[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-284":3,"related-284":63},{"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":23,"tags":25,"primary_topic":32,"secondary_topics":38,"classification":39,"search_phrases":57,"slug":60,"view_count":61,"doi":8,"paper":8,"created_at":62},284,"山东省农科院「九成熟十成收」实打测产印证——三地四品种平均亩增产超80斤,小麦适度高水分收获干燥一体化技术模式成熟可推广","https:\u002F\u002Fsd.news.163.com\u002F26\u002F0807\u002F08\u002FL3NDTHA104379D5J_pa11y.html","近日,山东省农业科学院作物研究所先后在淄博临淄、青岛莱西、临沂费县三处试验基地,对「适度高水分小麦收获干燥一体化技术模式」进行了系统的实打测产。三地涵盖了山农28、济麦22、济紫麦4号、垦星8号四个品种,分别在蜡熟末期(籽粒水分22%至27%)和完熟期(水分15%以下)进行收获对比。三个地点、四种品种、不同土壤条件和生态区,数据相互印证,结论高度一致:适度高水分收获较完熟期收获,亩增产幅度在5.5%至8.9%之间,平均亩增产超过80斤;机收损失率降低35%至82%;籽粒破碎率降低33%至51%。这些数据验证了老一辈农谚「九成熟十成收,十成熟九成收」:小麦在九成熟时收获,能拿到十成的收成;等到十成熟再收,反而要丢一成——小麦蜡熟末期干物质积累达到峰值,之后进入「养分回流」阶段,部分营养物质反而倒流到秸秆里;同时完熟期穗轴变脆,稍微摆动就容易掉穗掉粒。桓台县田庄镇大寨村种粮大户吕茂兴今年3200多亩小麦部分地块在含水量接近20%时便进行收割,新安装4台第三代智慧干燥储粮仓5天可将水分从20%降至13.8%-12.8%,每斤小麦干燥成本不到4厘钱,这套模式通过提前收割实现田间「开源」、依托密闭智能仓储实现储藏「节流」,双向提升种植收益,为粮食收储绿色减损提供了可复制、可推广的解决方案。",null,"近日，山东省农业科学院作物研究所先后在淄博临淄、青岛莱西、临沂费县三处试验基地，对“适度高水分小麦收获干燥一体化技术模式”进行了系统的实打测产。三地涵盖了山农28、济麦22、济紫麦4号、垦星8号四个品种，分别在蜡熟末期(籽粒水分22%至27%)和完熟期(水分15%以下)进行收获对比。三个地点、四种品种、不同土壤条件和生态区，数据相互印证，结论高度一致：适度高水分收获较完熟期收获，亩增产幅度在5.5%至8.9%之间，平均亩增产超过80斤;机收损失率降低35%至82%;籽粒破碎率降低33%至51%。\n\n这些数据验证的正是老一辈传下来的一句农谚——“九成熟十成收，十成熟九成收”。意思是小麦在九成熟时收获，能拿到十成的收成;等到十成熟再收，反而要丢一成。道理不难理解：小麦蜡熟末期干物质积累达到峰值，之后进入“养分回流”阶段，部分营养物质反而倒流到秸秆里;同时完熟期穗轴变脆，稍微摆动就容易掉穗掉粒。农谚代代相传，却没有精准的试验数据来支撑。“以前大家都这么说，但到底能差多少，谁也说不出个准数。”一位参与测产的农技人员坦言。如今，山东省农科院用三个地点、四种品种的实打测产，让这句老话有了扎扎实实的数据支撑。\n\n那问题来了：水分那么高收回来，怎么存?传统上农户必须等到麦粒晒干才能入仓，否则就会发热霉变。高水分小麦的干燥和储存，一直是制约“九成熟”收割的瓶颈。\n\n这次试验中，山东长江粮油仓储机械有限公司的智慧干燥储粮仓给出了答案。《小麦入仓通风干燥试验跟踪报告》详细记录了测试的成果。6月8日下午，150吨高水分小麦在淄博试验基地入仓——西仓90吨，初始水分24.5%;东仓60吨，初始水分23.7%。风机间歇式连续通风，干燥周期内东西仓各完成2次倒仓作业。到6月14日取样检测：东仓水分降至13.8%，西仓降至12.8%，5天时间平均降幅达10.8个水分点。\n\n成本账更是显而易见：整批小麦通风干燥总耗电1785度，以淄博地区农业用电均价0.54元\u002F度核算，总电费963.9元。折算下来，一斤小麦的干燥成本还不到4厘钱。经测算，每吨小麦每降低1个百分点水分仅耗电1.2度，较传统烘干模式优势显著。\n\n桓台县田庄镇大寨村种粮大户吕茂兴是这一技术的受益者之一。他规模种粮已有10余年，今年小麦种植面积达3200多亩。今夏麦收期间阴雨天气偏多，为了抢收抢种，吕茂兴部分地块在含水量接近20%时便进行了收割。今年年初，他联系山东长江粮油仓储机械有限公司，购置了4台第三代智慧干燥储粮仓，并配套建设了储粮仓库。\n\n“今年全靠新安装的智慧干燥储粮仓，含水量20%的小麦也敢收回家。不用晾晒，不用烘干塔加热，小麦也不会发热发霉。”吕茂兴表示。据介绍，该粮仓内部安装有多条密布通风小孔的通风管道，粮食入仓后开启鼓风机，干燥空气可通过自下而上和自上而下两种方式快速穿透粮食层，带走籽粒中的水分。第三代产品将平底仓改为锥底，使粮仓内部通风更均匀，同时加装了输送机和提升机，实现了快速倒仓，进一步加快了干燥速度。“含水量在20%的小麦，在智慧干燥储粮仓里经过倒仓和通风，四五天后就能降到安全含水量，运行成本只有烘干塔的三分之一。”\n\n6月18日，吕茂兴将第一批25吨新粮运至收粮点，经检测，水分、杂质等各项指标均合格，新麦顺利售出。\n\n此次实打测产的顺利完成，标志着“适度高水分小麦收获干燥一体化技术模式”在技术路径上已具备可复制、可推广的条件。该模式将农艺措施与仓储装备有机结合，既解决了晾晒难、储粮难的老问题，又实现了增产减损的双重目标。\n\n记者了解到，长江粮机智慧干燥储粮仓采用全封闭设计，防雨、防潮、防渗，自带防虫、防鼠、防鸟结构，全程无需高温烘干，依靠常温气流除湿，小麦色泽、面筋品质不受破坏，避免了露天晾晒带来的泥沙污染和籽粒破碎损耗。