"path":148,"parent_code":149},"A6","cash-crops","棉麻糖与特色经作","\u002Ftopic\u002Ffield-crops\u002Fcash-crops","A",[151,152],{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},{"code":106,"slug":153,"name":154,"path":155,"parent_code":156},"agricultural-ai","农业AI与大模型","\u002Ftopic\u002Fdigital-agriculture\u002Fagricultural-ai","I",{"status":38,"locked":13,"version":39,"method":40,"evidence":158},{"candidates":159,"agricultural_evidence":46},[160,166,172,179,187,194,201,207],{"code":31,"score":16,"supported":46,"title":161,"abstract":163,"tags":165},[162],"pesticide",[54,164,162],"生物防治",[27],{"code":145,"score":167,"supported":46,"title":168,"abstract":170,"tags":171},15,[169],"cotton",[142,169],[142],{"code":106,"score":12,"supported":46,"title":173,"abstract":174,"tags":178},[],[175,176,177],"机器学习","machine learning","artificial intelligence",[26],{"code":180,"score":45,"supported":46,"title":181,"abstract":182,"tags":186},"H6",[],[183,184,185],"生物多样性","农业生态","biodiversity",[],{"code":44,"score":188,"supported":46,"title":189,"abstract":190,"tags":193},7,[],[191,192],"精准农业","precision agriculture",[25],{"code":195,"score":19,"supported":46,"title":196,"abstract":197,"tags":200},"H7",[],[198,199],"气候变化","climate change",[],{"code":202,"score":58,"supported":46,"title":203,"abstract":204,"tags":206},"A4",[],[205],"花生",[],{"code":208,"score":58,"supported":46,"title":209,"abstract":210,"tags":212},"G2",[],[211],"小农户",[],[214,215],"农业人工智能 病虫害防治 农药减量 智慧农业","农业人工智能 病虫害防治","农业人工智能病虫害防治农药减量智慧农业-1325","10.14719\u002Fpst.16195",{"doi":217,"openalex_id":219,"authors":220,"venue":134,"cited_by_count":117,"oa_url":131,"card":251,"direction":256,"ingested_from":257},"W7204806269",[221,224,227,230,233,236,239,242,245,248],{"name":222,"orcid":223},"V Veeragowtham","https:\u002F\u002Forcid.org\u002F0009-0002-9822-4901",{"name":225,"orcid":226},"A. Suganthi","https:\u002F\u002Forcid.org\u002F0000-0001-7013-4459",{"name":228,"orcid":229},"M. Murugan","https:\u002F\u002Forcid.org\u002F0000-0002-7485-1153",{"name":231,"orcid":232},"P. Renukadevi","https:\u002F\u002Forcid.org\u002F0000-0001-9665-1681",{"name":234,"orcid":235},"S. Vellaikumar","https:\u002F\u002Forcid.org\u002F0000-0001-9277-457X",{"name":237,"orcid":238},"Ali Iqra","https:\u002F\u002Forcid.org\u002F0009-0008-6095-9471",{"name":240,"orcid":241},"J Kousika","https:\u002F\u002Forcid.org\u002F0000-0002-2455-5268",{"name":243,"orcid":244},"Sheela Venugopal","https:\u002F\u002Forcid.org\u002F0000-0002-4689-4105",{"name":246,"orcid":247},"Prakash Kolanchi","https:\u002F\u002Forcid.org\u002F0000-0003-1244-199X",{"name":249,"orcid":250},"Murugesh Dharani","https:\u002F\u002Forcid.org\u002F0009-0004-6705-1344",{"tldr":252,"method":253,"finding":254,"direction":122,"opportunity":255},"综述棉花害虫动态与农药使用变化，提出可持续管理策略。","综述文献，分析Bt棉影响、害虫抗性及IPM、精准农业等技术。","Bt棉导致次生害虫上升和抗性，需综合IPM与精准农业减少农药。","可研究AI与无人机在棉花害虫监测与精准施药中的实际应用效果及小农采纳机制。","农业人工智能与决策模型","openalex","2026-09-01T23:30:34.470501Z",{"id":260,"title":261,"url":262,"summary":263,"summary_zh":8,"content":264,"source_name":265,"source_url":8,"published_at":266,"category":267,"cover_url":8,"hotness":12,"is_selected":13,"score":268,"score_detail":269,"sources":274,"tags":276,"primary_topic":280,"secondary_topics":281,"classification":282,"search_phrases":308,"slug":311,"view_count":20,"doi":8,"paper":8,"created_at":312},5108,"广西西林:粤桂协作赋能 深山桔园请来「AI管家」 化肥农药减量20%以上","https:\u002F\u002Fdifang.gmw.cn\u002Fgx\u002F2026-10\u002F16\u002Fcontent_39050109.htm","广西百色市西林县古障镇仙仁掌村桔园,无人机升空巡测快速识别叶片黄化、缺水、病虫害等异常。依托粤桂协作对口帮扶资源,西林联合深圳市罗湖区、深圳市丰农控股,在233亩核心示范基地搭建「无人机+AI」全域监测平台,气象、墒情、虫情、灾情监测设备全天候运行。核心示范区化肥、农药用量减少20%以上,人工管护成本下降30%,果树亩均产量提升15%,优质果率提高8个百分点;全镇果园管理效率提升60%,每年减少农业灾害损失100万至150万元,全域每年节约农资成本超1426万元。","![Image 3](https:\u002F\u002Fimg.gmw.cn\u002Fpic\u002FgmwLogo_share.jpg)\n\n点击右上角![Image 4](https:\u002F\u002Fimg.gmw.cn\u002Fpic\u002Fmgmw\u002Ficonshare.png)微信好友\n\n![Image 5](https:\u002F\u002Fimg.gmw.cn\u002Fpic\u002Fmgmw\u002Fpengyouquan.png)朋友圈\n\n![Image 6](https:\u002F\u002Fimg.gmw.cn\u002Fpic\u002Fmgmw\u002Flayershare.png)\n\n请使用浏览器分享功能进行分享\n\n![Image 7](https:\u002F\u002Fimg.gmw.cn\u002Fpic\u002Fmgmw\u002Farrow.png)\n\n[![Image 8: 地方频道](https:\u002F\u002Fimg.gmw.cn\u002Fpic\u002Fcontentlogo\u002F12684.gif)](https:\u002F\u002Fdifang.gmw.cn\u002F)\n\n![Image 9](https:\u002F\u002Fimg.gmw.cn\u002Fpic\u002Fmgmw\u002Fmline.png)![Image 10](https:\u002F\u002Fimg.gmw.cn\u002Fpic\u002Fconimages\u002Fm_pc_btn.png)![Image 11](https:\u002F\u002Fimg.gmw.cn\u002Fpic\u002Fconimages\u002Fm_mobile_btn.png)\n\n[![Image 12](https:\u002F\u002Fimg.gmw.cn\u002Fpic\u002Fmgmw\u002FmClose.png)](javascript:void(0);)\n\n# 