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（记者刘真真）10月10日，山东水稻高质量发展研讨会暨“黄河口大米”现场观摩会在东营市垦利区举办。当日，山东省农业科学院（垦利）水稻试验示范基地、山东省农业科学院粳稻分子育种中心揭牌。\n\n山东省农业科学院粳稻分子育种中心是山东首个粳稻分子育种中心。据悉，该中心将聚焦黄淮稻区粳稻种源瓶颈问题，重点开展水稻种质挖掘、分子设计育种、优异新品种创制，瞄准优质粳稻攻关，补齐我省粳稻分子育种硬件平台短板。\n\n黄淮稻区是我国北方优质粳稻主产区和重要粮食生产基地，种植规模稳定、产业基础雄厚，是保障区域粮食安全、助力农民增收的重要板块。当前，随着规模化、轻简化、标准化种植快速普及，消费结构持续升级、盐碱地综合利用力度不断加大，现有主推粳稻品种短板逐步凸显，已难以适应现代农业高质量发展需求，主要存在三方面突出产业瓶颈：一是轻简化适配性不足，主栽品种普遍缺乏除草剂抗性，规模化生产杂草防控成本高、用工多、效率低，二是优质专用供给不足，品种类型以普通粳米为主，香米、软米、糯米等特色专用品种偏少，难以满足市场多元化、高品质消费需求，产业附加值提升空间受限；三是绿色抗逆能力偏弱，多数品种稻瘟病抗性不强、耐盐碱水平有限，易造成农药化肥过量投入，与绿色低碳、生态高效的发展导向不匹配。\n\n因此，山东省农业科学院立足湿地农业与生态研究所水稻种质改良与分子育种学科优势，整合全所分子育种、种质资源、示范推广优势资源，组建粳稻分子育种中心。\n\n据悉，山东省农科院粳稻分子育种中心将聚焦轻简化栽培需求，培育改良抗除草剂粳稻新品种，解决传统水稻生产除草难、成本高、用工重的痛点，支撑水稻规模化、机械化、轻简化生产。在补齐优质专用品种短板方面，该中心将针对市场消费升级趋势，定向改良食味品质，丰富香米、软米、糯稻等特色品种供给，优化品种结构，提升稻米产业附加值。在夯实绿色稳产生产基础方面，该中心将聚焦稻瘟病、盐碱胁迫等生产难题，提升品种抗病、耐盐、抗逆能力，推动水稻产业绿色低碳可持续发展。\n\n当日，山东省农业科学院（垦利）水稻试验示范基地揭牌。这是院地共建的盐碱地水稻综合试验示范平台，该基地将承担新品种鉴定评价、良种中试熟化、绿色栽培技术集成、现场观摩实训等任务，把实验室育种成果放到黄河三角洲盐碱地大田进行检验验证，破解科技成果转化“最后一公里”难题。\n\n黄河三角洲是我省盐碱地集中分布区域，垦利区近八成耕地属于不同程度的盐碱地，后备耕地资源潜力巨大，但土壤盐渍化是制约粮食生产的突出难题。近年来，山东省筛选了一大批适宜黄三角生态条件的水稻新品种，但黄河三角洲盐碱环境复杂多变，水稻品种还面临多重考验：部分品种耐盐适应性不稳定，适合重度盐碱地的优质粳稻仍然偏少；良种良法配套的普及程度有待提升；科企深度融合不够，优良品种产业化推广速度仍需加快。示范基地揭牌将有助于破解盐碱地水稻品种“水土不服”的难题，推动良种良法配套、科企深度融合。\n\n特别声明：以上文章内容仅代表作者本人观点，不代表新浪网观点或立场。如有关于作品内容、版权或其它问题请于作品发表后的30日内与新浪网联系。","农村大众报 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2026年10月10日","2026-10-10T00:00:00Z",65,{"impact":121,"substance":121,"depth":122,"authority":123,"freshness":74,"relevant":20,"comment":124},18,15,9,"省级首个粳稻分子育种平台落地，聚焦耐盐碱与轻简化育种，产业瓶颈分析具体，具行业参考价值。",[126],{"name":117,"url":114},[128,79,26,129,130],"盐碱地利用","耐盐碱水稻","黄河三角洲",{"code":132,"slug":133,"name":134,"path":135,"parent_code":136},"A1","rice","水稻","\u002Ftopic\u002Ffield-crops\u002Frice","A",[138],{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},{"status":38,"locked":14,"version":39,"method":40,"evidence":140},{"candidates":141,"agricultural_evidence":45},[142,146,150,156,160],{"code":132,"score":18,"supported":45,"title":143,"abstract":144,"tags":145},[134],[134],[129],{"code":31,"score":18,"supported":45,"title":147,"abstract":148,"tags":149},[26],[26],[26],{"code":151,"score":101,"supported":45,"title":152,"abstract":153,"tags":155},"F4",[],[154],"除草",[],{"code":50,"score":20,"supported":14,"title":157,"abstract":158,"tags":159},[],[],[79],{"code":161,"score":20,"supported":14,"title":162,"abstract":163,"tags":164},"H2",[],[],[128],[166,167],"山东农科院 粳稻分子育种中心","垦利 盐碱地 