仓体配套锥底出料结构，粮食可直接装车出库，省去了装载机转运环节，进一步降低人工投入和粮食破碎损耗。\n\n对种植户而言，这套模式的增收空间不止于增产和减损。提前收割腾茬，可提早夏玉米播种时间，改善玉米生长周期，有助于实现周年粮食增产。高水分小麦收储入仓后，还可择市场高价错峰售粮，进一步拓展种植收益。\n\n当前，受制于晾晒场地不足、烘干设备投入高，农户普遍选择完熟后晚收，不仅收割阶段落粒、破碎损耗加剧，还推迟夏玉米播种窗口期。本套技术模式通过提前收割实现田间“开源”，又依托密闭智能仓储实现储藏“节流”，双向提升种植收益，为粮食收储绿色减损提供了可复制、可推广的解决方案。","农村大众\u002F大众日报 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智慧干燥储粮仓","小麦适度高水分智慧干燥储粮仓山东省农科院实打测产-284",5,"2026-08-07T23:57:49.964624Z",{"total":64,"page":21,"page_size":64,"items":65},6,[66,103,137,172,232,278],{"id":67,"title":68,"url":69,"summary":70,"summary_zh":8,"content":71,"source_name":72,"source_url":8,"published_at":73,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":74,"score_detail":75,"sources":81,"tags":83,"primary_topic":89,"secondary_topics":90,"classification":91,"search_phrases":98,"slug":101,"view_count":64,"doi":8,"paper":8,"created_at":102},1015,"山东省农业科学院作物研究所育成的济麦115等强筋小麦品种通过国家审定","https:\u002F\u002Fwww.chinaseed114.com\u002Fseed\u002F20\u002Fseed_97716.html","济麦115审定编号为国审麦20263084,由山东省农业科学院作物研究所申请并育种,品种来源为泰农18\u002F周麦16。该品种为半冬性,全生育期228.9天,比对照品种济麦22熟期稍早;幼苗半匍匐,叶片细长,叶色深绿,分蘖力较强;株高76.0厘米,株型较紧凑,抗倒性较好。穗长方形,长芒,白粒,籽粒硬质,饱满度好。平均亩穗数43.8万穗,穗粒数37.4粒,千粒重41.0克。品质检测达中强筋小麦标准。2022—2023年度参加黄淮冬麦区北片水地组育种攻关联合体区域试验,平均亩产561.1千克,比对照济麦22增产4.79%;2023—2024年度续试平均亩产599.5千克,增产4.93%;2024—2025年度生产试验平均亩产635.7千克,增产5.35%。适宜在黄淮冬麦区北片的山东省全部、河北省保定市和沧州市的南部及其以南地区、山西省运城和临汾市的盆地灌区种植。","特征特性：半冬性，全生育期228.9天，比对照品种济麦22熟期稍早。幼苗半匍匐，叶片细长，叶色深绿，分蘖力较强。株高76.0厘米，株型较紧凑，抗倒性较好，整齐度好，穗层整齐，熟相好。穗长方形，长芒，白粒，籽粒硬质，饱满度好。平均亩穗数43.8万穗，穗粒数37.4粒，千粒重41.0克。抗病性鉴定：高感纹枯病，高感赤霉病，高感叶锈病，中感条锈病，中感白粉病。抗寒性较好。品质检测：籽粒容重792克\u002F升、817克\u002F升，蛋白质含量14.1%、13.6%，湿面筋含量30.4%、29.8%，稳定时间8.6分钟、28.3分钟，吸水率59.1%、61.9%，最大拉伸阻力576Rm.E.U.、748Rm.E.U.，拉伸面积115平方厘米、130平方厘米。2022—2023年度参加黄淮冬麦区北片水地组育种攻关联合体区域试验，品质指标达到中强筋小麦标准；2023—2024年度参加黄淮冬麦区北片水地组育种攻关联合体区域试验，品质指标达到中强筋小麦标准。\n\n产量表现：2022—2023年度参加黄淮冬麦区北片水地组育种攻关联合体区域试验，平均亩产561.1千克，比对照济麦22增产4.79%；2023—2024年度续试，平均亩产599.5千克，比对照济麦22增产4.93%；2024—2025年度生产试验，平均亩产635.7千克，比对照济麦22增产5.35%。","种业商务网 2026-08-25","2026-08-25T00:00:00Z",64,{"impact":76,"substance":77,"depth":78,"authority":13,"freshness":79,"relevant":21,"comment":80},15,20,12,7,"报道山东省农科院强筋小麦新品种通过国家审定，具有省级农业科技进展价值，数据详实，但信源为行业媒体，时效性稍差。",[82],{"name":72,"url":69},[26,84,85,86,87,88],"济麦22","国家审定","济麦115","中强筋小麦","黄淮冬麦区",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[],{"status":40,"locked":14,"version":41,"method":42,"evidence":92},{"candidates":93,"agricultural_evidence":46},[94],{"code":33,"score":78,"supported":46,"title":95,"abstract":96,"tags":97},[35],[35],[84],[99,100],"山东省农科院 中强筋小麦 黄淮冬麦区 国家审定","山东省农科院 