[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-1676":3,"related-1676":84},{"id":4,"title":5,"url":6,"summary":7,"summary_zh":8,"content":9,"source_name":10,"source_url":8,"published_at":11,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":15,"score_detail":16,"sources":24,"tags":26,"primary_topic":31,"secondary_topics":37,"classification":38,"search_phrases":79,"slug":82,"view_count":51,"doi":8,"paper":8,"created_at":83},1676,"北京市农林科学院玉米所：国内首个即将通过国家审定的矮秆玉米品种 LC6569 现场签约","https:\u002F\u002Fwww.toutiao.com\u002Farticle\u002F7681650592251150882","第三十三届中国北京种业大会上，北京市农林科学院玉米研究所首席科学家赵久然带来最新成果矮秆 LC6569 和京科 857D，并与北京联创种业有限公司签署科技成果转化合作协议。LC6569 是国内首个即将通过国家审定的矮秆玉米品种，株高仅 2.3 米左右，比常规玉米矮一大截，却能在每亩 6000 株的高密度下保持大果穗，实现矮秆、耐密、高产、抗倒伏和全程机械化，明年推广面积预计达 20 万亩以上。",null,"一颗玉米种子的育种旅程，曾需要十年光阴，如今在AI的加持下，这个周期正在被缩短一半。9月4日，第三十三届中国北京种业大会在京开幕，AI大模型公开征集、矮秆玉米品种被抢订一空、沙漠小麦烤馕成“爆款”……145项自主知识产权成果集中亮相，育种各环节人工智能渗透率已达90%以上，会场交易额预计突破5亿元。智能育种元年，中国种业正跑出加速度。\n\n**智能育种元年已到来，育种家：“AI大幅缩减育种周期”**\n\n在本届种业大会上，北京市农林科学院玉米研究所首席科学家赵久然带来了最新成果，矮秆LC6569和京科857D，并且现场签署了科技成果转化合作协议。北京市农林科学院玉米所将与北京联创种业有限公司，共同开发LC6569、LP6585两个矮秆玉米品种，以灵活许可模式推动科研成果向市场转化，打通从实验室到田间地头的种业产业化路径。\n\n![Image 1](https:\u002F\u002Fp3-sign.toutiaoimg.com\u002Ftos-cn-i-axegupay5k\u002Fe60dfd44c22143c28f79c5686e4fecfb~tplv-tt-origin-web:gif.jpeg?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1789171516&x-signature=WiGxshzcArhqgQHC0F9aTR6TqYU%3D)\n会场展出的矮秆LC6569和京科857D。新京报记者 耿子叶 摄\n\n赵久然从事玉米科研育种工作已有40年，其团队育成的数百个品种在生产上大面积应用，每年推广应用约6000万亩，累计超6亿亩。本次重点推出的LC6569是国内首个即将通过国家审定的矮秆玉米品种，株高仅2.3米左右，比常规玉米矮一大截，却能在每亩6000株的高密度下保持大果穗，实现矮秆、耐密、高产、抗倒伏和全程机械化。该品种已被头部种业企业列为主推品种，今年的制种早已经被种植大户订购一空，明年推广面积预计达20万亩以上。\n\n据悉，在本届大会成果发布区，35家单位发布了191项新品种、新技术、新设备等成果，通过线下发布、线上直播、短视频宣发相结合的方式，大会重点推介10项关键技术与14个突破性新品种，提升种业创新成果传播影响力。大会成功促成12项合作签约。\n\n该玉米品种的诞生，背后还采用了AI智能育种技术，精准聚合了矮秆大穗、耐密抗倒、宜机收等性状。赵久然表示，“原来培育一个新品种至少需要十年时间，通过AI育种技术，如今的育种周期大幅缩减，将传统育种周期缩短至5～6年。”赵久然还发出了征集令，“目前这套方案已经大幅提升了育种效率，但是我们也想发出邀请，如果有更好更适合育种的AI大模型，请与我们联系，我们将积极测试和使用。”\n\n值得一提的是融合生物技术、大数据信息技术、人工智能的智能育种元年已到来，本届大会邀请业内顶尖专家齐聚交流，聚焦智能育种体系构建，分享基因编辑、智能育种等前沿技术，充分发挥大会技术引领风向标作用，推出145项具有自主知识产权的育种芯片、大模型、表型采集智能设备等，育种各环节人工智能渗透率达90%以上，为智能育种变革提供可复制、可推广的“北京范式”。\n\n**在沙漠丰产的京字号小麦，做成的烤馕颇受欢迎**\n\n在主会场丰台京丰宾馆的京品体验区上，烤馕、吐司面包、油鸡等美食各种香气扑鼻，16家单位带来了近100项以新品种培育的主粮、蔬菜、肉鱼等优质农产品，以及延伸开发的各类特色加工产品，上万名参会者和市民现场品鉴体验“京种京味”产品。\n\n最让参会者挪不动步的，不是展板上的介绍数据，而是展台前杂交小麦“京麦189”磨的面粉制作的烤馕。北京市农林科学院杂交小麦研究所苑少华向记者介绍，这批馕是今天早上现烤的，供不应求，“放出来就没了，已经跟不上大家吃的节奏了”。不断有参观者循着香气聚拢过来，尝过之后都想买，苑少华只好反复解释“只展示不售卖”。有位参观者边吃边评价：“这烤馕味道很正，越嚼越香。”\n\n杂交小麦“京麦189”是我国首批通过国家审定的耐盐碱小麦品种之一，它耐干旱、耐贫瘠、耐盐碱，在中重度盐碱地也能稳产。