[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-931":3,"related-931":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":18,"tags":20,"primary_topic":27,"secondary_topics":33,"classification":34,"search_phrases":71,"slug":74,"view_count":75,"doi":8,"paper":8,"created_at":76},931,"中国农学会棉花分会2026年年会8月23-26日在河北石家庄召开 河北省农林科学院承办","https:\u002F\u002Fcaass.caas.cn\u002Fhdjj\u002Fxsjl\u002F7b1fd32647874101bdb5d202921791d0.htm","中国农学会棉花分会2026年年会定于8月23-26日在河北石家庄召开，承办单位包括河北省农林科学院棉花研究所、棉花生物育种与综合利用国家重点实验室、农业农村部黄淮海半干旱区棉花生物学与遗传育种重点实验室、河北省棉花产业协同创新中心、河北省棉花学会、河北省棉花生物育种与栽培生理重点实验室。设棉花基础研究、种质资源与遗传育种、栽培生理与生产管理、棉花产业科普与政策4个主题报告方向，聚焦深入学习贯彻习近平总书记在加强基础研究座谈会上重要讲话精神。",null,"（一）住宿酒店：河北太行国宾馆，标间350元\u002F天（含单早）；388元\u002F天(含双早）\n\n（二）交通安排：会务组将于8月23日在石家庄正定机场、石家庄站安排接站。请参会人员预订车票后可将信息发送至邮箱cotton269@163.com，以便接站。\n\n（三）欢迎加入中国农学会注册成为会员，请登录中国农学会网站会员系统完成在线注册（www.caass.org.cn，个人会员免费注册），或扫描下方二维码关注中国农学会微信公众号，点击【会员服务】—【会员注册】，发展来源选择“棉花分会”，完成个人会员注册。个人会员应当具有副高级以上职称或博士学位，学生会员应是身处科研一线的硕士、博士研究生。\n\n（四）会议期间，参会人员须认真贯彻落实中央八项规定及其实施细则精神，不得在会议期间违规相互宴请，也不得以同乡会、校友会、战友会等各种联谊活动名义违规请客送礼。本次会议厉行节约，反对铺张浪费，严格执行会议用餐、住宿标准，严禁组织高消费娱乐、健身活动。","中国农学会 2026-08-23","2026-08-23T00:00:00Z","报道",10,false,0,{"impact":15,"substance":15,"depth":15,"authority":15,"freshness":15,"relevant":15,"comment":17},"会议通知，非农业信息化相关资讯。",[19],{"name":10,"url":6},[21,22,23,24,25,26],"棉花","河北农林科学院","中国农学会","棉花分会","石家庄","国家重点实验室",{"code":28,"slug":29,"name":30,"path":31,"parent_code":32},"A6","cash-crops","棉麻糖与特色经作","\u002Ftopic\u002Ffield-crops\u002Fcash-crops","A",[],{"status":35,"locked":14,"version":36,"method":37,"evidence":38},"classified","2026-10-22.2","rules",{"candidates":39,"agricultural_evidence":42},[40,46,53,59,65],{"code":28,"score":41,"supported":42,"title":43,"abstract":44,"tags":45},12,true,[21],[21],[21],{"code":47,"score":48,"supported":42,"title":49,"abstract":50,"tags":52},"A4",3,[],[51],"花生",[],{"code":54,"score":48,"supported":42,"title":55,"abstract":56,"tags":58},"F1",[],[57],"种质资源",[],{"code":60,"score":48,"supported":42,"title":61,"abstract":62,"tags":64},"F2",[],[63],"生物育种",[],{"code":66,"score":48,"supported":42,"title":67,"abstract":68,"tags":70},"H7",[],[69],"干旱",[],[72,73],"国家重点实验室 河北农林科学院 中国农学会 棉花分会","国家重点实验室 