中强筋小麦","山东省农科院中强筋小麦黄淮冬麦区国家审定-1015","2026-08-28T00:07:00.118426Z",{"id":104,"title":105,"url":106,"summary":107,"summary_zh":8,"content":108,"source_name":109,"source_url":8,"published_at":110,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":111,"score_detail":112,"sources":116,"tags":118,"primary_topic":123,"secondary_topics":124,"classification":125,"search_phrases":132,"slug":135,"view_count":61,"doi":8,"paper":8,"created_at":136},819,"[山东省农科院]小麦遗传育种团队创建\"济麦家族\"——推广7亿亩、增产600多亿斤,济麦61抗5种病害","https:\u002F\u002Fwww.china.com.cn\u002Ftxt\u002F2026-08\u002F21\u002Fcontent_118658490.shtml","山东农业科学院小麦遗传育种团队创建的\"济麦家族\"30年累计推广7亿亩、增产600多亿斤。最近小麦育种专家刘建军团队实现小麦远缘杂交育种重大突破:全球首次直接利用二倍体黑麦与六倍体普通小麦杂交育成的六倍体普通小麦品种\"济麦61\",具有强筋、高产、抗逆等优良性状,兼抗5种病害。山东主要农作物良种覆盖率跃升至98%以上,良种对粮食增产贡献率达47%,2025年农业总产值迈上1.3万亿元台阶。","作物育种工作艰辛备至且周期较长。按照传统育种方式，育成一个小麦新品种大约需要花费10年时间，而构建一个小麦新品种家族更需久久为功。“‘济麦家族’由小至大，山东农业良种工程项目的持久资助功不可没。”刘建军说。\n\n1995年5月，山东启动实施山东省农业良种产业化开发工程（以下简称“良种工程”），开全国良种产业化探索之先河。首创“行政领导+首席专家”协同管理机制，起始阶段每年投入只有几百万元，“十四五”以来每年省级财政支持稳定在2亿元，迄今累计投入财政资金超24亿元。\n\n30年来，“齐鲁良种”为山东农业产业发展夯实了根基。“济麦家族”小麦累计推广7亿多亩，增产小麦600多亿斤；登海良种创造夏玉米亩产1402公斤的全国高产纪录；盐碱地玉米新品种“鲁单510”创全国高产纪录；大豆新品种“齐黄34”在3‰盐碱地亩产突破300公斤。目前，山东主要农作物良种覆盖率跃升至98%以上，良种对粮食增产贡献率达47%。\n\n30年来，山东主要粮食作物品种基本实现自给，80%的蔬菜品种实现国产化，很多育种基础研究由“跟跑”转向“领跑”，生物育种关键核心技术与装备创新也驶入“快车道”，助力该省成为全国首个农业总产值突破万亿元的省份，2025年更是迈上1.3万亿元新台阶。\n\n刘建军回忆，20世纪90年代，科研经费紧张，得益于山东良种工程一次次给予的资助，帮助课题组度过了最困难的时期。后来，随着项目资金的增加，小麦新品种的一个个问世，“济麦家族”得以发展壮大。最近，他带领团队实现了小麦远缘杂交育种的重大突破：全球首次直接利用二倍体黑麦与六倍体普通小麦杂交育成的六倍体普通小麦品种“济麦61”，具有强筋、高产、抗逆等优良性状，兼抗5种病害。","中国网 2026年8月21日","2026-08-21T00:00:00Z",86,{"impact":113,"substance":17,"depth":19,"authority":78,"freshness":114,"relevant":21,"comment":115},25,9,"报道山东小麦育种重大突破，兼具产业影响与数据支撑，权威性高，时效性强。",[117],{"name":109,"url":106},[26,119,120,121,122],"小麦育种","济麦家族","济麦61","远缘杂交",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[],{"status":40,"locked":14,"version":41,"method":42,"evidence":126},{"candidates":127,"agricultural_evidence":46},[128],{"code":33,"score":78,"supported":46,"title":129,"abstract":130,"tags":131},[35],[35],[119],[133,134],"山东省农科院 小麦育种 济麦家族 远缘杂交","山东省农科院 小麦育种","山东省农科院小麦育种济麦家族远缘杂交-819","2026-08-22T00:05:59.023453Z",{"id":138,"title":139,"url":140,"summary":141,"summary_zh":8,"content":8,"source_name":142,"source_url":8,"published_at":143,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":144,"score_detail":145,"sources":149,"tags":151,"primary_topic":158,"secondary_topics":159,"classification":160,"search_phrases":167,"slug":170,"view_count":61,"doi":8,"paper":8,"created_at":171},310,"四川省农科院作物所杨武云团队揭示弱筋小麦「川麦93」为优异制曲专用品种——高淀粉\u002F高粉质率特性赋能浓香型大曲品质","https:\u002F\u002Fweibo.com\u002F3811347182\u002F5328963539047109","四川省农科院作物所杨武云研究员团队在制曲专用小麦品种研究方面取得重要进展。