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十五五规划","人工智能+农业十五五规划新质生产力智慧农业-430","2026-08-12T23:57:20.478979Z",{"id":191,"title":192,"url":193,"summary":194,"summary_zh":8,"content":195,"source_name":196,"source_url":8,"published_at":197,"category":75,"cover_url":8,"hotness":12,"is_selected":13,"score":198,"score_detail":199,"sources":204,"tags":206,"primary_topic":210,"secondary_topics":214,"classification":225,"search_phrases":275,"slug":278,"view_count":279,"doi":8,"paper":8,"created_at":280},276,"湖北省人民政府办公厅印发《加快农业科技创新专项行动工作方案(2026—2030年)》——明确种业振兴、生物制造、智能农机、智慧农业、绿色低碳、农产品加工六大攻关方向","https:\u002F\u002Fwww.hubei.gov.cn\u002Fzfwj\u002Fezbf\u002F202607\u002Ft20260731_5987083.shtml","湖北省人民政府办公厅7月31日印发《湖北省加快农业科技创新专项行动工作方案(2026—2030年)》,为湖北加快发展农业新质生产力、培育壮大农业领域新兴产业绘制系统性战略地图。湖北是农业大省、科教大省,农业科技进步贡献率超过68%,位居中部第一。《方案》围绕「创新什么」「谁来创新」「如何保障创新」三方向给出明确指引:重点部署种业振兴、生物制造、智能农机、智慧农业、绿色低碳、农产品加工六大领域攻关任务,提出加快选育高产多抗优质新品种,开发替代蛋白、生物农兽药、生物肥料等标志性产品,创制农业机器人、低空无人机等智能装备,打造一批智慧农场;实施农业科技企业培育工程,力争新培育5家龙头型、50家高速成长型、500家潜力型科技企业;建设10个中试验证平台和30个中试熟化基地,布局一批农业科技大市场和企业孵化器;深入实施院士专家科技服务「515」行动,组建「揭榜挂帅」团队开展人才组团式科技服务。深入实施「人工智能+农业」工程,突破农业专用芯片、智能传感器、空天地跨尺度监测、多模态数据融合及算法、动植物生长与产量预测模型、智能决策调控等关键技术,构建种质资源、耕地、气候、多组学等核心数据库,研发农业大模型与专用智能体。","各市、州、县人民政府，省政府各部门：\n\n《湖北省加快农业科技创新专项行动工作方案（2026—2030年）》已经省政府同意，现印发给你们，请认真贯彻落实。\n\n2026年7月24日\n\n（此件公开发布）\n\n**湖北省加快农业科技创新**\n\n**专项行动工作方案（2026—2030年）**\n\n为深入贯彻习近平总书记关于科技创新的重要论述和考察湖北重要讲话精神，落实国家农业科技创新“十五五”规划要求，主动顺应现代农业发展趋势，坚持需求牵引和供给导向，大力推动科技创新与产业创新深度融合，为全省现代农业发展提供关键支撑，制定本工作方案。到2030年，全省农业科技进步贡献率突破72%、农作物耕种收综合机械化率达到84%、主要农作物良种覆盖率稳定在98%以上，农业领域新兴产业综合产值突破6000亿元。\n\n**一、实施有组织的协同攻关**\n\n**1.加强农业重大新品种培育。**统筹种质资源保护与创新利用，深入实施种业振兴工程和“尖刀工程”，加强农业生物杂种优势形成与固定机制、动物高效节粮减损机理等基础研究，集成应用基因编辑、干细胞育种、全基因组选择、智能设计育种等技术，高通量挖掘鉴定高产、优质、抗逆、抗病等重大基因，创制突破性新种质，推动育种技术体系向智能化、精准化升级。加快选育高产多抗优质粮油作物和经济作物新品种；挖掘特色畜禽资源，构建高效扩繁技术体系，选育高效节粮核心种源及优质高产抗逆新品种（配套系）；迭代无肌间刺鱼等种质创新技术，培育优质淡水水产新品种。\n\n**2.加大生物制造新产品创制。**统筹前沿技术攻关与产业化落地，深入实施合成生物重点研发和农业微生物产业发展重大专项，突破AI驱动的生物元件设计、特色底盘细胞构建、新型生物反应器创制、跨界生物合成、细胞功能编辑等关键技术，创制低成本微生物菌种生产装备。核心菌种自给率达到40%以上。开发未来功能食品、替代蛋白（肽）、动植物疫苗、生物农兽药、生物肥料、非粮生物基产品等标志性产品。\n\n**3.加快智能农机新装备研制。**统筹全程全面机械化与农机装备产业转型升级，深入实施装备制造业高质量发展专项、农机研发制造推广应用一体化项目，加强多场景人机协同智能操控原理研究，突破高精度卫星导航、新能源动力、精准变量作业等关键技术。研制智能播种、低损收获等大田农机和轻量化、小型丘陵山区适用农机，创制农业机器人、低空无人机、农产品产地高效保鲜干燥和精深加工智能装备等，构建涵盖粮油、果菜茶、畜禽水产等领域全程智能化装备技术体系。\n\n**4.