[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-1968":3,"related-1968":83},{"id":4,"title":5,"url":6,"summary":7,"summary_zh":8,"content":9,"source_name":10,"source_url":6,"published_at":11,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":16,"sources":23,"tags":25,"primary_topic":9,"secondary_topics":30,"classification":31,"search_phrases":54,"slug":57,"view_count":20,"doi":58,"paper":59,"created_at":82},1968,"Respiratory-metabolism-guided multimodal PM-RVGNet for nondestructive single-seed vigor and germination consistency inference in Chinese cabbage","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.compag.2026.112401","Respiratory-metabolism-guided multimodal PM-RVGNet for nondestructive single-seed vigor and germination consistency inference in Chinese cabbage。Computers and Electronics in Agriculture","呼吸代谢引导的多模态PM-RVGNet用于大白菜种子活力与发芽一致性的无损单粒推断。《Computers and Electronics in Agriculture》",null,"Computers and Electronics in Agriculture","2026-09-08T00:00:00Z","论文",10,false,64,{"impact":17,"substance":18,"depth":18,"authority":19,"freshness":20,"relevant":21,"comment":22},12,18,14,2,1,"研究提出基于呼吸代谢的多模态深度学习模型，实现白菜种子活力无损检测，方法新颖，对种业智能化有参考价值。",[24],{"name":10,"url":6},[26,27,28,29],"智慧农业","农业人工智能","种业振兴","种子检测",[],{"status":32,"locked":14,"version":33,"method":34,"evidence":35},"unclassified","2026-10-22.2","rules",{"candidates":36,"agricultural_evidence":52,"reason":53},[37,42,47],{"code":38,"score":21,"supported":14,"title":39,"abstract":40,"tags":41},"F1",[],[],[28],{"code":43,"score":21,"supported":14,"title":44,"abstract":45,"tags":46},"I1",[],[],[26],{"code":48,"score":21,"supported":14,"title":49,"abstract":50,"tags":51},"I2",[],[],[27],true,"缺少足够的主题证据",[55,56],"农业人工智能 智慧农业 种业振兴 种子检测","农业人工智能 智慧农业","农业人工智能智慧农业种业振兴种子检测-1968","10.1016\u002Fj.compag.2026.112401",{"doi":58,"openalex_id":60,"authors":61,"venue":10,"cited_by_count":74,"oa_url":9,"card":75,"direction":79,"ingested_from":81},"W7211958749",[62,65,67,69,71],{"name":63,"orcid":64},"Tianyu Yang","https:\u002F\u002Forcid.org\u002F0000-0002-9674-5220",{"name":66,"orcid":9},"Bo Peng",{"name":68,"orcid":9},"Jun Zhang",{"name":70,"orcid":9},"Dongfang Zhang",{"name":72,"orcid":73},"Xiaofei Fan","https:\u002F\u002Forcid.org\u002F0009-0008-6329-9616",0,{"tldr":76,"method":77,"finding":78,"direction":79,"opportunity":80},"提出PM-RVGNet多模态网络，基于呼吸代谢指导，无损推断白菜种子活力与发芽一致性。","融合呼吸代谢与多模态成像数据，构建PM-RVGNet深度学习网络。","PM-RVGNet能有效无损预测单粒种子活力及发芽一致性。","农业人工智能与决策模型","可探索将呼吸代谢与其他生理指标结合，提升种子活力预测精度，并扩展至其他作物。","openalex","2026-09-09T23:30:01.572816Z",{"total":84,"page":21,"page_size":84,"items":85},6,[86,144,191,239,371,418],{"id":87,"title":88,"url":89,"summary":90,"summary_zh":9,"content":91,"source_name":92,"source_url":9,"published_at":93,"category":94,"cover_url":9,"hotness":13,"is_selected":14,"score":95,"score_detail":96,"sources":102,"tags":104,"primary_topic":107,"secondary_topics":113,"classification":114,"search_phrases":139,"slug":142,"view_count":74,"doi":9,"paper":9,"created_at":143},4950,"'袁稻思源'杂交水稻智能育种平台发布 业界首个智能育种平台落户湖南","https:\u002F\u002Fwww.toutiao.com\u002Farticle\u002F7696096616441774642\u002F","10月11日,'袁稻思源'杂交水稻智能育种平台发布会在岳麓山实验室举行,由中国科学院自动化研究所联合湖南省农业科学院、北京中科闻歌科技股份有限公司共同研发。