[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-117":3,"related-117":51},{"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":8,"secondary_topics":31,"classification":32,"search_phrases":45,"slug":48,"view_count":49,"doi":8,"paper":8,"created_at":50},117,"中国科学院高彩霞团队首次提出'可编程植物合成免疫'新理念","https:\u002F\u002Fwww.cas.cn\u002Fcm\u002F202607\u002Ft20260730_5117475.shtml","中国科学院遗传与发育生物学研究所高彩霞团队首次提出'可编程植物合成免疫'新理念,建立可编程合成植物免疫受体(SPIR)设计平台,实现了植物免疫受体的精准定制化设计,突破天然抗病基因资源瓶颈,相关研究近日在线发表于《科学》。",null,"[PC](https:\u002F\u002Fwww.cas.cn\u002Fcm\u002F202607\u002Ft20260730_5117475.shtml#) \u002F [English](http:\u002F\u002Fenglish.cas.cn\u002F) \u002F [联系我们](https:\u002F\u002Fwww.cas.cn\u002Flx\u002F) \u002F[网站地图](https:\u002F\u002Fwww.cas.cn\u002Fwz\u002F) \u002F[邮箱](https:\u002F\u002Fmail.cstnet.cn\u002F) 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[人事任免](https:\u002F\u002Fwww.cas.cn\u002Fxxgkml\u002Fzgkxyyb\u002Frsrc\u002Frsrm\u002F)\n*   [人才招聘](https:\u002F\u002Fwww.cas.cn\u002Fxxgkml\u002Fzgkxyyb\u002Frsrc\u002Frczp\u002F)\n*   [招生与培养](https:\u002F\u002Fwww.cas.cn\u002Fxxgkml\u002Fzgkxyyb\u002Frsrc\u002Fzsypy\u002F)\n\n国际合作\n\n*   [国际组织](https:\u002F\u002Fwww.cas.cn\u002Fxxgkml\u002Fzgkxyyb\u002Fgjhz\u002Fgjzz\u002F)\n*   [政策法规](https:\u002F\u002Fwww.cas.cn\u002Fxxgkml\u002Fzgkxyyb\u002Fgjhz\u002Fzc\u002F)\n\n[首页](https:\u002F\u002Fwww.cas.cn\u002F \"首页\")>[传媒扫描](https:\u002F\u002Fwww.cas.cn\u002Fcm\u002F \"传媒扫描\")\n\n## 【中国科学报】新技术让植物免疫系统实现“按需定制”\n\n2026年07月30日 来源： 中国科学报 冯丽妃\n\n浏览量：138\n\n【字体：大 中 小】\n\n![Image 36](https:\u002F\u002Fwww.cas.cn\u002Fimages\u002Fz19_xfbb_1.png)\n语音播报\n\n![Image 37](https:\u002F\u002Fwww.cas.cn\u002Fimages\u002Fz19_xfbb_2.png)\n\n中国科学院遗传与发育生物学研究所研究员高彩霞团队首次提出“可编程植物合成免疫”新理念，建立可编程合成植物免疫受体（SPIR）设计平台，实现了植物免疫受体的精准定制化设计，突破天然抗病基因资源瓶颈，为快速应对新发及变异病原病害提供了全新技术路线。相关研究近日在线发表于《科学》。\n\n植物病害每年给全球农业造成数千亿美元经济损失，传统抗病育种高度依赖天然存在的抗病基因，其主要编码核苷酸结合富亮氨酸重复序列（NLR）免疫受体。但已鉴定的抗病基因数量有限，且病原物不断变异，导致抗性容易被突破。攻克“精准靶向设计植物免疫受体”这一科学难题，成为领域内长期的目标。\n\n高彩霞团队另辟蹊径，聚焦一类非典型NLR免疫受体中的“整合诱饵”结构域。该结构域体积小、功能独立，具备良好的模块化改造潜力。研究团队借助人工智能蛋白质设计工具，针对预测的病原蛋白结构从头设计结合蛋白，并将其作为人工“诱饵”整合至水稻免疫受体Pikm-1中，形成全新的合成免疫受体。整个设计过程无需依赖已有抗病基因，仅凭病原蛋白的预测结构信息即可完成，实现了植物免疫受体的可编程精准定制化创制。\n\n为验证平台可行性，研究团队首先针对马铃薯Y病毒衣壳蛋白设计48个SPIR，其中11个能特异性识别靶标并激活植物免疫反应。随后，他们进一步针对13种重要植物病毒以及细菌、真菌、卵菌等病原物的蛋白，共设计并测试391个SPIR，成功率达18.2%，首次证明人工智能辅助设计可实现植物免疫受体从头创制。\n\n针对部分SPIR存在的免疫活性不足、自激活等短板，研究团队将SPIR平台与前期开发的植物体内定向进化系统GRAPE相结合，显著增强了SPIR对病原蛋白的免疫活性，并有效降低了其自激活水平，完善了“设计-构建-测试-进化”全流程体系。进一步实验表明，不同SPIR具有高度特异性，且可通过基因叠加同时识别多种病原；表达SPIR的植物能有效抵御相应病毒的侵染，展现出在作物抗病改良中的良好应用前景。\n\n相关论文信息：https:\u002F\u002Fdoi.org\u002F10.1126\u002Fscience.aee1792\n\n（原载于《中国科学报》 2026-07-30 第1版 要闻）\n\n中国科学院遗传与发育生物学研究所研究员高彩霞团队首次提出“可编程植物合成免疫”新理念，建立可编程合成植物免疫受体（SPIR）设计平台，实现了植物免疫受体的精准定制化设计，突破天然抗病基因资源瓶颈，为快速应对新发及变异病原病害提供了全新技术路线。相关研究近日在线发表于《科学》。植物病害每年给全球农业造成数千亿美元经济损失，传统抗病育种高度依赖天然存在的抗病基因，其主要编码核苷酸结合富亮氨酸重复序列（NLR）免疫受体。但已鉴定的抗病基因数量有限，且病原物不断变异，导致抗性容易被突破。攻克“精准靶向设计植物免疫受体”这一科学难题，成为领域内长期的目标。高彩霞团队另辟蹊径，聚焦一类非典型NLR免疫受体中的“整合诱饵”结构域。该结构域体积小、功能独立，具备良好的模块化改造潜力。研究团队借助人工智能蛋白质设计工具，针对预测的病原蛋白结构从头设计结合蛋白，并将其作为人工“诱饵”整合至水稻免疫受体Pikm-1中，形成全新的合成免疫受体。整个设计过程无需依赖已有抗病基因，仅凭病原蛋白的预测结构信息即可完成，实现了植物免疫受体的可编程精准定制化创制。为验证平台可行性，研究团队首先针对马铃薯Y病毒衣壳蛋白设计48个SPIR，其中11个能特异性识别靶标并激活植物免疫反应。随后，他们进一步针对13种重要植物病毒以及细菌、真菌、卵菌等病原物的蛋白，共设计并测试391个SPIR，成功率达18.2%，首次证明人工智能辅助设计可实现植物免疫受体从头创制。针对部分SPIR存在的免疫活性不足、自激活等短板，研究团队将SPIR平台与前期开发的植物体内定向进化系统GRAPE相结合，显著增强了SPI","中国科学报 2026-07-30","2026-07-30T01:00:00Z","论文",10,true,92,{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":21,"relevant":22,"comment":23},28,23,18,14,9,1,"中科院团队提出植物合成免疫新理念，属重大科研突破，影响深远，信息增量大，权威性高，时效性好。",[25],{"name":10,"url":6},[27,28,29,30],"人工智能","植物免疫","蛋白质设计","中国科学院",[],{"status":33,"locked":34,"version":35,"method":36,"evidence":37},"needs_review",false,"2026-10-22.2","rules",{"candidates":38,"agricultural_evidence":34,"reason":44},[39],{"code":40,"score":22,"supported":34,"title":41,"abstract":42,"tags":43},"I2",[],[],[27],"农业相关性需要复核",[46,47],"中国科学院 蛋白质设计 人工智能 植物免疫","中国科学院 蛋白质设计","中国科学院蛋白质设计人工智能植物免疫-117",13,"2026-07-31T00:00:56.152836Z",{"total":52,"page":22,"page_size":52,"items":53},6,[54,118,198,244,286,370],{"id":55,"title":56,"url":57,"summary":58,"summary_zh":59,"content":8,"source_name":60,"source_url":57,"published_at":61,"category":12,"cover_url":8,"hotness":13,"is_selected":34,"score":62,"score_detail":63,"sources":65,"tags":67,"primary_topic":8,"secondary_topics":70,"classification":71,"search_phrases":95,"slug":98,"view_count":62,"doi":99,"paper":100,"created_at":117},5191,"Artificial intelligence in immovable