河北农林科学院","国家重点实验室河北农林科学院中国农学会棉花分会-931",1,"2026-08-25T00:03:28.250732Z",{"total":78,"page":75,"page_size":78,"items":79},6,[80,150,198,259,317,353],{"id":81,"title":82,"url":83,"summary":84,"summary_zh":85,"content":8,"source_name":86,"source_url":83,"published_at":87,"category":88,"cover_url":8,"hotness":13,"is_selected":14,"score":89,"score_detail":90,"sources":96,"tags":98,"primary_topic":103,"secondary_topics":104,"classification":105,"search_phrases":133,"slug":136,"view_count":75,"doi":137,"paper":138,"created_at":149},5233,"Cotton pest and disease multi-class classification with weather and temporal predictors features across Indian agroclimatic zones","https:\u002F\u002Fdoi.org\u002F10.25258\u002Fijddt.16.73s.45","The Pink Bollworm (Pectinophora gossypiella) remains one of the most destructive pests affecting cotton productivity, with infestation levels strongly driven by climatic fluctuations and crop phenology.This study presents a machine learning-based framework for early multi-classification and prediction of Pink Bollworm incidence using agro-meteorological variables.The dataset includes maximum and minimum air temperature, relative humidity, rainfall, sunshine hours, evaporation, and wind speed, all of which influence Pink Bollworm development, migration, and reproductive cycles.After preprocessing, applying cyclic encoding to temporal variables, and generating lagged climatic features, multiple machine learning algorithms-including SVM, Neural Networks, KNN, Regression models, Ensemble methods, and Naïve Bayes-were trained and systematically compared.SVM model demonstrated the best test accuracy, effectively capturing dynamic climate-pest interactions.The resulting MATLAB-based classification tool enables rapid assessment and supports climate-informed pest surveillance.A stratified 80:20 train-test split was employed, with 5-fold cross-validation on the training set for hyperparameter tuning, ensuring no data leakage between partitions.The validation and training accuracies of these models are 89.4% and 96 % respectively.Overall, the model offers a practical and interpretable solution for early detection of Pink Bollworm risk, thereby contributing to informed decision-making in integrated pest management (IPM) and precision agriculture.","棉红铃虫（Pectinophora gossypiella）仍是影响棉花产量最具破坏性的害虫之一，其发生程度受气候波动和作物物候的强烈驱动。本研究提出了一种基于机器学习的框架，利用农业气象变量对棉红铃虫的发生进行早期多分类与预测。数据集包括最高和最低气温、相对湿度、降雨量、日照时数、蒸发量和风速，这些因素均影响棉红铃虫的发育、迁移和繁殖周期。经过预处理、对时间变量应用循环编码并生成滞后气候特征后，训练并系统比较了多种机器学习算法，包括支持向量机（SVM）、神经网络、K近邻（KNN）、回归模型、集成方法和朴素贝叶斯。SVM模型表现出最佳的测试准确率，有效捕捉了气候与害虫之间的动态相互作用。所构建的基于MATLAB的分类工具可实现快速评估，并支持气候信息驱动的害虫监测。采用分层80：20的训练-测试划分，并在训练集上进行5折交叉验证以调优超参数，确保各分区之间无数据泄漏。