平台集成'问答助手''育种资源库''知识图谱''文献库'四大功能模块,收纳35570个水稻品种、689项性状、28648条基因数据和624757篇中英文文献。中国科学院院士李家洋、钱前、谢道昕,中国工程院院士柏连阳等共同见证。","来源：环球网\n\n水稻育种专家过去最头疼的是什么？翻资料。查一个品种亲本、找一个性状基因，动辄耗费大量时间。近期，中科闻歌带着决策智能入场了。10月11日，由湖南省农科院、中科院自动化所与中科闻歌联合打造的“袁稻思源”杂交水稻智能育种平台正式发布，把海量育种数据和AI决策能力送进育种一线。\n\n![Image 1](https:\u002F\u002Fp3-sign.toutiaoimg.com\u002Ftos-cn-i-axegupay5k\u002F2397644cc26144379c7e432950a2deec~tplv-tt-origin-web:gif.jpeg?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1792627757&x-signature=o8pNXOWnEqlIl4mnK12LZ8rHkeA%3D)\n**水稻育种：一个“数据富矿”**\n\n杂交水稻育种是一个典型的“数据富矿、决策洼地”领域。全球积累了海量品种、性状、基因和文献数据，但长期分散、难以检索，育种更多依赖科研人员的经验与记忆。为破解这一难题，今年7月2日，中国科学院自动化研究所、北京中科闻歌科技股份有限公司与湖南省农业科学院正式签约，围绕“人工智能+农业科研”开展联合攻关。“袁稻思源”正是这一合作的阶段性成果，平台名称取自袁隆平杂交水稻创新团队，寓意“饮水思源”，感怀袁隆平院士对中国水稻杂交育种作出的突出贡献。\n\n湖南省农科院院长余应弘介绍，“袁稻思源”是湖南落实国家种业振兴行动、推进育种数字化智能化转型的关键举措，旨在传承袁隆平院士科学精神，把数据资源和智能技术转化为育种创新的现实生产力。在中科闻歌的战略版图里，这次入局农业科研，是其“决策大模型”“AI国家队”能力向产业纵深的又一次延伸。\n\n![Image 2](https:\u002F\u002Fp3-sign.toutiaoimg.com\u002Ftos-cn-i-tjoges91tu\u002F328723c57ddce965a8efda71ad02f21a~tplv-tt-origin-web:gif.jpeg?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1792627757&x-signature=0csP6GpZya22ien7EebcU64%2FxRw%3D)\n**“袁稻思源”四大核心功能**\n\n“袁稻思源”平台构建四大核心功能模块，形成完整的智能育种知识和能力。\n\n数据资源库，将散落的育种数据统一“上牌”。目前平台收纳35570个水稻品种、689项性状、28648条基因数据和624757篇中英文文献。不育系按光敏、温敏、光温敏等维度精细分类，支持育种专种家像检索商品一样，快速定位目标种质。该数据资源库是“袁稻思源”平台的核心底座。\n\n基于资源库建立图谱，让品种、基因、文献等彼此“建联”。品种图谱勾画出每个品种的选育谱系和材料关系，基因图谱把基因、性状、品种与文献证据编织成一张可推理的网络。例如输入Y58S，系统可直接呈现该品种的千粒重、抗病性及相关基因。\n\n智能问答“小稻”，作为育种专家的对话式检索入口。专业科研人员只需自然语言，也可向平台提出专业问题，系统从文献和真实数据中生成答案，每条结论都标明来源，不凭空编造。在发布会现场，专家提问“第三代杂交水稻产业化有哪些障碍”，“小稻”当即从监管、生物安全、成本、知识产权等维度给出专业分析，并提示品种审定前需补充哪些数据。\n\n最后一个能力模块是育种智能体。品种审定智能体可根据品种性状，帮助科研人员预判审定通过率，杂交配组智能体可基于基因型数据预测候选组合的表现。育种家从“翻资料猜结果”变成“让AI算概率”，大幅提升工作效率。\n\n湖南省农科院副院长李莉现场演示了平台在育种资源查询、品种系谱呈现、基因关联展示等方面的能力，一套组合下来，育种专家从“盲试”变成“有据可依”。目前，平台已在第三代杂交水稻育种中开展应用示范，取得良好成效。\n\n**专家视角：这场变革会改变什么**\n\n平台发布当天，中国工程院院士、湖南省农科院党委书记柏连阳直言，“拥抱人工智能，是今天科研人员的必答题”。平台目前虽为初级版本，但已迈出AI赋能杂交水稻育种关键而可喜的一步。\n\n中国科学院院士、崖州湾国家实验室主任李家洋的判断更为前瞻：当前全球种业竞争加剧，育种正从“经验驱动”转向“数据驱动、设计育种”，“谁率先突破智能育种，谁就赢得下一轮农业产业革命的主动”。李家洋建议，平台可强化智能决策、深化协同创新、坚持服务产业，最终建设成为面向全国乃至全球的水稻智能育种公共产品。\n\n据中科闻歌方面表示，“袁稻思源”是决策智能第一次系统嵌入国家粮食安全的核心环节。从金融到政务，再到农业科研，AI行业正在把“数据决策”能力，嵌入更多关乎国计民生的领域。对育种行业而言，当AI助力科研人员更快、更准地“排雷”和“选路”，中国水稻育种的效率天花板或许才刚刚被打开。