加速智慧农业新技术开发。**统筹数字赋能与业态升级，深入实施“人工智能+农业”工程，以人工智能引领农业科研范式变革。突破农业专用芯片与智能传感器、空天地跨尺度监测、多模态数据融合及算法、动植物生长与产量预测模型、智能决策调控等关键技术，构建种质资源、耕地、气候、多组学等核心数据库。研发农情采集、大数据处理、动植物生长（产）智能诊断调控、畜禽健康与兽药智能应用等系统，开发农业大模型与专用智能体。推进农田水利智慧化升级，加快建成适宜耕作、旱涝保收、高产稳产的现代化良田。加快产地仓、烘干、冷链等设施数字化改造，支持企业建设数字工厂和数智生产线，打造一批智慧农场。\n\n**5.加力绿色低碳新模式集成。**统筹高水平保护和高质量发展，突破绿色防控、土壤改良、种养循环、资源综合利用等关键技术，研发绿色农药、生物有机肥、生物基可降解材料等绿色投入品，创制治理农田抗生素、微塑料、重金属等污染物的技术产品，集成推广“黑水虻+微生物”转化有机废弃物等先进技术，构建绿色低碳生产体系。开展碳汇监测、碳足迹核算与碳交易研究，探索生态产品价值实现路径。加强农产品质量安全检测技术研发，围绕农产品农兽药残留、生物毒素污染、新污染物等，攻克风险隐患快速识别与源头阻控关键技术，完善新型农食产品安全性评估技术体系，研发智能快速检测技术装备，支撑农产品质量安全监测合格率稳定在98%以上。\n\n**6.助力农产品加工提质增效。**统筹初加工、精深加工与副产物综合利用，开发营养健康的休闲食品、食药同源的保健食品、风味独特的调味品和定制化的预制食品。围绕粮油、果蔬、畜禽、水产、乳制品等，研发产后品质保持与贮运保鲜技术，开发智能分级、绿色加工与营养强化技术，创制高品质食材、高端食品基料与特需功能食品。推进加工副产物高值利用，开发功能脂质、蛋白（肽）、多糖等产品，加快构建覆盖产前、产中、产后的现代农业产业技术体系，引领产业升级。\n\n**二、推动科技成果高效转化**\n\n**7.畅通科技成果转化渠道。**支持建设一批概念验证中心，推进科技成果中试熟化、产业适配性与市场转化潜力验证。聚焦生物制造、智能农机、智慧农业等方向，建设10个中试验证平台和30个中试熟化基地。发挥国家技术转移中部中心引领作用，强化农业技术经理人队伍建设，布局建设一批农业科技型企业孵化器、农业科技成果转移服务中心、农业科技大市场，建设一批以企业为主体的产学研协同创新平台，促进成果、需求、资本精准对接。\n\n**8.推动重大成果落地应用。**深入实施院士专家科技服务农业产业链“515”行动、农业科技服务支点建设“五大提质行动”“乡村振兴荆楚行”和实用技术大赛等活动，遴选发布一批主推技术、主导品种、先进实用技术，组建一批“揭榜挂帅”团队，开展人才组团式科技服务。积极参与国家标准制定，加快推进转基因、基因编辑、合成生物学、微生物组学等领域科研成果产业化进程。布局建设一批乡村振兴科技创新基地、现代农业科技试验示范基地，集成推广“良田、良种、良机、良法”配套技术模式，推动更多科技成果转化为现实生产力。\n\n**9.提升农技推广服务效能。**积极培育农技社会化服务组织，引导种业、农资等企业和各类农机作业服务主体，通过技术托管、利润分成等方式，与农户结成利益共同体，将技术推广深度嵌入产业链，形成收益共享、持续服务的良性循环。推动供需精准对接和按效付费，探索市场化农技服务新模式。深化基层农技推广体系改革，健全以岗位绩效为核心的薪酬分配制度。支持院地、校地共建科技小院、专家大院等，引导科研院所深入一线开展农技推广。\n\n**三、大力培育农业新质生产力**\n\n**10.建强科技创新平台。**加快建设国家作物表型组学、农业微生物重大设施，推动洪山实验室、武汉国家现代农业产业科技创新中心联动发展，加强与全国重点实验室合作。支持高校、科研院所与企业共建技术创新中心、产业研究院和新型研发机构，推动产学研用协同创新。高标准建设“一带一路”联合实验室，推动区域合作与跨国协同等开放创新。支持襄阳创建国家农业高新技术产业示范区、宜昌建设农业微生物实验室、荆州打造洪湖水生态（水产品）实验室，加快构建以武汉为中心，以襄阳、宜昌、荆州为骨干，全域协同联动的“一芯三核多点支撑”农业科技创新格局。\n\n**11.培育壮大农业科技领军企业。**实施农业科技企业培育工程，力争新培育5家龙头型、50家高速成长型、500家潜力型科技企业。聚焦十大重点农业产业链，招引一批涉农世界500强和中国100强企业，推动在鄂建立区域总部、研发中心和高端生产制造基地。支持企业推进产品技术创新，将企业关键技术需求列为攻关重点。鼓励企业建立研发准备金制度，牵头组建创新联合体和新型研发机构，深度参与创新全过程。支持企业开展商业模式创新，通过并购重组、参股控股、改制上市等方式壮大实力，面向全国、全球重构供应链。鼓励企业推进经营管理模式创新，建立现代企业制度，提升可持续发展能力。\n\n**12.培育优势特色产业集群。**立足各地资源禀赋优化农业布局，支持将武汉都市圈建设成国家生物育种产业创新高地；支持武汉、宜昌、十堰等地打造国内领先的合成生物产业园；依托“汉孝随襄十”汽车走廊，加快建设智能农机装备产业园，形成农机装备产业带；支持江汉平原创建百万亩智慧农（牧、渔）场、鄂西山区及大别山区打造十万亩数字果（菜、茶）园。\n\n**四、持续优化农业科技创新生态**\n\n**13.加强政策服务供给。