[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-1685":3,"related-1685":72},{"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":30,"secondary_topics":36,"classification":42,"search_phrases":66,"slug":69,"view_count":70,"doi":8,"paper":8,"created_at":71},1685,"广东农科院质标所：2 项饲料中兽药检测方法农业行业标准获批发布","https:\u002F\u002Fwww.gdaas.cn\u002Fkxyjn\u002Fkyjz\u002Fcontent\u002Fpost_1337498.html","广东省农业科学院质标所牵头起草的《饲料中左旋咪唑的测定》（NY\u002FT 3139-2026）和《饲料中盐酸异丙嗪、盐酸氯丙嗪、安眠酮、地西泮、盐酸硫利达嗪和奋乃静的测定》（NY\u002FT 1458-2026）两项农业行业标准经农业农村部第 1056 号公告正式发布，将于 2027 年 2 月 1 日起实施。两项标准聚焦饲料药物违规添加监管，将进一步完善我国饲料检测标准体系。",null,"[![Image 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[成果转化（孵化器）](http:\u002F\u002Fwww.gdaas.cn\u002Ffwsnn\u002Fcgzhfhq\u002Findex.html)\n\n|*   [党建群团](http:\u002F\u002Fwww.gdaas.cn\u002Fdjqt\u002Findex.html)\n\n![Image 10](https:\u002F\u002Fwww.gdaas.cn\u002Fpub\u002Fpos.png)[首页](http:\u002F\u002Fwww.gdaas.cn\u002F)>[科学研究](http:\u002F\u002Fwww.gdaas.cn\u002Fkxyjn\u002F)>[科研进展](http:\u002F\u002Fwww.gdaas.cn\u002Fkxyjn\u002Fkyjz\u002F)\n\n### 质标所2项饲料中兽药检测方法农业行业标准获批发布\n\n时间：2026-09-02 15:07 来源：质标所【字体：大 中 小】\n\n 分享到： \n\n近日，我院质标所牵头起草的《饲料中左旋咪唑的测定》（NY\u002FT 3139-2026）和《饲料中盐酸异丙嗪、盐酸氯丙嗪、安眠酮、地西泮、盐酸硫利达嗪和奋乃静的测定》（NY\u002FT 1458-2026）两项农业行业标准经农业农村部第1056号公告正式发布，将于2027年2月1日起实施，由全国饲料工业标准化技术委员会（SAC\u002FTC 76）归口。\n\n两项标准聚焦饲料药物违规添加监管，覆盖配合饲料、浓缩饲料、精料补充料、添加剂预混合饲料、混合型饲料添加剂和饲料原料。NY\u002FT 3139-2026 在高效液相色谱法基础上新增液相色谱-串联质谱确证方法，优化提取净化流程，为饲料中禁用促生长药物的精准监测提供技术手段。NY\u002FT 1458-2026 可同时进行饲料中盐酸异丙嗪、盐酸氯丙嗪、安眠酮、地西泮、盐酸硫利达嗪和奋乃静等6种药物的准确定性和定量测定，为打击饲料中精神类药物违法添加提供依据。\n\n两项标准的实施将进一步完善我国饲料检测标准体系。有助于推动饲料企业规范生产经营、保障畜禽养殖投入品安全，进而促进产业健康发展、提升我国饲料产品的市场竞争力，为守护人民群众“舌尖上的安全”提供有力技术支撑。\n\n![Image 11: 图片1.png](http:\u002F\u002Fwww.gdaas.cn\u002Fimg\u002F0\u002F885\u002F885398\u002F1337498.png)\n\n院属单位\n\n*   [水稻研究所](https:\u002F\u002Fwww.gdaas.cn\u002Fgdrice\u002F)\n*   [果树研究所](https:\u002F\u002Fwww.gdaas.cn\u002Fgdfruit\u002F)\n*   [蔬菜研究所](https:\u002F\u002Fwww.gdaas.cn\u002Fgdvri\u002F)\n*   [作物研究所](https:\u002F\u002Fwww.gdaas.cn\u002Fcrigdaas\u002F)\n*   [植物保护研究所](https:\u002F\u002Fwww.gdaas.cn\u002Fgdppri\u002F)\n*   [农业质量标准与监测技术研究所](https:\u002F\u002Fwww.gdaas.cn\u002Fnkyjczx\u002F)\n*   [设施农业研究所](https:\u002F\u002Fwww.gdaas.cn\u002Fgdaasifa\u002F)\n*   [动物科学研究所](https:\u002F\u002Fwww.gdaas.cn\u002Fgdias\u002F)\n*   [蚕业与农产品加工研究所](https:\u002F\u002Fwww.gdaas.cn\u002Fsrigaas\u002F)\n*   [农业资源与环境研究所](https:\u002F\u002Fwww.gdaas.cn\u002Fgdiare\u002F)\n*   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行业标准 质量安全 饲料检测","兽药残留 