[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-4456":3,"related-4456":77},{"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":32,"secondary_topics":38,"classification":45,"search_phrases":71,"slug":74,"view_count":75,"doi":8,"paper":8,"created_at":76},4456,"农业农村部发布2026小麦秋冬种技术要点 培育冬前壮苗夯实夏粮丰收基础","https:\u002F\u002Fwww.163.com\u002Fdy\u002Farticle\u002FL8CUSJ610532ADW5.html","农业农村部发布2026小麦秋冬种技术要点，针对今年气候条件指出秋分过后主产区大部气温偏高、墒情良好，但受强厄尔尼诺事件影响秋冬春气象条件不确定性增大；黄淮海中北部麦区半冬性品种适宜播期10月初至10月15日，南部麦区10月15—25日；强调精选优良品种、合理施肥、提高整地质量、实施四适播种技术、全面推行种子包衣与药剂拌种技术。",null,"[![Image 8](https:\u002F\u002Fwww.163.com\u002Fdy\u002Farticle\u002FL8CUSJ610532ADW5.html)](javascript:void(0))\n\n[网易首页](https:\u002F\u002Fwww.163.com\u002F \"网易首页\")\n\n[应用](https:\u002F\u002Fwww.163.com\u002F#f=topnav)\n\n*   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[举报](https:\u002F\u002Fwww.163.com\u002Fspecial\u002F0077jt\u002Ftipoff.html?title=%E9%BA%A6%E6%92%AD%E5%9C%A8%E5%8D%B3%EF%BC%812026%E5%B0%8F%E9%BA%A6%E7%A7%8B%E5%86%AC%E7%A7%8D%E6%8A%80%E6%9C%AF%E8%A6%81%E7%82%B9%EF%BC%8C%E8%AF%B7%E6%94%B6%E5%A5%BD)\n\n[](https:\u002F\u002Fwww.163.com\u002Fdy\u002Farticle\u002FL8CUSJ610532ADW5.html#post_comment_area \"快速发贴\")[0](https:\u002F\u002Fcomment.tie.163.com\u002FL8CUSJ610532ADW5.html \"点击查看跟贴\")\n\n分享至\n*   [](javascript:;)\n*   [](javascript:;)\n*   [](javascript:;)\n\n[](javascript:; \"关闭\")\n\n![Image 11: Scan me!](blob:http:\u002F\u002Flocalhost\u002F6570a9b09c1ff3c4ca1a0f82eede8515)\n\n用微信扫码二维码\n\n分享至好友和朋友圈\n\n![Image 12](https:\u002F\u002Fnimg.ws.126.net\u002F?url=http%3A%2F%2Fdingyue.ws.126.net%2F2026%2F1004%2F5e8b832cj00tmd1rv002od200kp005lg00kp005l.jpg&thumbnail=660x2147483647&quality=80&type=jpg)\n\n秋分过后，小麦秋冬种即将展开。目前全国主产区气温整体较常年偏高，大部墒情良好，小麦种子供应充足，前茬作物预计可正常收获腾茬，秋冬种总体形势较为有利。但受强厄尔尼诺事件影响，秋冬春气象条件不确定性增大，冬前温高旺长、阶段性低温冻害、秋冬春干旱等风险较偏高。针对今年小麦秋冬种生产形势，各地需立足抗灾夺丰收，以培育冬前壮苗为目标，以提高播种质量为重点，以适墒适期适量适深“四适”为主线，加强冬前田间管理和防灾减灾，夯实明年夏粮丰收基础。\n\n**一、黄淮海麦区**\n\n**（一）精选优良品种，优化品种布局。