研究发现团队选育的大穗高产弱筋小麦品种川麦93具有制曲工艺低敏感性,可在较低能耗条件下实现高品质大曲的稳定生产,其高淀粉含量\u002F高粉质率特性有利于优质大曲的形成。相关研究发表在Journal of Agriculture and Food Research(2026年, IF=7.2)。研究首次实现原料品种、工艺参数与大曲多维品质之间因果权重的定量分配,从根本上改变了\"制曲质量主要靠工艺调控\"的传统认知。","四川省农业科学院作物所 2026-08-05","2026-08-05T00:00:00Z",81,{"impact":77,"substance":17,"depth":19,"authority":146,"freshness":147,"relevant":21,"comment":148},13,8,"省级科研机构在制曲专用小麦品种上的重要进展，具有行业影响，信息增量高，研究结论新颖，信源权威，时效性较好。",[150],{"name":142,"url":140},[31,152,153,154,155,156,157],"四川省农科院","川麦93","制曲小麦","浓香型大曲","杨武云","JAFR",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[],{"status":40,"locked":14,"version":41,"method":42,"evidence":161},{"candidates":162,"agricultural_evidence":46},[163],{"code":33,"score":20,"supported":46,"title":164,"abstract":165,"tags":166},[35],[35],[],[168,169],"四川省农科院 浓香型大曲 制曲小麦 作物所","四川省农科院 浓香型大曲","四川省农科院浓香型大曲制曲小麦作物所-310","2026-08-08T23:53:55.626153Z",{"id":173,"title":174,"url":175,"summary":176,"summary_zh":8,"content":177,"source_name":178,"source_url":8,"published_at":179,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":180,"score_detail":181,"sources":183,"tags":185,"primary_topic":190,"secondary_topics":196,"classification":204,"search_phrases":227,"slug":230,"view_count":79,"doi":8,"paper":8,"created_at":231},285,"山东省农科院小麦遗传育种团队+中国农科院蔬菜花卉所黄瓜遗传育种课题——「新天工开物」科技成就发布会生物育种专场发布两大突破性成果","https:\u002F\u002Fwww.toutiao.com\u002Farticle\u002F7670465473477165603\u002F","7月31日,「新天工开物」科技成就发布会生物育种专场首播,聚焦我国生物育种技术领域的自主创新成就,发布山东省农业科学院作物研究所所长曹新有的「高产优质济麦新品种的选育与推广」、中国农业科学院蔬菜花卉所副所长张圣平的「黄瓜高效分子育种技术创新与应用」两项科技成就,讲述农业科技工作者为「米袋子」和「菜篮子」装上「中国芯」的科研历程。山东省农科院小麦遗传育种团队聚焦高产广适、优质强筋、抗病耐逆、营养特色四大育种方向,育成济南17、济麦22、济麦44一系列突破性小麦新品种;团队还联合中国科学院遗传与发育生物学研究所以济麦44品种为对象构建了高质量参考基因图谱,让小麦育种更加精准高效。中国农业科学院蔬菜花卉所黄瓜遗传育种课题组针对黄瓜生产上缺乏耐低温、抗病毒病品种及高通量基因分型技术欠缺等产业痛点,历时15年攻关,率先完成黄瓜近完整参考基因组组装,建成全球首个黄瓜多组学数据库,建立高效分子育种技术,育成中农脆玉3号等多个新品种。","## 为“米袋子”和“菜篮子”装上“中国芯”\n\n2026-08-06 12:28·[热点新闻](https:\u002F\u002Fwww.toutiao.com\u002Fc\u002Fuser\u002Ftoken\u002FMS4wLjABAAAAy3ixMB26SkfW_SQ4LEtANZEU7v0FrVBqsXcxQ7CSLLw\u002F?source=tuwen_detail)\n\n作品声明：内容取材于网络\n\n种子是农业现代化的基础，种业是国家战略性、基础性核心产业。“新天工开物”科技成就发布会生物育种专场活动近日首播，聚焦我国生物育种技术领域的自主创新成就“高产优质济麦新品种的选育与推广”“黄瓜高效分子育种技术创新与应用”，讲述了农业科技工作者为“米袋子”和“菜篮子”装上“中国芯”的科研历程。\n\n山东省农业科学院作物研究所所长曹新有介绍，山东省农科院小麦遗传育种团队聚焦高产广适、优质强筋、抗病耐逆、营养特色四大育种方向，育成了济南17、济麦22、济麦44一系列突破性小麦新品种。团队还联合中国科学院遗传与发育生物学研究所，以济麦44品种为对象构建了高质量参考基因图谱，让小麦育种更加精准高效。\n\n中国农业科学院蔬菜花卉所副所长张圣平介绍，针对黄瓜生产上缺乏耐低温、抗病毒病品种及高通量基因分型技术欠缺等产业痛点，团队历时15年攻关，取得系统性突破。他们率先完成黄瓜近完整参考基因组组装，建成全球首个黄瓜多组学数据库，建立高效分子育种技术，育成中农脆玉3号等多个新品种。\n\n中国作物学会秘书长、中国农业科学院作物科学研究所原党委书记刘录祥，中国园艺学会原理事长、中国农业科学院蔬菜花卉研究所原所长杜永臣分别为两项科技成就进行推介。