cultural heritage research: a bibliometric and knowledge mapping review","https:\u002F\u002Fdoi.org\u002F10.1186\u002Fs43238-026-00324-1","Abstract In recent years, the application of artificial intelligence (AI) in immovable cultural heritage research has expanded rapidly, supporting new approaches to heritage documentation, condition assessment, conservation, management, and public communication. In this study, immovable cultural heritage primarily refers to historic buildings, archaeological sites, monuments, cultural landscapes, and other heritage places with fixed spatial locations. Movable cultural objects, museum collections, and intangible cultural heritage are not systematically examined unless the relevant studies directly address the documentation, monitoring, restoration, conservation, or management of immovable heritage. Despite the growing volume of research, existing studies have largely focused on individual technical applications, while comprehensive bibliometric analyses and knowledge-structure mapping from a global perspective remain limited. To address this gap, this study retrieved 382 English-language publications from the Web of Science Core Collection covering the period from 1 January 2015 to 1 October 2025. Using bibliometric methods and analytical tools including VOSviewer, CiteSpace, and ArcGIS, the study examines publication trends, geographical distribution, disciplinary categories, major authors, institutional affiliations, collaboration networks, thematic evolution, and emerging research topics. The results show that publication output increased substantially after 2020. China, Italy, and Spain were among the most productive countries and occupied important positions in the international collaboration network. Major research themes included digital heritage, structural health monitoring, virtual reconstruction, deep learning, remote sensing, and sustainability-related applications. These findings indicate that AI-related research on immovable cultural heritage is strongly represented in engineering, conservation science, computer science, remote sensing, and related technical fields. However, this pattern should not be interpreted as evidence of a general disciplinary shift across cultural heritage studies as a whole. Rather, it reflects the technological orientation of the literature captured by the present search strategy, which was limited to English-language publications indexed in the Web of Science Core Collection. This study maps the development and knowledge structure of AI applications in immovable cultural heritage research and provides quantitative evidence for identifying major research areas, collaboration patterns, methodological tendencies, and future research needs.","摘要 近年来，人工智能（AI）在不可移动文物保护研究中的应用迅速扩展，为遗产记录、状况评估、保护、管理和公众传播提供了新的方法路径。本研究中的不可移动文物主要指历史建筑、考古遗址、纪念物、文化景观及其他具有固定空间位置的遗产场所。可移动文物、博物馆藏品和非物质文化遗产不在系统考察范围内，除非相关研究直接涉及不可移动遗产的记录、监测、修复、保护或管理。尽管研究数量不断增长，现有研究大多聚焦于单项技术应用，而从全球视角开展的综合文献计量分析和知识结构图谱仍较为有限。为弥补这一空白，本研究从Web of Science核心合集检索了2015年1月1日至2025年10月1日期间的382篇英文文献，运用文献计量方法及VOSviewer、CiteSpace和ArcGIS等分析工具，考察了发文趋势、地理分布、学科类别、主要作者、机构隶属、合作网络、主题演化及新兴研究议题。结果表明，2020年后发文量显著增长。中国、意大利和西班牙是发文量最高的国家之一，并在国际合作网络中占据重要位置。主要研究主题包括数字遗产、结构健康监测、虚拟重建、深度学习、遥感及可持续性相关应用。这些发现表明，AI相关的不可移动文物研究在工程学、保护科学、计算机科学、遥感及相关技术领域具有较强的代表性。然而，这一格局不应被解释为整个文化遗产研究领域普遍发生学科转向的证据，而是反映了本研究所采用的检索策略所捕获文献的技术导向，该策略仅限于Web of Science核心合集收录的英文文献。本研究梳理了AI在不可移动文物保护研究中的应用发展与知识结构，并提供了定量证据","Built Heritage","2026-10-15T00:00:00Z",0,{"impact":62,"substance":62,"depth":62,"authority":62,"freshness":62,"relevant":62,"comment":64},"该文研究不可移动文化遗产领域的AI文献计量，与三农、农业信息化、智慧农业、数字乡村无关，相关性门槛未通过。",[66],{"name":60,"url":57},[27,68,69],"文献计量","文化遗产",[],{"status":33,"locked":34,"version":35,"method":36,"evidence":72},{"candidates":73,"agricultural_evidence":34,"reason":44},[74,81,88],{"code":40,"score":19,"supported":14,"title":75,"abstract":77,"tags":80},[76],"artificial intelligence",[78,79,76],"深度学习","deep learning",[27],{"code":82,"score":83,"supported":14,"title":84,"abstract":86,"tags":87},"I7",15,[85],"bibliometric",[68,85],[68],{"code":89,"score":52,"supported":14,"title":90,"abstract":91,"tags":94},"I3",[],[92,93],"遥感","remote sensing",[],[96,97],"不可移动文物 人工智能","人工智能 文化遗产 文献计量","不可移动文物人工智能-5191","10.1186\u002Fs43238-026-00324-1",{"doi":99,"openalex_id":101,"authors":102,"venue":60,"cited_by_count":62,"oa_url":108,"card":109,"direction":115,"ingested_from":116},"W7222247878",[103,106],{"name":104,"orcid":105},"Yating