（心月）","环球网 今日头条 2026 年 10 月 13 日","2026-10-13T00:00:00Z","报道",88,{"impact":97,"substance":98,"depth":18,"authority":99,"freshness":100,"relevant":21,"comment":101},26,23,13,8,"业界首个杂交水稻智能育种平台落地湖南，数据规模与AI决策功能具体，属种业数字化标志性进展，值得入选每日精选。",[103],{"name":92,"url":89},[26,27,28,105,106],"智能育种","杂交水稻",{"code":108,"slug":109,"name":110,"path":111,"parent_code":112},"A1","rice","水稻","\u002Ftopic\u002Ffield-crops\u002Frice","A",[],{"status":115,"locked":14,"version":33,"method":34,"evidence":116},"classified",{"candidates":117,"agricultural_evidence":52},[118,122,126,131,135],{"code":108,"score":17,"supported":52,"title":119,"abstract":120,"tags":121},[110],[110],[106],{"code":38,"score":21,"supported":14,"title":123,"abstract":124,"tags":125},[],[],[28],{"code":127,"score":21,"supported":14,"title":128,"abstract":129,"tags":130},"F2",[],[],[105],{"code":43,"score":21,"supported":14,"title":132,"abstract":133,"tags":134},[],[],[26],{"code":48,"score":21,"supported":14,"title":136,"abstract":137,"tags":138},[],[],[27],[140,141],"袁稻思源 杂交水稻 智能育种平台","湖南省农科院 中科闻歌 智能育种","袁稻思源杂交水稻智能育种平台-4950","2026-10-15T00:06:02.857637Z",{"id":145,"title":146,"url":147,"summary":148,"summary_zh":9,"content":9,"source_name":149,"source_url":9,"published_at":93,"category":94,"cover_url":9,"hotness":13,"is_selected":14,"score":150,"score_detail":151,"sources":156,"tags":158,"primary_topic":161,"secondary_topics":166,"classification":167,"search_phrases":186,"slug":189,"view_count":74,"doi":9,"paper":9,"created_at":190},4859,"机器人变身小麦育种专家——山东农大小麦育种具身机器人原型机公开亮相","https:\u002F\u002Fnews.sciencenet.cn\u002Fsbhtmlnews\u002F2026\u002F10\u002F391582.shtm","近日在山东泰安举行的小麦智能育种研讨会上,小麦育种具身机器人原型机首次公开亮相。该机器人由山东农业大学教授王宏伟、张亮团队联合研发,采用实时动态差分定位与视觉融合导航技术,可在试验田小区间自主移动作业;搭载滑台高清相机,可对田间小麦进行连续影像采集,并利用视觉算法自动量化株高、穗部性状等表型参数。系统结合智能决策模型对田间单株进行高通量初筛,自主识别具有进一步考察价值的候选植株。研究团队与山东极智生物科技有限公司达成合作意向。","中国科学报 科学网 2026 年 10 月 13 日 第 1 版",81,{"impact":152,"substance":153,"depth":154,"authority":99,"freshness":13,"relevant":21,"comment":155},22,20,16,"国内小麦育种具身机器人原型机首次公开亮相，技术路线与产学研合作信息具体，具备行业示范价值，值得进入每日精选。",[157],{"name":149,"url":147},[26,27,28,159,160],"小麦育种","具身机器人",{"code":162,"slug":163,"name":164,"path":165,"parent_code":112},"A2","wheat","小麦","\u002Ftopic\u002Ffield-crops\u002Fwheat",[],{"status":115,"locked":14,"version":33,"method":34,"evidence":168},{"candidates":169,"agricultural_evidence":52},[170,174,178,182],{"code":162,"score":17,"supported":52,"title":171,"abstract":172,"tags":173},[164],[164],[159],{"code":38,"score":21,"supported":14,"title":175,"abstract":176,"tags":177},[],[],[28],{"code":43,"score":21,"supported":14,"title":179,"abstract":180,"tags":181},[],[],[26],{"code":48,"score":21,"supported":14,"title":183,"abstract":184,"tags":185},[],[],[27],[187,188],"山东农业大学 小麦育种 具身机器人","王宏伟 小麦 表型采集","山东农业大学小麦育种具身机器人-4859","2026-10-14T00:04:08.166418Z",{"id":192,"title":193,"url":194,"summary":195,"summary_zh":9,"content":9,"source_name":196,"source_url":9,"published_at":93,"category":94,"cover_url":9,"hotness":13,"is_selected":14,"score":197,"score_detail":198,"sources":203,"tags":205,"primary_topic":206,"secondary_topics":207,"classification":208,"search_phrases":234,"slug":237,"view_count":20,"doi":9,"paper":9,"created_at":238},4852,"当AI走进稻田:杂交水稻育种有了'决策大脑'——袁稻思源智能育种平台解读","https:\u002F\u002Fnew.qq.com\u002Frain\u002Fa\u002F20261013A0B8CD00","10月11日,'袁稻思源'杂交水稻智能育种平台在岳麓山实验室发布。