**坚持抗逆稳产优先的品种选用原则，结合区域生产条件、产量水平、历年灾害发生规律及品种综合特性，依托试验示范结果科学筛选适宜优良品种。严格遵循“地力与产量匹配、熟期与播期匹配、抗性与灾情匹配”的布局原则，确定区域主导品种，持续优化品种种植结构。全面推行种子包衣、药剂拌种技术，最大限度降低“白籽”下地比例。针对今年部分种子田收获期遇雨、可能导致种子发芽率下降的问题，全覆盖开展备播种子质量检测，坚决杜绝不合格种子下地播种。\n\n![Image 13](https:\u002F\u002Fnimg.ws.126.net\u002F?url=http%3A%2F%2Fdingyue.ws.126.net%2F2026%2F1004%2F9703cad8j00tmd1rv000kd200b4007eg00hp00br.jpg&thumbnail=660x2147483647&quality=80&type=jpg)\n\n**（二）合理施肥，提高整地质量。**精细深耕打破犁底层，促进深层水分和养分吸收利用，提高抗逆、抗倒能力。秸秆还田地块着力做好秸秆粉碎、撒匀、压实。耕深达到25厘米以上，旋耕地块要求旋耕两遍以上，旋耕深度15厘米以上。无论深耕或旋耕田块，耕后均需耙实耙平，防止土壤喧虚播种，造成播种过深，影响出苗和培育壮苗。根据土壤质地、耕层养分含量和目标产量按需配方施肥。旱地麦田一次施足底肥，春季视苗情趁墒追肥，支持新型农业经营主体因地制宜推广应用水肥一体化技术。\n\n**（三）实施“四适”播种技术，确保一播全苗匀苗。**适期播种是培育冬前壮苗的核心关键，各地需依据天气情况、土壤墒情、品种特性等条件，合理确定适宜播期，其中黄淮海中北部麦区半冬性品种适宜播期10月初至10月15日，南部麦区10月15—25日；严禁前茬收获偏早的地块过早播种，晚于适播期的田块应推广“四补一促”技术。根据播期适度调整基本苗，一般每晚播2—3天可亩增1万—2万基本苗，但最多不宜超过30万。0—20厘米耕层土壤相对含水量保持75%左右时，适墒播种，有利于全苗、齐苗；在小麦适播期下限范围内，应坚持“播期服从墒情”的原则，对墒情不足的麦田应提前浇水造墒，若播种期间遇阴雨天气造成土壤过湿，要及时开沟沥湿散墒，确保适墒播种。一般播种深度3—5厘米，要大力推广播前播后双镇压，选用带镇压装置的播种机械进行播种，做到随种随压。\n\n**（四）强化冬前管理，育壮苗安全越冬。**冬前镇压可提高小麦抗逆能力，防止冬季冻害。要根据苗情、墒情和气温等条件综合判断，镇压做到“压干不压湿、压软不压硬、压轻不压重”。对整地粗放、坷垃较多、秸秆还田量大、土壤暄松的地块，要适时开展镇压作业。要依据土壤墒情和小麦苗情抓好冬前肥水管理。对地力较差、底肥施用不足，有缺肥症状的麦田，趁墒或浇水追肥；晚播弱苗要早促早管；对土壤墒情适宜、群体偏大、有旺长趋势的麦田，应及时采取镇压措施，控制旺长。坚持“春草秋治”防控策略，抓住冬前麦田化除的有利时机，根据田间草相和气温条件选择药剂，在小麦3—5叶期、杂草2—4叶期，用药前后3天日均温6℃以上，且无霜冻和降雨的晴天进行，做到不重喷不漏喷，防止出现药害。对于土壤墒情较差，特别是秸秆还田、土壤悬空不实且吊根苗多的麦田必须采取镇压和冬灌等防冻保墒措施，保苗安全越冬。冬灌要在土壤封冻前、日均温降至3℃左右开始，到夜冻昼消时结束。\n\n![Image 14](https:\u002F\u002Fnimg.ws.126.net\u002F?url=http%3A%2F%2Fdingyue.ws.126.net%2F2026%2F1004%2F790392e0j00tmd1rv000yd200dw009dg00hp00bx.jpg&thumbnail=660x2147483647&quality=80&type=jpg)\n\n**二、长江中下游麦区**\n\n**（一）结合区域备好种，适时收获调好墒。**按照市场化导向、区域化布局、规模化种植、标准化生产和周年粮食高产高效的要求，合理规划优质专用小麦品种的适宜种植区域，重点推广抗湿、抗倒、抗病（主要是赤霉病、白粉病、纹枯病）性强、黑胚率低、抗穗发芽、商品性好的优质高产中筋、弱筋小麦品种，部分地区可选用优质强筋小麦品种，播前选用种衣剂进行种子包衣或药剂拌种。不同区域结合土壤类型在水稻收割前10—15天开始断水晾田，促进水稻成熟和土壤散墒。以小麦播种时耕层土壤“手捏成团、落地即散”为适宜播种、一播全苗墒情标准。水稻收割后及时进行秸秆粉碎（长度≤10cm）匀抛还田，根据土壤墒情与天气条件适时整地，提升整地质量，为适期播种创造良好墒情条件。前茬收获前后如遇降雨应及时开沟，加速排水，减轻渍水对秋播的影响，旱茬地区小麦播种前墒情不足时应浇水造墒播种。