刘录祥表示：“山东省农科院小麦育种团队走出一条中国特色小麦优质高产协同育种之路，济麦系列小麦品种为保障口粮安全、推动小麦产业高质量发展作出重大贡献。”杜永臣表示：“中国农业科学院蔬菜花卉研究所黄瓜遗传育种课题组在国内率先开展黄瓜育种技术和新品种选育研究，为我国黄瓜育种科技和产业发展作出了巨大贡献。”\n\n“新天工开物”科技成就发布会是中国科协主办的科技成就教育品牌。活动聚焦中国具有标志性、战略性、引领性的科技成就，发布技术进步、工程进展、产业进阶，推介战略科学家、一流科技领军人才和卓越工程师等，传播科学家精神、科学精神，彰显新型举国体制优势，服务科技强国建设。\n\n来源：人民网","人民网\u002F中国日报 2026-08-06","2026-08-06T00:00:00Z",79,{"impact":113,"substance":19,"depth":76,"authority":78,"freshness":114,"relevant":21,"comment":182},"报道农业生物育种重大突破，涉及小麦和黄瓜新品种，影响全国，信息详实，来源权威，时效性好。",[184],{"name":178,"url":175},[186,26,84,187,188,189],"生物育种","中农脆玉3号","新天工开物","中国农科院蔬菜花卉所",{"code":191,"slug":192,"name":193,"path":194,"parent_code":195},"B1","vegetables","蔬菜","\u002Ftopic\u002Fhorticulture\u002Fvegetables","B",[197,203],{"code":198,"slug":199,"name":200,"path":201,"parent_code":202},"F2","biotechnology","生物育种与基因技术","\u002Ftopic\u002Finputs-equipment\u002Fbiotechnology","F",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},{"status":40,"locked":14,"version":41,"method":42,"evidence":205},{"candidates":206,"agricultural_evidence":46},[207,212,217,221],{"code":191,"score":17,"supported":46,"title":208,"abstract":210,"tags":211},[193,209],"黄瓜",[193,209],[],{"code":198,"score":76,"supported":46,"title":213,"abstract":214,"tags":216},[186],[186,215],"分子育种",[186],{"code":33,"score":78,"supported":46,"title":218,"abstract":219,"tags":220},[35],[35],[84],{"code":222,"score":20,"supported":46,"title":223,"abstract":225,"tags":226},"B4",[224],"花卉",[224],[],[228,229],"中国农科院蔬菜花卉所 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山东省农科院","中国农科院蔬菜花卉所山东省农科院中农脆玉3号新天工开物-285","2026-08-07T23:57:49.984407Z",{"id":233,"title":234,"url":235,"summary":236,"summary_zh":8,"content":237,"source_name":238,"source_url":8,"published_at":239,"category":12,"cover_url":8,"hotness":13,"is_selected":46,"score":240,"score_detail":241,"sources":243,"tags":245,"primary_topic":249,"secondary_topics":250,"classification":253,"search_phrases":273,"slug":276,"view_count":19,"doi":8,"paper":8,"created_at":277},141,"为\"米袋子\"和\"菜篮子\"装上\"中国芯\"——\"新天工开物\"科技成就发布会生物育种专场,山东省农科院+中国农科院蔬菜花卉所分别发布济麦系列小麦与黄瓜分子育种技术","https:\u002F\u002Fso.html5.qq.com\u002Fpage\u002Freal\u002Fsearch_news?docid=70000021_8626a6c6bd473252","7月31日,\"新天工开物\"科技成就发布会生物育种专场首播。山东省农业科学院作物研究所所长曹新有发布\"高产优质济麦新品种的选育与推广\":济麦系列小麦新品种聚焦高产广适、优质强筋、抗病耐逆、营养特色四大育种方向,联合中国科学院遗传与发育生物学研究所构建了济麦44高质量参考基因图谱。中国农业科学院蔬菜花卉所副所长张圣平发布\"黄瓜高效分子育种技术创新与应用\":针对黄瓜生产上缺乏耐低温、抗病毒病品种及高通量基因分型技术欠缺等痛点,历时15年攻关,率先完成黄瓜近完整参考基因组组装,建成全球首个黄瓜多组学数据库,建立高效分子育种技术,育成中农脆玉3号等多个新品种。","种子是农业现代化的基础，种业是国家战略性、基础性核心产业。7月31日，“新天工开物”科技成就发布会生物育种专场首播。