**健全面向产业征集需求的任务来源机制，完善“揭榜挂帅”“赛马”“定向委托”等项目组织实施机制。开展职务科技成果赋权改革试点，赋予研发人员所有权或10年以上长期使用权。鼓励以技术入股、分红等形式参与成果转化，转让净收入或股权按比例分配给科研团队。推行以创新能力、实效、贡献为导向的人才评价改革，实行高层次人才引进推荐认定制，支持符合条件的企业自主开展职称评审，在科技创新一线发现和培养农业战略科学家。探索“双重聘用、岗位特聘、双向兼职”用人机制，鼓励高校、科研院所选派人员依规兼任“科技副总”。提高企业人才参评“楚天英才计划”的比例，每年培训100名农业科技领军人才。\n\n**14.强化要素资源保障。**统筹财政支农资金和科技创新专项，加大对农业科技创新的支持力度。用好“投、补、贷、保”政策工具，发挥省农业产业发展母基金和农业创投基金作用，构建“创投+产投”基金体系。引导金融机构推出农业科技信贷产品，用好科技型中小微企业知识价值和民营中小企业商业价值信用贷款政策。举办农业科技金融对接活动和创新创业大赛，对关键核心技术领域的科技型企业，加强上市培育和融资服务。探索“先租后让、租让结合、弹性年期出让”等灵活土地供应方式，依法保障重点项目用地需求。注重发挥农村综合改革牵引作用，稳妥推进农村要素资源市场化配置、土地适度规模经营等重点领域改革。\n\n**15.营造良好创新氛围。**制定科技创新容错清单，探索“沙盒监管”方式，加强知识产权保护和科技伦理、科研诚信建设，维护各类创新主体公平竞争环境。加快生物育种、生物制造、人工智能等领域科研成果登记、审定、评价，提升准入审批效率。深化农业科技管理体制机制改革，明晰涉农高校、科研院所功能定位，支持各类创新主体紧密协作、联动发展。弘扬新时代科学家精神，加大科普宣传力度，营造敢为人先、勇于创新的良好生态。\n\n健全完善工作机制，省农业农村厅、省科技厅加强统筹协调，省直相关部门按照工作职责协同推进；相关涉农高校、科研院所和领军企业，聚合资源深度参与；各市县结合实际，同步推进落实。加强跟踪监测、总结分析，激发各地开展农业科技创新的主动性与积极性。\n\n附件：重点任务清单\n\n![Image 1: 1.png](https:\u002F\u002Fwww.hubei.gov.cn\u002Fzfwj\u002Fezbf\u002F202607\u002FW020260731583511140852.png)\n\n![Image 2: 2.png](https:\u002F\u002Fwww.hubei.gov.cn\u002Fzfwj\u002Fezbf\u002F202607\u002FW020260731583512765245.png)\n\n![Image 3: 3.png](https:\u002F\u002Fwww.hubei.gov.cn\u002Fzfwj\u002Fezbf\u002F202607\u002FW020260731583514427701.png)\n\n![Image 4: 4.png](https:\u002F\u002Fwww.hubei.gov.cn\u002Fzfwj\u002Fezbf\u002F202607\u002FW020260731583515956206.png)\n\n![Image 5: 5.png](https:\u002F\u002Fwww.hubei.gov.cn\u002Fzfwj\u002Fezbf\u002F202607\u002FW020260731583517619020.png)\n\n![Image 6: 6.png](https:\u002F\u002Fwww.hubei.gov.cn\u002Fzfwj\u002Fezbf\u002F202607\u002FW020260731583519546555.png)\n\n![Image 7: 7.png](https:\u002F\u002Fwww.hubei.gov.cn\u002Fzfwj\u002Fezbf\u002F202607\u002FW020260731583521119684.png)\n\n编辑：汪 丽\n\n责编：梁唯雅\n\n审核：涂亚卓\n\n姚 盼","湖北省人民政府网 2026-07-31","2026-07-31T00:00:00Z",83,{"impact":200,"substance":200,"depth":201,"authority":18,"freshness":202,"relevant":20,"comment":203},24,18,5,"省级农业科技创新五年规划，六大攻关方向明确，条款与数据详实，对区域农业信息化与智慧农业有指导意义。",[205],{"name":196,"url":193},[25,145,207,208,26,209],"种业振兴","农业科技创新","湖北省",{"code":167,"slug":211,"name":212,"path":213,"parent_code":147},"seed-industry","种业与品种管理","\u002Ftopic\u002Finputs-equipment\u002Fseed-industry",[215,221],{"code":216,"slug":217,"name":218,"path":