行业标准","兽药残留行业标准质量安全饲料检测-1685",2,"2026-09-05T00:04:38.446139Z",{"total":73,"page":21,"page_size":73,"items":74},6,[75,115,156,265,331,387],{"id":76,"title":77,"url":78,"summary":79,"summary_zh":8,"content":80,"source_name":81,"source_url":8,"published_at":11,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":82,"score_detail":83,"sources":86,"tags":88,"primary_topic":92,"secondary_topics":93,"classification":95,"search_phrases":110,"slug":113,"view_count":21,"doi":8,"paper":8,"created_at":114},1863,"两项饲料中兽药检测方法农业行业标准获批发布——广东农科院质标所牵头起草","https:\u002F\u002Fnews.sciencenet.cn\u002Fhtmlnews\u002F2026\u002F9\u002F570809.shtm","广东省农业科学院农业质量标准与监测技术研究所质标所牵头起草的《饲料中左旋咪唑的测定》(NY\u002FT 3139-2026)和《饲料中盐酸异丙嗪、盐酸氯丙嗪、安眠酮、地西泮、盐酸硫利达嗪和奋乃静的测定》(NY\u002FT 1458-2026)两项农业行业标准经农业农村部第1056号公告正式发布，将于2027年2月1日起实施。","[![Image 1: 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质标所有关负责人表示，两项标准的实施将进一步完善我国饲料检测标准体系，有助于推动饲料企业规范生产经营、保障畜禽养殖投入品安全，进而促进产业健康发展、提升我国饲料产品的市场竞争力。下一步，质标所将将配合主管部门做好标准宣贯培训与推广，持续为农产品质量安全保驾护航。 版权声明：凡本网注明“来源：中国科学报、科学网、科学新闻杂志”的所有作品，网站转载，请在正文上方注明来源和作者，且不得对内容作实质性改动；微信公众号、头条号等新媒体平台，转载请联系授权。邮箱：shouquan@stimes.cn。\n\n打印 发E-mail给：\n\n以下评论只代表网友个人观点，不代表科学网观点。\n\n 无标题页 \n\n[![Image 2](https:\u002F\u002Fnews.sciencenet.cn\u002Fimages\u002Fnewcomm.gif)](https:\u002F\u002Fnews.sciencenet.cn\u002Fhtml\u002Fcomment.aspx?id=570809)\n\n相关新闻 相关论文\n*   1\n*   [从“找问题”出发，他破解了一个60年数学物理难题](https:\u002F\u002Fnews.sciencenet.cn\u002Fhtmlnews\u002F2026\u002F9\u002F570797.shtm)\n\n*   2\n*   [人体不同组织结构衰老呈现三种模式](https:\u002F\u002Fnews.sciencenet.cn\u002Fhtmlnews\u002F2026\u002F9\u002F570796.shtm)\n\n*   3\n*   [6人，湖北省杰出人才奖推荐人选公示](https:\u002F\u002Fnews.sciencenet.cn\u002Fhtmlnews\u002F2026\u002F9\u002F570795.shtm)\n\n*   4\n*   [天津市公示第二批博士后创新岗位拟资助人选名单](https:\u002F\u002Fnews.sciencenet.cn\u002Fhtmlnews\u002F2026\u002F9\u002F570794.shtm)\n\n*   5\n*   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2026-09",72,{"impact":17,"substance":17,"depth":18,"authority":19,"freshness":84,"relevant":21,"comment":85},5,"两项饲料兽药检测行业标准发布，完善检测体系，保障养殖投入品安全，具有行业影响力。",[87],{"name":81,"url":78},[26,89,90,91],"饲料安全","兽药检测","农业标准",{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},[94],{"code":38,"slug":39,"name":40,"path":41,"parent_code":35},{"status":43,"locked":14,"version":44,"method":45,"evidence":96},{"candidates":97,"agricultural_evidence":50},[98,102,106],{"code":31,"score":19,"supported":50,"title":99,"abstract":100,"tags":101},[52],[52],[89],{"code":38,"score":56,"supported":50,"title":103,"abstract":104,"tags":105},[58],[],[],{"code":62,"score":21,"supported":14,"title":107,"abstract":108,"tags":109},[],[],[26],[111,112],"兽药检测 