全部导航\n\n*   [时政](https:\u002F\u002Fpolitics.gmw.cn\u002F)\n*   [国际](https:\u002F\u002Fworld.gmw.cn\u002F)\n*   [时评](https:\u002F\u002Fguancha.gmw.cn\u002F)\n*   [理论](https:\u002F\u002Ftheory.gmw.cn\u002F)\n*   [文化](https:\u002F\u002Fculture.gmw.cn\u002F)\n*   [科技](https:\u002F\u002Ftech.gmw.cn\u002F)\n*   [教育](https:\u002F\u002Fedu.gmw.cn\u002F)\n*   [经济](https:\u002F\u002Feconomy.gmw.cn\u002F)\n*   [生活](https:\u002F\u002Flife.gmw.cn\u002F)\n*   [法治](https:\u002F\u002Flegal.gmw.cn\u002F)\n*   [专题](https:\u002F\u002Ftopics.gmw.cn\u002F)\n*   [ENGLISH](https:\u002F\u002Fen.gmw.cn\u002F)\n\n*   [时政](https:\u002F\u002Fpolitics.gmw.cn\u002F)\n*   [国际](https:\u002F\u002Fworld.gmw.cn\u002F)\n*   [时评](https:\u002F\u002Fguancha.gmw.cn\u002F)\n*   [理论](https:\u002F\u002Ftheory.gmw.cn\u002F)\n*   [文化](https:\u002F\u002Fculture.gmw.cn\u002F)\n*   [科技](https:\u002F\u002Ftech.gmw.cn\u002F)\n*   [教育](https:\u002F\u002Fedu.gmw.cn\u002F)\n*   [![Image 13](https:\u002F\u002Fimg.gmw.cn\u002Fpic\u002Fconimages\u002Fcon_headIcon.png)](https:\u002F\u002Fwww.gmw.cn\u002Fmap.htm)\n\n正在阅读：广西西林:粤桂协作赋能，深山桔园请来 “AI 管家”\n\n[首页](https:\u002F\u002Fwww.gmw.cn\u002F)>[![Image 14](https:\u002F\u002Fimg.gmw.cn\u002Fpic\u002Fcontentlogo\u002F12684.gif)](https:\u002F\u002Fdifang.gmw.cn\u002F)[地方频道](https:\u002F\u002Fdifang.gmw.cn\u002F)>[地方频道－广西](https:\u002F\u002Fdifang.gmw.cn\u002Fgx\u002F)>[当地新闻](https:\u002F\u002Fdifang.gmw.cn\u002Fgx\u002Fnode_12944.htm)>正文\n\n# 广西西林:粤桂协作赋能，深山桔园请来 “AI 管家”\n\n来源：[光明日报客户端](https:\u002F\u002Fapp.gmdaily.cn\u002Fas\u002Fopened\u002Fn\u002F59cdd34806ab4ec7b66540c2cb9dc89e)2026-10-16 12:43\n\n[](https:\u002F\u002Fdifang.gmw.cn\u002Fgx\u002F2026-10\u002F16\u002Fcontent_39050109.htm)[X](javascript:;)[](https:\u002F\u002Fdifang.gmw.cn\u002Fgx\u002F2026-10\u002F16\u002Fcontent_39050109.htm)\n\n清晨，广西百色市西林县古障镇仙仁掌村桔园，晨露未消，无人机升空巡测，快速识别叶片黄化、缺水、病虫害等果园异常。智慧管护，正成为当地沙糖桔产业的生产常态。\n\n西林是“中国沙糖桔之乡”，沙糖桔种植面积达22.46万亩，是群众增收的支柱产业。但境内山地多、果园地块零散，长期沿用传统管护模式，施肥打药依靠经验，收成受天气影响大。粗放种植造成果品品质不稳定，病虫害、自然灾害带来减产风险，制约产业效益提升。\n\n![Image 15: twitter](https:\u002F\u002Fimgdifang.gmw.cn\u002Fattachement\u002Fpng\u002Fsite2\u002F20261016\u002Fe4232a100a384446b18875424e94dd72.png)\n\n依托粤桂协作对口帮扶资源，西林联合深圳市罗湖区、深圳市丰农控股，在古障镇仙仁掌村打造智慧农业试点，搭建“无人机+AI”全域监测平台，探索山地桔园数字化管护，破解“看天吃饭”困境。\n\n在233亩核心示范基地，气象、墒情、虫情、灾情监测设备全天候运行，无人机定期空中巡园，土壤、病虫害、气象等数据实时回传。AI系统自动分析研判，给出农事指导，改变过去果农肉眼巡查果园的传统方式。\n\n项目按照“基地做示范，全镇一张图，全县一个码”三步走推进智慧果园建设。先以上、下俄屯基地打造样板，配套海拔梯度采集点，跑通“数据采集—AI建模—标准输出”流程，优化适配本地沙糖桔的算法模型，解决智慧农业技术“水土不服”问题。第二步完成全镇7.13万亩沙糖桔标准化航测，建成“产业一张图”数字平台，地块信息、产业风险一屏可查，产业管理由凭经验估变为凭数据管。第三步打造“掌上桔事”小程序，把灾害预警、农事指导、AI问诊直达农户手机。目前小程序正在内测，上线后将惠及全县8万多户果农。\n\n![Image 16: twitter](https:\u002F\u002Fimgdifang.gmw.cn\u002Fattachement\u002Fpng\u002Fsite2\u002F20261016\u002Ff025b13ba3384034afba14495fc87f4d.png)\n\n“以前种果全靠摸索，天天跑果园巡查，病虫害也不好分辨。现在靠AI系统管护省心很多，期待明年好收成。”首批试点果农、古障镇仙仁掌村上俄屯组长秦锋说。\n\n数字化落地成效显著。核心示范区化肥、农药用量减少20%以上，人工管护成本下降30%，果树亩均产量提升15%，优质果率提高8个百分点；全镇果园管理效率提升60%，每年减少农业灾害损失100万至150万元，全域每年节约农资成本超1426万元。\n\n不少地方智慧农业容易变成观赏“盆景”。西林立足山地特点，聚焦生产实效、农户增收，让数字技术扎根田间。丰农控股广西总经理陈洁介绍，依托AI技术加持，深山沙糖桔产业迎来新机遇。西林计划用三到五年推动沙糖桔产业从“靠人力、凭经验”转向“靠系统、用数据”，打造山地沙糖桔全链路数智化样板。（光明日报全媒体记者 周仕兴 通讯员 杨先能）\n\n[ 责编：王宏泽 ]\n\n阅读剩余全文（）\n\n![Image 17](https:\u002F\u002Fimg.gmw.cn\u002Fcontent_banner\u002Fcontent_840x120_qrcodes.jpg)\n\n## 相关阅读\n\n*   [![Image 18](https:\u002F\u002Fdifang.gmw.cn\u002Fgx\u002F2026-10\u002F16\u002Fcontent_39050109.htm)](javascript:;)    \n*   [![Image 19](https:\u002F\u002Fdifang.gmw.cn\u002Fgx\u002F2026-10\u002F16\u002Fcontent_39050109.htm)](javascript:;)    \n*   [](javascript:;)[](javascript:;)[](javascript:;)[](javascript:;)\n\n## 您此时的心情\n\n[![Image 20: 光明云投](https:\u002F\u002Fimg.gmw.cn\u002Fpic\u002Fconimages\u002Fyuntoulogo.png)](https:\u002F\u002Fvote.gmw.cn\u002F)\n\n新闻表情排行[日](https:\u002F\u002Fwww.gmw.cn\u002Fmotionsdaytop.htm)\u002F[周](https:\u002F\u002Fwww.gmw.cn\u002Fmotionsweektop.htm)\n\n*   [![Image 21](https:\u002F\u002Fimg.gmw.cn\u002Fpic\u002Fconimages\u002Fico_motion_1.png)](https:\u002F\u002Fdifang.gmw.cn\u002Fgx\u002F2026-10\u002F16\u002Fcontent_39050109.htm)开心   0   \n*   [![Image 22](https:\u002F\u002Fimg.gmw.cn\u002Fpic\u002Fconimages\u002Fico_motion_2.png)](https:\u002F\u002Fdifang.gmw.cn\u002Fgx\u002F2026-10\u002F16\u002Fcontent_39050109.htm)难过   0   \n*   [![Image 23](https:\u002F\u002Fimg.gmw.cn\u002Fpic\u002Fconimages\u002Fico_motion_3.png)](https:\u002F\u002Fdifang.gmw.cn\u002Fgx\u002F2026-10\u002F16\u002Fcontent_39050109.htm)点赞   0   \n*   [![Image 24](https:\u002F\u002Fimg.gmw.cn\u002Fpic\u002Fconimages\u002Fico_motion_4.png)](https:\u002F\u002Fdifang.gmw.cn\u002Fgx\u002F2026-10\u002F16\u002Fcontent_39050109.htm)飘过   0   \n\n## 视觉焦点\n\n*   [![Image 25](https:\u002F\u002Fimgdifang.gmw.cn\u002Fattachement\u002Fjpg\u002Fsite2\u002F20261016\u002F3ab721cf47be4960823a8636e4478b8e.jpg)](https:\u002F\u002Fkepu.gmw.cn\u002F2026-10\u002F16\u002Fcontent_39050695.htm)  \n来中国科技馆，和科学家击掌！