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Empirical remote sensing models often overfit because of confounding effects of three-dimensional canopy structure. Incorporating structural parameters can stabilize biochemical inversions, but concurrent in situ morphological measurements are difficult to acquire at scale. We developed the Morphology-Aware Latent Embedding Network (MALENet), a hybrid framework integrating physiological and morphological mechanisms with hyperspectral data. The Decision Support System for Agrotechnology Transfer (DSSAT), coupled with the PROSAIL radiative transfer model, generated a structurally rich synthetic hyperspectral prior. A convolutional neural network (CNN) with a Squeeze-and-Excitation (SE) attention mechanism, was pre-trained on these data to distill ecophysiological knowledge into a dense latent representation. This mechanistically derived embedding was then fused with empirical hyperspectral measurements collected under diverse field conditions. Evaluation using multi-year field quadrats in the Hexi Corridor showed improved predictive performance ( R² = 0.71, RMSE = 0.30%) relative to conventional machine learning and deep learning models (LASSO-ANN: R² = 0.61; CNN: R² = 0.66). Feature attribution indicated that MALENet used near-infrared multiple scattering (58.3% attribution) as a structural proxy to calibrate nitrogen concentration retrieval against the confounding effects of canopy architecture. Despite constraints imposed by sample size and PROSAIL's 1D canopy assumption, these findings demonstrate the potential of physically guided deep learning to use structural information for agricultural trait retrieval in precision forage management.","准确估算紫花苜蓿（Medicago sativa L.）的氮浓度有助于饲草品质评估和收获期安排。经验性遥感模型常因三维冠层结构的混杂效应而出现过拟合。引入结构参数可以稳定生化反演，但同步开展原位形态学测量难以大规模获取。我们开发了形态感知潜在嵌入网络（Morphology-Aware Latent Embedding Network，MALENet），这是一个将生理与形态机制同高光谱数据相结合的混合框架。农业技术转移决策支持系统（Decision Support System for Agrotechnology Transfer，DSSAT）与PROSAIL辐射传输模型耦合，生成了结构信息丰富的合成高光谱先验数据。在此基础上，预训练了一个带有挤压—激励（Squeeze-and-Excitation，SE）注意力机制的卷积神经网络（convolutional neural network，CNN），将生态生理学知识提炼为稠密潜在表征。随后，将这一机制性导出的嵌入与在不同田间条件下采集的经验性高光谱测量数据相融合。利用河西走廊多年田间样方进行的评估显示，相较于传统机器学习和深度学习模型（LASSO-ANN：R² = 0.61；CNN：R² = 0.66），预测性能有所提升（R² = 0.71，RMSE = 0.30%）。特征归因表明，MALENet利用近红外多次散射（归因占比58.3%）作为结构代理，以校准氮浓度反演，抵御冠层结构的混杂效应。