农业标准 行业标准 饲料安全","兽药检测 农业标准","兽药检测农业标准行业标准饲料安全-1863","2026-09-08T00:07:13.728134Z",{"id":116,"title":117,"url":118,"summary":119,"summary_zh":8,"content":120,"source_name":121,"source_url":8,"published_at":122,"category":123,"cover_url":8,"hotness":13,"is_selected":50,"score":124,"score_detail":125,"sources":130,"tags":132,"primary_topic":136,"secondary_topics":137,"classification":138,"search_phrases":150,"slug":153,"view_count":154,"doi":8,"paper":8,"created_at":155},5196,"中华人民共和国农业农村部公告 第1073号","https:\u002F\u002Fwww.moa.gov.cn\u002Fgovpublic\u002Fxmsyj\u002F202610\u002Ft20261016_6488649.htm","2026年10月15日农业农村部发布公告,自《中国兽药典(第七版)》三部公布之日起实施,2027年5月1日起申报兽用生物制品批准文号应按符合新版兽药典要求的、经核准的兽药注册标准进行样品检验,进一步规范兽药质量控制,提升行业监管水平。","根据《兽药管理条例》规定，我部组织完成《中华人民共和国兽药典（第七版）》（以下简称《中国兽药典（第七版）》）三部的编制工作，现予发布，自2027年5月1日起施行。现就有关事宜公告如下。\n\n一、《中华人民共和国兽药典》是兽药研制、生产（进口）、经营、使用和监督管理活动应遵循的法定技术标准。\n\n二、《中国兽药典（第七版）》三部收载兽用生物制品，包括凡例、品种正文和附录。其中，品种正文属于通用标准，是基于单一抗原制定的、适用于同类制品的兽药国家标准。\n\n三、自施行之日起，《中国兽药典（第七版）》三部未收载且未公布废止的品种标准，包括历版《中华人民共和国兽药典》三部、《兽药质量标准（2017年版）》生物制品卷、《中国兽用生物制品规程（2000年版）》收载的产品标准仍继续有效，但应符合《中国兽药典（第七版）》三部相关通用要求。\n\n《中国兽药典（第七版）》三部施行之日前，相关产品生产企业应及时开展标准对比研究工作，评估兽药注册标准是否符合《中国兽药典（第七版）》三部有关要求，并根据需要履行相关标准变更程序（见附件）。\n\n四、2027年5月1日起生产的有关兽药产品应同时符合《中国兽药典（第七版）》三部要求和经农业农村部核准的兽药注册标准。2027年4月30日（含）前生产的有关兽药产品可按原兽药质量标准进行检验，并在产品有效期内流通使用。\n\n五、2027年5月1日起申报兽用生物制品新兽药注册和进口兽药注册的，应符合《中国兽药典（第七版）》三部要求。\n\n六、2027年5月1日起申报兽用生物制品批准文号的，应按照符合《中国兽药典（第七版）》三部要求的、经农业农村部核准的兽药注册标准进行样品检验。换发兽药产品批准文号的，应提供符合《中国兽药典（第七版）》三部要求的技术文件。2027年4月30日（含）前申报的，兽药检验报告的执行标准可为原兽药注册标准，也可为符合《中国兽药典（第七版）》三部有关要求、经农业农村部新核准的兽药注册标准。\n\n七、各级畜牧兽医主管部门要积极做好《中国兽药典（第七版）》三部宣传贯彻和实施工作，收集和反馈相关问题和意见。中国兽药典委员会办公室应及时答复各地反映的有关问题，做好技术指导、标准勘误等工作。\n\n八、各兽药企业要认真执行《中国兽药典（第七版）》三部，不断提高兽药产品质量控制水平。","农业农村部(2026-10-15)","2026-10-15T00:00:00Z","政策",94,{"impact":126,"substance":127,"depth":128,"authority":18,"freshness":56,"relevant":21,"comment":129},28,24,19,"农业农村部发布第七版兽药典三部，属全国性兽药法定技术标准更新，条款与过渡安排具体，权威性和信息增量高，值得进入每日精选。",[131],{"name":121,"url":118},[26,133,134,135],"兽药典","兽药监管","兽用生物制品",{"code":38,"slug":39,"name":40,"path":41,"parent_code":35},[],{"status":43,"locked":14,"version":44,"method":45,"evidence":139},{"candidates":140,"agricultural_evidence":50},[141,146],{"code":38,"score":142,"supported":50,"title":143,"abstract":144,"tags":145},4,[],[58],[134],{"code":62,"score":21,"supported":14,"title":147,"abstract":148,"tags":149},[],[],[26],[151,152],"中国兽药典 第七版 三部","兽用生物制品 