\n\n**（二）精细整地保全苗，精准播种育壮苗。**秸秆优先打捆离田，留茬高度≤10厘米；秸秆还田地块，收割机加装秸秆粉碎抛洒装置，碎草长度控制在5厘米左右；整地坚持“深、碎、细、平、实”，耕翻后要及时机耙或旋耕细整，要控制机械行进速度，切实提高秸秆还田与整地质量。播种作业后未开“三沟”（畦沟、腰沟、田头沟）的田块及时机械开沟，确保三沟相通，排灌通畅、降渍防旱。坚持播期服从墒情原则，长江中游的北部地区适宜播期为10月15日至30日，南部地区适宜播期为10月25日至11月10日；坚持播量与播期匹配、宁稀勿稠与晚播增量原则，结合种子质量、土壤墒情及播种质量等因素综合确定播种量，适期播种条件下大面积生产亩基本苗控制在15万—18万，高产创建田亩基本苗控制在12万—15万；抢墒早播，应降低播量；随播期推迟，播种量适当增加，每推迟2天，亩播种量增加0.5公斤左右，但最高基本苗不宜超过预期穗数的90%。坚持播深与墒情匹配、宁浅勿深原则。稻茬小麦播深以2—3厘米为宜，旱茬小麦播深以3—4厘米为宜。播后及时镇压，紧实土壤、压碎土块，确保种子与土壤密接，提高小麦抗旱抗冻能力。\n\n**（三）精准施肥提质增效，精确防灾保产减损。**亩产500公斤左右的中筋和强筋小麦，亩施纯氮14—16公斤，基苗肥占60%，拔节孕穗肥占40%。根据土壤基础地力水平，氮磷钾配比宜为1:（0.4—0.6）:（0.4—0.6），磷钾肥以基肥:拔节肥5:5为宜。推介缓控肥、生物有机肥等新型高效肥料的配合施用。秸秆还田量大的田尤其要注意施足基肥，基肥不足的要早施苗肥，基苗肥应达到计划总施肥量的60%左右，推广种肥同播方式和无人机施肥方式。对于杂草较多地块，播种至苗期可进行播后封闭除草。冬春季节根据田间草情、天气和墒情再适度化除。对有旺长趋势的麦田，可在冬前进行镇压或喷施化控剂，预防冻害。密切关注天气变化，对墒情较差、悬根苗麦田，以及耕种粗放、坷垃较多及秸秆还田地块适时浇水促壮。\n\n**三、西南麦区**\n\n**（一）优化品种布局，强化种子处理。**基于西南冬麦区特定气候生态条件、面临的主要障碍因素和市场需求，进一步扩大抗病抗逆高产品种的种植面积，选用耐低温冷害和抗穗发芽的品种，云南、四川旱地小麦要选用耐旱耐瘠品种。加大优质专用品种如膨化品种、酿酒制曲品种的示范转化力度，积极推进订单种植。针对性开展种子包衣或药剂拌种，以控制蚜虫、黄花叶病毒病、茎基腐病等，杜绝“白籽”下种。\n\n![Image 15](https:\u002F\u002Fnimg.ws.126.net\u002F?url=http%3A%2F%2Fdingyue.ws.126.net%2F2026%2F1004%2F718b1349j00tmd1rv001zd200m800cjg00hp009z.jpg&thumbnail=660x2147483647&quality=80&type=jpg)\n\n**（二）开沟排水降渍，科学处置秸秆。**针对稻麦两熟区，加强水稻生育后期的水分管理，灌浆后期及时开沟排水。收获后要立即开沟，且必须做到沟沟相通、田内水沟与田外沟渠相通，最大限度排干沥尽田间积水。部分丘陵旱地要根据地势适当开沟降湿。结合前茬收获方式和小麦播种方式综合处理秸秆，对下茬拟采取免耕栽培或翻耕埋草的田块，应优先选择切草或碎草抛撒模式，采用免耕露播稻草覆盖栽培的田块最好留长秸秆，便于高效盖种作业。对丘陵地区机械或人工收获玉米果穗的田块，可视土壤墒情选择不同的秸秆处理方式；墒情适宜拟旋耕作业的田块，应先行灭茬再旋耕埋草；有立茬播种机的农户，可以直接进行立茬播种而无需再处理秸秆。\n\n**（三）合理耕作，高质量播种。**适宜耕作的地块，可适时进行深耕碎土，深埋秸秆（不低于15厘米），耙平压实，创造良好播种环境。对于常年黏湿的稻茬麦田和部分黏湿的旱地，尽量采取免耕带旋播种方式以实现免耕覆盖栽培，既能高质量立苗，又能提高保墒抗旱能力，一定程度缓解西南冬干春旱问题。西南地域广阔，海拔差异较大，播期从云南南部的9月中旬持续到四川盆地南部的11月中旬，其中11月上旬是较为稳定的高产播期，最迟不宜晚于11月15日。适期播种的小麦，以每亩基本苗15—20万为宜，最高亩基本苗不宜超过25万，早播田块基本苗可适度调减，晚播田块基本苗可适度调增。\n\n**（四）强化冬前管理，培育壮苗。**因种子质量、耕作粗放、肥料施用不当、撒播遭遇持续高温或土壤过湿等因素，造成缺苗断垄地块，及时查苗补缺，进行局部补种甚至全田重播。种子萌发出苗阶段对水分十分敏感，要注意遇旱浇水，促进出苗全苗。对出现渍害的地块要排湿降渍，并少量多次追施速效肥。对播种时没有开展封闭除草的麦田，应在苗期进行化学除草。