这些模型的验证准确率和训练准确率分别为89.4%和96%。总体而言，该模型为棉红铃虫风险的早期检测提供了一种实用且可解释的解决方案，从而有助于综合害虫管理（IPM）和精准农业中的科学决策。","International Journal of Drug Delivery Technology","2026-10-17T00:00:00Z","论文",55,{"impact":91,"substance":92,"depth":93,"authority":78,"freshness":94,"relevant":75,"comment":95},8,18,14,9,"研究用多类机器学习模型结合气象与时序特征预测棉铃虫风险，方法扎实但属细分领域应用研究，信源期刊权威性一般，公共影响有限。",[97],{"name":86,"url":83},[99,100,21,101,102],"智慧农业","机器学习","农业气象","病虫害预警",{"code":28,"slug":29,"name":30,"path":31,"parent_code":32},[],{"status":35,"locked":14,"version":36,"method":37,"evidence":106},{"candidates":107,"agricultural_evidence":42},[108,114,122,128],{"code":28,"score":109,"supported":42,"title":110,"abstract":112,"tags":113},15,[111],"cotton",[21,111],[21],{"code":115,"score":116,"supported":42,"title":117,"abstract":118,"tags":121},"I1",7,[],[119,120],"精准农业","precision agriculture",[99],{"code":123,"score":116,"supported":42,"title":124,"abstract":125,"tags":127},"I2",[],[100,126],"machine learning",[100],{"code":66,"score":129,"supported":42,"title":130,"abstract":131,"tags":132},4,[],[101],[101],[134,135],"棉铃虫 机器学习 预测","棉花 病虫害 气象因子","棉铃虫机器学习预测-5233","10.25258\u002Fijddt.16.73s.45",{"doi":137,"openalex_id":139,"authors":140,"venue":86,"cited_by_count":15,"oa_url":83,"card":141,"direction":147,"ingested_from":148},"W7222826491",[],{"tldr":142,"method":143,"finding":144,"direction":145,"opportunity":146},"用农业气象变量与时间特征构建机器学习模型，实现印度棉区棉铃虫多级发生预测。","气象数据加周期编码与滞后特征，比较SVM等模型，5折交叉验证。","SVM测试精度最高达89.4%，能有效刻画气候与虫害动态关系。","农业人工智能与决策模型","可引入遥感植被指数与实时气象物联网数据，构建跨区域可迁移的病虫害预警系统。","智慧农业 \u002F 农业物联网","openalex","2026-10-18T23:30:07.725427Z",{"id":151,"title":152,"url":153,"summary":154,"summary_zh":8,"content":155,"source_name":156,"source_url":8,"published_at":157,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":158,"score_detail":159,"sources":164,"tags":166,"primary_topic":170,"secondary_topics":171,"classification":172,"search_phrases":193,"slug":196,"view_count":75,"doi":8,"paper":8,"created_at":197},5031,"智慧棉田成就新疆新一代科技棉农","https:\u002F\u002Fwww.news.cn\u002Flocal\u002F20261015\u002F048734cea69b466eac74966f7b4d0074\u002Fc.html","金秋十月,天山南北棉花吐絮迎来采收。在塔克拉玛干沙漠北缘的尉犁县'超级棉田',采棉机来回穿梭,朵絮归仓。新疆是中国最大优质棉花生产基地,2025年新疆棉花产量占全国92.8%,总产、单产连续32年居全国第一。2021年极飞科技在尉犁县启动'超级棉田'项目,目前管理环节无人化作业率已达75%,栽培管理模式在全疆推广面积已超200万亩。今年更新的X150新型农业无人机可自动配药、加药、充电、规划航线,自主喷药作业。'90后'家庭农场主郭腾承包2.5万亩棉田,日常管护只需50名工人,返乡种棉成为越来越多年轻人的选择。","  新华社乌鲁木齐10月14日电（记者潘莹、宿传义、高晗）金秋十月，天山南北棉花吐絮，迎来采收。