正是这些“皮实”特性，让它从北京顺义的育种基地出发，一路扎根到新疆喀什。今年麦收季，“京麦189”在塔克拉玛干沙漠改良地块，亩产超过350公斤，同时在新疆喀什地区麦盖提县的一块改良盐碱地实测亩产更是达到768公斤。\n\n在种业大会上一抢而空的烤馕，也道出了京麦189最独特的地方，既能在沙漠盐碱地上高产稳产，磨出的面粉还能烤出地道的馕。农业科技的温度，藏进了观众喜爱的这口馕里。\n\n本次在主会场举办的科技成果交流体验活动上，首次聚焦智能育种，设置了“1核4区”，有京品体验区、成果发布区、重点企业区、交流交易区等，共汇集了北京及国内外138家科研院所、种业企业、技术服务商的621项前沿技术成果。\n\n![Image 2](https:\u002F\u002Fp3-sign.toutiaoimg.com\u002Ftos-cn-i-tjoges91tu\u002Fec5ba31d64e1311b40c1d98bbb8c80d8~tplv-tt-origin-web:gif.jpeg?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1789171516&x-signature=HlwG%2BmZTa4T4Nc6KZiEhqMZ%2BaK8%3D)\n会场展出的农产品。新京报记者 耿子叶 摄\n\n现场，一款机器人“吉儿”2.0同样引人关注，这也是全球首款具身智能育种机器人，今年的“吉儿”2.0升级有了双手，可以专门为作物牵线搭桥，实现15秒“撮合”一朵花，柱头识别准确率约90%，单次巡航授粉成功率82%以上。“最重要的是，吉儿可以白加黑24小时不间断地工作。”相关负责人介绍，未来还可以在去除老叶、采摘、监测病虫害、施肥等发挥作用，为破解种源“卡脖子”难题提供装备支撑。\n\n**京种再出海，“朋友圈”越来越大**\n\n来自平谷区的北京市华都峪口禽业有限责任公司总经理杜守山，在本届大会上有了新收获。公司与乌兹别克斯坦巴拉卡·哈姆科尔·帕兰达有限责任公司签署蛋鸡种业国际战略合作协议，计划未来三年在乌兹别克斯坦建成6万套祖代鸡产能的项目，项目达产后向中亚五国、俄罗斯、白俄罗斯及阿富汗地区推广约5亿只商品代白羽肉鸡。\n\n京种扬帆出海的脚步加快，俄罗斯联邦国家科学中心渔业与海洋学研究所与北京市农林科学院水产所共建国际合作实验室，达成了渔业与海洋学领域项目研究、人员交流等四项合作，实现鲟鱼种质资源保护、遗传多样性研究与国际可持续贸易监管的协同攻关。\n\n本届大会共邀请联合国粮农组织、植物新品种保护联盟、国际种子联盟、亚太种子协会等国际组织和19个国家的45名外宾，引导本地种业企业走出国门、开拓国际市场，合作伙伴从东南亚、非洲、中南美洲，向北美、中西亚、东欧、西欧拓展。同时，8场论坛密集呈现国际化元素。在论坛上，联合国粮农组织原总干事特别顾问、国际植物保护公约原秘书长夏敬源分享了全球种业发展趋势与中国种业国际化的战略思考，倡导中国品种、中国标准走向世界舞台。\n\n**农企现场洽谈合作，预计会场交易额突破5亿元**\n\n现场一家来自内蒙古的蔬菜企业，其企业推出的盆栽辣椒很新颖。一盆辣椒价格和普通绿植相差无几，但是可以同时满足观赏和采摘的双重价值。“这盆辣椒可观赏，也可以食用，养得好可以达到半年甚至更久。”企业负责人常瑞青向记者介绍，“这些盆栽辣椒，在内蒙古的水果店、花店里可以买得到。目前，尚未进入北京市场，但在这次种业大会上有几家企业也看中了，正在洽谈合作，相信很快北京的市民也可以买到。”\n\n据悉，本届种业大会采用“实物展示＋现场互动体验＋商务洽谈”的形式，推动合作项目和商业订单签约。在主会场“重点企业区”“交易交流区”，先正达、大北农等220家种业企业现场展示最新品种，通过种子交流交易等活动，与潜在客户进行面对面洽谈，开展精准供需对接。\n\n![Image 3](https:\u002F\u002Fp3-sign.toutiaoimg.com\u002Ftos-cn-i-tjoges91tu\u002F114727dc63670ace4b8afa1c1f3896db~tplv-tt-origin-web:gif.jpeg?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1789171516&x-signature=JUbdAOl%2FQkffmcFrgFjoE5rVPn0%3D)\n种业大会现场。新京报记者 耿子叶 摄\n\n预计今年会场交易额将远超去年，突破5亿元。此外，会议配套引入金融服务和知识产权服务，推动北京农商银行与北京拉索生物科技有限公司达成1项金融支持种业发展签约，打通资金链、创新链、产业链融合通道。\n\n为了办成“永不落幕”的大会，5月-10月大会因时因地举办10项展示观摩活动，开设“田间会客厅”。截至目前，共展示玉米、小麦、春季蔬菜新优特品种2400余个，在京郊示范种植4000亩，通过专家、市场、消费者多方评选，发布玉米、小麦、蔬菜优新品种166个，吸引来自全国各地的2万余名专业人员看“禾”选种，“京紫糯519”鲜食玉米、“农大918”强筋小麦、“红心蜜”黄瓜、“京番串红1号”番茄等一批新品种受到京津冀种植大户追捧，成为爆款新品种。