尽管受样本量和PROSAIL一维冠层假设的限制，这些发现表明，物理引导的深度学习有潜力利用结构信息，在精准饲草管理中进行农业性状反演。","European Journal of Agronomy","2026-10-21T00:00:00Z","论文",80,{"impact":142,"substance":143,"depth":103,"authority":56,"freshness":13,"relevant":21,"comment":144},16,22,"该研究将作物模型与辐射传输模型耦合生成结构先验，并结合无人机高光谱数据反演苜蓿氮素，方法新颖、田间验证扎实，对精准饲草管理有参考价值，值得进入每日精选。",[146],{"name":137,"url":134},[148,149,150,151,152],"智慧农业","农业人工智能","农业遥感","氮素监测","紫花苜蓿",{"code":154,"slug":155,"name":156,"path":157,"parent_code":158},"A7","forage-cropping","饲草与耕作制度","\u002Ftopic\u002Ffield-crops\u002Fforage-cropping","A",[160,166],{"code":161,"slug":162,"name":163,"path":164,"parent_code":165},"I3","remote-sensing","遥感与农情监测","\u002Ftopic\u002Fdigital-agriculture\u002Fremote-sensing","I",{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},{"status":50,"locked":14,"version":51,"method":52,"evidence":168},{"candidates":169,"agricultural_evidence":57},[170,177,184,189,199],{"code":161,"score":103,"supported":57,"title":171,"abstract":173,"tags":176},[172],"hyperspectral",[174,175,172],"遥感","remote 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Liang","https:\u002F\u002Forcid.org\u002F0000-0001-5599-6587",{"name":224,"orcid":8},"Yongjia Hu",{"name":226,"orcid":227},"Qisheng Feng","https:\u002F\u002Forcid.org\u002F0009-0000-1391-9591",{"name":229,"orcid":8},"吴彩霞",{"tldr":231,"method":232,"finding":233,"direction":234,"opportunity":235},"构建MALENet融合DSSAT-PROSAIL结构先验与无人机高光谱，提升苜蓿氮浓度估算精度。","DSSAT耦合PROSAIL生成合成高光谱先验，预训练CNN-SE网络，再融合田","MALENet精度优于传统机器学习和深度学习模型，R²达0.71，近红外多次散射作为结构代理贡献58","农业遥感与作物表型","可探索将作物模型结构先验迁移至其他牧草或作物生化参数反演，并缓解PROSAIL一维冠层假设局限。","openalex","2026-10-22T11:20:39.622844Z",{"id":239,"title":240,"url":241,"summary":242,"summary_zh":8,"content":243,"source_name":244,"source_url":8,"published_at":245,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":246,"score_detail":247,"sources":249,"tags":251,"primary_topic":257,"secondary_topics":258,"classification":259,"search_phrases":266,"slug":269,"view_count":90,"doi":8,"paper":8,"created_at":270},5515,"2026年山东省粮油学会学术年会在淄博召开 聚焦数智融合与健康粮油","http:\u002F\u002Fwww.sdncps.com\u002Farticles\u002Fch12342\u002F202610\u002F6676fb19-35b5-4044-b9aa-00a21cb2aff1.shtml","10月10日至12日未来粮油大健康学术交流会暨健康校园专题研讨会在淄博举行，由山东理工大学农业工程与食品科学学院与山东省农科院农产品加工与营养研究所共同承办，300余名专家学者参会。会议以「数智融合，健康粮油」为主题，并举办首届大学生「三美农食」创新创意大赛与粮油学会科学技术奖颁奖。","10月10日至12日，未来粮油大健康学术交流会暨健康校园专题研讨会—2026年山东省粮油学会学术年会在淄博举行。本次年会由中国粮油学会、山东理工大学、山东省农业科学院指导，山东省粮油学会主办，我所与山东理工大学农业工程与食品科学学院共同承办，山东省学校后勤协会、齐鲁粮油产教联合体、中国海洋大学食品科学与工程学院协办。我所党委书记、所长刘丽娜出席本次会议并主持开幕式颁奖环节。\n\n11日上午，年会在山东理工大学齐创大厦会议中心开幕。中国海洋大学食品科学与工程学院教授薛长湖，中国农科院油料作物研究所研究员李培武，中国粮油学会理事长卢景波，山东省科协副主席张波，山东省粮食和物资储备局副局长刘萍，山东理工大学校长李玉霞，山东理工大学校党委副书记、山东省粮油学会理事长杜方岭出席开幕式。\n\n主旨报告环节，薛长湖教授作了题为《海洋水产品加工的发展趋势》的报告。李培武研究员线上分享了《食用油脂与生命健康》报告。江南大学食品学院王兴国教授、农业农村部食物与营养发展研究所所长王凤忠分别作专题报告。\n\n大会期间，举行了“中裕杯”首届山东省大学生“三美农食”创新创意大赛、2026年度山东省粮油学会科学技术奖、优秀论文奖颁奖仪式，现场发布了山东省粮油学会会标。山东省粮油学会与山东省学校后勤协会进行了战略合作签约。\n\n为促进健康粮油与校园营养健康需求有效衔接，会议同期举办健康校园专题研讨会，聚焦高校食堂大宗食材政府采购管理、小麦源功能食品开发等议题，邀请粮油科研机构、食品企业及学校后勤管理领域代表，围绕校园粮油食材采购、产品品质保障、健康粮油开发应用等内容展开研讨。