219,"parent_code":220},"E1","food-processing","加工与食品制造","\u002Ftopic\u002Ffood-supply\u002Ffood-processing","E",{"code":115,"slug":222,"name":223,"path":224,"parent_code":147},"machinery","农机装备与机械化","\u002Ftopic\u002Finputs-equipment\u002Fmachinery",{"status":95,"locked":13,"version":31,"method":32,"evidence":226},{"candidates":227,"agricultural_evidence":37},[228,233,237,242,246,250,256,261,267,271],{"code":167,"score":17,"supported":37,"title":229,"abstract":230,"tags":232},[170],[170,231],"种质资源",[207],{"code":36,"score":18,"supported":37,"title":234,"abstract":235,"tags":236},[25],[25],[25],{"code":216,"score":64,"supported":37,"title":238,"abstract":240,"tags":241},[239],"农产品加工",[239],[],{"code":115,"score":64,"supported":37,"title":243,"abstract":244,"tags":245},[118],[118],[],{"code":55,"score":99,"supported":37,"title":247,"abstract":248,"tags":249},[],[106],[26],{"code":251,"score":43,"supported":37,"title":252,"abstract":253,"tags":255},"C5",[],[254],"兽药",[],{"code":49,"score":43,"supported":37,"title":257,"abstract":258,"tags":260},[],[259],"肥料",[],{"code":262,"score":43,"supported":37,"title":263,"abstract":264,"tags":266},"F6",[],[265],"农业机器人",[],{"code":121,"score":20,"supported":13,"title":268,"abstract":269,"tags":270},[],[],[145],{"code":161,"score":20,"supported":13,"title":272,"abstract":273,"tags":274},[],[],[208],[276,277],"人工智能+农业 农业科技创新 十五五规划 智慧农业","人工智能+农业 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2026-08-02","2026-08-02T00:00:00Z",64,{"impact":16,"substance":17,"depth":291,"authority":12,"freshness":202,"relevant":20,"comment":292},14,"报道山东农业遥感大模型发布，结合水肥一体化与智能育种案例，省级产业进展，信息较充实，但时效稍旧。",[294],{"name":287,"url":284},[25,296,26,297,298],"山东省农科院","舜耕粮安","农业遥感大模型",{"code":300,"slug":301,"name":302,"path":303,"parent_code":92},"I3","remote-sensing","遥感与农情监测","\u002Ftopic\u002Fdigital-agriculture\u002Fremote-sensing",[305],{"code":55,"slug":89,"name":90,"path":91,"parent_code":92},{"status":95,"locked":13,"version":31,"method":32,"evidence":307},{"candidates":308,"agricultural_evidence":37},[309,315,319,325,331],{"code":300,"score":291,"supported":37,"title":310,"abstract":312,"tags":314},[311],"遥感",[311,313],"估产",[],{"code":55,"score":18,"supported":37,"title":316,"abstract":317,"tags":318},[106],[106],[26],{"code":320,"score":43,"supported":37,"title":321,"abstract":322,"tags":324},"B2",[],[323],"葡萄",[],{"code":326,"score":43,"supported":37,"title":327,"abstract":328,"tags":330},"I5",[],[329],"物联网",[],{"code":36,"score":20,"supported":13,"title":332,"abstract":333,"tags":334},[],[],[25],[336,337],"农业遥感大模型 