在塔克拉玛干沙漠北缘的尉犁县“超级棉田”，伴随着一台台采棉机来回穿梭，洁白的棉花被采摘、压缩、打包，朵絮归仓。\n\n  “前不久，田里用上一款新款农业无人机，不需要飞手操作，棉花采收环节更加智能化。”“超级棉田”项目负责人艾海鹏说。\n\n  新疆是中国最大优质棉花生产基地，2025年新疆棉花产量占全国产量的92.8%，总产、单产连续32年居全国第一。如今，在新疆，这样的智慧化场景正逐渐贯穿棉花生产全过程，并加速从示范走向普及，一批懂技术、善经营、会管理的“新一代棉农”应运而生。\n\n  在新疆巴音郭楞蒙古自治州尉犁县“超级棉田”中，农业无人机在田间喷洒脱叶剂（2026年9月20日摄，无人机照片）。新华社发（汪志鹏 摄）\n\n  尉犁县气候干燥、光热充足，是中国优质商品棉种植基地，棉花种植面积稳定在100多万亩。2021年，在尉犁县支持下，农业机器人企业极飞科技启动“超级棉田”项目，派出艾海鹏、凌磊两位“90后”管理经营3000亩棉田，探索可复制、可推广的无人化农业管理模式。\n\n  两人从解决棉花管理中最耗人工的灌溉难题入手，持续升级无人化、智能化监测管理的新技术、新设备，让“超级棉田”管理模式与大规模棉花种植高度适配，实现产量更高、品质更优。\n\n  “通过多年努力，‘超级棉田’已实现水、肥、药的智能化管理，目前管理环节无人化作业率已达75%。”艾海鹏说。截至2025年底，“超级棉田”的栽培管理模式在全疆推广面积已超200万亩。\n\n  今年，“超级棉田”又更新了一批新装备：耕种环节用上最新的APC4自驾仪，播种机可自动断膜断带，进一步节省人工。最让管理者津津乐道的，当属X150新型农业无人机。这款无人机可自动配药、加药、充电、规划航线、自主喷药作业，适配除草、防虫、防病等一系列田间需求。\n\n  在棉花吐絮关键期，记者在“超级棉田”作业现场看到，艾海鹏在手机上选好模板、点击“立即开始”，机器人便自主起降、补能，既不需要飞手，也不需要遥控器。手机屏上，药箱空满状态和地面药罐余量一目了然。\n\n  “往年打药虽然也用无人机，但还需要飞手控制轨迹、及时补药换电池。现在把飞机放这儿就不用管了。晚上回去睡觉，第二天早上过来，它已经按要求完成了全部植保任务。”艾海鹏说，目前这款新型农业无人机已在全国推广。\n\n  “我们的目的是想要吸引越来越多年轻人回到农业这一行业。一个行业有年轻人加入，才能有朝气，有更大的发展空间。”艾海鹏说。\n\n  在新疆巴音郭楞蒙古自治州尉犁县“超级棉田”中，采棉机在采收棉花（2026年10月14日摄，无人机照片）。新华社发\n\n  在天山北麓的昌吉市佃坝镇东沟村，“90后”家庭农场主郭腾正盯着屏幕，调度巨大的采棉机在棉海里缓缓行进，源源不断吐出打包好的棉包。\n\n  郭腾是土生土长的昌吉人，一家两代人的种棉经历，正是新疆棉花从“靠人力”到“靠科技”转型发展的鲜活缩影。\n\n  他说，父辈种棉是实打实的苦差事：棉田管护加采收要投入大量人工，采收成本高，种植户收入却很有限。\n\n  “如今农村可发展的空间大了。”郭腾介绍，自己毕业后在城里闯荡过一段时间，随着新疆棉田科技含量越来越高，看到新一代棉农正面临机遇无限的职业图景，决定回乡种棉花。\n\n  如今，郭腾的家庭农场已配齐整套自主农机：4台采棉机、6台植保无人机、十余台播种机、3台大马力拖拉机；棉田用上水肥一体化精准滴灌、无人机植保，犁地、播种、打药、采收，全流程机械化。\n\n  “一台采棉机一天能收400至450亩，每亩采收环节油费加人工成本仅60元。”郭腾说，他承包的2.5万亩棉田日常管护只需50名工人，自己在手机上就能查看田间情况、调度农机作业。\n\n  返乡种棉正成为越来越多年轻人的选择。郭腾发现，与他长期合作的团队里，返乡年轻人越来越多。“只要掌握技术，采棉季每月赚5万元不成问题。”他说。\n\n  随着越来越多科技装备、先进技术在新疆广袤棉田推广普及，新疆棉田加速智慧化，更多年轻人在天山南北的棉田里，找到创业舞台。","新华社 2026 年 10 月 15 日","2026-10-14T23:50:00Z",84,{"impact":160,"substance":161,"depth":162,"authority":109,"freshness":91,"relevant":75,"comment":163},24,20,17,"央媒实地报道，以新疆超级棉田与新一代棉农为样本，呈现农业无人机自主作业与无人化管理模式从示范走向普及的产业级进展，数据与多方信源扎实，具主题聚合价值。",[165],{"name":156,"url":153},[99,167,21,168,169],"农业无人机","无人化农场","新疆棉田",{"code":28,"slug":29,"name":30,"path":31,"parent_code":32},[],{"status":35,"locked":14,"version":36,"method":37,"evidence":173},{"candidates":174,"agricultural_evidence":42},[175,179,183,189],{"code":28,"score":129,"supported":42,"title":176,"abstract":177,"tags":178},[],[21],[21],{"code":47,"score":48,"supported":42,"title":180,"abstract":181,"tags":182},[],[51],[],{"code":184,"score":48,"supported":42,"title":185,"abstract":186,"tags":188},"G2",[],[187],"家庭农场",[],{"code":115,"score":75,"supported":14,"title":190,"abstract":191,"tags":192},[],[],[99],[194,195],"新疆 