\n\n*   [![Image 26](https:\u002F\u002Fimgdifang.gmw.cn\u002Fattachement\u002Fjpg\u002Fsite2\u002F20261016\u002F115e67cd19084c568c2edd94f9e6391c.jpg)](https:\u002F\u002Ftheory.gmw.cn\u002F2026-10\u002F16\u002Fcontent_39046807.htm)  \n理响中国·幸福有“理”\n\n## 最热文章\n\n*   [一见·习近平主席三封广交会贺信的“开放”底色](https:\u002F\u002Fpolitics.gmw.cn\u002F2026-10\u002F16\u002Fcontent_39050949.htm) 1\n*   [和总书记面对面丨每一代人都要走好自己的长征路](https:\u002F\u002Fpolitics.gmw.cn\u002F2026-10\u002F16\u002Fcontent_39050945.htm) 2\n*   [微视频丨聆听总书记深情话语 赓续伟大长征精神](https:\u002F\u002Fpolitics.gmw.cn\u002F2026-10\u002F16\u002Fcontent_39050729.htm) 3\n*   [多项数据创新高！“进博时间”将开启 筹备已基本就绪](https:\u002F\u002Fpolitics.gmw.cn\u002F2026-10\u002F16\u002Fcontent_39050957.htm) 4\n*   [30年，这粒种子守护大国粮仓](https:\u002F\u002Fpolitics.gmw.cn\u002F2026-10\u002F16\u002Fcontent_39050997.htm) 5\n*   [深入实施全谷物行动计划 促进节粮减损和营养健康](https:\u002F\u002Fpolitics.gmw.cn\u002F2026-10\u002F16\u002Fcontent_39049378.htm) 6\n*   [群众身边不正之风和腐败问题集中整治成效观察](https:\u002F\u002Fpolitics.gmw.cn\u002F2026-10\u002F16\u002Fcontent_39049141.htm) 7\n*   [2025年我国研究与试验发展经费投入突破3.9万亿元](https:\u002F\u002Fpolitics.gmw.cn\u002F2026-10\u002F16\u002Fcontent_39050803.htm) 8\n*   [国防部：中方将以有力行动遏制任何祸乱南海的行径](https:\u002F\u002Fpolitics.gmw.cn\u002F2026-10\u002F16\u002Fcontent_39050720.htm) 9\n*   [外交部：望欧方同中方相向而行推动中欧贸易发展](https:\u002F\u002Fpolitics.gmw.cn\u002F2026-10\u002F16\u002Fcontent_39050765.htm) 10\n\n## 独家策划\n\n*   [![Image 27](https:\u002F\u002Fimgdifang.gmw.cn\u002Fattachement\u002Fjpg\u002Fsite2\u002F20260918\u002Fdcd47048fbc148c18e29bbf71cbb75c6.jpg)](https:\u002F\u002Ftopics.gmw.cn\u002Fnode_170734.htm) [赓续长征精神 奋进复兴征程](https:\u002F\u002Ftopics.gmw.cn\u002Fnode_170734.htm)  [第十一个全民国家安全教育日](https:\u002F\u002Ftopics.gmw.cn\u002Fnode_168693.htm) [![Image 28](https:\u002F\u002Fimgdifang.gmw.cn\u002Fattachement\u002Fjpg\u002Fsite2\u002F20260415\u002F005056b837832b49959d02.jpg)](https:\u002F\u002Ftopics.gmw.cn\u002Fnode_168693.htm)  \n*   [![Image 29](https:\u002F\u002Fimgdifang.gmw.cn\u002Fattachement\u002Fjpg\u002Fsite2\u002F20260918\u002F0aba89129d0f45b8a77ac2b07d7dbfeb.jpg)](https:\u002F\u002Ftopics.gmw.cn\u002Fnode_170718.htm) [2026年亚运会](https:\u002F\u002Ftopics.gmw.cn\u002Fnode_170718.htm)  [树立和践行正确政绩观](https:\u002F\u002Ftopics.gmw.cn\u002Fnode_168213.htm) [![Image 30](https:\u002F\u002Fimgdifang.gmw.cn\u002Fattachement\u002Fjpg\u002Fsite2\u002F20260308\u002Ff44d305ea6dd2b175a4037.jpg)](https:\u002F\u002Ftopics.gmw.cn\u002Fnode_168213.htm)  \n*   [![Image 31](https:\u002F\u002Fimgdifang.gmw.cn\u002Fattachement\u002Fjpg\u002Fsite2\u002F20260617\u002Ff44d305ea6dd2b9c4b4626.jpg)](https:\u002F\u002Ftopics.gmw.cn\u002Fnode_169453.htm) [庆祝中国共产党成立105周年](https:\u002F\u002Ftopics.gmw.cn\u002Fnode_169453.htm)  [2026年全国两会](https:\u002F\u002Ftopics.gmw.cn\u002Fnode_168093.htm) [![Image 32](https:\u002F\u002Fimgdifang.gmw.cn\u002Fattachement\u002Fjpg\u002Fsite2\u002F20260303\u002Ff44d305ea48e2b1074620b.jpg)](https:\u002F\u002Ftopics.gmw.cn\u002Fnode_168093.htm)  \n\n推荐阅读\n\n[](https:\u002F\u002Fkepu.gmw.cn\u002Feco\u002F2026-10\u002F16\u002Fcontent_39050641.htm)\n\n[2026世界生态环境十大科技进展揭晓](https:\u002F\u002Fkepu.gmw.cn\u002Feco\u002F2026-10\u002F16\u002Fcontent_39050641.htm)\n\n当前全球生态环境挑战日益严峻，科技创新是应对可持续发展挑战的核心力量。\n\n2026-10-16 16:29\n\n[](https:\u002F\u002Fkepu.gmw.cn\u002F2026-10\u002F16\u002Fcontent_39048568.htm)\n\n[全国粮食安全宣传周｜玉米“吨粮田”里的科技密码](https:\u002F\u002Fkepu.gmw.cn\u002F2026-10\u002F16\u002Fcontent_39048568.htm)\n\n10月16日是第四十六个世界粮食日，所在周是全国粮食安全宣传周，主题为“创新当下，粮安未来”。从良种选育、智能农机到数字农业、精准储运，创新正成为粮食增产、节粮减损、营养提升的关键引擎。即日起，光明网联合科普中国推出系列科普视频，深入解读科技创新绘就的粮安答卷。\n\n2026-10-16 08:46\n\n[](https:\u002F\u002Ftech.gmw.cn\u002F2026-10\u002F16\u002Fcontent_39049222.htm)\n\n[科技观察｜电子纸的彩色突围：从电子阅读走向智能办公](https:\u002F\u002Ftech.gmw.cn\u002F2026-10\u002F16\u002Fcontent_39049222.htm)\n\n在显示技术升级与人工智能赋能的双重驱动下，行业正跳出传统数字阅读的固有边界\n\n2026-10-16 08:45\n\n[](https:\u002F\u002Ftech.gmw.cn\u002F2026-10\u002F16\u002Fcontent_39049208.htm)\n\n[香港首个具身智能国际应用训练场开幕](https:\u002F\u002Ftech.gmw.cn\u002F2026-10\u002F16\u002Fcontent_39049208.htm)\n\n打造集技术研发、模型训练、系统验证及场景测试于一体的创新基地，推动人形机器人及具身智能技术从实验室研发阶段走向大规模产业应用。\n\n2026-10-16 08:39\n\n[](https:\u002F\u002Ftech.gmw.cn\u002F2026-10\u002F16\u002Fcontent_39049199.htm)\n\n[工信部等三部门联合调查有关车辆刹车踏板支架断裂问题](https:\u002F\u002Ftech.gmw.cn\u002F2026-10\u002F16\u002Fcontent_39049199.htm)\n\n工业和信息化部、中央网信办、市场监管总局高度重视，在前期调查工作基础上，成立联合调查组开展核查，并依法依规处理。