水稻示范基地","山东农科院粳稻分子育种中心-5044","2026-10-16T00:13:11.440215Z",{"id":171,"title":172,"url":173,"summary":174,"summary_zh":8,"content":175,"source_name":176,"source_url":8,"published_at":177,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":178,"score_detail":179,"sources":184,"tags":186,"primary_topic":191,"secondary_topics":192,"classification":193,"search_phrases":200,"slug":203,"view_count":204,"doi":8,"paper":8,"created_at":205},4390,"中国农科院基因组所李伟团队揭示被子植物异嗪皮啶生物合成与演化规律—《Nature Communications》","https:\u002F\u002Fwww.toutiao.com\u002Farticle\u002F7691749797241324072","中国农科院基因组所(大鹏湾实验室)李伟团队联合王丽团队在《Nature Communications》发表研究,完成草珊瑚染色体水平高质量基因组组装(基因组大小 4.23 Gb),鉴定出活性成分异嗪皮啶生物合成的关键 O-甲基转移酶 SgOMT3 及关键氨基酸残基 Leu127;揭示 OMT 在被子植物远缘科属中的功能保守性与分化轨迹,为传统中药现代分子育种提供关键基因靶点。","近日，中国农科院基因组所（大鹏湾实验室） **李伟团队**联合**王丽团队**在 《自然通讯（_Nature Communications_）》 在线发表了题为“_Sarcandra glabra_ genome unveils functional conservation and divergence of O-methyltransferases catalyzing isofraxidin biosynthesis in angiosperms”的研究论文。该研究整合基因组、转录组和代谢组等多组学分析，并结合体外酶活性验证与体内毛状根功能验证，鉴定出活性成分异嗪皮啶生物合成的关键O-甲基转移酶，并通过该酶及其同源基因的演化分析和定点突变揭示了异嗪皮啶生物合成相关O-甲基转移酶（OMT）在被子植物远缘科属中的功能保守性与分化轨迹，为传统中药现代分子育种提供了关键基因靶点和理论技术支撑。\n\n”\n\n![Image 1](https:\u002F\u002Fp3-sign.toutiaoimg.com\u002Ftos-cn-i-ezhpy3drpa\u002F52d32e7001fc448d94441a59ef287f02~tplv-tt-origin-web:gif.jpeg?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1792022824&x-signature=FnezJUtYgnT72O7Dc6V4nEcVwcc%3D)\n研究首先根据物质结构推测了异嗪皮啶的生物合成途径：秦皮素前体在O-甲基转移酶的催化下分别生成异嗪皮啶和嗪皮啶。代谢分析结果表明异嗪皮啶在根组织中含量最高。利用PacBio HiFi联合Hi-C技术完成草珊瑚染色体水平高质量基因组组装，基因组大小4.23 Gb（图1）。\n\n![Image 2](https:\u002F\u002Fp3-sign.toutiaoimg.com\u002Ftos-cn-i-ezhpy3drpa\u002F05dad0e3958a4e5094a1c1b0d34a80f6~tplv-tt-origin-web:gif.jpeg?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1792022824&x-signature=CQZfDN4OTsqt0Ickpd%2BxmniqsQQ%3D)\n**图1 | 异嗪皮啶生物合成途径、组织特异性与草珊瑚基因组组装分析**\n\n基于草珊瑚转录组与异嗪皮啶含量的相关性分析，筛选出4个与异嗪皮啶合成高度相关的OMT基因。体外蛋白酶活结果表明SgOMT3能够催化底物秦皮素生成异嗪皮啶，而SgOMT3的旁系同源基因均已丧失催化生成异嗪皮啶的能力（图2）。\n\n![Image 3](https:\u002F\u002Fp3-sign.toutiaoimg.com\u002Ftos-cn-i-ezhpy3drpa\u002F0694156a6d9741fd9920619f75b3d229~tplv-tt-origin-web:gif.jpeg?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1792022824&x-signature=dOPTVX0AR0cVSkEFZWgTMCR1hik%3D)\n**图2 | 草珊瑚中异嗪皮啶合成关键OMT酶的筛选与催化活性鉴定**\n\n对来源于双子叶和金粟兰科的11个SgOMT3直系同源蛋白进行比对，筛选决定异嗪皮啶催化合成活性的关键氨基酸位点。结合蛋白质结构预测、分子动力学模拟、定点突变与活性测定，表明Leu127是SgOMT3催化合成异嗪皮啶的关键氨基酸残基（图3）。\n\n![Image 4](https:\u002F\u002Fp3-sign.toutiaoimg.com\u002Ftos-cn-i-ezhpy3drpa\u002Fb2100fb1615047eb806ee34b82a91844~tplv-tt-origin-web:gif.jpeg?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1792022824&x-signature=oghmmFr5e4jTZ6XAeE4AZ9AB8LQ%3D)\n**图3 | SgOMT3催化异嗪皮啶合成的关键氨基酸残基鉴定**\n\n8个SgOMT3直系同源基因酶活结果表明，在双子叶植物的演化过程中，异嗪皮啶合成特异性逐渐增强，而作为进化早期的金粟兰科OMT蛋白保留了较为原始的催化特征。