[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-2918":3,"related-2918":54},{"id":4,"title":5,"url":6,"summary":7,"summary_zh":8,"content":9,"source_name":10,"source_url":6,"published_at":11,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":16,"sources":24,"tags":26,"search_phrases":32,"slug":35,"view_count":36,"doi":37,"paper":38,"created_at":53},2918,"Weeds as beneficial sources of plant diversity in high tunnel tomato","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1904933","Weeds are often viewed as antagonists in agroecosystems because they can compete with crops and provide refuge for invertebrate pests. However, it is possible that weeds serve as beneficial sources of plant diversity that contribute toward pest regulation in agroecosystems. We conducted a two-year study across 15 farms in Indiana, United States to describe the benefits and risks of weeds in tomato high tunnel production systems. At these farms, we identified common weed species and broadly identified invertebrates they hosted. We also measured weed coverage to link “weediness” with pest pressure and insect diversity on a focal crop, tomato. We also conducted a one-year study at our Purdue research farm to refine these observations and extend the impacts of weeds to overall tomato yield. Across farms, weeds did not increase pest risk and was linked to lower pest pressure at our research site. We also found little impact of weed presence on tomato yield or marketability. Natural enemy abundance on tomatoes was largely unaffected by weed presence, although there were some exceptions among particular groups that were all found in higher abundance in weedy tunnels. Chickweed, Virginia pepperweed, foxtail grasses, and cleavers supported relatively high ratios of natural enemies to herbivores, while other weeds hosted both herbivores and natural enemies. Overall, our results suggest that selectively managed weeds can support beneficial invertebrates and contribute to pest suppression without reducing crop productivity.","杂草常被视为农业生态系统中的对立面，因为它们会与作物竞争，并为无脊椎动物害虫提供庇护所。然而，杂草也可能作为植物多样性的有益来源，有助于农业生态系统中的害虫调控。我们在美国印第安纳州的15个农场开展了一项为期两年的研究，旨在描述番茄高隧道生产系统中杂草的益处与风险。在这些农场中，我们鉴定了常见杂草种类，并对其携带的无脊椎动物进行了大致分类。我们还测量了杂草覆盖度，以将“杂草化”程度与目标作物番茄上的害虫压力和昆虫多样性联系起来。此外，我们在普渡研究农场开展了一项为期一年的研究，以细化这些观察结果，并将杂草的影响扩展至番茄总体产量。在各农场中，杂草并未增加害虫风险，且在我们研究地点与较低的害虫压力相关。我们还发现杂草的存在对番茄产量或市场适销性影响甚微。番茄上天敌的丰度在很大程度上未受杂草存在的影响，尽管某些特定类群存在例外，这些类群在有杂草的隧道中丰度均较高。繁缕、弗吉尼亚胡椒草、狗尾草和猪殃殃支持相对较高的天敌与植食者比例，而其他杂草则同时携带植食者和天敌。总体而言，我们的结果表明，选择性管理的杂草可以支持有益无脊椎动物，并有助于害虫抑制，而不会降低作物生产力。",null,"Frontiers in Sustainable Food Systems","2026-09-18T00:00:00Z","论文",10,false,67,{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":21,"relevant":22,"comment":23},8,20,17,13,9,1,"美国普渡大学两年15农场研究，提出选择性保留杂草可提升天敌比例、不损番茄产量，为设施番茄绿色防控提供新思路，但属国外区域性研究，公共影响有限。",[25],{"name":10,"url":6},[27,28,29,30,31],"设施农业","番茄","生物防治","杂草管理","害虫调控",[33,34],"普渡大学 高隧道 番茄 杂草","害虫调控 杂草管理 生物防治 设施农业","普渡大学高隧道番茄杂草-2918",0,"10.3389\u002Ffsufs.2026.1904933",{"doi":37,"openalex_id":39,"authors":40,"venue":10,"cited_by_count":36,"oa_url":6,"card":46,"direction":50,"ingested_from":52},"W7213552161",[41,43],{"name":42,"orcid":9},"Samantha