本场发布会聚焦我国生物育种技术领域的自主创新成就，由山东省农业科学院作物研究所所长曹新有、中国农业科学院蔬菜花卉所副所长张圣平分别发布“高产优质济麦新品种的选育与推广”“黄瓜高效分子育种技术创新与应用”两项科技成就，讲述了他们为“米袋子”和“菜篮子”装上“中国芯”的科研历程。\n\n曹新有在发布中介绍，山东省农科院小麦遗传育种团队聚焦高产广适、优质强筋、抗病耐逆、营养特色四大育种方向，育成了济南17、济麦22、济麦44一系列突破性小麦新品种。团队还联合中国科学院遗传与发育生物学研究所，以济麦44品种为对象构建了高质量参考基因图谱，让小麦育种更加精准高效。\n\n张圣平在发布中介绍，针对黄瓜生产上缺乏耐低温、抗病毒病品种及高通量基因分型技术欠缺等产业痛点，团队历时15年攻关，取得系统性突破。他们率先完成黄瓜近完整参考基因组组装，建成全球首个黄瓜多组学数据库，建立高效分子育种技术，育成中农脆玉3号等多个新品种。\n\n上述两项成就由中国作物学会、中国园艺学会分别推荐。中国作物学会秘书长、中国农业科学院作物科学研究所原党委书记刘录祥，中国园艺学会原理事长、中国农业科学院蔬菜花卉研究所原所长杜永臣分别为两项科技成就进行推介。\n\n刘录祥表示：“山东省农科院小麦育种团队走出一条中国特色小麦优质高产协同育种之路，济麦系列小麦品种为保障口粮安全、推动小麦产业高质量发展作出重大贡献。”\n\n杜永臣表示：“中国农业科学院蔬菜花卉研究所黄瓜遗传育种课题组在国内率先开展黄瓜育种技术和新品种选育研究，为我国黄瓜育种科技和产业发展作出了巨大贡献。”\n\n发布会后还举行了科技成就数字展品入藏仪式，所发科技成就作为入藏资源纳入科技成就展数字展品库。\n\n“新天工开物”科技成就发布会是中国科协主办的科技成就教育品牌。活动聚焦中国具有标志性、战略性、引领性的科技成就，发布技术进步、工程进展、产业进阶，推介战略科学家、一流科技领军人才和卓越工程师等，传播科学家精神、科学精神，彰显新型举国体制优势，服务科技强国建设。（光明网记者宋雅娟）","光明网 2026-07-31","2026-07-31T00:00:00Z",89,{"impact":113,"substance":17,"depth":19,"authority":76,"freshness":114,"relevant":21,"comment":242},"国家级科研机构发布生物育种重大突破，涉及小麦和黄瓜分子育种，信息详实，权威性高，时效性强。",[244],{"name":238,"url":235},[246,186,26,247,248],"中国农科院","济麦","黄瓜分子育种",{"code":191,"slug":192,"name":193,"path":194,"parent_code":195},[251,252],{"code":198,"slug":199,"name":200,"path":201,"parent_code":202},{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},{"status":40,"locked":14,"version":41,"method":42,"evidence":254},{"candidates":255,"agricultural_evidence":46},[256,261,265,269],{"code":198,"score":257,"supported":46,"title":258,"abstract":259,"tags":260},23,[186,215],[186,215],[186],{"code":191,"score":17,"supported":46,"title":262,"abstract":263,"tags":264},[193,209],[193,209],[],{"code":33,"score":20,"supported":46,"title":266,"abstract":267,"tags":268},[35],[35],[],{"code":222,"score":20,"supported":46,"title":270,"abstract":271,"tags":272},[224],[224],[],[274,275],"山东省农科院 黄瓜分子育种 中国农科院 生物育种","山东省农科院 黄瓜分子育种","山东省农科院黄瓜分子育种中国农科院生物育种-141","2026-08-01T06:01:54.292634Z",{"id":279,"title":280,"url":281,"summary":282,"summary_zh":283,"content":8,"source_name":284,"source_url":281,"published_at":285,"category":286,"cover_url":8,"hotness":13,"is_selected":14,"score":287,"score_detail":288,"sources":293,"tags":295,"primary_topic":301,"secondary_topics":302,"classification":314,"search_phrases":353,"slug":356,"view_count":357,"doi":358,"paper":359,"created_at":379},5558,"Estimation of Soil Water Content in Winter Wheat Field at Jointing Stage Using Multi-Source Features and Machine Learning","https:\u002F\u002Fdoi.org\u002F10.3390\u002Fagronomy16202071","Accurate and timely monitoring of soil water content (SWC) plays an essential supporting role in crop irrigation management