[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-250":3,"related-250":101},{"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":33,"secondary_topics":39,"classification":40,"search_phrases":95,"slug":98,"view_count":99,"doi":8,"paper":8,"created_at":100},250,"农业农村部答复关于构建多元化食物供给体系的建议——落实大食物观,部署科技创新+多元食物开发两大主线","https:\u002F\u002Fwww.toutiao.com\u002Farticle\u002F7669817205516747299","农业农村部答复于东霞代表提出的关于构建多元化食物供给体系的建议,经商国家林草局,围绕\"加大农业科技创新力度,夯实粮食生产能力\"与\"拓展食物来源渠道,提高多元食物供给能力\"两大主线部署:深入实施农机装备补短板行动,推动具备自主感知、智能决策的农机装备产业化应用;加快发展现代设施农业,2025年落实超长期特别国债资金15.2亿元支持21省份54县开展种植业老旧设施更新改造,积极探索利用戈壁、荒漠等非耕地发展现代设施农业;推进畜牧业提档升级,印发《生猪产能综合调控实施方案(2026年修订)》,成立生猪产业监测预警专家咨询委员会;实施肉牛肉羊增量提质行动,推动粮改饲项目,将青贮玉米纳入粮食安全党政同责考核。",null,"![Image 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促进木本粮油和林下经济高质量发展的意见》，鼓励利用各类适宜林地发展木本粮油和林下经济。2022年，印发《加快油茶产业发展三年行动方案（2023—2025年）》，推动油茶产业高质量发展。2025年，印发《关于金融支持林业高质量发展的通知》，加大对经济林果等森林食品产业的信贷支持力度，印发《关于促进林下经济发展的若干措施》，明确用林、用地等8个方面支持措施。下一步，我部将会同有关部门，实施畜禽养殖提质增效等项目，引导湖泊水库资源丰富的地区因地制宜发展大水面生态渔业，支持在沿海重点渔区集中建设一批辐射带动作用明显的海上牧场。国家林草局将进一步加强政策引导、要素保障、科技支撑，促进林下经济和森林食品产业高质量发展，进一步做大森林“粮库”。\n\n**三、关于加强全产业链建设，构建现代农业大产业体系**\n\n坚持全链打造，深度开发，充分开发农业多种功能，提升产供储加销全产业链韧性和弹性。**一是提升农产品加工水平。**2024年，印发《促进农产品加工业发展三年行动方案（2024—2026年）》，协同推进农产品生产和加工。印发《农产品产地加工项目入库指南》和《农产品产地加工项目重点建设内容目录》，引导中央财政衔接推进乡村振兴补助资金更多用于农产品产地加工。**二是推进产业集聚发展。**截至2026年，会同财政部安排中央财政奖补资金，累计支持各地建设300个优势特色产业集群、400个现代农业产业园和2109个农业产业强镇项目。加大龙头企业培育力度，截至2025年底，全国累计培育县级以上龙头企业9.8万家，其中国家重点龙头企业2250家。**三是加强农产品冷链物流建设。**持续推进农产品产地冷链物流建设，重点支持建设一批产地冷藏保鲜设施，推动建设一批产地冷链集配中心，建设培育一批农产品骨干冷链物流关键枢纽，指导各地特别是欠发达地区谋划一批产地冷藏保鲜设施建设项目和产地冷链集配中心建设项目。截至2025年底，向金融机构推选的冷链重点项目累计获贷款授信超2248亿元，用信超1372亿元。下一步，我部将扎实推进促进农产品加工业发展行动，支持新建一批优势特色产业集群、现代农业产业园、农业产业强镇项目。编制“十五五”全国农产品产地市场体系发展规划，制定关于深入推进农产品产地冷链物流发展的意见，组织开展产地冷链重大项目金融对接活动。\n\n**四、关于推动粮食节约减损，确保全链条提质增效**\n\n深入贯彻习近平总书记关于粮食节约减损重要指示精神，抓好《粮食节约和反食品浪费行动方案》落实，推动粮食节约减损取得积极成效。**一是扎实推进机收减损。**加力推进农机购置与应用补贴“优机优补”、“有进有出”和老旧农机报废更新，加快高效低损适用收获机械研发制造和推广应用。2025年全国小麦、水稻、玉米平均机收损失率同比分别下降0.09个、0.11个和0.15个百分点，近三年小麦、水稻、玉米三大主粮机收减损合计达2500万吨以上。**二是深入推进饲料粮减量替代。**深入实施饲用豆粕减量替代行动，组织开展精准配方低蛋白日粮技术体系的示范推广，制定发布低蛋白日粮技术标准和规范。印发《关于实施养殖业节粮行动的意见》，推行“提效、开源、优化结构”等措施。开发利用新型蛋白饲料资源，开展餐余食物等资源饲料化利用试点，新蛋白饲料产品产能达20万吨。