\n\n新京报记者 耿子叶\n\n编辑 张树婧 校对 李立军","新京报","2026-09-04T00:00:00Z","报道",10,true,85,{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":21,"relevant":22,"comment":23},25,22,18,11,9,1,"报道北京种业大会，聚焦AI育种缩短周期及矮秆玉米品种突破，产业影响大，信息详实。",[25],{"name":10,"url":6},[27,28,29,30],"农业人工智能","种业振兴","智能育种","矮秆玉米",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},"A3","maize","玉米","\u002Ftopic\u002Ffield-crops\u002Fmaize","A",[],{"status":39,"locked":40,"version":41,"method":42,"evidence":43},"classified",false,"2026-10-22.2","rules",{"candidates":44,"agricultural_evidence":14},[45,49,56,63,69,74],{"code":32,"score":20,"supported":14,"title":46,"abstract":47,"tags":48},[34],[34],[],{"code":50,"score":51,"supported":14,"title":52,"abstract":53,"tags":55},"F1",4,[],[54],"种业",[28],{"code":57,"score":58,"supported":14,"title":59,"abstract":60,"tags":62},"F5",3,[],[61],"机械化",[],{"code":64,"score":58,"supported":14,"title":65,"abstract":66,"tags":68},"G1",[],[67],"成果转化",[],{"code":70,"score":22,"supported":40,"title":71,"abstract":72,"tags":73},"F2",[],[],[29],{"code":75,"score":22,"supported":40,"title":76,"abstract":77,"tags":78},"I2",[],[],[27],[80,81],"农业人工智能 智能育种 矮秆玉米 种业振兴","农业人工智能 智能育种","农业人工智能智能育种矮秆玉米种业振兴-1676","2026-09-05T00:04:37.833878Z",{"total":85,"page":22,"page_size":85,"items":86},6,[87,197,254,319,365,408],{"id":88,"title":89,"url":90,"summary":91,"summary_zh":92,"content":8,"source_name":93,"source_url":90,"published_at":94,"category":95,"cover_url":8,"hotness":13,"is_selected":40,"score":96,"score_detail":97,"sources":101,"tags":103,"primary_topic":106,"secondary_topics":107,"classification":108,"search_phrases":150,"slug":153,"view_count":154,"doi":155,"paper":156,"created_at":196},3199,"Recommendation of Suitable Planting Locations for Hybrid Maize Varieties Based on Graph Collaborative Filtering","https:\u002F\u002Fdoi.org\u002F10.1093\u002Finsilicoplants\u002Fdiag026","Abstract Enhancing the precision of crop variety adaptability evaluation is critical for maximizing yields and ensuring food security under climate change. Traditional methods relying on expert knowledge or process-based models face scalability challenges and difficulties in capturing complex variety–environment interactions. This study proposes a scalable graph-based collaborative filtering framework for assessing suitable planting locations for hybrid maize varieties, reformulating adaptability evaluation as a ranking task. The framework integrates two key innovations: a multi-layer perceptron (MLP) encoding module that leverages 15 variety trait features and 24 environmental variables to address the cold-start problem, enabling recommendations for previously unseen varieties; and a BPR+ loss function that distinguishes unsuitable environments from merely unplanted