有关情况将及时公布。\n\n2026-10-16 08:40\n\n[](https:\u002F\u002Ftech.gmw.cn\u002F2026-10\u002F16\u002Fcontent_39049177.htm)\n\n[2026世界储能大会在福建宁德开幕 18个产业项目集中对接](https:\u002F\u002Ftech.gmw.cn\u002F2026-10\u002F16\u002Fcontent_39049177.htm)\n\n大会延续“零碳·科技”永久主题，以“智储新程 绿动全球”为年度主题\n\n2026-10-16 08:35\n\n[](https:\u002F\u002Ftech.gmw.cn\u002F2026-10\u002F15\u002Fcontent_39047749.htm)\n\n[久久为功 “点绿成金”](https:\u002F\u002Ftech.gmw.cn\u002F2026-10\u002F15\u002Fcontent_39047749.htm)\n\n“戈壁荒滩老风口，飞沙走石雁不留。托里县老风口蝶变的三部曲，为生态脆弱地区推动高质量发展、树立和践行正确政绩观，提供了深刻启示。树立和践行正确政绩观，就要算大账、算长远账、算整体账，既做显功、也做潜功，把生态优势转化为发展优势、民生福祉。\n\n2026-10-15 09:51\n\n[](https:\u002F\u002Ftech.gmw.cn\u002F2026-10\u002F15\u002Fcontent_39047718.htm)\n\n[我科学家首次观测到临界拓扑态](https:\u002F\u002Ftech.gmw.cn\u002F2026-10\u002F15\u002Fcontent_39047718.htm)\n\n常压下，水到0℃会结冰，这就是人们熟悉的相变，0℃即是相变的临界点。两篇论文的共同通讯作者、宁波东方理工大学助理教授余雪佳，把这个难题比作“在沸水中完好保存一件冰雕”。\n\n2026-10-15 09:49\n\n[](https:\u002F\u002Ftech.gmw.cn\u002F2026-10\u002F15\u002Fcontent_39047675.htm)\n\n[这个打破常识的发现因何而来](https:\u002F\u002Ftech.gmw.cn\u002F2026-10\u002F15\u002Fcontent_39047675.htm)\n\n长久以来，古生物学界与教科书普遍认为琥珀皆源自种子植物（裸子或被子植物），最古老的确切记录定格在美国约3.2亿年前的石炭纪晚期。\n\n2026-10-15 09:48\n\n[](https:\u002F\u002Ftech.gmw.cn\u002F2026-10\u002F15\u002Fcontent_39047658.htm)\n\n[科技创新下一程，不是“接力赛”！](https:\u002F\u002Ftech.gmw.cn\u002F2026-10\u002F15\u002Fcontent_39047658.htm)\n\n在芯片制造、航空发动机等高端硬核制造领域，技术迭代具有长周期、累积性、阶梯式特征，遵循循序渐进、层层突破的线性攻关规律。新征程上，持续深耕创新生态建设、迭代升级现代化创新体系，必能培育形成扎根中国、联通世界、内生增长、开放共生的创新新格局。\n\n2026-10-15 09:46\n\n[](https:\u002F\u002Ftech.gmw.cn\u002F2026-10\u002F15\u002Fcontent_39047651.htm)\n\n[冲刺顶刊，我们还有多远](https:\u002F\u002Ftech.gmw.cn\u002F2026-10\u002F15\u002Fcontent_39047651.htm)\n\n受困于“小散弱”的格局，长期以来，我国科技期刊在国际学术传播体系中缺少属于自己的“拳头产品”与平台话语权——“在精品化发展方面，经过70余年积淀，我国已形成以《中国科学》《科学通报》《国家科学评论》等刊群为代表的高水平期刊方阵。\n\n2026-10-15 09:45\n\n[](https:\u002F\u002Ftech.gmw.cn\u002F2026-10\u002F14\u002Fcontent_39045808.htm)\n\n[AI想选题，人越来越不会“提出问题”](https:\u002F\u002Ftech.gmw.cn\u002F2026-10\u002F14\u002Fcontent_39045808.htm)\n\nAI时代，科研的“源头活水”是什么？不是算力，不是数据，而是人对未知世界的好奇与追问。\n\n2026-10-14 11:28\n\n[](https:\u002F\u002Ftech.gmw.cn\u002F2026-10\u002F14\u002Fcontent_39045305.htm)\n\n[通信网含“新”量与日俱增——我国推动信息通信行业高质量发展](https:\u002F\u002Ftech.gmw.cn\u002F2026-10\u002F14\u002Fcontent_39045305.htm)\n\n截至8月末，三家基础电信企业的固定互联网宽带接入用户总数7.04亿户，比上年末净增1365万户；三家基础电信企业及中国广电的移动电话用户总数18.49亿户，其中5G移动电话用户13.11亿户。\n\n2026-10-14 09:34\n\n[](https:\u002F\u002Ftech.gmw.cn\u002F2026-10\u002F14\u002Fcontent_39045218.htm)\n\n[我国优化调整矿产资源目录](https:\u002F\u002Ftech.gmw.cn\u002F2026-10\u002F14\u002Fcontent_39045218.htm)\n\n自然资源部会同国家发展改革委12日发布《矿产资源目录》。自然资源部矿产资源保护监督司负责人表示，矿产资源目录是矿产资源管理制度的重要基础，是制定矿产资源规划、实施矿业权管理、规范矿产资源勘查开采行为、征缴矿产资源税费、制定产业政策等工作的依据。\n\n2026-10-14 09:40\n\n[](https:\u002F\u002Ftech.gmw.cn\u002F2026-10\u002F14\u002Fcontent_39045301.htm)\n\n[海拔3650米，高原水稻突破种植上限（秋收进行时·不一样的水稻品种）](https:\u002F\u002Ftech.gmw.cn\u002F2026-10\u002F14\u002Fcontent_39045301.htm)\n\n与共康村相邻的巴达村，是第一批参与试种的村，也是西藏首个高海拔水稻实测亩产破千斤的村子，村民把“海拔3175米种水稻”写进村史。一粒水稻种子，不只改写了亩产数字，更改变了“西藏水稻只能在察隅、墨脱海拔1500米以下种植”的历史，为高原水稻纳入地方主粮增添可能。\n\n2026-10-14 09:41\n\n[](https:\u002F\u002Ftech.gmw.cn\u002F2026-10\u002F14\u002Fcontent_39045297.htm)\n\n[面对AI，如何成为会提问的人](https:\u002F\u002Ftech.gmw.cn\u002F2026-10\u002F14\u002Fcontent_39045297.htm)\n\n如今，AI正改变许多行业的底层逻辑，固守单一思维模式将面临严峻挑战，文理兼备、跨界融合才是稀缺能力——既有理科生的技术思维和逻辑能力，又有文科生的人文洞察和情感素养。未来更有竞争力的，可能不是最典型的文科生或理科生，而是既有专业深度，又能跨学科解决问题的人。\n\n2026-10-14 09:48\n\n[](https:\u002F\u002Ftech.gmw.cn\u002F2026-10\u002F14\u002Fcontent_39045293.htm)\n\n[深海科技，下水见真章](https:\u002F\u002Ftech.gmw.cn\u002F2026-10\u002F14\u002Fcontent_39045293.htm)\n\n不久前，在海南三亚崖州湾科技城，一场名为“青年π”的海洋主题对话临海开讲。高频下潜试出的不只有装备可靠性，也不断刷新人们对深海的认识。同一园区，由哈尔滨工程大学南海研究院孵化的海南水之声海洋科技有限公司，正给海洋装备搭水下“Wi－Fi”。\n\n2026-10-14 09:49\n\n[](https:\u002F\u002Ftech.gmw.cn\u002F2026-10\u002F13\u002Fcontent_39042838.htm)\n\n[重点人群尽量在流感季来临前接种疫苗](https:\u002F\u002Ftech.gmw.cn\u002F2026-10\u002F13\u002Fcontent_39042838.htm)\n\n目前各地正在开展流感疫苗接种。今年开始，国家对农村地区“一老一小”重点人群实施免费接种等相关支持性政策。为什么要接种流感疫苗？去年接种过，今年是否还需要接种？到哪里接种？\n\n2026-10-13 10:03\n\n[](https:\u002F\u002Ftech.gmw.cn\u002F2026-10\u002F13\u002Fcontent_39042835.htm)\n\n[让山河可触，尊严可感](https:\u002F\u002Ftech.gmw.cn\u002F2026-10\u002F13\u002Fcontent_39042835.htm)\n\n我国城市盲道总里程以万公里计，公共场所无障碍设施持续铺开。数字世界的“盲道”畅通起来。精神文化的“视界”也在扩大。中国传媒大学师生发起的“光明影院”项目，近十年间每年制作上百部无障碍电影，把电影送到视障朋友耳边，今年还走进联合国教科文组织总部举办专场放映。\n\n2026-10-13 10:01\n\n[](https:\u002F\u002Fpolitics.gmw.cn\u002F2026-10\u002F13\u002Fcontent_39042222.htm)\n\n[截至今年上半年我国生成式人工智能用户规模超7亿人](https:\u002F\u002Fpolitics.gmw.cn\u002F2026-10\u002F13\u002Fcontent_39042222.htm)\n\n记者近期从中国互联网络信息中心获悉：截至今年上半年，我国生成式人工智能用户规模超7亿人，普及率超50%。