平台由湖南省农业科学院、中科院自动化所与中科闻歌共同推进。平台构建四大核心功能模块:数据资源库(35570个水稻品种、689项性状、28648条基因数据、624757篇中英文文献)、品种与基因图谱、智能问答'小稻'、育种智能体(包括品种审定智能体、杂交配组智能体),已在第三代杂交水稻育种中开展应用示范,推动湖南杂交水稻育种正式迈入数据驱动、智能决策新阶段。","腾讯新闻 2026 年 10 月 13 日",80,{"impact":199,"substance":152,"depth":200,"authority":201,"freshness":100,"relevant":21,"comment":202},24,17,9,"省级科研机构联合发布的杂交水稻智能育种平台，数据规模与功能模块具体，属种业数字化实质进展，值得进入每日精选。",[204],{"name":196,"url":194},[26,27,28,105,106],{"code":108,"slug":109,"name":110,"path":111,"parent_code":112},[],{"status":115,"locked":14,"version":33,"method":34,"evidence":209},{"candidates":210,"agricultural_evidence":52},[211,216,222,226,230],{"code":108,"score":153,"supported":52,"title":212,"abstract":214,"tags":215},[110,213],"稻田",[110],[106],{"code":38,"score":217,"supported":52,"title":218,"abstract":219,"tags":221},4,[],[220],"品种审定",[28],{"code":127,"score":21,"supported":14,"title":223,"abstract":224,"tags":225},[],[],[105],{"code":43,"score":21,"supported":14,"title":227,"abstract":228,"tags":229},[],[],[26],{"code":48,"score":21,"supported":14,"title":231,"abstract":232,"tags":233},[],[],[27],[235,236],"袁稻思源 智能育种平台","湖南省农科院 杂交水稻 智能育种","袁稻思源智能育种平台-4852","2026-10-14T00:04:07.585104Z",{"id":240,"title":241,"url":242,"summary":243,"summary_zh":244,"content":9,"source_name":245,"source_url":242,"published_at":246,"category":12,"cover_url":9,"hotness":13,"is_selected":52,"score":247,"score_detail":248,"sources":251,"tags":253,"primary_topic":257,"secondary_topics":263,"classification":264,"search_phrases":336,"slug":339,"view_count":74,"doi":340,"paper":341,"created_at":370},4832,"Applications and Future Prospects of Plant Multi-Omics Technologies in Precision Agriculture","https:\u002F\u002Fdoi.org\u002F10.3390\u002Fijms27209034","Against the backdrop of global population growth, intensifying climate change, and limited arable land, ensuring food security and promoting sustainable agriculture have become critical issues. The limitations of conventional agricultural systems are becoming increasingly apparent, creating an urgent need for innovation driven by science and technology. In this context, plant multi-omics technologies serve as the foundational data and technical cornerstone of systems biology and precision agriculture. Integrating multi-level data from genomics, transcriptomics, proteomics, metabolomics, epigenomics, and microbiomics offers substantial advantages for systematically