随后通过多序列比对、分子动力学模拟与活性解析，表明Leu307是决定异嗪皮啶合成特异性的关键氨基酸残基（图4）。\n\n![Image 5](https:\u002F\u002Fp3-sign.toutiaoimg.com\u002Ftos-cn-i-ezhpy3drpa\u002F05a5aac2ad94414ebfe3dd5ff0426a6d~tplv-tt-origin-web:gif.jpeg?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1792022824&x-signature=Y4QKmNTIMQvHsHDEFgaJ0yz%2B7no%3D)\n> 图4 | 被子植物中异嗪皮啶合成OMT酶功能保守性与区域选择性差异\n\n基因组所（大鹏湾实验室） **李伟**研究员和**王丽**研究员为论文的**共同通讯作者**。基因组所助理研究员**谢德金**博士、中国科学院大学博士研究生**余熙恺**和深势科技**陈家楠**博士为论文**共同第一作者**。该研究得到了国家重点研发计划、国家自然科学基金、中国农科院青年英才和深圳市科技计划项目和中国农业科学院重大科技任务等项目的支持。\n\nhttps:\u002F\u002Fwww.nature.com\u002Farticles\u002Fs41467-026-77631-9","中国科学报 今日头条 2026-10-02","2026-10-02T00:00:00Z",83,{"impact":180,"substance":181,"depth":182,"authority":17,"freshness":74,"relevant":20,"comment":183},22,23,19,"国家级科研机构在核心期刊发表的中药材基因组与合成生物学突破，方法扎实、结论可靠，对中药分子育种有实质指导价值。",[185],{"name":176,"url":173},[26,187,188,189,190],"基因组学","合成生物学","草珊瑚","中药材育种",{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},[],{"status":38,"locked":14,"version":39,"method":40,"evidence":194},{"candidates":195,"agricultural_evidence":45},[196],{"code":31,"score":19,"supported":45,"title":197,"abstract":198,"tags":199},[],[26],[26,188,187],[201,202],"中国农科院基因组所 草珊瑚 异嗪皮啶","SgOMT3 异嗪皮啶 生物合成","中国农科院基因组所草珊瑚异嗪皮啶-4390",2,"2026-10-08T00:06:56.116132Z",{"id":207,"title":208,"url":209,"summary":210,"summary_zh":8,"content":211,"source_name":212,"source_url":8,"published_at":213,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":214,"score_detail":215,"sources":217,"tags":219,"primary_topic":224,"secondary_topics":225,"classification":226,"search_phrases":248,"slug":251,"view_count":204,"doi":8,"paper":8,"created_at":252},3949,"数博会上新农事——智慧农事场景集中呈现，河北省农科院紫麦品种受关注","https:\u002F\u002Fwww.toutiao.com\u002Farticle\u002F7689625980238889514","9月25日，2026中国国际数字经济博览会现场，一套鱼菜共生种植设备吸引不少参观者驻足。石家庄博瑞迪生物技术有限公司带来一套2.0版分子育种检测产线，占地更小、检测通量和准确率更高；石家庄市栾城区天亮种植专业合作社展台前展示的紫麦是河北省农科院粮油所研发的品种，依托当地富硒土壤种植紫麦，目前已开发出系列产品。","## 数博会上新农事\n\n2026-09-26 07:56·[石家庄日报](https:\u002F\u002Fwww.toutiao.com\u002Fc\u002Fuser\u002Ftoken\u002FMS4wLjABAAAA3fLP3IhZPJBvNHdqKwV1gY03kpOoxRp1LnYZcQ6Hodc\u002F?source=tuwen_detail)\n\n“什么是鱼菜共生？”9月25日，2026中国国际数字经济博览会现场，一套鱼菜共生种植设备吸引不少参观者驻足。上层菜叶翠绿，下方水箱鱼儿穿梭，独特的种植模式让小学生邓泽凯倍感新奇。\n\n“水泵循环输水，鱼类排泄物经过处理，可以为蔬菜提供养分。”技术经理侯利明指着管道介绍。随后，他打开手机控制页面，轻点屏幕便可远程调节灯光、水泵的运行状态。\n\n展台上，智慧农事场景集中呈现。演示沙盘上的按钮分别控制生长灯、风扇和水泵；机械臂稳稳抓取果蔬模型，再将其放回原位，引得孩子们排队体验。浇水、补光、环境调节、果蔬分拣等农业生产环节，被浓缩在方寸展台上。\n\n田间种养有了新设备，育种也用上了新技术。石家庄博瑞迪生物技术有限公司带来一套2.0版分子育种检测产线。