Wen","https:\u002F\u002Forcid.org\u002F0009-0003-0289-3199",{"name":107,"orcid":8},"Marzudi Md Yunus","https:\u002F\u002Flink.springer.com\u002Fcontent\u002Fpdf\u002F10.1186\u002Fs43238-026-00324-1.pdf",{"tldr":110,"method":111,"finding":112,"direction":113,"opportunity":114},"用文献计量与知识图谱方法梳理2015-2025年AI在不可移动文化遗产研究中的应用格局。","Web of Science核心合集382篇英文文献，用VOSviewer、Ci","2020年后发文量激增，中意西三国领先，主题集中于数字遗产、结构健康监测、虚拟重建、深度学习与遥感。","其他","可借鉴其遥感与深度学习主题，探索AI在农业文化遗产、传统村落等不可移动农业遗产监测保护中的空白。","数字乡村与农业信息化","openalex","2026-10-17T23:30:41.024676Z",{"id":119,"title":120,"url":121,"summary":122,"summary_zh":123,"content":8,"source_name":124,"source_url":121,"published_at":125,"category":12,"cover_url":8,"hotness":13,"is_selected":34,"score":126,"score_detail":127,"sources":130,"tags":132,"primary_topic":137,"secondary_topics":143,"classification":144,"search_phrases":159,"slug":162,"view_count":62,"doi":163,"paper":164,"created_at":197},4894,"Asymptomatic colonization by Botrytis cinerea reveals polarized plant-fungus interfaces before widespread disease","https:\u002F\u002Fdoi.org\u002F10.64898\u002F2026.10.12.758352","Botrytis cinerea is a necrotrophic pathogen whose destructive growth is typically studied under conditions that rapidly generate visible disease. Yet symptomless associations are well documented, the fungal and host processes operating before widespread tissue collapse remain poorly resolved. We developped an intact Arabidopsis thaliana seedling pathosystem that extends the interval between infection establishment and widespread visible disease. Fungal colonization was quantified using qPCR and a constitutively bioluminescent reporter strain, together with longitudinal plant phenotyping, hormone profiling and multiscale fluorescence microscopy. Substantial fungal colonization occurred while seedlings remained largely green and continued to grow, whereas robust whole seedling accumulation of salicylic and jasmonic acids occurred later. During this interval, B. cinerea displayed diverse tissue-associated infection morphologies. At individual contact sites, fungal walls showed heterogeneous exposure of chitin-associated epitopes, while host cells exhibited focal plasma-membrane polarization toward fungal contact sites, together with cortical actin reorganization. These results show that the interval preceding widespread visible disease is an active and spatially heterogeneous interaction state, in which substantial fungal development and highly organized local host responses are already established. Intact seedlings therefore provide a powerful system for resolving plant-pathogen interactions that are largely obscured in rapid disease assays.","灰葡萄孢（Botrytis cinerea）是一种死体营养型病原菌，其破坏性生长通常在迅速产生可见病害的条件下进行研究。然而，无症状关联已有充分记载，在组织大面积崩溃之前真菌与宿主所进行的过程仍鲜有阐明。我们建立了一个完整的拟南芥（Arabidopsis thaliana）幼苗病理系统，延长了侵染建立与大面积可见病害之间的时间间隔。利用qPCR和组成型生物发光报告菌株对真菌定殖进行定量，并结合纵向植物表型分析、激素谱分析和多尺度荧光显微镜。在幼苗大部分仍保持绿色并持续生长期间，真菌已发生大量定殖，而整株幼苗中水杨酸和茉莉酸的大量积累则出现较晚。在此期间，灰葡萄孢表现出多样的组织相关侵染形态。在单个接触位点，真菌细胞壁显示出几丁质相关表位的异质性暴露，而宿主细胞则表现出质膜向真菌接触位点的局灶性极化，并伴随皮层肌动蛋白重组。这些结果表明，大面积可见病害出现之前的间隔期是一个活跃且空间异质的互作状态，其中大量的真菌发育和高度有序的局部宿主反应已经建立。因此，完整幼苗为解析在快速病害测定中大多被掩盖的植物-病原菌互作提供了一个强有力的系统。","bioRxiv (Cold Spring Harbor Laboratory)","2026-10-13T00:00:00Z",80,{"impact":19,"substance":128,"depth":19,"authority":49,"freshness":21,"relevant":22,"comment":129},22,"该研究揭示灰霉病菌无症状定殖阶段的植物-真菌互作机制，方法新颖、结论可靠，对设施农业病害绿色防控与抗病育种有参考价值，但属基础研究，产业影响有限。",[131],{"name":124,"url":121},[133,28,134,135,136],"设施农业","抗病育种","植物病理","灰霉病",{"code":138,"slug":139,"name":140,"path":141,"parent_code":142},"B2","fruit","果树","\u002Ftopic\u002Fhorticulture\u002Ffruit","B",[],{"status":145,"locked":34,"version":35,"method":36,"evidence":146},"classified",{"candidates":147,"agricultural_evidence":14},[148,154],{"code":138,"score":149,"supported":14,"title":150,"abstract":151,"tags":153},3,[],[152],"葡萄",[],{"code":155,"score":22,"supported":34,"title":156,"abstract":157,"tags":158},"F2",[],[],[134],[160,161],"Botrytis cinerea Arabidopsis 无症状定殖","灰霉病 无症状 侵染机制","BotrytiscinereaArabidopsis无症状定殖-4894","10.64898\u002F2026.10.12.758352",{"doi":163,"openalex_id":165,"authors":166,"venue":124,"cited_by_count":62,"oa_url":189,"card":190,"direction":196,"ingested_from":116},"W7221591933",[167,169,171,173,175,177,179,182,184,186],{"name":168,"orcid":8},"Tguafaiti Ines",{"name":170,"orcid":8},"Ferdinand Perrine",{"name":172,"orcid":8},"Adrien Pons",{"name":174,"orcid":8},"Malbert Bastien",{"name":176,"orcid":8},"de Vallée Amélie",{"name":178,"orcid":8},"Christophe