国家标准","中国兽药典第七版三部-5196",0,"2026-10-18T00:05:13.276915Z",{"id":157,"title":158,"url":159,"summary":160,"summary_zh":161,"content":8,"source_name":162,"source_url":159,"published_at":163,"category":164,"cover_url":8,"hotness":13,"is_selected":14,"score":165,"score_detail":166,"sources":172,"tags":174,"primary_topic":180,"secondary_topics":186,"classification":194,"search_phrases":231,"slug":234,"view_count":154,"doi":235,"paper":236,"created_at":264},5573,"Improving alfalfa nitrogen estimation with canopy structural priors from DSSAT–PROSAIL and UAV hyperspectral data","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.eja.2026.128375","Accurate estimation of nitrogen (N) concentration in alfalfa ( Medicago sativa L .) supports forage quality assessment and harvest scheduling. 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":167,"substance":168,"depth":169,"authority":170,"freshness":13,"relevant":21,"comment":171},16,22,18,14,"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。",[173],{"name":162,"url":159},[175,176,177,178,179],"智慧农业","农业人工智能","农业遥感","氮素监测","紫花苜蓿",{"code":181,"slug":182,"name":183,"path":184,"parent_code":185},"A7","forage-cropping","饲草与耕作制度","\u002Ftopic\u002Ffield-crops\u002Fforage-cropping","A",[187,193],{"code":188,"slug":189,"name":190,"path":191,"parent_code":192},"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":43,"locked":14,"version":44,"method":45,"evidence":195},{"candidates":196,"agricultural_evidence":50},[197,204,210,216,226],{"code":188,"score":169,"supported":50,"title":198,"abstract":200,"tags":203},[199],"hyperspectral",[201,202,199],"遥感","remote sensing",[177],{"code":181,"score":18,"supported":50,"title":205,"abstract":207,"tags":209},[206],"alfalfa",[208,206],"苜蓿",[179],{"code":31,"score":13,"supported":50,"title":211,"abstract":212,"tags":215},[],[213,208,214],"饲草","forage",[179],{"code":217,"score":13,"supported":50,"title":218,"abstract":219,"tags":225},"I2",[],[220,221,222,223,224],"深度学习","机器学习","machine learning","deep learning","decision support",[176],{"code":227,"score":21,"supported":14,"title":228,"abstract":229,"tags":230},"I1",[],[],[175],[232,233],"DSSAT PROSAIL 苜蓿 氮素","无人机 高光谱 苜蓿","DSSATPROSAIL苜蓿氮素-5573","10.1016\u002Fj.eja.2026.128375",{"doi":235,"openalex_id":237,"authors":238,"venue":162,"cited_by_count":154,"oa_url":159,"card":257,"direction":261,"ingested_from":263},"W7223154576",[239,241,243,245,247,250,252,255],{"name":240,"orcid":8},"Shuai Fu",{"name":242,"orcid":8},"Yunhao Li",{"name":244,"orcid":8},"Chunli Miao",{"name":246,"orcid":8},"Jie Liu",{"name":248,"orcid":249},"Tiangang Liang","https:\u002F\u002Forcid.org\u002F0000-0001-5599-6587",{"name":251,"orcid":8},"Yongjia