A. Willden",{"name":44,"orcid":45},"Laura L. Ingwell","https:\u002F\u002Forcid.org\u002F0000-0002-9552-9227",{"tldr":47,"method":48,"finding":49,"direction":50,"opportunity":51},"研究高隧道番茄中杂草对害虫调控和产量的影响。","在15个农场进行两年调查，结合研究站一年试验，分析杂草、害虫和天敌。","杂草不增加害虫风险，部分杂草支持高天敌比，且不影响番茄产量或商品性。","农业绿色发展与碳","可探索特定杂草组合的生态调控机制，开发基于杂草管理的生物防治策略。","openalex","2026-09-19T23:30:08.394706Z",{"total":55,"page":22,"page_size":55,"items":56},6,[57,90,134,185,236,267],{"id":58,"title":59,"url":60,"summary":61,"summary_zh":9,"content":9,"source_name":62,"source_url":9,"published_at":63,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":64,"score_detail":65,"sources":70,"tags":72,"search_phrases":76,"slug":79,"view_count":36,"doi":9,"paper":80,"created_at":89},2904,"Decoupled Foundation Models:基于YOLO26m+SAM2+DINOv2的湿度诱导番茄叶坏死实例分割与检测,登MDPI Agriculture 16(18)1997","https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F18\u002F1997","本研究针对温室番茄相对湿度过高引发的非生物胁迫(生理性叶坏死,与生物感染症状相似),提出多步AI管道自动化分割与分类坏死叶斑。采集218张RGB图像、3218个标注(棕色坏死斑\u002F黄色坏死斑\u002F无坏死),系统评估6种端到端实例分割管道(YOLO26m检测+SAM2零样本分割+微调DINOv2或EfficientNet-B3分类);微调DINOv2宏F1达0.926,优于EfficientNet-B3、ResNet-50、Swin-Small基线(0.886-0.901);最佳配置mAP@50=0.828,较YOLO26m单模型提升约8%。","MDPI Agriculture","2026-09-17T00:00:00Z",78,{"impact":66,"substance":67,"depth":68,"authority":20,"freshness":21,"relevant":22,"comment":69},16,22,18,"方法组合新颖、数据规模与对比基线扎实，对温室番茄生理性叶坏死自动识别有实用价值，值得进入每日精选。",[71],{"name":62,"url":60},[73,74,27,28,75],"智慧农业","农业人工智能","病害识别",[77,78],"番茄叶坏死 实例分割","农业人工智能 智慧农业 病害识别 设施农业","番茄叶坏死实例分割-2904",{"doi":9,"openalex_id":9,"authors":81,"venue":9,"cited_by_count":36,"oa_url":9,"card":82,"direction":86,"ingested_from":88},[],{"tldr":83,"method":84,"finding":85,"direction":86,"opportunity":87},"用YOLO26m+SAM2+DINOv2多步管道分割并分类高湿诱导的番茄叶坏死斑。","218张RGB图像、3218个标注，评估6种实例分割管道并微调DINOv2分类。","微调DINOv2宏F1达0.926，最佳配置mAP@50=0.828，较单模型提升约8%。","农业人工智能与决策模型","可探索零样本基础模型在多种非生物胁迫症状上的泛化与轻量化温室部署。","agent","2026-09-19T00:06:09.021594Z",{"id":91,"title":92,"url":93,"summary":94,"summary_zh":95,"content":9,"source_name":96,"source_url":93,"published_at":97,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":98,"score_detail":99,"sources":102,"tags":104,"search_phrases":107,"slug":110,"view_count":36,"doi":111,"paper":112,"created_at":133},2774,"SpatioFormer: spatial perception enhancement for lightweight agricultural pest and disease detection","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffpls.2026.1925867","Introduction In precision agriculture, accurate and efficient detection of crop pests and diseases is crucial. However, existing models in complex environments are prone to insufficient spatial perception and attenuation of disease texture features, making it difficult to balance recognition accuracy and lightweighting. Methods To address this, this study proposes a lightweight spatial perception enhancement hybrid architecture, SpatioFormer. First, a Pixel-level Detail Retrieval (PDR) mechanism is designed. This mechanism leverages