Bruel",{"name":180,"orcid":181},"Mathias Choquer","https:\u002F\u002Forcid.org\u002F0000-0002-3768-160X",{"name":183,"orcid":8},"Poussereau Nathalie",{"name":185,"orcid":8},"Bournaud Caroline",{"name":187,"orcid":188},"François Gillet","https:\u002F\u002Forcid.org\u002F0000-0002-3334-1069","https:\u002F\u002Fwww.biorxiv.org\u002Fcontent\u002Fbiorxiv\u002Fearly\u002F2026\u002F10\u002F13\u002F2026.10.12.758352.full.pdf",{"tldr":191,"method":192,"finding":193,"direction":194,"opportunity":195},"构建拟南芥幼苗病理系统，揭示灰霉病菌无症状定殖期的植物-真菌互作。","拟南芥幼苗活体接种、qPCR、生物发光报告菌株、激素谱与多尺度荧光显微。","广泛发病前已存在大量真菌定殖和局部宿主极化响应，激素积累滞后。","农业人工智能与决策模型","可开发早期无症状侵染的活体成像与分子标记，用于病害预警和抗性筛选。","农业遥感与作物表型","2026-10-14T23:30:22.477415Z",{"id":199,"title":200,"url":201,"summary":202,"summary_zh":203,"content":8,"source_name":204,"source_url":201,"published_at":205,"category":12,"cover_url":8,"hotness":13,"is_selected":34,"score":62,"score_detail":206,"sources":208,"tags":210,"primary_topic":8,"secondary_topics":214,"classification":215,"search_phrases":225,"slug":228,"view_count":62,"doi":229,"paper":230,"created_at":243},4817,"Use of artificial intelligence and other data-driven technologies for coastal management","https:\u002F\u002Fdoi.org\u002F10.33175\u002Fmtr.2027.289835","Biogeochemical cycles occur naturally in coastal regions. Estuaries, wetlands, and tidal creeks assist these cycles. Since increased anthropogenic activities and naturally occurring events act as stressors, they impact physical, chemical, and biological processes in maritime spaces and hence these cycles. This makes existing ecosystems susceptible to trophic imbalance. Resultantly, researchers began monitoring and mapping coastal environments to understand how different stressors impact these biogeochemical processes using numerical and empirical models. With advances in computation infrastructure, use of data-driven techniques such as Artificial Intelligence, Machine Learning, and Deep Learning in different hydrological systems have become commonplace. This has invigorated the use of predictive and decision-making frameworks in coastal management, making habitat conservation more scientific. Such frameworks balance ecological health and human activities through hard and soft engineering, nature-based solutions, and managed retreat. Though substantial literature on the use of Artificial Intelligence and Machine Learning in the coastal environment exists, they focus on independent domains, with limited discussion of their combined impact on coastal management. Accordingly, this desk-based qualitative review discusses recent developments in Artificial Intelligence, Machine Learning, Deep Learning, and other data-driven techniques used for coastal management. In addition, it will identify future directions for such studies, especially with combined stressors. ------------------------------------------------------------------------------Cite this article: APA Style:Agarwala, N. (2027). Use of artificial intelligence and other data-driven technologies for coastal management. Maritime Technology and Research, 9(1), 289835. https:\u002F\u002Fdoi.org\u002F10.33175\u002Fmtr.2027.289835 MDPI Style:Agarwala, N. Use of artificial intelligence and other data-driven technologies for coastal management. Marit. Technol. Res. 2027, 9, 289835. https:\u002F\u002Fdoi.org\u002F10.33175\u002Fmtr.2027.289835 Vancouver Style:Agarwala N. (2027). Use of artificial intelligence and other data-driven technologies for coastal management. Marit. Technol. Res. 9(1):289835. https:\u002F\u002Fdoi.org\u002F10.33175\u002Fmtr.2027.289835 ------------------------------------------------------------------------------ Highlights Provides an overview tying disparate AI\u002FML to cohesive coastal management frameworks Shows how coastal modeling has transitioned from traditional linear systems to modern multi-physics data-driven frameworks Shows how PINNs addresses AI limitations like hallucinations and physical anomalies Shows how AI optimizes hard gray infrastructure while scaling up soft green solutions Showcases how Decision Support Systems use spatial-temporal algorithms to balance ecosystem preservation with economic priorities","生物地球化学循环在沿海地区自然发生。河口、湿地和潮汐溪流对这些循环起到辅助作用。由于人类活动增加和自然发生的事件作为压力源，它们影响海洋空间中的物理、化学和生物过程，进而影响这些循环。这使得现有生态系统易受营养失衡的影响。因此，研究人员开始监测和绘制沿海环境，以了解不同压力源如何利用数值模型和经验模型影响这些生物地球化学过程。随着计算基础设施的进步，人工智能、机器学习和深度学习等数据驱动技术在不同水文系统中的应用已变得普遍。这推动了预测和决策框架在海岸管理中的应用，使栖息地保护更加科学。