企业工作人员介绍，与现有产线相比，新产线占地更小，检测通量和准确率更高，可以通过基因检测快速筛选符合目标的育种材料，提高育种效率。\n\n科技赋能农业的成果，也能现场尝一尝。石家庄市栾城区天亮种植专业合作社展台前，不少观众围在一起品尝紫麦馍片。销售部苏经理介绍，紫麦是河北省农科院粮油所研发的品种，合作社依托当地富硒土壤种植紫麦，目前已开发出系列产品。\n\n石家庄市农业农村局市场信息科科长韩继强介绍，现场集中展示了智慧农业、数字种植养殖、农产品电商、农业大数据和农产品品牌建设等方面的成果。“我们借助数博会平台展示农业农村数字化建设成果、对接数字技术资源，推动数字技术与乡村产业、乡村治理深度融合，加快农业农村现代化，助力乡村全面振兴。”（记者 徐 阳 见习记者 李雅雯）","今日头条·石家庄日报·2026年09月26日","2026-09-25T23:56:00Z",51,{"impact":18,"substance":17,"depth":18,"authority":73,"freshness":74,"relevant":20,"comment":216},"数博会农业数字化场景的综合报道，涵盖鱼菜共生、分子育种与紫麦品种，信息面广但以展会动态为主，属地方媒体行业观察。",[218],{"name":212,"url":209},[220,221,26,222,223],"数字乡村","智慧农业","紫麦","鱼菜共生",{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},[],{"status":38,"locked":14,"version":39,"method":40,"evidence":227},{"candidates":228,"agricultural_evidence":45},[229,233,238,243],{"code":31,"score":51,"supported":45,"title":230,"abstract":231,"tags":232},[],[26],[26],{"code":161,"score":101,"supported":45,"title":234,"abstract":235,"tags":237},[],[236],"土壤",[],{"code":239,"score":20,"supported":14,"title":240,"abstract":241,"tags":242},"I1",[],[],[221],{"code":244,"score":20,"supported":14,"title":245,"abstract":246,"tags":247},"I6",[],[],[220],[249,250],"河北省农科院 紫麦","数博会 智慧农事","河北省农科院紫麦-3949","2026-10-02T11:53:12.454864Z",{"id":254,"title":255,"url":256,"summary":257,"summary_zh":258,"content":8,"source_name":259,"source_url":256,"published_at":260,"category":261,"cover_url":8,"hotness":13,"is_selected":14,"score":262,"score_detail":263,"sources":265,"tags":267,"primary_topic":273,"secondary_topics":279,"classification":286,"search_phrases":356,"slug":359,"view_count":204,"doi":360,"paper":361,"created_at":376},2625,"Multi-omics and artificial intelligence for climate-resilient and nutrient-enriched food crops: advances, applications and future perspectives","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1931230","Climate change has intensified both abiotic and biotic stresses, threatening global crop productivity, nutritional quality, and agricultural sustainability. These challenges have accelerated the adoption of advanced multi-omics technologies, including genomics, transcriptomics, proteomics, and metabolomics, together with artificial intelligence (AI) to accelerate the development of climate-resilient and nutrient-enriched crops. This review provides an integrated view of the recent advances in AI-enabled multi-omics, genome editing and precision agriculture for climate-resilient and nutrient-rich crops along with emerging trends, current challenges, and future research priorities. Machine learning-enhanced genomic selection