ones to accommodate the unique sparsity structure of agricultural trial data. Evaluated against six state-of-the-art graph-based recommendation models on a dataset of 189 locations and 1,102 hybrid maize varieties across China's major agro-ecological zones, our method consistently outperforms existing approaches, achieving approximately 5% improvement over the strongest baseline. The MLP module attains cold-start NDCG above 0.8, and BPR+ yields significant gains in Recall@1–4 and NDCG@1–5. A case study of the widely cultivated variety ZD958, validated against both national promotion data (2019–2024) and multi-year field-trial yields from 40 locations (2017–2024), confirms that the model's rank-ordered recommendations align closely with independent yield evidence: top-ranked locations achieve both the highest productivity and the greatest yield stability. This framework provides an AI-based decision support tool for variety placement optimization and climate-resilient agriculture.","摘要 提高作物品种适应性评价的精度，对于在气候变化背景下最大化产量和保障粮食安全至关重要。依赖专家知识或过程模型的传统方法面临可扩展性挑战，且难以捕捉复杂的品种–环境互作。本研究提出了一种可扩展的基于图协同过滤框架，用于评估杂交玉米品种的适宜种植地点，将适应性评价重新表述为排序任务。该框架融合了两项关键创新：一是多层感知机（MLP）编码模块，利用15个品种性状特征和24个环境变量来缓解冷启动问题，从而能够对未见过的品种进行推荐；二是BPR+损失函数，将不适宜环境与仅未种植环境区分开来，以适应农业试验数据特有的稀疏结构。在中国主要农业生态区189个地点和1，102个杂交玉米品种的数据集上，与六种最先进的基于图的推荐模型进行对比评估，我们的方法始终优于现有方法，相较最强基线提升约5%。MLP模块的冷启动NDCG达到0.8以上，BPR+在Recall@1–4和NDCG@1–5上均带来显著提升。对广泛种植品种ZD958的案例研究，结合国家推广数据（2019–2024年）和40个地点多年田间试验产量数据（2017–2024年）进行验证，证实模型的排序推荐与独立产量证据高度一致：排名靠前的地点既具有最高生产力，也具有最大产量稳定性。该框架为品种布局优化和气候韧性农业提供了基于人工智能的决策支持工具。","in silico Plants","2026-09-20T00:00:00Z","论文",79,{"impact":19,"substance":18,"depth":19,"authority":98,"freshness":99,"relevant":22,"comment":100},13,8,"提出基于图协同过滤的杂交玉米品种适宜种植区推荐框架，覆盖全国189个地点、1102个品种，冷启动与排序指标均有提升，对品种布局优化有实用价值。",[102],{"name":93,"url":90},[104,27,28,34,105],"智慧农业","品种布局",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":40,"version":41,"method":42,"evidence":109},{"candidates":110,"agricultural_evidence":14},[111,116,123,130,135,141,145],{"code":32,"score":112,"supported":14,"title":113,"abstract":114,"tags":115},15,[33],[34,33],[34],{"code":117,"score":85,"supported":14,"title":118,"abstract":119,"tags":122},"A8",[],[120,121],"粮食安全","food security",[],{"code":124,"score":85,"supported":14,"title":125,"abstract":126,"tags":129},"H7",[],[127,128],"气候变化","climate change",[],{"code":75,"score":51,"supported":14,"title":131,"abstract":132,"tags":134},[],[133],"decision 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