此类框架通过硬工程和软工程、基于自然的解决方案以及有管理的后退，平衡生态健康与人类活动。尽管关于人工智能和机器学习在沿海环境中应用的文献已相当丰富，但它们聚焦于独立领域，对其在海岸管理中的综合影响讨论有限。因此，本项基于案头的定性综述讨论了人工智能、机器学习、深度学习及其他用于海岸管理的数据驱动技术的最新进展。此外，它将确定此类研究的未来方向，尤其是在复合压力源方面。 ------------------------------------------------------------------------------ 引用本文： APA格式：Agarwala, N. (2027). Use of artificial intelligence and other data-driven technologies for coastal management. Maritime Technology and Research, 9(1), 289835. https:\u002F\u002Fdoi.org\u002F10.33175\u002Fmtr.2027.289835 MDPI格式：Agarwala, N. Use of artificial intelligence and other data-driven technologies for coastal management. Marit. Technol. Res. 2027, 9, 289835. https:\u002F\u002Fdoi.org\u002F10.33175\u002Fmtr.2027.289835 Vancouver格式：Agarwala N. (2027). Use of artificial intelligence and other data-driven technologies for coastal management. Marit. Technol. Res. 9(1):289835. https:\u002F\u002Fdoi.org\u002F10.33175\u002Fmtr.2027.289835 ------------------------------------------------------------------------------ 亮点 提供概述，将分散的人工智能\u002F机器学习与连贯的海岸管理框架联系起来 展示海岸建模如何转变","Maritime Technology and Research","2026-10-11T00:00:00Z",{"impact":62,"substance":62,"depth":62,"authority":62,"freshness":62,"relevant":62,"comment":207},"该论文聚焦海岸带管理与海洋生态，属海洋与海事领域，与三农、农业信息化、智慧农业、数字乡村无直接关联，相关性门槛未通过。",[209],{"name":204,"url":201},[211,27,212,213],"机器学习","数据驱动","海岸带管理",[],{"status":33,"locked":34,"version":35,"method":36,"evidence":216},{"candidates":217,"agricultural_evidence":34,"reason":44},[218],{"code":40,"score":219,"supported":14,"title":220,"abstract":221,"tags":224},19,[76],[78,211,222,79,76,223],"machine learning","decision support",[27,211],[226,227],"海岸带管理 人工智能 数据驱动 机器学习","海岸带管理 人工智能","海岸带管理人工智能数据驱动机器学习-4817","10.33175\u002Fmtr.2027.289835",{"doi":229,"openalex_id":231,"authors":232,"venue":204,"cited_by_count":62,"oa_url":236,"card":237,"direction":242,"ingested_from":116},"W7221479771",[233],{"name":234,"orcid":235},"Nitin Agarwala","https:\u002F\u002Forcid.org\u002F0000-0003-0916-3044","https:\u002F\u002Fso04.tci-thaijo.org\u002Findex.php\u002FMTR\u002Farticle\u002Fdownload\u002F289835\u002F193722",{"tldr":238,"method":239,"finding":240,"direction":196,"opportunity":241},"综述人工智能与数据驱动技术在海岸带管理中的应用，并指出未来方向。","基于文献的定性综述，梳理AI、机器学习与深度学习在海岸环境建模中的应用。","现有研究多局限于独立领域，缺乏对多重压力下综合管理框架的整合讨论。","可探索多压力源耦合下AI决策框架，并迁移至农业面源污染与滨海湿地协同治理。","智慧农业 \u002F 农业物联网","2026-10-13T23:30:14.084085Z",{"id":245,"title":246,"url":247,"summary":248,"summary_zh":249,"content":8,"source_name":250,"source_url":247,"published_at":251,"category":12,"cover_url":8,"hotness":13,"is_selected":34,"score":62,"score_detail":252,"sources":254,"tags":256,"primary_topic":8,"secondary_topics":259,"classification":260,"search_phrases":269,"slug":272,"view_count":22,"doi":273,"paper":274,"created_at":285},4496,"Artificial Intelligence and Cultural Heritage: A Review of Opportunities, Risks, and Ethical Challenges","https:\u002F\u002Fdoi.org\u002F10.61424\u002Fijcgrs.v3i1.1060","Artificial intelligence (AI) is increasingly transforming the documentation, preservation, interpretation, and public engagement of cultural heritage. This review examines the opportunities, risks, and ethical challenges associated with the application of AI in cultural heritage management and research. Drawing on interdisciplinary literature spanning heritage studies, computer science, digital humanities, museum studies, and information ethics, the review synthesizes evidence on the use of machine learning, computer vision, natural language processing, generative AI, and three-dimensional technologies in heritage contexts. The findings indicate that AI can enhance the digitization and classification of cultural collections, reconstruct damaged or lost heritage assets, support archaeological analysis, improve multilingual access to heritage resources, and create more interactive experiences for museums and heritage sites. AI also offers opportunities for predictive conservation through automated monitoring of environmental conditions, material deterioration, and structural changes. However, these benefits are accompanied by significant risks, including algorithmic bias, inaccurate reconstruction, cultural misrepresentation, intellectual-property disputes, data privacy concerns, technological dependency, and the marginalization of communities whose cultural knowledge is incorporated into AI systems without meaningful participation or consent. Generative AI presents additional challenges because synthetic representations