对播种时没有施底肥的麦田，应在出苗后1周左右，及时施肥。施肥量按既定全生育期用量的60%—70%（氮肥）、80%—100%（磷钾肥）施用。\n\n**四、西北麦区**\n\n**（一）选好适宜品种，抓实种子处理。**根据品种审定适宜区域、当地水热条件和灌溉保障能力选种，旱地突出抗旱抗寒、稳产耐瘠，水浇地兼顾节水高产、抗倒抗病。高寒及冻害易发麦区优先选用经当地验证的抗寒冬性品种，严格把握半冬性品种适种范围，避免盲目跨区引种。播前精选种子，检查发芽率、发芽势和千粒重，依据种子质量核定用种量。针对当地主要种传、土传病害和地下害虫，选用已登记用于小麦相应防治对象和施用方式的药剂包衣或拌种。\n\n**（二）抓好耕整镇压，提高播种质量。**统筹前茬收获、秸秆处理和整地播种，适收地块及时腾茬。旱地以保墒为重点，对已完成夏闲期蓄墒耕作的地块减少反复翻动；秋茬田抓住适墒窗口，衔接灭茬、施肥、耕整作业。秸秆还田地块要粉碎均匀、分散混埋。对犁底层明显、连年浅旋的田块，结合耕层厚度和墒情进行深耕或深松，并耙平压实，避免只松不压、透风失墒。播前土壤过于暄松的地块先适度镇压，播种配套镇压装置，促进种土密接。土壤过湿时先排水散墒，达到适耕条件后作业，防止湿土碾压板结和烂耕烂种。\n\n**（三）统筹播期播量，落实精量播种。**依据当地适播窗口、品种冬春性、土壤墒情和近期天气预报确定播期。对温度偏高、墒情适宜且生长期较充足的麦区，可在适播期内适当推迟播种，防止过早下种形成旺苗；高寒、早霜风险较高及适播期较短的麦区，要抓住适墒时机适时播种，陕西渭北旱地、甘肃高海拔麦区和新疆北疆等地，要防止待墒、等茬挤占时间。要根据目标基本苗、千粒重、发芽率和田间出苗率计算播量。对晚播地块，结合积温和品种分蘖能力适度增加基本苗，防止盲目加量形成稠弱苗。按地块条件配套宽幅匀播、探墒沟播或与滴灌带匹配的宽窄行播种；播深一般掌握3—5厘米，保持深浅一致。\n\n![Image 16](https:\u002F\u002Fnimg.ws.126.net\u002F?url=http%3A%2F%2Fdingyue.ws.126.net%2F2026%2F1004%2F5772236cj00tmd1rw0012d200eu00adg00hp00cc.jpg&thumbnail=660x2147483647&quality=80&type=jpg)\n\n**（四）坚持以墒定播，强化节水保苗。**旱作麦区加强表层与耕层墒情检查，有墒及时播，墒情不足时采取保墒耕作、探墒沟播等措施。具备灌溉条件的缺墒田块，提前协调水源、检修设施，实行测墒补灌造墒。新疆等滴灌条件成熟、水源有保障的麦田，可应用干播湿出技术，播种与铺带、供水同步衔接，播后及时滴水，确保各播种行湿润均匀。陕西等有秋淋风险地区提前疏通田间排水通道，雨后及时排湿散墒，利用短时适播窗口提高作业效率。因连阴雨晚播的地块，配套适宜机具和晚播补偿措施，以播种质量保障出苗质量。\n\n**（五）加强田间管理，防旺抗旱防冻。**出苗后及时查苗，对缺苗断垄地段尽早用同一品种补种；播后遇雨形成板结的，适墒破除板结，帮助出苗。加强秋苗调查，陇南及周边条锈病菌源区及时清除自生麦苗，发现发病中心迅速组织防治，减少菌源扩散；关中等地重点监测茎基腐病、地下害虫和苗蚜，黄矮病发生区注意传毒蚜虫防控，新疆相关麦区做好雪霉雪腐等病害预防。根据草相、草龄和小麦叶龄选择适宜除草剂，在药剂要求的温度、墒情条件下用药。缺肥弱苗趁有效降水或结合灌溉适量追肥，旺苗控制肥水并适墒镇压。缺墒且有灌溉条件的麦田，结合苗情和降温过程及时浇越冬水，做到灌后及时下渗、地面不积水，避免封冻后灌水结冰伤苗；墒情充足地块要合理减灌或免灌，确保苗情安全越冬。\n\n![Image 17](https:\u002F\u002Fnimg.ws.126.net\u002F?url=http%3A%2F%2Fdingyue.ws.126.net%2F2026%2F1004%2F51816c0cg00tmd1rw0304d200i200krg00i200kr.gif&thumbnail=660x2147483647&quality=80&type=gif)\n\n**编辑**｜李紫来**审核**｜赵允\n\n**来源**｜农业农村部、全国农业技术推广服务中心\n\n![Image 18](https:\u002F\u002Fnimg.ws.126.net\u002F?url=http%3A%2F%2Fdingyue.ws.126.net%2F2026%2F1004%2F2e695dfaj00tmd1rx0020d200u000dbg00it008c.jpg&thumbnail=660x2147483647&quality=80&type=jpg)\n\n特别声明：以上内容(如有图片或视频亦包括在内)为自媒体平台“网易号”用户上传并发布，本平台仅提供信息存储服务。