超级棉田 极飞科技","尉犁县 智慧棉田 无人机","新疆超级棉田极飞科技-5031","2026-10-16T00:13:02.993245Z",{"id":199,"title":200,"url":201,"summary":202,"summary_zh":8,"content":8,"source_name":203,"source_url":8,"published_at":8,"category":88,"cover_url":8,"hotness":13,"is_selected":14,"score":204,"score_detail":205,"sources":210,"tags":212,"primary_topic":216,"secondary_topics":217,"classification":223,"search_phrases":246,"slug":249,"view_count":15,"doi":8,"paper":250,"created_at":258},4966,"基于改进YOLO 11n模型的棉花田间复杂环境障碍物检测方法","http:\u002F\u002Fwww.qikanzj.com\u002Fhek\u002Fnyjxxb\u002Fmulu\u002F455619.html","韩科立、王振坤等(中国农业机械化科学研究院集团有限公司;现代农装科技股份有限公司;农业装备技术全国重点实验室)针对棉花田间复杂环境障碍物被遮挡致准确检测难、边缘设备算力有限的问题,提出一种基于改进YOLO 11n模型的田间障碍物检测方法。采用StarNet作为主要特征提取网络并引入DBA模块增强多尺度特征交互能力;使用KAGNConv替换C3k2瓶颈结构增强灵活性与可解释性;集成分离与增强注意力模块SEAM至检测头增强遮挡场景能力。试验结果表明,改进模型YOLO 11n-SKS精确率、召回率、mAP50、mAP50-95分别提升2.3、2.1、1.3、1.4个百分点,达到91.7%、88.3%、91.9%、62.3%。","《农业机械学报》",71,{"impact":206,"substance":207,"depth":92,"authority":93,"freshness":208,"relevant":75,"comment":209},16,21,2,"改进YOLO 11n实现棉花田间遮挡障碍物检测，方法新颖、指标提升明确，属农业人工智能细分领域实质进展，但发布日期未知、时效性偏弱。",[211],{"name":203,"url":201},[99,213,21,214,215],"农业人工智能","障碍物检测","采棉机",{"code":28,"slug":29,"name":30,"path":31,"parent_code":32},[218],{"code":123,"slug":219,"name":220,"path":221,"parent_code":222},"agricultural-ai","农业AI与大模型","\u002Ftopic\u002Fdigital-agriculture\u002Fagricultural-ai","I",{"status":35,"locked":14,"version":36,"method":37,"evidence":224},{"candidates":225,"agricultural_evidence":42},[226,230,235,242],{"code":28,"score":41,"supported":42,"title":227,"abstract":228,"tags":229},[21],[21],[21],{"code":123,"score":41,"supported":42,"title":231,"abstract":233,"tags":234},[232],"YOLO",[232],[213],{"code":236,"score":78,"supported":42,"title":237,"abstract":238,"tags":241},"F5",[],[239,240],"农业机械","机械化",[],{"code":115,"score":75,"supported":14,"title":243,"abstract":244,"tags":245},[],[],[99],[247,248],"中国农业机械化科学研究院 采棉机 障碍物检测","YOLO 11n 棉花 田间障碍物","中国农业机械化科学研究院采棉机障碍物检测-4966",{"doi":8,"openalex_id":8,"authors":251,"venue":8,"cited_by_count":15,"oa_url":8,"card":252,"direction":145,"ingested_from":257},[],{"tldr":253,"method":254,"finding":255,"direction":145,"opportunity":256},"提出改进YOLO 