作为本次年会的承办单位之一，我所参与专题研讨会的组织工作，并与参会代表进行了交流。\n\n本次年会以“数智融合，健康粮油”为主题，旨在搭建思想交锋、产学研对接和青年成长的平台。我所将以承办本次年会为契机，进一步深化与省内外高校、科研院所及粮油企业的交流合作，加强农产品加工与营养领域科技创新与成果转化，为保障国家粮食安全、推进健康中国建设贡献更大力量。\n\n来自国内粮油领域的专家学者、高校科研院所代表、粮油企业负责人等300余人参会。（撰写：岳昊   核稿：刘丽娜）","山东省农业科学院农产品加工与营养研究所 2026-10-17","2026-10-17T00:00:00Z",63,{"impact":103,"substance":142,"depth":17,"authority":17,"freshness":122,"relevant":21,"comment":248},"省级粮油学会年会，主题涉及数智融合与健康粮油，有产学研签约和专题研讨等实质内容，但属行业会议通稿，时效偏旧，可作一般资讯而非每日精选。",[250],{"name":244,"url":241},[252,253,254,255,256],"产学研对接","粮油加工","健康粮油","数智融合","校园营养",{"code":38,"slug":39,"name":40,"path":41,"parent_code":42},[],{"status":50,"locked":14,"version":51,"method":52,"evidence":260},{"candidates":261,"agricultural_evidence":57},[262],{"code":38,"score":75,"supported":57,"title":263,"abstract":264,"tags":265},[],[111],[],[267,268],"山东省粮油学会 学术年会","数智融合 健康粮油","山东省粮油学会学术年会-5515","2026-10-22T00:07:04.000276Z",{"id":272,"title":273,"url":274,"summary":275,"summary_zh":8,"content":276,"source_name":277,"source_url":8,"published_at":278,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":279,"score_detail":280,"sources":283,"tags":285,"primary_topic":290,"secondary_topics":291,"classification":292,"search_phrases":300,"slug":303,"view_count":90,"doi":8,"paper":8,"created_at":304},5510,"中国农科院加工所研发3D打印仿生三文鱼 破解老年人吞咽进食难题","https:\u002F\u002Fwww.caas.cn\u002Fxwzx\u002Fmtxw\u002Fed0d9b62360a486d96bc32e04531bc1a.htm","农产品加工所食物营养与功能性食品创新团队构建核桃蛋白与蛋清蛋白复合乳液凝胶体系，用挤出式3D打印复刻三文鱼红白纹理。100℃烘烤3分钟为最佳方案，可分别达到国际吞咽障碍食品标准5级和6级，产品蛋白含量达22%，蛋白补充效率较传统产品提高200%。","科研人员对比了蒸制与烘烤两种方式，发现烘烤后的样品中关键风味物质含量明显增加，色泽、香气和吞咽顺滑度都更胜一筹。其中，100℃烘烤3分钟是效果最佳的方案，产品感官评分最高。通过调整烘烤时间，可以精准控制食物的软硬度，分别达到国际吞咽障碍食品标准的5级和6级，适配吞咽能力不同的老人。\n\n经专业测试，这款仿生三文鱼蛋白含量达到22%，质地柔软湿润、易于成团、不易散开，完全符合“可安全吞咽”的食物质地要求。","人民日报海外版 2026-10-19","2026-10-19T00:00:00Z",81,{"impact":143,"substance":281,"depth":142,"authority":56,"freshness":18,"relevant":21,"comment":282},21,"国家级科研机构在适老食品与3D打印领域取得实质突破，数据与标准等级明确，具备行业示范价值，值得进入每日精选。",[284],{"name":277,"url":274},[111,286,287,288,289],"适老食品","3D打印食品","吞咽障碍食品","仿生食品",{"code":38,"slug":39,"name":40,"path":41,"parent_code":42},[],{"status":50,"locked":14,"version":51,"method":52,"evidence":293},{"candidates":294,"agricultural_evidence":57},[295],{"code":38,"score":296,"supported":57,"title":297,"abstract":298,"tags":299},4,[],[111],[111],[301,302],"中国农科院 加工所 仿生三文鱼","3D打印 适老食品 吞咽障碍","中国农科院加工所仿生三文鱼-5510","2026-10-22T00:07:03.681391Z",{"id":306,"title":307,"url":308,"summary":309,"summary_zh":310,"content":8,"source_name":311,"source_url":308,"published_at":11,"category":139,"cover_url":8,"hotness":13,"is_selected":14,"score":312,"score_detail":313,"sources":315,"tags":317,"primary_topic":322,"secondary_topics":327,"classification":329,"search_phrases":366,"slug":369,"view_count":90,"doi":370,"paper":371,"created_at":387},5475,"Adoption