may blur distinctions between historically documented evidence and machine-generated interpretations. The review therefore emphasizes the importance of human oversight, transparent documentation of AI-generated outputs, culturally sensitive data governance, community participation, provenance tracking, and equitable access to digital heritage technologies. Overall, AI should be understood not simply as a technological tool but as a socio-cultural intervention whose deployment requires collaboration among technologists, heritage professionals, researchers, governments, and source communities. Responsible and inclusive AI governance can enable technological innovation while protecting the authenticity, diversity, ownership, and cultural significance of heritage resources.","人工智能（AI）正日益改变文化遗产的记录、保存、阐释与公众参与方式。本文综述了AI在文化遗产管理与研究中应用所带来的机遇、风险与伦理挑战。通过整合涵盖遗产研究、计算机科学、数字人文、博物馆学与信息伦理学的跨学科文献，本文综合了机器学习、计算机视觉、自然语言处理、生成式AI及三维技术在遗产领域应用的证据。研究结果表明，AI能够促进文化藏品的数字化与分类，重建受损或遗失的遗产资产，支持考古分析，改善遗产资源的多语言获取，并为博物馆与遗产地创造更具互动性的体验。AI还通过自动监测环境条件、材料劣化与结构变化，为预测性保护提供了机遇。然而，这些益处伴随着显著风险，包括算法偏见、重建不准确、文化误现、知识产权争议、数据隐私问题、技术依赖，以及那些其文化知识在缺乏实质性参与或同意的情况下被纳入AI系统的社区所面临的边缘化。生成式AI带来了额外挑战，因为合成表征可能模糊历史文献证据与机器生成阐释之间的界限。因此，本文强调人工监督、AI生成产出的透明记录、文化敏感的数据治理、社区参与、来源追踪以及数字遗产技术公平获取的重要性。总体而言，AI不应仅被理解为一种技术工具，而应被视为一种社会文化干预，其部署需要技术人员、遗产专业人员、研究者、政府与来源社区之间的协作。负责任且包容的AI治理能够在保护遗产资源真实性、多样性、所有权与文化意义的同时，推动技术创新。","OpenAlex","2026-10-07T00:00:00Z",{"impact":62,"substance":62,"depth":62,"authority":62,"freshness":62,"relevant":62,"comment":253},"主题为AI在文化遗产领域的综述，与三农、农业信息化、智慧农业无直接关联，不进入每日精选。",[255],{"name":250,"url":247},[27,69,257,258],"数字人文","伦理治理",[],{"status":33,"locked":34,"version":35,"method":36,"evidence":261},{"candidates":262,"agricultural_evidence":34,"reason":44},[263],{"code":40,"score":19,"supported":14,"title":264,"abstract":265,"tags":268},[76],[211,266,222,76,267],"计算机视觉","computer vision",[27],[270,271],"人工智能 伦理治理 数字人文 文化遗产","人工智能 伦理治理","人工智能伦理治理数字人文文化遗产-4496","10.61424\u002Fijcgrs.v3i1.1060",{"doi":273,"openalex_id":275,"authors":276,"venue":8,"cited_by_count":62,"oa_url":279,"card":280,"direction":242,"ingested_from":116},"W7220858187",[277],{"name":278,"orcid":8},"Morgan Roberts","https:\u002F\u002Fbluemarkpublishers.com\u002Findex.php\u002FIJCGRS\u002Farticle\u002Fdownload\u002F1060\u002F916",{"tldr":281,"method":282,"finding":283,"direction":113,"opportunity":284},"综述AI在文化遗产管理中的机遇、风险与伦理挑战，强调负责任治理。","跨学科文献综述，涵盖机器学习、计算机视觉、生成式AI与3D技术。","AI可助力遗产数字化与预测性保护，但存在偏见、误重建与社区边缘化风险。","可探索文化遗产AI的社区参与式数据治理与生成内容溯源机制，平衡创新与真实性。","2026-10-09T23:30:11.121326Z",{"id":287,"title":288,"url":289,"summary":290,"summary_zh":291,"content":8,"source_name":292,"source_url":289,"published_at":251,"category":12,"cover_url":8,"hotness":13,"is_selected":34,"score":293,"score_detail":294,"sources":298,"tags":300,"primary_topic":8,"secondary_topics":306,"classification":307,"search_phrases":349,"slug":352,"view_count":22,"doi":353,"paper":354,"created_at":369},4495,"A review of forest innovation: Technologies and sustainable practices for environmental conservation","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.nxsust.2026.100546","Forests play a crucial role in climate regulation, biodiversity conservation, ecosystem service provision, and sustainable socio-economic development. However, increasing deforestation, climate change, habitat fragmentation, and unsustainable resource exploitation continue to threaten forest ecosystems worldwide. The objective of this review is to determine the ecological, economic, and governance conditions under which specific forest innovations translate into measurable sustainability outcomes, and to synthesize these conditions into coherent, evidence-based pathways applicable across different regional contexts. Framed through a social-ecological systems (SES) and resilience lens, this review critically examines recent advances in forest innovation by integrating sustainable forest management practices with emerging technological developments, including precision forestry, remote sensing, geographic information systems (GIS), LiDAR, unmanned aerial vehicles (UAVs), biotechnology, artificial intelligence (AI), digital forestry, biomass utilization, and forest-based bioeconomy approaches. Unlike conventional narrative reviews, this study applies a common five criterion evaluation framework comprising ecological effectiveness, technological maturity, economic feasibility, governance requirements, and regional applicability to comparatively