人工智能+农业 山东省农科院 智慧农业","农业遥感大模型 人工智能+农业","农业遥感大模型人工智能+农业山东省农科院智慧农业-234","2026-08-05T23:53:01.179071Z",{"id":341,"title":342,"url":343,"summary":344,"summary_zh":8,"content":286,"source_name":345,"source_url":8,"published_at":288,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":346,"score_detail":347,"sources":352,"tags":354,"primary_topic":357,"secondary_topics":358,"classification":359,"search_phrases":392,"slug":395,"view_count":99,"doi":8,"paper":8,"created_at":396},156,"山东实施'人工智能+农业'行动：数据'种'进泥土，云端守护丰收","https:\u002F\u002Fnew.qq.com\u002Frain\u002Fa\u002F20260802A03UUS00","山东出台实施'人工智能+农业'行动方案。在寿光，新增大棚已迭代升级至第七代智能物联网'云棚'，物联网应用率超过85%，劳动生产效率较以往翻倍；省农科院发布'舜耕·粮安'农业遥感大模型；由中国农业科学院与山东极智生物联合研发的iWheat小麦智能设计育种平台整合3万余份小麦种质资源，结合快速繁育体系能将传统8年育种周期压缩2至3年。2025年全省应用水肥一体化技术的粮油作物面积达到630万亩。","新华社 2026-08-02 \u002F 腾讯网转载",85,{"impact":200,"substance":348,"depth":201,"authority":349,"freshness":350,"relevant":20,"comment":351},22,13,8,"报道山东实施'人工智能+农业'行动，含具体案例与数据，省级政策影响，央媒权威，时效性稍差。",[353],{"name":345,"url":343},[25,355,26,356,297],"山东","寿光云棚",{"code":55,"slug":89,"name":90,"path":91,"parent_code":92},[],{"status":95,"locked":13,"version":31,"method":32,"evidence":360},{"candidates":361,"agricultural_evidence":37},[362,366,372,376,380,384,388],{"code":55,"score":99,"supported":37,"title":363,"abstract":364,"tags":365},[],[106],[26],{"code":367,"score":43,"supported":37,"title":368,"abstract":369,"tags":371},"A2",[],[370],"小麦",[],{"code":167,"score":43,"supported":37,"title":373,"abstract":374,"tags":375},[],[231],[],{"code":49,"score":43,"supported":37,"title":377,"abstract":378,"tags":379},[],[52],[],{"code":300,"score":43,"supported":37,"title":381,"abstract":382,"tags":383},[],[311],[],{"code":326,"score":43,"supported":37,"title":385,"abstract":386,"tags":387},[],[329],[],{"code":36,"score":20,"supported":13,"title":389,"abstract":390,"tags":391},[],[],[25],[393,394],"人工智能+农业 寿光云棚 智慧农业 舜耕粮安","人工智能+农业 