of Climate-Smart Conservation Agriculture in Improving Food Security in Zimbabwe: The Case of Marondera District, Zimbabwe","https:\u002F\u002Fdoi.org\u002F10.71458\u002Fwby9rf15","Climate change is negatively impacting the global community and local communities in the Southern African Development Community (SADC) region. Extreme weather events are occurring more frequently, posing a threat to human lives and well-being. Climate change-induced disasters have exacerbated the risks of hunger and under nutrition through reduced yields of agricultural crops. The detrimental effects of climate change are particularly seen in Zimbabwe. It is best to use climate-smart agriculture (CSA) in the smallholder agricultural sector, which produces the majority of the nation's food. Therefore, it is important to learn lessons from past events and manage risks effectively as part of an integrated set of interventions directed at mitigating the harmful impacts of disasters and risks. The research explores community adaptation and coping strategies in addressing the effects of climate change on food security using Marondera District as a case study. The research was conducted using the qualitative research methodology. Data were collected from a population of 50 people that included smallscale farmers, Agritex officers, extension officers, non-governmental organisation (NGO) representatives, village herdsman and the chief. Documentary research was analysed thematically. The research concludes that climate change has had a negative impact on food security. It affected all the four dimensions of food security, that is; food availability, food accessibility, food utilisation and food systems stability. In response, various projects aimed at ensuring community resilience to cope in the face of climatological hazards have been implemented by NGOs, government institutions and other actors, with community members being key stakeholder. The research recommends continued mobilisation of social protection interventions, building of resilient agricultural systems to make them more resilient to climate change and improving the management of the environment to ensure effectiveness in efforts to mitigate the impact of climate change on food security.","气候变化正在对全球社会以及南部非洲发展共同体（SADC）区域的当地社区产生负面影响。极端天气事件发生频率增加，对人类生命和福祉构成威胁。气候变化引发的灾害通过降低农作物产量，加剧了饥饿和营养不足的风险。气候变化的不利影响在津巴布韦尤为显著。在小农农业部门——该部门生产了全国大部分粮食——最好采用气候智能型农业（CSA）。因此，重要的是从过去的事件中吸取教训，并作为旨在减轻灾害和风险有害影响的一套综合干预措施的一部分，有效管理风险。