\n\n2026-10-13 09:58\n\n[加载更多](javascript:void(0);)\n\n光明网版权所有\n\n*   [光明日报社概况](https:\u002F\u002Fabout.gmw.cn\u002Fnode_21441.htm)\n*   [关于光明网](https:\u002F\u002Fabout.gmw.cn\u002Faboutus.htm)\n*   [报网动态](https:\u002F\u002Fabout.gmw.cn\u002Fnode_8926.htm)\n*   [联系我们](https:\u002F\u002Fabout.gmw.cn\u002Fnode_46280.htm)\n*   [法律声明](https:\u002F\u002Fabout.gmw.cn\u002Fnode_46279.htm)\n*   [光明网邮箱](https:\u002F\u002Fmail.gmw.cn\u002F)\n*   [网站地图](https:\u002F\u002Fwww.gmw.cn\u002Fmap.htm)\n\n![Image 33](https:\u002F\u002Fchannel-analysis.gmw.cn\u002F1.gif?s=1792195992041&cl=12944&pd=2026-10-16&ci=39050109&r=https:\u002F\u002Fdifang.gmw.cn\u002Fgx\u002F2026-10\u002F16\u002Fcontent_39050109.htm&at=%E7%8E%8B%E5%AE%8F%E6%B3%BD&tt=%E5%B9%BF%E8%A5%BF%E8%A5%BF%E6%9E%97:%E7%B2%A4%E6%A1%82%E5%8D%8F%E4%BD%9C%E8%B5%8B%E8%83%BD%EF%BC%8C%E6%B7%B1%E5%B1%B1%E6%A1%94%E5%9B%AD%E8%AF%B7%E6%9D%A5%20%E2%80%9CAI%20%E7%AE%A1%E5%AE%B6%E2%80%9D%20_%E5%85%89%E6%98%8E%E7%BD%91)\n\n[](https:\u002F\u002Fwww.facebook.com\u002Fguangmingonline)[](https:\u002F\u002Fwww.facebook.com\u002Fguangmingonline)\n\n[](https:\u002F\u002Ftwitter.com\u002FGuangming_Daily)[](https:\u002F\u002Ftwitter.com\u002FGuangming_Daily)\n\n[](javascript:;)","光明日报全媒体 光明网地方频道 2026 年 10 月 16 日","2026-10-16T00:00:00Z","报道",77,{"impact":16,"substance":270,"depth":271,"authority":272,"freshness":12,"relevant":20,"comment":273},20,16,13,"粤桂协作推动山地桔园AI全域监测落地，化肥农药减量20%以上、亩均增产15%等数据具体，是智慧农业从示范盆景走向生产实效的可复制样本。",[275],{"name":265,"url":262},[277,25,26,278,279],"数字乡村","粤桂协作","沙糖桔",{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},[],{"status":38,"locked":13,"version":39,"method":40,"evidence":283},{"candidates":284,"agricultural_evidence":46},[285,290,295,299,303],{"code":31,"score":286,"supported":46,"title":287,"abstract":288,"tags":289},11,[54],[54],[],{"code":70,"score":58,"supported":46,"title":291,"abstract":292,"tags":294},[],[293],"果树",[],{"code":44,"score":20,"supported":13,"title":296,"abstract":297,"tags":298},[],[],[25],{"code":106,"score":20,"supported":13,"title":300,"abstract":301,"tags":302},[],[],[26],{"code":304,"score":20,"supported":13,"title":305,"abstract":306,"tags":307},"I6",[],[],[277],[309,310],"广西西林 沙糖桔 AI管家","粤桂协作 智慧果园 西林","广西西林沙糖桔AI管家-5108","2026-10-17T00:13:01.843117Z",{"id":314,"title":315,"url":316,"summary":317,"summary_zh":318,"content":8,"source_name":319,"source_url":316,"published_at":320,"category":11,"cover_url":8,"hotness":321,"is_selected":13,"score":322,"score_detail":323,"sources":329,"tags":334,"primary_topic":338,"secondary_topics":339,"classification":340,"search_phrases":367,"slug":370,"view_count":117,"doi":371,"paper":372,"created_at":391},5069,"The impact of digital technology on green economies","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1787960","Introduction Digital agriculture is regarded as an important instrument for achieving green economies, with the potential to raise productivity while reducing environmental impacts. This study explores how digitalization in agriculture affects greenhouse gas emissions, pesticide use and productivity. Methods The research uses a mixed-methods design. Quantitative analysis draws on international environmental and economic indicators for approximately 180 countries between 2000 and 2023 (415 country-year observations), combining Spearman correlations, regression models with GDP interaction terms, and K-means cluster analysis. A qualitative case study of digital agriculture in Latin America complements the statistical findings. Results Digital infrastructure is strongly associated with the adoption of agricultural digital technologies, and smart farming investment is associated with better economic performance of the agricultural sector. Investment in digital agriculture shows a positive association with both emissions and pesticide use, while the interaction with GDP is negative and significant. Cluster analysis confirms that countries with higher GDP and stronger digital infrastructure achieve more balanced environmental outcomes. Discussion The environmental benefits of digital agriculture are conditional on economic capacity. In economically advanced settings, digital technologies reduce resource use, waste and emissions; in economically constrained regions, higher output can offset the environmental gains. Digital agricultural transformation therefore offers opportunities for sustainable development, but its success depends on equitable access to digital technologies and on policy support that mitigates the trade-off between productivity and environmental protection.","引言 数字农业被视为实现绿色经济的重要工具，具有提高生产力同时减少环境影响的潜力。