\n\nNotice: The content above (including the pictures and videos if any) is uploaded and posted by a user of NetEase Hao, which is a social media platform and only provides information storage services.\n\n[![Image 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[711关闭印度全部门店](https:\u002F\u002Fwww.163.com\u002Fdy\u002Farticle\u002FL8N729BU05345ARG.html?f=post2020_dy_recommends)\n\n扬子晚报 2026-10-08 09:45:30\n\n[1446 _跟贴_ 1446](https:\u002F\u002Fwww.163.com\u002Fdy\u002Farticle\u002FL8N729BU05345ARG.html?f=post2020_dy_recommends) \n*   [![Image 31](https:\u002F\u002Fnimg.ws.126.net\u002F?url=http:\u002F\u002Fdingyue.ws.126.net\u002F2026\u002F1008\u002F7515b50fj00tmktdc004hd000u0018zg.jpg&thumbnail=140y88&quality=80&type=jpg)](https:\u002F\u002Fwww.163.com\u002Fdy\u002Farticle\u002FL8NPJJMP0514R9P4.html?f=post2020_dy_recommends)### [浙江小百花越剧院致歉：因李云霄身体原因，《九斤姑娘》武汉演出延期](https:\u002F\u002Fwww.163.com\u002Fdy\u002Farticle\u002FL8NPJJMP0514R9P4.html?f=post2020_dy_recommends)\n\n澎湃新闻 2026-10-08 15:04:09\n\n[99 _跟贴_ 99](https:\u002F\u002Fwww.163.com\u002Fdy\u002Farticle\u002FL8NPJJMP0514R9P4.html?f=post2020_dy_recommends) \n*   [![Image 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旱作所 玉米密植","小麦秋冬种 技术培训","河北旱作所玉米密植-4631","2026-10-11T00:09:41.871761Z",{"id":260,"title":261,"url":262,"summary":263,"summary_zh":264,"content":8,"source_name":265,"source_url":262,"published_at":266,"category":267,"cover_url":8,"hotness":13,"is_selected":14,"score":268,"score_detail":269,"sources":272,"tags":274,"primary_topic":279,"secondary_topics":280,"classification":293,"search_phrases":329,"slug":332,"view_count":75,"doi":333,"paper":334,"created_at":354},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":90,"substance":270,"depth":19,"authority":158,"freshness":13,"relevant":22,"comment":271},21,"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。",