本研究以马龙德拉区为案例，探讨社区在应对气候变化对粮食安全影响方面的适应和应对策略。研究采用定性研究方法开展。数据从50人的群体中收集，包括小规模农户、Agritex官员、推广官员、非政府组织（NGO）代表、村级牧民和酋长。文献研究进行了主题分析。研究得出结论，气候变化对粮食安全产生了负面影响。它影响了粮食安全的所有四个维度，即粮食可供性、粮食可及性、粮食利用和粮食系统稳定性。作为回应，非政府组织、政府机构和其他行为体实施了旨在确保社区抵御气候灾害能力的各类项目，社区成员是关键利益相关者。研究建议继续动员社会保护干预措施，建设有韧性的农业系统以使其更能抵御气候变化，并改善环境管理，以确保减轻气候变化对粮食安全影响的努力取得实效。","Ngenani The Zimbabwe Ezekiel Guti Journal of Community Engagement and Societal Transformations",54,{"impact":18,"substance":103,"depth":56,"authority":20,"freshness":18,"relevant":21,"comment":314},"以津巴布韦Marondera区为案例的定性研究，探讨气候智慧型保护性农业对粮食安全四维度的影响，属区域案例研究，国际借鉴价值有限，不建议进入每日精选。",[316],{"name":311,"url":308},[318,319,320,321],"粮食安全","小农户","气候智慧农业","津巴布韦",{"code":323,"slug":324,"name":325,"path":326,"parent_code":158},"A8","yield-food-security","单产提升与粮食安全","\u002Ftopic\u002Ffield-crops\u002Fyield-food-security",[328],{"code":44,"slug":45,"name":46,"path":47,"parent_code":48},{"status":50,"locked":14,"version":51,"method":52,"evidence":330},{"candidates":331,"agricultural_evidence":57},[332,337,342,349,355,360],{"code":323,"score":178,"supported":57,"title":333,"abstract":335,"tags":336},[334],"food security",[318,334],[318],{"code":44,"score":18,"supported":57,"title":338,"abstract":340,"tags":341},[339],"conservation agriculture",[],[],{"code":343,"score":104,"supported":57,"title":344,"abstract":345,"tags":348},"H7",[],[346,347],"气候变化","climate change",[320],{"code":350,"score":296,"supported":57,"title":351,"abstract":352,"tags":354},"G2",[],[353],"smallholder",[319],{"code":200,"score":75,"supported":57,"title":356,"abstract":357,"tags":359},[],[358],"smart agriculture",[],{"code":361,"score":75,"supported":57,"title":362,"abstract":363,"tags":365},"I7",[],[364],"研究方法",[],[367,368],"Marondera 气候智慧农业","津巴布韦 小农户 粮食安全","Marondera气候智慧农业-5475","10.71458\u002Fwby9rf15",{"doi":370,"openalex_id":372,"authors":373,"venue":311,"cited_by_count":90,"oa_url":8,"card":380,"direction":386,"ingested_from":236},"W7223010488",[374,377],{"name":375,"orcid":376},"Irony Mazuruse","https:\u002F\u002Forcid.org\u002F0009-0007-5600-7825",{"name":378,"orcid":379},"Judith Chokumanyara","https:\u002F\u002Forcid.org\u002F0009-0000-7386-9960",{"tldr":381,"method":382,"finding":383,"direction":384,"opportunity":385},"研究津巴布韦Marondera地区小农户采用气候智能型保护性农业对粮食安全的影响。","定性研究，访谈50名小农户、推广员、NGO代表等，并进行主题分析。","气候变化损害粮食安全四个维度，多方项目提升了社区抗灾韧性。","农业绿色发展与碳","可量化气候智能型保护性农业对粮食安全四维度的贡献，并评估数字推广工具在其中的作用。","智慧农业 \u002F 农业物联网","2026-10-21T23:30:08.757283Z",{"id":389,"title":390,"url":391,"summary":392,"summary_zh":8,"content":393,"source_name":394,"source_url":8,"published_at":278,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":395,"score_detail":396,"sources":399,"tags":401,"primary_topic":407,"secondary_topics":412,"classification":414,"search_phrases":439,"slug":442,"view_count":90,"doi":8,"paper":8,"created_at":443},5440,"黑龙江农科院青贮大麦复种大豆模式熟化 