本研究探讨农业数字化如何影响温室气体排放、农药使用和生产力。方法 研究采用混合方法设计。定量分析基于约180个国家2000年至2023年的国际环境和经济指标（415个国家-年份观测值），结合斯皮尔曼相关性分析、包含GDP交互项的回归模型以及K均值聚类分析。拉丁美洲数字农业的定性案例研究补充了统计发现。结果 数字基础设施与农业数字技术的采用密切相关，智慧农业投资与农业部门更好的经济表现相关。数字农业投资与排放量和农药使用量均呈正相关，而与GDP的交互项为负且显著。聚类分析证实，GDP较高且数字基础设施较强的国家实现了更平衡的环境结果。讨论 数字农业的环境效益以经济能力为条件。在经济发达环境中，数字技术减少了资源使用、浪费和排放；在经济受限地区，更高的产出可能抵消环境收益。因此，数字农业转型为可持续发展提供了机遇，但其成功取决于数字技术的公平获取以及能够缓解生产力与环境保护之间权衡的政策支持。","Frontiers in Sustainable Food Systems","2026-10-15T00:00:00Z",25,86,{"impact":17,"substance":324,"depth":325,"authority":326,"freshness":327,"relevant":20,"comment":328},23,19,14,8,"基于180国2000—2023年面板数据与拉美案例，揭示数字农业环境效益受经济水平制约，方法扎实、结论有政策参考价值。",[330,331],{"name":319,"url":316},{"name":332,"url":333},"Frontiers in Sustainable Food Systems 2026-10-15","https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fsustainable-food-systems\u002Farticles\u002F10.3389\u002Ffsufs.2026.1787960\u002Ffull",[335,25,336,337,27],"数字农业","农业数字化","农业碳排放",{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},[],{"status":38,"locked":13,"version":39,"method":40,"evidence":341},{"candidates":342,"agricultural_evidence":46},[343,348,352,359,363],{"code":44,"score":18,"supported":46,"title":344,"abstract":345,"tags":347},[],[25,335,346],"digital agriculture",[336,335,25],{"code":31,"score":188,"supported":46,"title":349,"abstract":350,"tags":351},[],[54,162],[27],{"code":353,"score":19,"supported":46,"title":354,"abstract":355,"tags":358},"B7",[],[356,357],"温室","greenhouse",[],{"code":88,"score":20,"supported":13,"title":360,"abstract":361,"tags":362},[],[],[337],{"code":156,"score":20,"supported":13,"title":364,"abstract":365,"tags":366},[],[],[336],[368,369],"数字农业 温室气体排放","拉丁美洲 数字农业 案例","数字农业温室气体排放-5069","10.3389\u002Ffsufs.2026.1787960",{"doi":371,"openalex_id":373,"authors":374,"venue":319,"cited_by_count":117,"oa_url":384,"card":385,"direction":390,"ingested_from":257},"W7221916400",[375,378,381],{"name":376,"orcid":377},"Botond Géza Kálmán","https:\u002F\u002Forcid.org\u002F0000-0001-8031-8016",{"name":379,"orcid":380},"Zsuzsanna Szeiner","https:\u002F\u002Forcid.org\u002F0000-0003-3051-9674",{"name":382,"orcid":383},"Szilvia Valéria Módosné Szalai","https:\u002F\u002Forcid.org\u002F0009-0005-2164-9014","https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fsustainable-food-systems\u002Farticles\u002F10.3389\u002Ffsufs.2026.1787960\u002Fpdf",{"tldr":386,"method":387,"finding":388,"direction":122,"opportunity":389},"研究约180国2000-2023年数据，分析农业数字化对温室气体排放、农药使用与生产率的影响。","混合方法：Spearman相关、含GDP交互项的回归、K-means聚类，辅以拉","数字农业环境效益取决于经济能力，高GDP国家更均衡，低GDP国家增产抵消环境收益。","可探究不同经济水平下数字农业减排阈值与政策干预机制，关注数字鸿沟对绿色转型的调节作用。","智慧农业 \u002F 农业物联网","2026-10-16T23:30:06.211945Z",{"id":393,"title":394,"url":395,"summary":396,"summary_zh":8,"content":8,"source_name":397,"source_url":8,"published_at":398,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":136,"score_detail":399,"sources":401,"tags":403,"primary_topic":407,"secondary_topics":408,"classification":414,"search_phrases":434,"slug":437,"view_count":114,"doi":8,"paper":438,"created_at":445},4648,"[预印本]面向农业机器人在多变天气与地形下基于视觉-语言模型的上下文自适应农药喷洒(Context-Aware Adaptive Pesticide Spraying for Agricultural Robots under Changing Weather and Terrain Using Vision-Language Models)","https:\u002F\u002Farxiv.org\u002Fabs\u002F2610.08807","arXiv论文(2610.08807,2026年10月6日提交)提出基于视觉-语言模型(VLM)的上下文自适应喷洒框架,通过空间推理整合作物、农药、气象数据驱动喷洒决策,并结合MPPI轨迹跟踪控制。作物行检测精度至少提升30%,机器人可在两种环境中灵活调节喷洒量与行驶速度并减少农药漂移。[预印本未经同行评议,尚未实地部署验证]。","arXiv 2026-10-06 [预印本]","2026-10-06T00:00:00Z",{"impact":16,"substance":270,"depth":16,"authority":12,"freshness":19,"relevant":20,"comment":400},"预印本提出VLM驱动的自适应喷洒框架，方法新颖且减药减排指向明确，但未经同行评议与实地验证，宜作前沿动态收录而非重点精选。",[402],{"name":397,"url":395},[25,404,405,406,27],"农业机器人","精准施药","视觉语言模型",{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},[409],{"code":410,"slug":411,"name":412,"path":413,"parent_code":35},"F6","agricultural-robots","机器人与无人农场","\u002Ftopic\u002Finputs-equipment\u002Fagricultural-robots",{"status":38,"locked":13,"version":39,"method":40,"evidence":415},{"candidates":416,"agricultural_evidence":46},[417,422,426,430],{"code":31,"score":418,"supported":46,"title":419,"abstract":420,"tags":421},21,[54,162],[54],[27,405],{"code":410,"score":45,"supported":46,"title":423,"abstract":424,"tags":425},[404],[],[404],{"code":44,"score":20,"supported":13,"title":427,"abstract":428,"tags":429},[],[],[25],{"code":106,"score":20,"supported":13,"title":431,"abstract":432,"tags":433},[],[],[406],[435,436],"农业机器人 视觉语言模型 农药喷洒","MPPI 轨迹跟踪 