[273],{"name":265,"url":262},[275,276,277,278,99],"智慧农业","机器学习","遥感监测","土壤墒情",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[281,287],{"code":282,"slug":283,"name":284,"path":285,"parent_code":286},"H2","soil","土壤健康与改良","\u002Ftopic\u002Fenvironment\u002Fsoil","H",{"code":288,"slug":289,"name":290,"path":291,"parent_code":292},"I2","agricultural-ai","农业AI与大模型","\u002Ftopic\u002Fdigital-agriculture\u002Fagricultural-ai","I",{"status":46,"locked":14,"version":47,"method":48,"evidence":294},{"candidates":295,"agricultural_evidence":53},[296,301,306,311,319,324],{"code":33,"score":17,"supported":53,"title":297,"abstract":299,"tags":300},[298,34],"winter wheat",[35,298,34],[99],{"code":282,"score":91,"supported":53,"title":302,"abstract":303,"tags":305},[283],[304,283],"土壤",[278],{"code":288,"score":91,"supported":53,"title":307,"abstract":309,"tags":310},[308],"machine learning",[276,308],[276],{"code":312,"score":13,"supported":53,"title":313,"abstract":314,"tags":318},"I3",[],[315,316,317],"遥感","remote sensing","multispectral",[277],{"code":244,"score":21,"supported":53,"title":320,"abstract":321,"tags":323},[],[247,322],"irrigation",[],{"code":325,"score":125,"supported":53,"title":326,"abstract":327,"tags":328},"I1",[],[275],[275],[330,331],"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","10.3390\u002Fagronomy16202071",{"doi":333,"openalex_id":335,"authors":336,"venue":265,"cited_by_count":75,"oa_url":262,"card":346,"direction":352,"ingested_from":353},"W7223156204",[337,340,342,344],{"name":338,"orcid":339},"Mingliang Jiang","https:\u002F\u002Forcid.org\u002F0000-0002-6486-6087",{"name":341,"orcid":8},"Yi Zhang",{"name":343,"orcid":8},"WEI Lei",{"name":345,"orcid":8},"Chengcai