**三是加强科普宣传推广。**在第二十二届中国国际农产品交易会设立践行大食物观展区，依托中国农学会举办多元食物开发学术研讨暨新成果发布活动，组织开展“二十四节气中的大食物”系列宣传等，推广多元食物开发成果和营养健康消费理念。深入挖掘各地典型做法，形成一批可复制可推广的典型案例。下一步，我部将持续推进饲料粮减量替代，全面推广低蛋白日粮技术，稳步开发新型蛋白饲料，优化草食家畜饲草料结构，减少饲料粮消耗。加强典型推介与宣传引导，引导公众养成科学合理膳食习惯。\n\n感谢您对我部工作的关心，希望继续对“三农”工作给予支持。\n\n来源：农业农村部网站\n\n![Image 2](https:\u002F\u002Fp3-sign.toutiaoimg.com\u002Ftos-cn-i-6w9my0ksvp\u002F3632344baf324587bfd6a73e79fc48a8~tplv-tt-origin-web:gif.jpeg?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1786666717&x-signature=0D%2FLo4Ch6liSdiASlu4G2UC2%2FBI%3D)\n\n《中国农民合作社》期刊","中国农民合作社 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(2026) 开发一种基于区域特定计算机视觉特征的牛肉牛体况自动评分(BCS)方法。研究通过 YOLO 检测 + 深度估计提取脊柱、尾根、体廓等区域特征,使用 SHAP 进行可解释 AI 分析,并以 XGBoost 融合。在 5 折交叉验证中两种模式均稳定。验证集仅 72 只动物且极端值样本少,深度图来自推断而非实测。框架可作为后续发展的方法学基础。DOI: 10.1016\u002Fj.atech.2026.102628。","Smart Agricultural Technology Vol.15 Article 102628 2026-10-15","2026-10-15T00:00:00Z",{"impact":245,"substance":114,"depth":222,"authority":223,"freshness":21,"relevant":22,"comment":379},"方法学上有新意，但验证样本仅72头且深度图为推断值，属细分领域论文进展，未达每日精选门槛。",[381],{"name":376,"url":374},[383,228,384,385,386],"智慧农业","计算机视觉","肉牛养殖","体况评分",{"code":34,"slug":35,"name":36,"path":37,"parent_code":38},[389],{"code":236,"slug":237,"name":238,"path":239,"parent_code":240},{"status":41,"locked":42,"version":43,"method":44,"evidence":391},{"candidates":392,"agricultural_evidence":14},[393,397,401],{"code":236,"score":18,"supported":14,"title":394,"abstract":395,"tags":396},[384,251],[384,251],[228,384],{"code":34,"score":245,"supported":14,"title":398,"abstract":399,"tags":400},[50],[50],[385],{"code":402,"score":22,"supported":42,"title":403,"abstract":404,"tags":405},"I1",[],[],[383],[407,408],"YOLO 深度估计 牛体况评分","牛肉牛 计算机视觉 BCS","YOLO深度估计牛体况评分-5363",{"doi":8,"openalex_id":8,"authors":411,"venue":8,"cited_by_count":194,"oa_url":8,"card":412,"direction":416,"ingested_from":266},[],{"tldr":413,"method":414,"finding":415,"direction":416,"opportunity":417},"用YOLO检测与深度估计提取牛体区域特征，实现肉牛体况自动评分。","YOLO检测、深度估计、SHAP可解释分析与XGBoost融合，5折交叉验证。","区域特征融合评分稳定，但验证集仅72头且深度图为推断值。","农业遥感与作物表型","可引入实测深度传感器与更大样本，提升极端体况评分鲁棒性。","2026-10-20T02:47:54.361149Z"]