approaches such as convolutional neural network (CNN)-based models and transformer models enhance the accuracy of predictions for complex stress-tolerant and nutritional traits. AI-assisted unmanned aerial vehicle (UAV) remote sensing allows measurement of traits at an unprecedented scale and with high-throughput and quantitative phenotyping. AI-driven multi-omics integration approaches, such as pan-omics pipelines, decipher abiotic stress tolerance regulatory networks. The AI-assisted CRISPR-Cas9 genome editing systems have accelerated crop biofortification outcomes by improving target prioritization and guide RNA design. Genome-editing studies have reported enhanced iron and zinc bioavailability in experimental wheat lines, reduced phytic acid content in soybean, and enhanced vitamin and amino acid content in cassava and maize, highlighting the potential of AI-assisted genome-editing approaches for crop biofortification. AI-enabled precision agriculture platforms use AI together with satellite data and Internet of Things (IoT) sensors and predictive modeling to enhance crop management while decreasing environmental resource usage. This review examines data standardization and model interpretability together with access and regulations while it presents a future roadmap for achieving 2050 food security targets. By integrating multi-omics, artificial intelligence, genome engineering, and precision agriculture into a unified framework, this review identifies future research directions and key knowledge gaps for the development of climate-resilient and nutrient-rich crops.","气候变化加剧了非生物与生物胁迫，对全球作物生产力、营养品质和农业可持续性构成威胁。这些挑战加速了先进多组学技术（包括基因组学、转录组学、蛋白质组学和代谢组学）以及人工智能（AI）的应用，以加快气候韧性及营养强化作物的开发。本综述综合阐述了AI赋能的多组学、基因组编辑和精准农业在气候韧性及营养丰富作物方面的最新进展，以及新兴趋势、当前挑战和未来研究重点。机器学习增强的基因组选择方法，如基于卷积神经网络（CNN）的模型和Transformer模型，提高了对复杂耐逆性和营养性状预测的准确性。AI辅助的无人机（UAV）遥感能够以前所未有的规模进行高通量定量表型测量。AI驱动的多组学整合方法，如泛组学流程，可解析非生物胁迫耐受调控网络。AI辅助的CRISPR-Cas9基因组编辑系统通过改进靶标优先级排序和引导RNA设计，加速了作物生物强化成果。基因组编辑研究报告了实验小麦品系中铁和锌生物利用度的提高、大豆中植酸含量的降低，以及木薯和玉米中维生素和氨基酸含量的增强，凸显了AI辅助基因组编辑方法在作物生物强化方面的潜力。AI赋能的精准农业平台利用AI结合卫星数据、物联网（IoT）传感器和预测建模，在减少环境资源使用的同时增强作物管理。本综述审视了数据标准化和模型可解释性以及可及性和监管问题，同时提出了实现2050年粮食安全目标的未来路线图。通过将多组学、人工智能、基因组工程和精准农业整合为统一框架，本综述确定了开发气候韧性及营养丰富作物的未来研究方向和关键知识空白。","Frontiers in Sustainable Food