作物行检测","农业机器人视觉语言模型农药喷洒-4648",{"doi":8,"openalex_id":8,"authors":439,"venue":8,"cited_by_count":117,"oa_url":8,"card":440,"direction":390,"ingested_from":124},[],{"tldr":441,"method":442,"finding":443,"direction":390,"opportunity":444},"提出基于视觉-语言模型的上下文自适应农药喷洒框架，结合MPPI控制实现精准喷洒。","视觉-语言模型空间推理，融合作物、农药与气象数据，MPPI轨迹跟踪控制。","作物行检测精度至少提升30%，可灵活调节喷洒量与速度并减少农药漂移。","预印本未实地验证，可探索真实多变天气地形下的VLM鲁棒性与多模态数据融合优化。","2026-10-11T00:09:47.810289Z",{"id":447,"title":448,"url":449,"summary":450,"summary_zh":8,"content":451,"source_name":452,"source_url":8,"published_at":453,"category":267,"cover_url":8,"hotness":454,"is_selected":13,"score":455,"score_detail":456,"sources":459,"tags":470,"primary_topic":474,"secondary_topics":475,"classification":476,"search_phrases":501,"slug":504,"view_count":20,"doi":8,"paper":8,"created_at":505},4255,"AI赋能农业如何走出建得起养不起怪圈","https:\u002F\u002Fwww.farmer.com.cn\u002F2026\u002F09\u002F30\u002F991030157.html","农民日报评论：我国农业科技进步贡献率超过64%、农业生产信息化率超过30%、30余万架植保无人机年作业面积突破4.6亿亩、116个国家智慧农业创新应用项目分品种落地、16个人工智能+行动典型场景。2026年智慧农业市场规模将突破1340亿元。AI农业存在高前期投入、长回报周期、强公共属性，建议健全多元主体参与机制，以财政撬动替代财政兜底。","一、健全多元主体参与机制，以“财政撬动”替代“财政兜底”，是引导社会资本参与涉农数智化建设的核心路径。由于涉农数智化建设具有多元受益属性，必须在强化政府引领作用的基础上构建“政府主导+社会协同”机制，通过投入资金多源化有效降低政府财政负担。一方面，激发内生动力，有效组织农业生产者仍是首要任务。组织化程度直接决定着涉农数智化建设成效——通过提升新型农业经营主体的协同能力，不仅能优化生产效率，更有助于搭建科学的利益分配与风险共担长效机制，从而充分激发农业生产实际出资主体对涉农数智化建设的长远规划意识与持续投资意愿，构建起稳定的建设主体架构。另一方面，要把着力点从“买设备”转向“买服务”。当前，“农业即服务”模式快速兴起，农户无需一次性投入巨资购置智能装备，而是通过按亩付费、以租代售、分时租赁获得植保飞防、变量施肥、智能巡检等服务。地方政府应顺势而为，把有限的补贴资金从“补建设”转向“补作业、补成效”，用作业量和服务农户数说话，让财政资金四两拨千斤。与此同时，要用好信贷、担保、保险等金融工具，并抓住公共数据资源开发利用的机遇，探索涉农数据确权、估值与质押融资，把田间数据从“沉睡资源”转化为可变现资产，为轻资产的涉农AI服务商打开融资通道。在试点选择上，应优先在农业基础好、市场区位优的县市先行先试，重点在智能农机协作平台、农业低空经济、AI智能体托管种植、智慧农（牧、渔）场等市场化程度高的项目上，探索创新收益分配与风险分担模式，切实增强运营商、互联网企业及金融机构等社会资本的投资意愿。\n\n二、推广标准化生产是AI赋能农业的基础，更是降低财政投入强度的“省钱之道”。各级政府若期望AI赋能农业经济发展，必须提前在辖区内开展农业标准化体系建设。首先，只有标准化才能为涉农AI模型训练提供高质量数据。大模型竞争归根结底是数据竞争，国务院《加快农业农村现代化“十五五”规划》明确要求“建设大规模、多模态、高质量数据集，完善数据标准和规范”。通过政策引导使农业生产各环节执行统一操作规范，才能系统性生成结构化、可机读的数据；否则，分散经营造成的数据碎片化会成倍推高模型训练成本，财政投入也将事倍功半。其次，标准化可有效降低智能终端设备的落地门槛。统一技术接口与应用场景，才能让无人机、机器人、传感器、大模型真正“即插即用”，避免各搞一套“土标准”带来的重复建设和适配成本。2026年6月，农业农村部归口管理的8项农业人工智能行业标准获立项，覆盖智能装备、作物智能监测、农业农村大模型等领域，地方应主动对标国家标准、行业标准，让一次投入、多方复用成为现实。最后，标准化是分级奖补的依据。《数字乡村高质量发展行动计划（2026—2030年）》首次提出建立智慧农（牧、渔）场数字化场景认证体系，地方可据此把“感知—决策—执行—数据闭环”的能力分级量化，按级奖补、精准滴灌，推动农业生产模式从“个体经验”向“数据驱动”转型，以边际成本递减效应加速农业现代化进程。\n\n三、打造差异化品牌是利用智能营销体系实现农产品溢价的前提。良好品牌能为智能营销体系提供信任背书与内容抓手，同时为AI驱动的各类新业态提供坚实的价值支撑。例如，高市场认可度的农副产品在利用AI进行精准推送或开展虚拟主播营销时，更易获得消费者信任与青睐，从而显著提升营销转化效率。需要看到的是，品牌建设已不再是“吆喝”层面的事。农业农村部印发的《全国农产品产地市场体系发展“十五五”规划》明确提出“推进‘人工智能+’农产品流通发展”，加强农产品消费大数据分析与生产端反馈应用，打造面向市场、数据驱动、高效协同的智能供应链。这意味着，AI可以把消费端的偏好实时反馈给生产端，实现“以销定产”，既减少滞销带来的资源浪费和财政兜底压力，又让好产品卖出好价钱。2025年全国农村网络零售额已突破3万亿元，较“十三五”末增长67.6%，线上渠道为品牌溢价提供了广阔舞台。因此，尚有余力的地方政府应前瞻性布局，积极引领农企、合作社等经营主体，将农副产品品牌建设与AI技术深度融合，探索“AI+品牌溯源”“AI+内容生成”等应用，并积极参与区块链溯源认证和智慧农（牧、渔）场场景认证，用可验证的数据为品牌背书。上述举措不仅能实现本地优质农副产品的“跨区量价齐升”，更能系统性培育出具有市场号召力的农业品牌，并最终凭借品牌价值与流通效率的双重提升，加速实现农产品溢价。\n\n需要指出的是，破解财政瓶颈，归根结底要处理好“政府有为”与“市场有效”的关系。政府把钱花在标准、数据集、基础设施和联农带农机制上，把经营性环节交给市场，把运营成本摊薄到服务之中，才能真正走出“财政背包袱、设备睡大觉”的怪圈。同时也要守住一条底线：在引导社会资本和数据要素下乡的过程中，应通过明晰的数据权属和利益联结机制，确保农民不仅是数据的提供者，更是增值收益的分享者，防止“算法”成为新的中间商。唯其如此，智能化发展红利才能更多更公平惠及广大农民群众，为农业强国建设和中国式现代化提供坚实支撑。","中国农网 农民日报 2026-09-30","2026-09-30T00:00:00Z",55,82,{"impact":457,"substance":17,"depth":16,"authority":326,"freshness":51,"relevant":20,"comment":458},24,"央媒深度分析AI赋能农业的财政可持续路径，提出财政撬动、标准化、品牌溢价三大抓手，政策与数据细节扎实，但发布已逾一周，时效性偏弱。",[460,461,464,467],{"name":452,"url":449},{"name":462,"url":463},"新疆维吾尔自治区农业农村厅 2026-10-12","https:\u002F\u002Fnynct.xinjiang.gov.cn\u002Fxjnynct\u002Fc113576\u002F202610\u002F24505848b5c346999ef97ecec7734c21.shtml",{"name":465,"url":466},"农民日报电子版 2026 年 10 月 13 日","https:\u002F\u002Fszb.farmer.com.cn\u002Fnmrb\u002Fhtml\u002F2026\u002F20261013\u002F20261013_6\u002Fnmrb_20261013_13424_6_2109757807733608534.html",{"name":468,"url":469},"农民日报 转载定西市畜牧兽医局 2026 年 10 月 13 日","http:\u002F\u002Fxmj.dingxi.gov.cn\u002Fart\u002F2026\u002F10\u002F13\u002Fart_8322_1916899.html",[277,25,26,471,472,473],"农产品品牌","财政撬动","农业标准化",{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},[],{"status":38,"locked":13,"version":39,"method":40,"evidence":477},{"candidates":478,"agricultural_evidence":46},[479,483,488,493,497],{"code":44,"score":51,"supported":46,"title":480,"abstract":481,"tags":482},[],[25],[25],{"code":31,"score":58,"supported":46,"title":484,"abstract":485,"tags":487},[],[486],"植保",[],{"code":489,"score":20,"supported":13,"title":490,"abstract":491,"tags":492},"E5",[],[],[471],{"code":106,"score":20,"supported":13,"title":494,"abstract":495,"tags":496},[],[],[26],{"code":304,"score":20,"supported":13,"title":498,"abstract":499,"tags":500},[],[],[277],[502,503],"农业人工智能 行业标准 立项","智慧农场 