and smart agricultural practice. Remote sensing technology provides rapid and convenient approaches to large-scale farmland SWC estimation or inversion. However, existing mechanistic modeling methods are limited by parameter localization and land surface heterogeneity, while machine learning data-driven methods lack quite good physical interpretability. To address deficiencies in single data-driven methods and single vegetation microwave scattering models, and explore the estimation effect of different feature variables in machine learning. This study proposes an innovative estimation model that integrates machine learning strategies and multi-source features, including spectral indices and features derived from the classic water cloud model (WCM). The novelty of the proposed model lies in balancing physical interpretability and data-driven accuracy, namely extracting relevant soil backscattering parameters through WCM, which are then used as input features in the machine learning. A combination of field-measured data and unmanned aerial vehicle (UAV) multi-source remote sensing data, including multispectral and synthetic aperture radar (SAR) data, was acquired synchronously at the jointing stage of winter wheat. Through extracting variables such as the SAR microwave backscattering coefficient and the optical vegetation index, and conducting feature screening and parameter sensitivity analysis, we optimized the input variable sets of models based on back-propagation (BP) neural network, support vector regression (SVR) and random forest (RF) algorithms. The study results showed that the established estimation model had excellent estimation performance, especially for the RF algorithm, with the highest R2 of 0.855, lowest MAE of 0.0212 cm3\u002Fcm3, and lowest RMSE of 0.0253 cm3\u002Fcm3. It was also shown that different feature input schemes have obvious effects on SWC estimation performance. On the whole, RF had the best estimation accuracy, followed by SVR and then BPNN. This study demonstrated that models integrating multi-source remote sensing data and machine learning could enhance SWC estimation ability for winter wheat fields, and could also serve as a promising approach for SWC monitoring in winter wheat fields in the North China Plain.","准确、及时地监测土壤含水量（SWC）对作物灌溉管理和智慧农业实践具有重要的支撑作用。遥感技术为大规模农田土壤含水量估算或反演提供了快速便捷的手段。然而，现有机理建模方法受参数本地化和地表异质性限制，机器学习数据驱动方法则缺乏良好的物理解释性。针对单一数据驱动方法和单一植被微波散射模型的不足，并探究不同特征变量在机器学习中的估算效果，本研究提出了一种融合机器学习策略与多源特征的创新估算模型，所采用特征包括光谱指数和经典水云模型（WCM）衍生的特征。该模型的新颖性在于平衡物理解释性与数据驱动精度，即通过WCM提取相关土壤后向散射参数，再将其作为机器学习的输入特征。研究在冬小麦拔节期同步获取了田间实测数据与无人机（UAV）多源遥感数据，包括多光谱和合成孔径雷达（SAR）数据。