后茬「龙豆27号」亩产 208.93 公斤","https:\u002F\u002Fwww.stdaily.com\u002Fweb\u002Fgdxw\u002F2026-10\u002F19\u002Fcontent_598876.html","由国家产业技术体系哈尔滨综合试验站站长孙丹带领的黑龙江省农科院团队，完成 3 月至 10 月青贮大麦复种大豆全年种植收获周期。哈尔滨双城区示范基地前茬「龙饲麦7号」平均亩产 1.8 吨，后茬早熟高油大豆「龙豆27号」经东北地理与农业生态所、东北农业大学、省农科院植保所与耕作栽培研究所等专家实收测产，平均亩产 208.93 公斤，较去年 201.2 公斤增长约 3.84%，再创历史新高。鹤岗军川农场 3000 亩规模化示范取得青贮大麦亩产 1.6 吨、大豆亩产 186.67 公斤。","近日，由国家产业技术体系哈尔滨综合试验站站长孙丹带领团队在哈尔滨市双城区、鹤岗军川农场等地开展的青贮大麦复种大豆试验示范顺利完成了3月至10月的全年种植收获周期。今年，该模式进一步扩大示范面积，标志着黑龙江省麦豆复种技术从创新突破迈向成熟应用，为寒地农业提高土地利用效率、实现粮食增产增效提供了成熟可靠的技术路径。\n\n今年，哈尔滨市双城区“大麦-大豆”复种技术示范基地迎来丰收测产。其中，6月收获的前茬青贮大麦“龙饲麦7号”平均亩产达1.8吨；后茬早熟高油大豆“龙豆27号”经中国科学院东北地理与农业生态研究所农业技术中心、东北农业大学、黑龙江省农业科学院植物保护研究所、省农业科学院耕作栽培研究所、双城区农业技术推广中心等单位专家组成的测产组现场实收测产，平均亩产达208.93公斤，较去年的201.2公斤增长约3.84%，再创历史新高。两茬作物均取得良好收成，前茬青贮大麦在干旱条件下仍保持较高产量，后茬大豆同比增产，进一步彰显了麦豆复种模式的稳产增收优势与推广应用潜力。\n\n实实在在的丰收成果，让麦豆复种模式有了更强的推广底气，也让越来越多农户看到了“一年双收”的增产潜力。示范成效的持续显现，进一步增强了农户对这一种植模式的信心。今年，在鹤岗军川农场的3000亩土地开展麦豆复种规模化示范，最终取得了前茬青贮大麦亩产1.6吨、后茬大豆亩产186.67公斤的良好收成。从最初的“不敢试、不会种、怕卖不出”，到如今敢于尝试、主动参与，农户种植信心的逐步增强，背后既离不开早熟高产品种的有力支撑，更得益于科研、政府、农户与企业的协同发力。\n\n麦豆复种模式的成功实践，离不开科技创新的有力支撑。黑龙江省农科院孙丹团队充分发挥科研优势，针对寒地生长季短、两茬作物茬口衔接紧等难题，提供适宜寒地种植的早熟青贮大麦和早熟高油大豆优良品种，并通过全程技术指导、田间培训和关键环节技术服务，为两茬作物高效衔接、稳产增收提供了坚实科技保障。在科研团队的示范引领下，当地政府积极推动、农户主动参与，麦豆复种模式逐步从试验示范走向规模化应用。同时，针对当地奶业新鲜饲草供应不足、依赖外购的现实需求，该模式通过粮饲兼顾、一地双收，有效拓宽了青贮饲料来源，为缓解季节性饲草供需矛盾、推动种养结合和农业增效、农民增收提供了新路径。","科技日报 2026-10-19",71,{"impact":103,"substance":397,"depth":178,"authority":17,"freshness":20,"relevant":21,"comment":398},20,"省级科研团队主导的麦豆复种模式规模化示范，含实测产量新数据与品种支撑，具推广参考价值，但属区域技术进展，时效稍滞后。",[400],{"name":394,"url":391},[402,403,404,405,406],"寒地农业","大豆育种","种养结合","青贮大麦","麦豆复种",{"code":408,"slug":409,"name":410,"path":411,"parent_code":158},"A4","soybean-oilseeds","大豆与油料","\u002Ftopic\u002Ffield-crops\u002Fsoybean-oilseeds",[413],{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},{"status":50,"locked":14,"version":51,"method":52,"evidence":415},{"candidates":416,"agricultural_evidence":57},[417,422,427,433],{"code":408,"score":17,"supported":57,"title":418,"abstract":420,"tags":421},[419],"大豆",[419],[403],{"code":31,"score":64,"supported":57,"title":423,"abstract":425,"tags":426},[424],"青贮",[424],[],{"code":428,"score":75,"supported":57,"title":429,"abstract":430,"tags":432},"F4",[],[431],"植保",[],{"code":434,"score":75,"supported":57,"title":435,"abstract":436,"tags":438},"H6",[],[437],"农业生态",[],[440,441],"黑龙江农科院 青贮大麦 复种大豆","龙豆27号 亩产 208.93公斤","黑龙江农科院青贮大麦复种大豆-5440","2026-10-21T00:10:01.631122Z"]