寿光云棚","人工智能+农业寿光云棚智慧农业舜耕粮安-156","2026-08-01T23:53:42.061928Z",{"id":398,"title":399,"url":400,"summary":401,"summary_zh":402,"content":8,"source_name":403,"source_url":400,"published_at":404,"category":405,"cover_url":8,"hotness":12,"is_selected":13,"score":406,"score_detail":407,"sources":410,"tags":412,"primary_topic":417,"secondary_topics":423,"classification":425,"search_phrases":442,"slug":445,"view_count":446,"doi":447,"paper":448,"created_at":464},5592,"Evaluation of Concept-Rank Collapse Audits for Computer Vision Agriculture Disease Classifiers Under Low-Label Regimes: An Interpretability Capacity Bound for Smallholder Fungicide Selectivity","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.23545193","Concept-based interpretability methods for plant-disease classifiers are typically evaluated by whether their concept activations correlate with human-annotated labels, but this criterion is silent on a prior question: whether the classifier's internal representation retains enough concept-rank structure for any audit to be informative. the present analysis formalises that prior question as an interpretability capacity bound. A classifier is modelled as a concept-rank operator whose singular values govern how much concept-level signal survives the projection from pixel space to class logits, and a collapse audit is defined as the ratio of retained concept-rank energy to total concept energy. Under a low-label regime, where concept annotations are scarce and the audit must be estimated from few labelled examples, the bound predicts that audit reliability degrades as a function of the concept-rank spectrum and the label budget. The analysis is a theoretical and methodological contribution: it derives the bound, states the conditions under which a collapse audit is identifiable, and characterises the operating characteristics of the audit as a decision procedure under a declared variance structure (between-cluster SD = 6.0, residual SD = 4.5, intraclass correlation = 0.64). Power was estimated across 2000 design cells for cluster counts of 8, 16, 24 and 32 and effect sizes of 3, 5 and 8 percentage points; 52 clusters were required for 5 percentage points at 80% power. The bound reframes concept audits as capacity tests rather than fidelity tests, with consequences for how smallholder fungicide-selectivity decisions should be supported by interpretable disease classifiers.","面向植物病害分类器的基于概念的可解释性方法，通常以其概念激活是否与人工标注标签相关作为评价标准，但该标准对一个更先前的问题保持沉默：分类器的内部表征是否保留了足够的概念秩结构，从而使任何审计具有信息量。