Systems","2026-09-16T00:00:00Z","论文",86,{"impact":180,"substance":180,"depth":182,"authority":17,"freshness":123,"relevant":20,"comment":264},"核心期刊综述，系统梳理AI驱动多组学、基因编辑与精准农业在气候韧性及营养强化作物上的进展，方法新颖、结论可靠，对智慧育种与农业AI方向有较高参考价值。",[266],{"name":259,"url":256},[268,269,270,271,272,27],"农业人工智能","精准农业","基因编辑","气候韧性","智慧育种",{"code":274,"slug":275,"name":276,"path":277,"parent_code":278},"I2","agricultural-ai","农业AI与大模型","\u002Ftopic\u002Fdigital-agriculture\u002Fagricultural-ai","I",[280,281],{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},{"code":282,"slug":283,"name":284,"path":285,"parent_code":278},"I5","agricultural-iot","物联网传感与边缘计算","\u002Ftopic\u002Fdigital-agriculture\u002Fagricultural-iot",{"status":38,"locked":14,"version":39,"method":40,"evidence":287},{"candidates":288,"agricultural_evidence":45},[289,296,302,309,317,322,329,336,343,349],{"code":274,"score":121,"supported":45,"title":290,"abstract":292,"tags":295},[291],"artificial intelligence",[293,294,291],"机器学习","machine learning",[268],{"code":31,"score":123,"supported":45,"title":297,"abstract":298,"tags":301},[],[299,300],"基因组选择","genomic selection",[270,27,272],{"code":282,"score":123,"supported":45,"title":303,"abstract":304,"tags":308},[],[305,306,307],"物联网","internet of things","IoT",[],{"code":310,"score":311,"supported":45,"title":312,"abstract":313,"tags":316},"H7",7,[],[314,315],"气候变化","climate change",[271],{"code":239,"score":311,"supported":45,"title":318,"abstract":319,"tags":321},[],[269,320],"precision agriculture",[269],{"code":323,"score":19,"supported":45,"title":324,"abstract":325,"tags":328},"A2",[],[326,327],"小麦","wheat",[],{"code":330,"score":19,"supported":45,"title":331,"abstract":332,"tags":335},"A3",[],[333,334],"玉米","maize",[],{"code":337,"score":19,"supported":45,"title":338,"abstract":339,"tags":342},"A4",[],[340,341],"大豆","soybean",[],{"code":100,"score":19,"supported":45,"title":344,"abstract":345,"tags":348},[],[346,347],"粮食安全","food security",[],{"code":350,"score":19,"supported":45,"title":351,"abstract":352,"tags":355},"I3",[],[353,354],"遥感","remote sensing",[],[357,358],"农业人工智能 基因编辑 智慧育种 气候韧性","农业人工智能 基因编辑","农业人工智能基因编辑智慧育种气候韧性-2625","10.3389\u002Ffsufs.2026.1931230",{"doi":360,"openalex_id":362,"authors":363,"venue":259,"cited_by_count":59,"oa_url":256,"card":368,"direction":374,"ingested_from":375},"W7213241547",[364,366],{"name":365,"orcid":8},"Surasreeta Paul",{"name":367,"orcid":8},"Sandeep Singh Rana",{"tldr":369,"method":370,"finding":371,"direction":372,"opportunity":373},"综述AI赋能多组学、基因编辑与精准农业，培育气候韧性与营养强化作物。","整合基因组、转录组、蛋白与代谢组学，结合CNN、Transformer、UAV遥","AI辅助多组学与基因编辑可提升耐逆与营养性状预测及生物强化效率。","农业人工智能与决策模型","多组学数据标准化与模型可解释性不足，可研究跨物种可迁移的AI决策框架。","智慧农业 \u002F 