11n模型，实现棉花田间复杂遮挡环境下障碍物高精度检测。","以StarNet为骨干，引入DBA、KAGNConv与SEAM注意力模块，改进Y","改进模型精确率91.7%、召回率88.3%、mAP50达91.9%，各项指标均提升。","可探索轻量化模型在边缘设备实时部署，并扩展至多作物多类障碍物检测。","agent","2026-10-15T00:06:08.577388Z",{"id":260,"title":261,"url":262,"summary":263,"summary_zh":8,"content":264,"source_name":265,"source_url":8,"published_at":266,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":267,"score_detail":268,"sources":271,"tags":273,"primary_topic":277,"secondary_topics":278,"classification":283,"search_phrases":312,"slug":315,"view_count":48,"doi":8,"paper":8,"created_at":316},4935,"中国农科院棉花所揭示角鲨烯合成协同促进棉花生长发育与抗逆性","https:\u002F\u002Fcricaas.com.cn\u002Fsylm\u002Fkyjz\u002Fc44ab2cf89bc44c682ab8105af99fbaf.htm","中国农业科学院棉花研究所棉花分子遗传改良创新团队在棉花角鲨烯生物合成及功能研究方面取得新进展,发现棉花角鲨烯合成关键基因GhSQS1能够提高棉花组织中的角鲨烯积累水平,并促进棉花生长发育,改善干旱和碱胁迫耐受性。相关成果发表于《实验植物学杂志》。过表达GhSQS1的代表性株系OE2叶片角鲨烯含量达989.1 mg\u002Fkg干重,较野生型提高约70%,叶片增大、根系发育改善、纤维伸长和种子增大。","### 角鲨烯合成促进棉花生长发育与抗逆性\n\n发布时间:2026-10-14 来源 ：**棉花分子遗传改良创新团队**作者：**徐雅梦**\n\n近日，中国农业科学院棉花研究所棉花分子遗传改良创新团队在棉花角鲨烯生物合成及功能研究方面取得新进展，发现棉花角鲨烯合成关键基因 _GhSQS1_ 能够提高棉花组织中的角鲨烯积累水平，并促进棉花生长发育，改善干旱和碱胁迫耐受性，为棉花遗传改良与副产物高值化利用提供了新思路。相关成果以“GhSQS1-mediated squalene accumulation coordinates cotton development and stress resilience”为题，发表于国际植物科学期刊《实验植物学杂志（Journal of Experimental Botany）》上。\n\n棉花是重要的天然纤维作物，其棉叶、棉籽等副产物也具有较高的开发利用潜力。角鲨烯是一种具有较高应用价值的三萜类化合物，在化妆品、营养保健等领域具有广泛应用，同时也是植物甾醇及其他三萜类化合物生物合成的重要前体。然而，角鲨烯生物合成与棉花生长发育及逆境适应之间的关系尚不明确，其潜在调控机制仍有待深入研究。\n\n该研究发现适宜浓度的角鲨烯可促进棉花主根伸长和离体胚珠发育，并鉴定出棉花中角鲨烯合成关键基因 _GhSQS1_。进一步研究发现，过表达该基因伴随油菜素内酯相关代谢及信号通路变化，且显著提高棉花叶片角鲨烯含量，其中代表性株系OE2达到989.1 mg\u002Fkg干重，较野生型提高约70%，同时表现出叶片增大、根系发育改善、纤维伸长和种子增大等性状。在模拟干旱和碱胁迫条件下，过表达该基因的植株表现出较强的耐受能力，并伴随抗氧化能力增强和膜脂过氧化程度降低。此外，异源表达真菌来源角鲨烯合酶也获得了类似的促生长表型，表明增强角鲨烯合成有助于改善棉花发育。研究结果表明，增强角鲨烯生物合成与棉花生长发育及逆境适应能力改善之间的联系，为通过代谢工程协同改良作物性状与提高功能性天然产物积累提供了新思路，也为棉花副产物高值化利用提供了研究基础。\n\n该研究得到中国农业科学院青年创新专项、河南省自然科学基金、新疆维吾尔自治区重点研发计划、国家自然科学基金、国家现代农业产业技术体系等项目支持。中棉所徐雅梦、张志甜、刘乐和贾舒元为论文共同第一作者，李付广研究员和杨作仁研究员为共同通讯作者。\n\n原文链接：https:\u002F\u002Fdoi.org\u002F10.1093\u002Fjxb\u002Ferag424\n\n![Image 1: 未标题-1xiu.jpg](https:\u002F\u002Fcricaas.com.cn\u002Fimages\u002F2026-10\u002F790d9cb6eae848e29b5c94cf46779bc5.jpg)\n\n角鲨烯合成增强协同促进棉花生长发育、抗逆性及生物质高值化利用示意图\n\n打印本页\n\n关闭本页","中国农业科学院棉花研究所 2026 年 10 月 14 