本分析将该先前问题形式化为一个可解释性容量上界。分类器被建模为概念秩算子，其奇异值支配着从像素空间到类别logits的投影中概念级信号得以保留的程度，并将坍缩审计定义为保留的概念秩能量与总概念能量之比。在低标签情形下，概念标注稀缺且审计必须由少量标注样本估计，该上界预测审计可靠性会随概念秩谱和标签预算的函数而退化。本分析是一项理论和方法论贡献：推导出该上界，陈述坍缩审计可识别的条件，并在声明的方差结构（簇间SD = 6.0，残差SD = 4.5，组内相关系数 = 0.64）下刻画审计作为决策程序的操作特征。在2000个设计单元中，针对簇数为8、16、24和32以及效应量为3、5和8个百分点的情形估计了功效；在80%功效下达到5个百分点需要52个簇。该上界将概念审计重新框定为容量检验而非保真度检验，并对可解释病害分类器应如何支持小农杀菌剂选择性决策具有启示意义。","Zenodo (CERN European Organization for Nuclear Research)","2026-10-21T00:00:00Z","论文",69,{"impact":350,"substance":408,"depth":201,"authority":18,"freshness":12,"relevant":20,"comment":409},21,"理论方法论文，提出可解释性容量上界并给出审计功效分析，对智慧农业病害识别可信度有参考价值，但属小众方法学研究、缺乏田间实证，暂不宜进入每日精选。",[411],{"name":403,"url":400},[25,413,414,415,416],"农业人工智能","小农户","植物病害识别","可解释性",{"code":418,"slug":419,"name":420,"path":421,"parent_code":422},"G2","farm-services","社会化服务与规模经营","\u002Ftopic\u002Frural-services\u002Ffarm-services","G",[424],{"code":55,"slug":89,"name":90,"path":91,"parent_code":92},{"status":95,"locked":13,"version":31,"method":32,"evidence":426},{"candidates":427,"agricultural_evidence":37},[428,433,438],{"code":418,"score":18,"supported":37,"title":429,"abstract":431,"tags":432},[430],"smallholder",[430],[414],{"code":55,"score":12,"supported":37,"title":434,"abstract":436,"tags":437},[435],"computer vision",[],[413,415],{"code":36,"score":20,"supported":13,"title":439,"abstract":440,"tags":441},[],[],[25],[443,444],"农业人工智能 植物病害识别 可解释性 智慧农业","农业人工智能 植物病害识别","农业人工智能植物病害识别可解释性智慧农业-5592",0,"10.5281\u002Fzenodo.23545193",{"doi":447,"openalex_id":449,"authors":450,"venue":403,"cited_by_count":446,"oa_url":400,"card":457,"direction":461,"ingested_from":463},"W7223137323",[451,453,455],{"name":452,"orcid":8},"Akshay Ramgoolam",{"name":454,"orcid":8},"Priya Bundhoo Appadoo",{"name":456,"orcid":8},"Jean-Noël LEspérance",{"tldr":458,"method":459,"finding":460,"direction":461,"opportunity":462},"提出可解释性容量上界，评估低标签下概念秩崩溃审计的可靠性。","将分类器建模为概念秩算子，推导容量上界并做2000格功效模拟。","审计可靠性随概念秩谱与标签预算下降；5个百分点效应需52个聚类达80%功效。","农业人工智能与决策模型","可将容量上界用于小农户杀菌剂选择性决策的可解释模型审计与标签预算设计。","openalex","2026-10-22T11:21:10.425290Z"]