数字化场景认证","农业人工智能行业标准立项-4255","2026-10-06T00:04:59.914874Z",{"id":507,"title":508,"url":509,"summary":510,"summary_zh":511,"content":8,"source_name":319,"source_url":509,"published_at":512,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":513,"score_detail":514,"sources":516,"tags":518,"primary_topic":523,"secondary_topics":524,"classification":525,"search_phrases":546,"slug":549,"view_count":58,"doi":550,"paper":551,"created_at":572},3460,"Knowledge graph-based expert system for tea pesticide residue compliance verification and detection method selection optimization","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1865601","Introduction Strict Maximum Residue Limits (MRLs) and complex residue definitions in pesticide standards (e.g., GB 2763) pose significant challenges for compliance verification and detection method selection in tea safety management. Manual inspection is prone to systematic errors, particularly false negatives caused by neglecting metabolites or isomers. Methods This study proposes a Knowledge Graph-based Expert System to address these issues. We constructed a domain-specific knowledge graph integrating 110 tea-registered pesticide active substances (comprising 847 entities and 2,156 relationships) and 37 detection standards using a human-in-the-loop verification process. A semantic classification model categorizing residue definitions into six patterns (Type A–F) was developed to enable automated, logic-driven compliance verification. A weighted set-cover algorithm was implemented to optimize the selection of detection methods among existing standardized methods. Validation included a small exploratory pilot user study (n = 5) and a retrospective analysis of 500 historical laboratory samples. Results In the retrospective analysis, the system’s automated verdicts agreed with the laboratory’s human Final Verdict in all 500 cases (95% CI: 99.3%–100.0%), demonstrating faithful reproduction of institutional interpretation of GB 2763. Notably, the system independently flagged three metabolite-summation (Type B) cases that first-level manual review had passed, illustrating its value as a redundant safeguard for multi-component residue definitions. The pilot user study illustrated qualitative trends consistent with cognitive load theory, whereas the system produced deterministic verdicts at a mean of 0.63 s per sample. Discussion This system provides an effective decision-support tool for laboratory quality control and regulatory compliance.","引言 农药标准（如GB 2763）中严格的最高残留限量（MRLs）和复杂的残留物定义，给茶叶安全管理中的合规性验证和检测方法选择带来了重大挑战。人工审查容易产生系统性错误，尤其是因忽视代谢物或异构体而导致的假阴性。方法 本研究提出了一种基于知识图谱的专家系统来解决这些问题。我们采用人在回路验证流程，构建了整合110种茶叶登记农药活性物质（包含847个实体和2，156个关系）及37项检测标准的领域专用知识图谱。开发了将残留物定义归类为六种模式（A型–F型）的语义分类模型，以实现自动化、逻辑驱动的合规性验证。实现了加权集合覆盖算法，以在现有标准化方法中优化检测方法的选择。验证包括一项小型探索性试点用户研究（n = 5）和对500份历史实验室样本的回顾性分析。结果 在回顾性分析中，系统的自动判定在所有500个案例中均与实验室人工最终判定一致（95% CI：99.3%–100.0%），表明系统忠实再现了GB 2763的机构解释。值得注意的是，系统独立标记出3例一级人工审查已通过的代谢物加和（B型）案例，说明其作为多组分残留物定义冗余保障的价值。试点用户研究显示了与认知负荷理论一致的定性趋势，而系统以平均每样本0.63秒的速度产生确定性判定。讨论 该系统为实验室质量控制和法规合规提供了有效的决策支持工具。","2026-09-24T00:00:00Z",78,{"impact":271,"substance":17,"depth":16,"authority":272,"freshness":45,"relevant":20,"comment":515},"知识图谱专家系统用于茶叶农残合规判定与检测方法优选，500例回溯验证一致率100%，方法新颖、数据扎实，对农产品质量安全监管有实用价值。",[517],{"name":319,"url":509},[25,26,519,520,521,522],"知识图谱","农药残留","茶叶安全","检测标准",{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},[],{"status":38,"locked":13,"version":39,"method":40,"evidence":526},{"candidates":527,"agricultural_evidence":46},[528,532,538,542],{"code":31,"score":326,"supported":46,"title":529,"abstract":530,"tags":531},[162],[54,162],[],{"code":533,"score":58,"supported":46,"title":534,"abstract":535,"tags":537},"B3",[],[536],"茶叶",[],{"code":106,"score":114,"supported":13,"title":539,"abstract":540,"tags":541},[],[],[26,519],{"code":44,"score":20,"supported":13,"title":543,"abstract":544,"tags":545},[],[],[25],[547,548],"农药残留 知识图谱","GB 2763 茶叶 检测方法","农药残留知识图谱-3460","10.3389\u002Ffsufs.2026.1865601",{"doi":550,"openalex_id":552,"authors":553,"venue":319,"cited_by_count":117,"oa_url":509,"card":567,"direction":256,"ingested_from":257},"W7214240413",[554,556,558,560,562,564],{"name":555,"orcid":8},"Yanyan Zhang",{"name":557,"orcid":8},"Jianrong Wen",{"name":559,"orcid":8},"Xuexiang Su",{"name":561,"orcid":8},"Tingxin Chen",{"name":563,"orcid":8},"Min Xie",{"name":565,"orcid":566},"Jindong Chen","https:\u002F\u002Forcid.org\u002F0000-0002-5560-1431",{"tldr":568,"method":569,"finding":570,"direction":256,"opportunity":571},"构建知识图谱专家系统，自动核验茶叶农药残留合规并优化检测方法选择。","整合110种农药与37项标准构建知识图谱，用语义分类和加权集合覆盖算法。","500例回溯判定与人工一致，并额外发现3例被人工漏检的代谢物加和案例。","可扩展至其他作物与多残留定义，并探索知识图谱与实验室LIMS实时联动。","2026-09-25T23:30:06.985753Z"]