understanding and improving plants. Unlike previous reviews that mainly catalog omics technologies or focus on individual crops, this review adopts a unified discovery-to-translation framework and critically evaluates the strength of evidence across applications. This review focuses on cutting-edge applications of multi-omics in three key areas: improving the traits of cereal crops (rice, wheat and maize), remediating soil health, and innovating products such as biofertilizers and biostimulants for agriculture. We systematically explore the roles of multi-omics in accelerating breeding processes, deciphering complex agronomic traits, restoring soil ecosystems, and constructing intelligent decision-support systems. The review also examines current challenges, including the complexity of data integration and the difficulties of predicting genotype-by-environment interactions. Furthermore, it outlines future directions involving deeper convergence with artificial intelligence, high-throughput phenomics, and digital twins. In summary, plant multi-omics technology is a vital tool for unravelling the mysteries of plant life and is also a key enabler of intelligent, precise and sustainable agricultural transformation.","在全球人口增长、气候变化加剧和耕地有限的背景下，保障粮食安全和促进可持续农业已成为关键议题。传统农业系统的局限性日益显现，迫切需要由科学和技术驱动的创新。在此背景下，植物多组学技术作为系统生物学和精准农业的基础数据与技术基石，整合基因组学、转录组学、蛋白质组学、代谢组学、表观基因组学和微生物组学等多层次数据，为系统理解和改良植物提供了显著优势。与以往主要罗列组学技术或聚焦单一作物的综述不同，本综述采用统一的“从发现到转化”框架，并批判性评估各应用中的证据强度。本综述聚焦多组学在三个关键领域的前沿应用：改良谷类作物（水稻、小麦和玉米）的性状、修复土壤健康，以及创新生物肥料和生物刺激素等农业产品。我们系统探讨了多组学在加速育种进程、解析复杂农艺性状、恢复土壤生态系统和构建智能决策支持系统中的作用。本综述还审视了当前挑战，包括数据整合的复杂性和预测基因型与环境互作的困难。此外，文章展望了未来方向，涉及与人工智能、高通量表型组学和数字孪生的更深层次融合。总之，植物多组学技术是揭示植物生命奥秘的重要工具，也是智能、精准和可持续农业转型的关键使能技术。","International Journal of Molecular Sciences","2026-10-12T00:00:00Z",83,{"impact":152,"substance":249,"depth":18,"authority":19,"freshness":100,"relevant":21,"comment":250},21,"核心期刊综述，系统梳理植物多组学在精准农业中的应用与AI、数字孪生等未来方向，专业深度与信源权威度俱佳，值得进入每日精选。",[252],{"name":245,"url":242},[26,27,28,254,255,256],"精准农业","土壤健康","多组学",{"code":258,"slug":259,"name":260,"path":261,"parent_code":262},"H2","soil","土壤健康与改良","\u002Ftopic\u002Fenvironment\u002Fsoil","H",[],{"status":115,"locked":14,"version":33,"method":34,"evidence":265},{"candidates":266,"agricultural_evidence":52},[267,274,280,284,288,295,302,309,316,321,328,332],{"code":43,"score":268,"supported":52,"title":269,"abstract":271,"tags":273},19,[270],"precision 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intelligence",[27],{"code":322,"score":323,"supported":52,"title":324,"abstract":325,"tags":327},"F3",3,[],[326],"肥料",[],{"code":38,"score":21,"supported":14,"title":329,"abstract":330,"tags":331},[],[],[28],{"code":127,"score":21,"supported":14,"title":333,"abstract":334,"tags":335},[],[],[256],[337,338],"植物多组学 精准农业","多组学 