农业物联网","openalex","2026-09-16T23:30:07.496425Z",{"id":378,"title":379,"url":380,"summary":381,"summary_zh":382,"content":8,"source_name":383,"source_url":380,"published_at":384,"category":261,"cover_url":8,"hotness":13,"is_selected":14,"score":385,"score_detail":386,"sources":388,"tags":390,"primary_topic":392,"secondary_topics":397,"classification":399,"search_phrases":421,"slug":424,"view_count":204,"doi":425,"paper":426,"created_at":450},2521,"From family trials to genomic mate allocation: statistical and genomic strategies to accelerate sugarcane genetic improvement","https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs00122-026-05373-9","Sugarcane (Saccharum spp.) underpins global sugar and bioenergy supply and is increasingly valued as a renewable biomass feedstock. Sustained improvement in commercial traits and resilience is constrained by long breeding cycles, clonal propagation, multi-stage testing, and a highly polyploid, heterozygous, and frequently aneuploid genome with substantial non-additive genetic variation. Genomic selection has demonstrated value for predicting elite-clone performance, yet its operational use remains limited at earlier decision points, including family selection, parent evaluation, and cross design. This review examines the biological, statistical, and genomic factors that shape these decisions, with emphasis on the Australian breeding context based on progeny assessment trials (PATs), clonal assessment trials (CATs), and final assessment trials (FATs). We evaluate challenges arising from family plot means, the use of different full-sib samples as nominal family replicates, spatial heterogeneity, competition, genotype-by-environment interaction, and the partitioning of additive and non-additive effects. We also assess the integration of pedigree and genomic relationship, genotype representation, allele-dosage estimation, aneuploidy, genomic prediction models, and training-population design. We then consider genomic prediction of cross performance and constrained mate allocation as approaches for improving expected family performance, accounting for cross-specific non-additive effects and managing relatedness. We propose a decision-centred framework that links family and clonal data across breeding stages, tracks the propagation of information and uncertainty, and supports parent recycling and cross allocation. We conclude with a practical research agenda for stage-integrated mixed-model and single-step analyses that connect early family evaluation with genomic prediction and cross-level decision support in sugarcane breeding.","甘蔗（\u003Ci>Saccharum\u003C\u002Fi> spp.）支撑着全球糖料与生物能源供应，并作为可再生生物质原料日益受到重视。商业性状与适应性的持续改良受到长育种周期、无性繁殖、多阶段测试以及高度多倍体、杂合且常为非整倍体基因组的制约，后者具有大量非加性遗传变异。