evaluates the strengths, limitations, implementation challenges of these innovations across diverse ecological and socio-economic contexts, thereby moving beyond the largely descriptive, single-domain coverage of prior forest technology and forest governance reviews to an explicitly cross-domain, comparative synthesis. The review further explores the contributions of community-based forest management, climate-smart forestry, carbon management strategies, ecosystem services, green infrastructure, and innovative forest-derived products toward achieving long-term environmental sustainability. The analysis demonstrates that technological innovations alone cannot ensure sustainable forest management unless supported by effective governance, equitable community participation, adequate financial investment, and adaptive policy frameworks. The review identifies critical knowledge gaps related to technology adoption, institutional capacity, climate resilience, and long-term monitoring, and derives four specific, evidence-anchored integrated pathways that combine ecological, technological, economic, and governance innovations. This review provides a comprehensive, deliberately broad-scope synthesis of contemporary forest innovation and offers practical recommendations for researchers, policymakers, and forest managers working toward resilient forest ecosystems and the achievement of the United Nations Sustainable Development Goals, particularly SDG 15 (Life on Land).","森林在气候调节、生物多样性保护、生态系统服务供给以及可持续社会经济发展中发挥着至关重要的作用。然而，日益加剧的森林砍伐、气候变化、栖息地破碎化以及不可持续的资源开发持续威胁着全球森林生态系统。本综述旨在明确特定森林创新在何种生态、经济与治理条件下能够转化为可衡量的可持续性成果，并将这些条件综合为适用于不同区域背景的连贯且基于证据的路径。本综述以社会-生态系统（SES）和韧性为理论框架，通过将可持续森林管理实践与新兴技术发展相结合，批判性地审视了森林创新的最新进展，这些技术包括精准林业、遥感、地理信息系统（GIS）、激光雷达（LiDAR）、无人机（UAV）、生物技术、人工智能（AI）、数字林业、生物质利用以及基于森林的生物经济方法。与传统叙述性综述不同，本研究采用统一的五标准评价框架，包括生态有效性、技术成熟度、经济可行性、治理要求和区域适用性，对上述创新在不同生态和社会经济背景下的优势、局限及实施挑战进行比较评估，从而超越以往森林技术和森林治理综述 largely 描述性、单一领域的覆盖范围，实现明确的跨领域比较综合。本综述进一步探讨了社区森林管理、气候智慧型林业、碳管理策略、生态系统服务、绿色基础设施以及创新性林产品对实现长期环境可持续性的贡献。分析表明，除非得到有效治理、公平的社区参与、充足的财政投资和适应性政策框架的支持，否则仅靠技术创新无法确保可持续森林管理。本综述识别了与技术采用、机构能力、气候韧性和长期监测相关的关键知识空白，并推导出四条具体的、以证据为锚点的综合路径，这些路径融合了生态、技术、经济和治理创新。Th","Next Sustainability",77,{"impact":19,"substance":295,"depth":19,"authority":49,"freshness":296,"relevant":22,"comment":297},21,7,"该综述系统整合精准林业、遥感、AI等技术与治理条件，提出四条证据支撑路径，对智慧林业与数字乡村建设有较高参考价值，但属综述类论文、时效性一般，适合进入主题聚合而非头条精选。",[299],{"name":292,"url":289},[27,301,302,303,304,305],"智慧林业","遥感监测","森林碳汇","数字林业","可持续经营",[],{"status":33,"locked":34,"version":35,"method":36,"evidence":308},{"candidates":309,"agricultural_evidence":34,"reason":44},[310,319,327,335,339,344],{"code":311,"score":21,"supported":14,"title":312,"abstract":313,"tags":318},"H6",[],[314,315,316,317],"生物多样性","生态系统服务","biodiversity","ecosystem service",[],{"code":320,"score":21,"supported":14,"title":321,"abstract":322,"tags":326},"H7",[],[323,324,325],"气候变化","climate change","climate resilience",[],{"code":328,"score":21,"supported":14,"title":329,"abstract":330,"tags":334},"I4",[],[331,332,333],"地理信息","GIS","geographic information",[],{"code":89,"score":296,"supported":14,"title":336,"abstract":337,"tags":338},[],[92,93],[302],{"code":40,"score":340,"supported":14,"title":341,"abstract":342,"tags":343},4,[],[76],[27],{"code":345,"score":22,"supported":34,"title":346,"abstract":347,"tags":348},"H4",[],[],[303],[350,351],"森林创新 遥感 LiDAR 无人机","数字林业 森林碳汇 可持续经营","森林创新遥感LiDAR无人机-4495","10.1016\u002Fj.nxsust.2026.100546",{"doi":353,"openalex_id":355,"authors":356,"venue":292,"cited_by_count":62,"oa_url":363,"card":364,"direction":242,"ingested_from":116},"W7220854619",[357,360],{"name":358,"orcid":359},"Shivani Garg","https:\u002F\u002Forcid.org\u002F0000-0001-7879-7177",{"name":361,"orcid":362},"Pooja Arora","https:\u002F\u002Forcid.org\u002F0000-0002-4860-4714","https:\u002F\u002Fwww.sciencedirect.com\u002Fscience\u002Farticle\u002Fpii\u002FS2949823626003016\u002Fpdf",{"tldr":365,"method":366,"finding":367,"direction":196,"opportunity":368},"综述森林创新技术，用五标准框架比较其可持续性成效与实施条件。","社会生态系统与韧性视角，五标准评估框架，综合遥感、AI、数字林业等。","技术创新需治理、社区参与、投资和适应性政策配合才能实现可持续森林管理。","可研究遥感\u002FAI在森林碳汇监测中的技术采纳障碍与制度适配路径。","2026-10-09T23:30:10.090218Z",{"id":371,"title":372,"url":373,"summary":374,"summary_zh":8,"content":375,"source_name":376,"source_url":8,"published_at":377,"category":378,"cover_url":8,"hotness":13,"is_selected":14,"score":379,"score_detail":380,"sources":384,"tags":386,"primary_topic":391,"secondary_topics":397,"classification":398,"search_phrases":428,"slug":431,"view_count":432,"doi":8,"paper":8,"created_at":433},4458,"中国农科院植保所李方方团队开发TI-TA合成免疫模块破解植物抗病与生长两难","https:\u002F\u002Fnews.foodmate.net\u002F2026\u002F10\u002F754322.html","中国农业科学院植物保护研究所李方方、周雪平研究员团队创新构建翻译抑制-转录激活（TI-TA）病毒响应型合成免疫模块，精准靶向依赖亚基因组RNA增殖的正链RNA病毒，可在不干扰作物正常生长发育的前提下智能启动抗病毒防御；为番茄、烟草等重要农作物抗RNA病毒育种提供全新可编程技术工具，也为植物病毒病害绿色防控开辟新思路；研究成果发表于Science子刊Science Advances。","近日，[中国](https:\u002F\u002Fnews.foodmate.net\u002Ftag_5027.html \"中国相关食品资讯\")农业科学院植物保护研究所李方方、周雪平研究员团队创新突破，成功开发出翻译抑制-转录激活（TI-TA）[病毒](https:\u002F\u002Fnews.foodmate.net\u002Ftag_4505.html \"病毒相关食品资讯\")响应型合成[免疫](https:\u002F\u002Fnews.foodmate.net\u002Ftag_4719.html \"免疫相关食品资讯\")模块。