智能育种","植物多组学精准农业-4832","10.3390\u002Fijms27209034",{"doi":340,"openalex_id":342,"authors":343,"venue":245,"cited_by_count":74,"oa_url":242,"card":364,"direction":369,"ingested_from":81},"W7221567543",[344,347,349,352,354,356,359,362],{"name":345,"orcid":346},"Tao Tong","https:\u002F\u002Forcid.org\u002F0000-0002-9003-9667",{"name":348,"orcid":9},"Wang Qingxia",{"name":350,"orcid":351},"Fanrong Zeng","https:\u002F\u002Forcid.org\u002F0000-0001-7742-5195",{"name":353,"orcid":9},"Shuzhen Ye",{"name":355,"orcid":9},"Zhijuan Ji",{"name":357,"orcid":358},"Zhong‐Hua Chen","https:\u002F\u002Forcid.org\u002F0000-0002-7531-320X",{"name":360,"orcid":361},"Jiaoyu Wang","https:\u002F\u002Forcid.org\u002F0000-0002-0249-808X",{"name":363,"orcid":9},"Younan Ouyang",{"tldr":365,"method":366,"finding":367,"direction":79,"opportunity":368},"综述植物多组学在精准农业中的应用，涵盖作物改良、土壤修复和生物产品创新。","整合基因组、转录组、蛋白组、代谢组等多组学数据，采用发现到转化框架。","多组学可加速育种、解析复杂农艺性状、修复土壤生态并构建智能决策系统。","多组学与AI、高通量表型、数字孪生融合，解决基因型-环境互作预测难题。","数字乡村与农业信息化","2026-10-13T23:30:29.504594Z",{"id":372,"title":373,"url":374,"summary":375,"summary_zh":9,"content":376,"source_name":377,"source_url":9,"published_at":378,"category":94,"cover_url":9,"hotness":379,"is_selected":52,"score":380,"score_detail":381,"sources":383,"tags":388,"primary_topic":389,"secondary_topics":390,"classification":391,"search_phrases":414,"slug":416,"view_count":21,"doi":9,"paper":9,"created_at":417},4771,"袁稻思源杂交水稻智能育种平台在长沙发布","https:\u002F\u002Fwww.stdaily.com\u002Fweb\u002Fgdxw\u002F2026-10\u002F11\u002Fcontent_594274.html","10月11日,湖南省农业科学院联合中国科学院自动化研究所、北京中科闻歌发布的袁稻思源杂交水稻智能育种平台在岳麓山实验室亮相。平台集成问答助手、育种资源库、知识图谱、文献库四大模块,已在第三代杂交水稻育种中应用示范。柏连阳、李家洋两位院士共同为平台发布致辞,标志着湖南杂交水稻育种进入数据驱动新阶段。","10月11日，“袁稻思源”杂交水稻智能育种平台发布会在岳麓山实验室举行。该平台的发布和应用，标志着湖南杂交水稻育种将正式迈入数据驱动、智能决策的新阶段。\n\n今年7月2日，中国科学院自动化研究所、北京中科闻歌科技股份有限公司与湖南省农业科学院签署合作协议，三方团队围绕“人工智能+农业科研”展开联合攻关。“袁稻思源”平台是三方合作的阶段性成果之一，也是贯彻落实国家种业振兴行动、推动育种技术数字化智能化转型的重要举措。平台以“饮水思源”之意铭记中国工程院院士袁隆平的历史贡献，传承和弘扬袁隆平科学家精神，把数据资源和智能技术转化为育种创新的现实生产力。\n\n会上，湖南省农业科学院副院长李莉现场演示了平台核心功能。平台集成了“问答助手”“育种资源库”“知识图谱”和“文献库”四大功能模块，覆盖了杂交水稻育种信息检索、数据查询与智能决策需求。“问答助手”展示出品种审定智能体的应答能力，“育种资源库”种质资源查询功能可直观呈现品种系谱关系，“知识图谱”可展示品种—性状—基因之间的关联网络，结合“文献库”实现育种文献知识快速检索与溯源。目前，平台已在第三代杂交水稻育种中开展应用示范，取得良好成效。\n\n中国工程院院士柏连阳表示，湖南省农业科学院水稻智能育种团队联合中国科学院自动化研究所、北京中科闻歌公司研发出“袁稻思源”智能育种平台，迈出了AI赋能杂交水稻育种的关键一步。他提出未来要持续迭代完善平台功能，进一步推动人工智能与育种实践深度融合，为种业创新提供坚实支撑。\n\n中国科学院院士李家洋则指出，平台建设是落实种业振兴行动、保障国家粮食安全、抢占农业科技制高点、传承袁隆平精神的重要实践。当前全球种业竞争加剧，生物技术、信息技术与人工智能加速融合，育种正从“经验驱动”转向“数据驱动、设计育种”。率先突破智能育种，有望赢得下一轮农业产业革命的主动。他建议平台进一步强化智能决策，整合基因组、表型、环境等多维数据，提高组合推荐与亲本选择精度；深化协同创新，连接高校、院所、企业的数据、算法、算力与人才，打破信息孤岛；坚持服务产业，形成科研、企业、推广、政府决策闭环，让成果从实验室走向大田；建设公共平台，不仅服务湖南，同时要打造为面向全国、全球的水稻智能育种领域的重要公共产品。\n\n另悉，中国科学院院士李家洋、钱前、谢道昕，中国工程院院士柏连阳，以及来自科研院所、湖南省有关部门、种业企业等单位近200人出席了发布会，共同见证了平台正式上线，探讨智能育种技术创新与产业应用路径。","科技日报 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