Hu",{"name":253,"orcid":254},"Qisheng Feng","https:\u002F\u002Forcid.org\u002F0009-0000-1391-9591",{"name":256,"orcid":8},"吴彩霞",{"tldr":258,"method":259,"finding":260,"direction":261,"opportunity":262},"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":266,"title":267,"url":268,"summary":269,"summary_zh":8,"content":270,"source_name":271,"source_url":8,"published_at":272,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":273,"score_detail":274,"sources":277,"tags":279,"primary_topic":284,"secondary_topics":285,"classification":298,"search_phrases":326,"slug":329,"view_count":154,"doi":8,"paper":8,"created_at":330},5519,"四川农科院资环所赴简阳调研 推进粗饲料加工与种养循环落地","https:\u002F\u002Fwww.chinawestagr.com\u002Ftszl\u002Fshowts.asp?id=67504","10月9日院资环所（草业所）副所长朱永群一行赴简阳市平泉街道调研座谈，汇报「天府农科」四川省平原丘陵区粗饲料加工利用研究院项目建设进展。三方就共建饲草料加工示范点、推进种草养猪等绿色循环项目达成共识，强调立足实际选准主导品种与技术模式，形成「饲料—养殖—粪肥—农田」闭环，把示范基地建成可学可复制的样板。","λԺʻ                ʱ䣺2026\u002F10\u002F16331\n\nΪ᳹ʵҹƶDzݲҵչľ߲𣬼ӿƼɹת2026109գԺʻҵȺоԱһиƽȪ̸ֵƽȪֵίֵ֣ίǡ´¼ֵũҵۺϷġͩйظͬ־пũƼ޹˾³¡ܾˣԺʻҵƹܿƿƳ޸㸱оԱҵ̷оʿȲμӡ\n\nϣ㱨“‘츮ũ’ĴʡƽԭϼӹоԺĿ”Ľ豳岼ֺ½չ¶³˹˾ҵͺϣDzϼӹʾ㣬ӿƽֲɫѭĿ˽ֵԴͲҵʾֵոԴḻֳϺãDzֲϻôַţϣڼ˲ϵõԺֵ֧֣õءùϡ\n\nȺڽָҪʵѡ׼ƷֺͼģʽḻDzϲƷߣͻ“Բݴ”ѭγ“—ֳ——ũ”ջעر׼ƶƷʾؽɿѧɸƵ塣","四川省农业科学院 2026-10-20","2026-10-20T00:00:00Z",49,{"impact":19,"substance":13,"depth":56,"authority":275,"freshness":73,"relevant":21,"comment":276},13,"省级科研机构赴地方推进粗饲料加工与种养循环落地的调研通稿，有具体合作与示范意图，但属区域性进展，信息增量有限，不宜进入每日精选。",[278],{"name":271,"url":268},[280,281,282,283],"院企合作","科技成果转化","种养循环","粗饲料加工",{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},[286,292],{"code":287,"slug":288,"name":289,"path":290,"parent_code":291},"E1","food-processing","加工与食品制造","\u002Ftopic\u002Ffood-supply\u002Ffood-processing","E",{"code":293,"slug":294,"name":295,"path":296,"parent_code":297},"H8","sustainable-agriculture","可持续与保护性农业","\u002Ftopic\u002Fenvironment\u002Fsustainable-agriculture","H",{"status":43,"locked":14,"version":44,"method":45,"evidence":299},{"candidates":300,"agricultural_evidence":50},[301,305,309,314,321],{"code":31,"score":170,"supported":50,"title":302,"abstract":303,"tags":304},[52],[52,213],[],{"code":287,"score":49,"supported":50,"title":306,"abstract":307,"tags":308},[283],[283],[],{"code":293,"score":310,"supported":50,"title":311,"abstract":312,"tags":313},9,[282],[],[282],{"code":315,"score":316,"supported":50,"title":317,"abstract":318,"tags":320},"C1",3,[],[319],"养猪",[],{"code":322,"score":70,"supported":14,"title":323,"abstract":324,"tags":325},"G1",[],[],[281,280],[327,328],"四川省农科院 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