Zhang",{"tldr":347,"method":348,"finding":349,"direction":350,"opportunity":351},"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",{"id":356,"title":357,"url":358,"summary":359,"summary_zh":8,"content":8,"source_name":360,"source_url":8,"published_at":266,"category":267,"cover_url":8,"hotness":13,"is_selected":14,"score":361,"score_detail":362,"sources":365,"tags":367,"primary_topic":372,"secondary_topics":373,"classification":382,"search_phrases":402,"slug":405,"view_count":22,"doi":8,"paper":406,"created_at":414},5535,"基于无人机多光谱图像与VGG21模型的小麦渍害调控效果识别","https:\u002F\u002Ffinance.sina.cn\u002F2026-10-16\u002Fdetail-inivmprm8363597.d.html","江苏省农科院农业信息研究所联合中国农科院环发所与湖北省农科院粮作所，在小麦拔节至抽穗、抽穗至灌浆两个阶段设置对照、渍水胁迫、硅肥与氨基酸调控试验，用大疆精灵4采集冠层多光谱影像。VGG21模型对硅肥调控识别正确率超91%，精度96.42%、召回率89.53%。","智慧农业（中英文）2026-10-21",82,{"impact":363,"substance":18,"depth":363,"authority":20,"freshness":13,"relevant":22,"comment":364},18,"省级科研机构联合攻关，方法新颖、数据扎实，对渍害遥感识别与调控评估有实质参考价值，值得入选。",[366],{"name":360,"url":358},[275,368,369,370,371],"农业遥感","作物表型","无人机多光谱","小麦渍害",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[374,378],{"code":312,"slug":375,"name":376,"path":377,"parent_code":292},"remote-sensing","遥感与农情监测","\u002Ftopic\u002Fdigital-agriculture\u002Fremote-sensing",{"code":124,"slug":379,"name":380,"path":381,"parent_code":286},"climate","气候适应与防灾减灾","\u002Ftopic\u002Fenvironment\u002Fclimate",{"status":46,"locked":14,"version":47,"method":48,"evidence":383},{"candidates":384,"agricultural_evidence":53},[385,389,393,398],{"code":33,"score":60,"supported":53,"title":386,"abstract":387,"tags":388},[35],[35],[],{"code":312,"score":60,"supported":53,"title":390,"abstract":391,"tags":392},[370],[],[369,368,370],{"code":124,"score":201,"supported":53,"title":394,"abstract":396,"tags":397},[395],"渍害",[],[],{"code":325,"score":22,"supported":14,"title":399,"abstract":400,"tags":401},[],[],[275],[403,404],"江苏省农科院 小麦渍害 多光谱","VGG21 小麦 硅肥调控","江苏省农科院小麦渍害多光谱-5535",{"doi":8,"openalex_id":8,"authors":407,"venue":8,"cited_by_count":75,"oa_url":8,"card":408,"direction":350,"ingested_from":413},[],{"tldr":409,"method":410,"finding":411,"direction":350,"opportunity":412},"用无人机多光谱图像和VGG21模型识别小麦渍害后硅肥与氨基酸调控效果。","大疆精灵4采集冠层多光谱影像，构建VGG21深度学习分类模型。","VGG21对硅肥