通过提取SAR微波后向散射系数和光学植被指数等变量，并进行特征筛选和参数敏感性分析，优化了基于反向传播（BP）神经网络、支持向量回归（SVR）和随机森林（RF）算法的模型输入变量集。研究结果表明，所建立的估算模型具有优良的估算性能，尤其是RF算法，最高R²为0.855，最低MAE为0.0212 cm³\u002Fcm³，最低RMSE为0.0253 cm³\u002Fcm³。研究还表明，不同特征输入方案对土壤含水量估算性能有明显影响。总体而言，RF估算精度最佳，SVR次之，BPNN再次之。本研究证明，融合多源遥感数据与机器学习的模型能够提升冬小麦田土壤含水量估算能力，也可为华北平原冬小麦田土壤含水量监测提供一种有前景的方法。","Agronomy","2026-10-21T00:00:00Z","论文",77,{"impact":289,"substance":290,"depth":291,"authority":146,"freshness":13,"relevant":21,"comment":292},16,21,17,"该研究融合多源遥感与机器学习估算冬小麦拔节期土壤含水量，方法有创新、结论可靠，对智慧灌溉有参考价值，但属细分领域论文，影响范围有限。",[294],{"name":284,"url":281},[296,297,298,299,300],"智慧农业","机器学习","遥感监测","土壤墒情","冬小麦",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[303,308],{"code":51,"slug":304,"name":305,"path":306,"parent_code":307},"soil","土壤健康与改良","\u002Ftopic\u002Fenvironment\u002Fsoil","H",{"code":309,"slug":310,"name":311,"path":312,"parent_code":313},"I2","agricultural-ai","农业AI与大模型","\u002Ftopic\u002Fdigital-agriculture\u002Fagricultural-ai","I",{"status":40,"locked":14,"version":41,"method":42,"evidence":315},{"candidates":316,"agricultural_evidence":46},[317,323,327,332,340,347],{"code":33,"score":318,"supported":46,"title":319,"abstract":321,"tags":322},26,[320,34],"winter wheat",[35,320,34],[300],{"code":51,"score":76,"supported":46,"title":324,"abstract":325,"tags":326},[304],[55,304],[299],{"code":309,"score":76,"supported":46,"title":328,"abstract":330,"tags":331},[329],"machine learning",[297,329],[297],{"code":333,"score":13,"supported":46,"title":334,"abstract":335,"tags":339},"I3",[],[336,337,338],"遥感","remote sensing","multispectral",[298],{"code":341,"score":64,"supported":46,"title":342,"abstract":343,"tags":346},"H3",[],[344,345],"灌溉","irrigation",[],{"code":348,"score":349,"supported":46,"title":350,"abstract":351,"tags":352},"I1",4,[],[296],[296],[354,355],"冬小麦 土壤含水量 遥感","多源遥感 机器学习 墒情","冬小麦土壤含水量遥感-5558",0,"10.3390\u002Fagronomy16202071",{"doi":358,"openalex_id":360,"authors":361,"venue":284,"cited_by_count":357,"oa_url":281,"card":371,"direction":377,"ingested_from":378},"W7223156204",[362,365,367,369],{"name":363,"orcid":364},"Mingliang Jiang","https:\u002F\u002Forcid.org\u002F0000-0002-6486-6087",{"name":366,"orcid":8},"Yi Zhang",{"name":368,"orcid":8},"WEI Lei",{"name":370,"orcid":8},"Chengcai Zhang",{"tldr":372,"method":373,"finding":374,"direction":375,"opportunity":376},"融合WCM物理特征与多源遥感，用机器学习估算冬小麦拔节期土壤含水量。","无人机多光谱与SAR数据，WCM参数+光谱指数，BP\u002FSVR\u002FRF建模。","RF最优，R²达0.855，RMSE为0.0253 cm³\u002Fcm³，特征方案影响显著。","农业遥感与作物表型","可探索物理约束与深度学习耦合，并迁移至多生育期、多作物及不同土壤质地验证。","智慧农业 \u002F 农业物联网","openalex","2026-10-22T11:20:18.887301Z"]