日","2026-10-14T00:00:00Z",87,{"impact":269,"substance":269,"depth":92,"authority":109,"freshness":13,"relevant":75,"comment":270},22,"国家级科研机构在棉花角鲨烯合成基因GhSQS1上的新发现，兼具生长发育促进与抗旱耐碱改良价值，数据具体、期刊权威，值得进入每日精选。",[272],{"name":265,"url":262},[274,63,21,275,276],"种业振兴","功能成分","抗旱耐盐",{"code":28,"slug":29,"name":30,"path":31,"parent_code":32},[279],{"code":47,"slug":280,"name":281,"path":282,"parent_code":32},"soybean-oilseeds","大豆与油料","\u002Ftopic\u002Ffield-crops\u002Fsoybean-oilseeds",{"status":35,"locked":14,"version":36,"method":37,"evidence":284},{"candidates":285,"agricultural_evidence":42},[286,290,295,299,304,308],{"code":28,"score":41,"supported":42,"title":287,"abstract":288,"tags":289},[21],[21],[21],{"code":47,"score":291,"supported":42,"title":292,"abstract":293,"tags":294},11,[51],[51],[],{"code":66,"score":48,"supported":42,"title":296,"abstract":297,"tags":298},[],[69],[],{"code":300,"score":75,"supported":14,"title":301,"abstract":302,"tags":303},"E2",[],[],[275],{"code":54,"score":75,"supported":14,"title":305,"abstract":306,"tags":307},[],[],[274],{"code":60,"score":75,"supported":14,"title":309,"abstract":310,"tags":311},[],[],[63],[313,314],"中国农科院棉花所 GhSQS1","棉花 角鲨烯 抗逆","中国农科院棉花所GhSQS1-4935","2026-10-15T00:06:01.753012Z",{"id":318,"title":319,"url":320,"summary":321,"summary_zh":8,"content":322,"source_name":323,"source_url":8,"published_at":324,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":325,"score_detail":326,"sources":329,"tags":331,"primary_topic":335,"secondary_topics":336,"classification":337,"search_phrases":348,"slug":351,"view_count":15,"doi":8,"paper":8,"created_at":352},4766,"棉花关键技术集成助力高温逆境下产量品质效益三丰收","https:\u002F\u002Fwap.sciencenet.cn\u002Fmobile.php?cat=T&id=572667","中国农业科学院西部农业研究中心在昌吉州老龙河综合试验基地举办棉花优质高产关键技术集成示范观摩会。千亩示范方实测籽棉平均亩产601.4公斤,集成中棉113优系、中新棉1号、3号等优质多抗新品种,以及高光效群体调控、智慧棉田管理、绿色病虫害防控等成套技术,节药15%以上、人工成本降低30%以上。","科学网—\n\n## [![Image 1: 科学网](https:\u002F\u002Fwap.sciencenet.cn\u002Fstatic\u002Fimage\u002Fcommon\u002Flogo.png)](https:\u002F\u002Fwap.sciencenet.cn\u002F \"科学网\")\n\n*   [要闻](https:\u002F\u002Fwap.sciencenet.cn\u002Fmobile.php?type=news&cat=yaowen&mobile=1)\n*   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[针对无人机电子垃圾危机，天大团队《科学》发文](https:\u002F\u002Fwap.sciencenet.cn\u002Fmobile.php?type=detail&cat=T&id=572765&mobile=1)\n*   [“核聚山城?智驭靶向”：第十八届全国放射性药物与标记化合物学术交流会在重庆举办](https:\u002F\u002Fwap.sciencenet.cn\u002Fmobile.php?type=detail&cat=T&id=572754&mobile=1)\n*   [通往“器官再生之路”](https:\u002F\u002Fwap.sciencenet.cn\u002Fmobile.php?type=detail&cat=T&id=572753&mobile=1)\n*   [AI写的字，开始自带“暗号”](https:\u002F\u002Fwap.sciencenet.cn\u002Fmobile.php?type=detail&cat=T&id=572752&mobile=1)","中国科学报 科学网 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