调控识别正确率超91%，精度96.42%、召回率89.53%。","可扩展多生育期、多调控组合与轻量化模型，探索渍害胁迫等级与调控效果的同步识别。","agent","2026-10-22T00:07:10.070916Z",{"id":416,"title":417,"url":418,"summary":419,"summary_zh":8,"content":420,"source_name":421,"source_url":8,"published_at":422,"category":155,"cover_url":8,"hotness":13,"is_selected":14,"score":15,"score_detail":423,"sources":425,"tags":427,"primary_topic":431,"secondary_topics":432,"classification":433,"search_phrases":454,"slug":457,"view_count":75,"doi":8,"paper":8,"created_at":458},5502,"全国秋粮收获超七成 中晚稻已收购1800万吨","https:\u002F\u002Fwww.peopleweekly.cn\u002Fhtml\u002F2026\u002Fsannong_1019\u002F279469.html","农业农村部最新农情调度显示，全国秋粮收获过七成，其中东北过六成，黄淮海、西南过八成，西北近八成，长江中下游过六成，华南过三成。冬小麦播种过一成，冬油菜播种过三成。国家粮食和物资储备局数据显示，各类经营主体已收购中晚稻1800万吨；秋粮产量占全年粮食产量约四分之三。","本报北京10月18日电  （记者郁静娴）据农业农村部最新农情调度，全国秋粮收获过七成。其中，东北过六成，黄淮海、西南过八成，西北近八成，长江中下游过六成，华南过三成。同时，各地秋冬种有序推进，冬小麦播种过一成，冬油菜播种过三成。\n\n本报北京10月18日电  （记者王东辉）记者从国家粮食和物资储备局获悉：各地秋粮旺季收购正有序展开。初步统计，各类经营主体已收购中晚稻1800万吨。\n\n当前秋粮已开始收获上市，秋粮产量占全年粮食产量的3\u002F4左右，涉及品种多、数量规模大、覆盖区域广。相关部门将加强秋粮收购工作统筹组织，抓好市场化收购和政策性收储，落实落细各项政策举措，全力保障农民售粮渠道顺畅、市场平稳运行。","人民日报 2026-10-19","2026-10-19T00:00:00Z",{"impact":17,"substance":18,"depth":91,"authority":91,"freshness":118,"relevant":22,"comment":424},"全国性秋粮收获与收购权威数据，信息增量足、信源权威，时效稍滞后但值得进入每日精选。",[426],{"name":421,"url":418},[134,99,428,429,430],"秋粮收购","农情调度","中晚稻",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[],{"status":46,"locked":14,"version":47,"method":48,"evidence":434},{"candidates":435,"agricultural_evidence":53},[436,440,446,450],{"code":33,"score":125,"supported":53,"title":437,"abstract":438,"tags":439},[],[35],[99],{"code":441,"score":66,"supported":53,"title":442,"abstract":443,"tags":445},"A4",[],[444],"油菜",[],{"code":131,"score":146,"supported":14,"title":447,"abstract":448,"tags":449},[],[],[428,134],{"code":312,"score":22,"supported":14,"title":451,"abstract":452,"tags":453},[],[],[429],[455,456],"全国秋粮收获 中晚稻收购","国家粮食和物资储备局 秋粮收购","全国秋粮收获中晚稻收购-5502","2026-10-22T00:06:58.371818Z"]