基因组选择在预测优良无性系表现方面已显示出价值，但其在更早期决策节点（包括家系选择、亲本评价和杂交设计）中的实际应用仍然有限。本文综述了影响这些决策的生物学、统计学和基因组学因素，重点聚焦于基于后代评估试验（PATs）、无性系评估试验（CATs）和最终评估试验（FATs）的澳大利亚育种背景。我们评估了由家系小区均值、使用不同全同胞样本作为名义家系重复、空间异质性、竞争、基因型×环境互作以及加性与非加性效应划分所带来的挑战。我们还评估了系谱与基因组亲缘关系的整合、基因型代表性、等位基因剂量估计、非整倍性、基因组预测模型和训练群体设计。随后，我们考虑了杂交表现的基因组预测和约束配对分配作为改善预期家系表现的方法，同时兼顾杂交特异性非加性效应并管理亲缘关系。我们提出了一个以决策为中心的框架，该框架连接育种各阶段的家系与无性系数据，追踪信息和不确定性的传播，并支持亲本循环利用与杂交分配。最后，我们提出了一个面向阶段整合混合模型和单步分析的实际研究议程，将早期家系评价与基因组预测及甘蔗育种中的杂交水平决策支持相连接。","Theoretical and Applied Genetics","2026-09-12T00:00:00Z",80,{"impact":121,"substance":180,"depth":121,"authority":17,"freshness":73,"relevant":20,"comment":387},"核心期刊综述，系统梳理甘蔗育种中基因组预测与亲本选配的统计与基因组策略，方法新颖、专业深度高，对作物智能育种有参考价值，但属细分领域学术进展，公共影响范围有限。",[389],{"name":383,"url":380},[268,79,26,299,391],"甘蔗育种",{"code":393,"slug":394,"name":395,"path":396,"parent_code":136},"A6","cash-crops","棉麻糖与特色经作","\u002Ftopic\u002Ffield-crops\u002Fcash-crops",[398],{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},{"status":38,"locked":14,"version":39,"method":40,"evidence":400},{"candidates":401,"agricultural_evidence":45},[402,408,412,417],{"code":393,"score":122,"supported":45,"title":403,"abstract":405,"tags":407},[404],"sugarcane",[406,404],"甘蔗",[391],{"code":31,"score":73,"supported":45,"title":409,"abstract":410,"tags":411},[],[299,300],[26,299],{"code":274,"score":51,"supported":45,"title":413,"abstract":414,"tags":416},[],[415],"decision support",[268],{"code":50,"score":20,"supported":14,"title":418,"abstract":419,"tags":420},[],[],[79],[422,423],"农业人工智能 基因组选择 分子育种 甘蔗育种","农业人工智能 基因组选择","农业人工智能基因组选择分子育种甘蔗育种-2521","10.1007\u002Fs00122-026-05373-9",{"doi":425,"openalex_id":427,"authors":428,"venue":383,"cited_by_count":59,"oa_url":443,"card":444,"direction":449,"ingested_from":375},"W7212382599",[429,432,434,437,440],{"name":430,"orcid":431},"Andrew Rigby","https:\u002F\u002Forcid.org\u002F0009-0006-3626-3875",{"name":433,"orcid":8},"Felicity Atkin",{"name":435,"orcid":436},"Ben J. Hayes","https:\u002F\u002Forcid.org\u002F0000-0002-5606-3970",{"name":438,"orcid":439},"Lee T. Hickey","https:\u002F\u002Forcid.org\u002F0000-0001-6909-7101",{"name":441,"orcid":442},"Seema Yadav","https:\u002F\u002Forcid.org\u002F0000-0001-7191-7770","https:\u002F\u002Flink.springer.com\u002Fcontent\u002Fpdf\u002F10.1007\u002Fs00122-026-05373-9.pdf",{"tldr":445,"method":446,"finding":447,"direction":372,"opportunity":448},"综述甘蔗育种早期决策的统计与基因组策略，提出连接家系与无性系数据的决策框架。","基于澳大利亚PAT\u002FCAT\u002FFAT试验，整合系谱与基因组关系、等位基因剂量及预测","基因组预测与约束交配分配可优化家系表现，需处理非加性效应和亲缘关系。","开发阶段整合的混合模型与单步分析，将早期家系评估与基因组预测及杂交决策支持相连。","农业遥感与作物表型","2026-09-15T23:30:16.012181Z"]