该技术精准靶向各类依赖亚基因组RNA增殖的正链RNA病毒，可在不干扰作物正常生长发育的前提下，智能启动抗病毒防御，为番茄、烟草等重要农作物抗RNA病毒育种提供了全新的可编程技术工具，也为植物病毒病害绿色防控开辟了新思路。相关研究成果“Specific and Efficient Translation Inhibition-Trans cription Activation Resistance Module Against Viruses in Plants”发表于Science子刊《Science Advances》期刊上。\n\n正链RNA病毒是威胁全球农业生产与公共卫生安全的核心病原类群。在植物病原中，番茄褐色皱果病毒、黄瓜花叶病毒、烟草花叶病毒、凤果花叶病毒等千余种重要作物病毒均归属于此类；动物病原方面，新冠病毒、基孔肯雅病毒、风疹病毒、传染性支气管炎病毒、猪繁殖与呼吸综合征病毒等重大人畜病毒同样属于该类群。该类病毒多数依靠亚基因组RNA完成关键蛋白表达，普遍具有传播速度快、寄主范围广、变异能力强的特点：在农业领域常年造成作物大幅减产与品质劣变，严重威胁粮食安全与农民增收；在公共卫生领域极易引发跨物种传播与疫情暴发，持续对人类健康和畜禽养殖业构成重大风险。\n\n长期以来，植物抗病毒育种与防控存在显著技术瓶颈。传统天然抗病毒R基因稀少有限、抗性谱窄而且易因病毒基因突变被突破，而传统组成型免疫激活策略会持续消耗作物自身能量用于防御，导致作物产量下降，引发“生长-防御权衡”矛盾，因此，兼顾高效抗病与稳产增产一直是农业生产中亟待攻克的难题。开发“病毒入侵才启动、无病静默生长”的智能精准抗病系统是植物免疫与育种领域的核心攻关目标。\n\n研究团队另辟蹊径，跳出传统抗病技术逻辑，精准捕捉病毒侵染专属、寄主不具备的亚基因组RNA生成特征，创新性构建TI-TA双层人工合成免疫模块，打造出一套可控、精准、高效的植物智能抗病毒系统。该模块由两大核心功能单元构成：具备强效静默功能的TI翻译抑制元件dsBC，以及病毒专属响应的TA微型复制子转录激活模块Virusmini，并搭载BAX、INF1、NLPPya等高效抗性诱导蛋白作为核心免疫效应执行者，形成“精准感知、快速激活、高效抑制”的闭环免疫体系。\n\n这套智能系统实现了“无病休眠、有病激活”的精准调控，相当于为作物装上了全天候智能病毒安防警报系统。在无病毒侵染的正常生长环境下，dsBC元件可在mRNA层面强力抑制下游抗性蛋白的翻译过程，让免疫防御系统完全处于静默休眠状态，彻底规避免疫耗能对作物生长的影响，保障植株正常萌发、生长与发育。一旦病毒入侵寄主植株，病毒自身的RNA依赖RNA聚合酶会特异性识别Virusmini微型复制子，启动病毒专属的亚基因组转录程序，精准解除免疫抑制，快速诱导抗性蛋白大量表达，激活植株细胞坏死与抗病毒防御通路，快速遏制病毒增殖与扩散。\n\n研究团队通过多轮元件筛选与系统迭代优化，敲定了最优技术组合。通过系统性对比多类元件及串联组合，筛选出抑制效率最优的dsBC翻译抑制元件；突破单一启动子激活局限，重构整合病毒UTR、亚基因组启动子等核心顺式元件的微型复制子Virusmini，实现病毒依赖型的高效特异性转录激活。同时，团队探明了不同病毒的系统适配规律，针对不同RNA病毒的RNA结构特征，微调模块插入位点，大幅提升了系统的适配性与抗病稳定性，实现了技术体系的定制化、可拓展优化。\n\n研究团队分别构建靶向凤果花叶病毒、烟草花叶病毒、黄瓜花叶病毒的三套TI-TA转基因材料，在烟草、番茄、拟南芥等多种模式植物与经济作物中完成系统性功能验证。试验结果表明，无病毒胁迫下，转基因植株的种子萌发、根系发育、株型长势、叶片形态等农艺性状与野生型植株无显著差异，无任何发育缺陷与生长抑制；在病毒侵染胁迫下，系统可快速特异性激活免疫应答，显著降低植株体内病毒积累量，大幅减轻病害症状。其中，靶向黄瓜花叶病毒的转基因拟南芥可近乎完全阻断病毒系统性侵染，实现免疫级抗性；靶向凤果花叶病毒的转基因番茄也展现出极强的抗病能力，应用潜力突出。\n\n尤为关键的是，该合成免疫体系突破了传统抗病技术“一对一抗病、易突变逃逸”的短板，具备优异的广谱交叉抗病能力。靶向凤果花叶病毒的株系可抵御同属马铃薯X病毒侵染，靶向烟草花叶病毒的材料可减轻番茄褐色皱纹果病毒危害，靶向黄瓜花叶病毒的株系可高效抵抗不同病毒株系侵染。同时，多组对照试验证实，该系统免疫特异性极强，仅特异性响应病毒侵染，不会被细菌、真菌等其他病原以及高温、干旱等非生物胁迫误激活，可有效避免植株自身免疫损伤，抗性安全稳定。\n\n该成果革新了传统抗病毒策略的技术逻辑，跳出了靶向病毒核酸、识别病毒特异蛋白、依托寄主固有抗病基因的传统技术路径，创新性劫持病毒自身复制转录的核心生命过程作为专属免疫激活开关，耦合强效抗性功能蛋白精准启动植物防御应答。相较于传统抗病体系，该技术从底层原理上破解了病毒基因突变引发的抗性逃逸难题，突破了新发、变异病毒无天然抗病基因可用的育种瓶颈，彻底规避了组成型免疫激活带来的“生长-防御权衡”弊端，在保障作物正常生长与稳产的同时，显著提升了抗病稳定性，并实现跨毒株、跨近缘病毒的广谱交叉保护效应。TI-TA人工合成免疫框架，不仅为亚基因组RNA病毒抗性作物分子育种提供了模块化、可编辑、可拓展的新型技术工具箱，还为动物RNA病毒的人工合成免疫治疗提供了原创性概念与理论启发，兼具重要的基础理论价值与广阔的产业应用前景。\n\n中国农业科学院植物保护研究所博士后李召雷（现浙江农林大学青年教师）、硕士生张婧（现西安大略大学博士生）为论文共同第一作者，李。方方研究员、周雪平教授为论文通讯作者。西湖大学博士后杨欣欣，中国农科院植保所研究生卢若滨、何浩、徐子妍、陈元也参与研究工作。研究过程得到浙江大学吴建祥教授、清华大学刘玉乐教授、美国弗吉尼亚理工大学王晓峰教授等病毒专家的大力支持与指导，该研究获中国农业科学院农业科技创新工程基础中心项目资助。\n\n全文链接：https:\u002F\u002Fwww.science.org\u002Fdoi\u002F10.1126\u002Fsciadv.aeg0007.","中国农业科学院植物保护研究所 2026-10-08","2026-10-08T00:00:00Z","报道",95,{"impact":381,"substance":382,"depth":219,"authority":83,"freshness":13,"relevant":22,"comment":383},27,24,"国家级科研机构在Science子刊发表的原创性合成免疫技术突破，兼具理论价值与产业前景，值得进入每日精选。",[385],{"name":376,"url":373},[387,28,388,389,390],"粮食安全","番茄","合成生物学","抗病毒育种",{"code":392,"slug":393,"name":394,"path":395,"parent_code":396},"F4","crop-protection","农药与绿色防控","\u002Ftopic\u002Finputs-equipment\u002Fcrop-protection","F",[],{"status":145,"locked":34,"version":35,"method":36,"evidence":399},{"candidates":400,"agricultural_evidence":14},[401,408,413,419,424],{"code":392,"score":402,"supported":14,"title":403,"abstract":405,"tags":407},11,[404],"植保",[406],"绿色防控",[],{"code":409,"score":340,"supported":14,"title":410,"abstract":411,"tags":412},"B1",[],[388],[388],{"code":414,"score":149,"supported":14,"title":415,"abstract":416,"tags":418},"A6",[],[417],"烟草",[],{"code":420,"score":22,"supported":34,"title":421,"abstract":422,"tags":423},"A8",[],[],[387],{"code":155,"score":22,"supported":34,"title":425,"abstract":426,"tags":427},[],[],[389],[429,430],"中国农科院植保所 TI-TA 合成免疫模块","李方方 周雪平 Science Advances 抗病毒","中国农科院植保所TI-TA合成免疫模块-4458",2,"2026-10-09T00:04:55.922919Z"]