cross-layer dynamic routing to facilitate the fusion of deep semantic features with shallow texture features, significantly enhancing the capability to capture disease features. Second, we design a Spatially Adaptive Modulation Attention (SA-SHMA) mechanism, which utilizes large-kernel depthwise convolution to capture contextual information and combines dynamic modulation maps for fine-grained focusing, efficiently recovering spatial details, and suppressing background noise. Furthermore, this paper introduces a Context-Guided Asymmetric Gated Linear Unit (CGA-GLU), which utilizes an asymmetric design focusing on the gating branch and incorporates contextual information for guidance, enhancing the inter-channel representation capability with minimal computational overhead. Results Finally, extensive experiments on the PDDD and Tomato-Village datasets validated the effectiveness of the proposed model. The proposed model achieves a Top-1 accuracy of 81.05% on the PDDD dataset and an AP 50 of 61.53% on the Tomato-Village dataset, with testing latency on edge devices being highly competitive among existing models. Discussion Compared to existing lightweight hybrid models, SpatioFormer effectively recovers shallow spatial details and precisely suppresses complex background noise under an extremely low parameter budget. Consequently, it achieves a superior balance between practical disease localization capability and inference latency on resource-constrained edge devices.","引言 在精准农业中，准确高效地检测作物病虫害至关重要。然而，复杂环境下的现有模型容易出现空间感知不足和病害纹理特征衰减的问题，难以兼顾识别精度与轻量化。方法 为解决这一问题，本研究提出了一种轻量级空间感知增强混合架构——SpatioFormer。首先，设计了像素级细节检索（Pixel-level Detail Retrieval，PDR）机制。该机制利用跨层动态路由，促进深层语义特征与浅层纹理特征的融合，显著增强了对病害特征的捕捉能力。其次，设计了空间自适应调制注意力（Spatially Adaptive Modulation Attention，SA-SHMA）机制，该机制利用大核深度卷积捕获上下文信息，并结合动态调制图进行细粒度聚焦，高效恢复空间细节并抑制背景噪声。此外，本文引入了上下文引导非对称门控线性单元（Context-Guided Asymmetric Gated Linear Unit，CGA-GLU），其采用聚焦门控分支的非对称设计，并融入上下文信息进行引导，以极小的计算开销增强了通道间表征能力。结果 最后，在PDDD和Tomato-Village数据集上的大量实验验证了所提模型的有效性。所提模型在PDDD数据集上取得了81.05%的Top-1准确率，在Tomato-Village数据集上取得了61.53%的AP 50，其在边缘设备上的测试延迟在现有模型中极具竞争力。讨论 与现有轻量级混合模型相比，SpatioFormer在极低的参数预算下有效恢复了浅层空间细节，并精确抑制了复杂背景噪声。因此，它在实际病害定位能力与资源受限边缘设备上的推理延迟之间实现了更优的平衡。","Frontiers in Plant Science","2026-09-16T00:00:00Z",77,{"impact":66,"substance":100,"depth":68,"authority":20,"freshness":21,"relevant":22,"comment":101},21,"提出轻量化空间感知增强架构，在边缘设备上兼顾检测精度与推理延迟，方法新颖、实验扎实，对农业病虫害智能识别有参考价值。",[103],{"name":96,"url":93},[73,74,105,28,106],"边缘计算","病虫害检测",[108,109],"农业人工智能 病虫害检测 智慧农业 边缘计算","农业人工智能 病虫害检测","农业人工智能病虫害检测智慧农业边缘计算-2774","10.3389\u002Ffpls.2026.1925867",{"doi":111,"openalex_id":113,"authors":114,"venue":96,"cited_by_count":36,"oa_url":126,"card":127,"direction":132,"ingested_from":52},"W7213437661",[115,117,120,122,124],{"name":116,"orcid":9},"Wenbo Ma",{"name":118,"orcid":119},"Hao Sun","https:\u002F\u002Forcid.org\u002F0000-0002-6983-8149",{"name":121,"orcid":9},"Kun Zhou",{"name":123,"orcid":9},"Meichun Wang",{"name":125,"orcid":9},"Rui Fu","https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fplant-science\u002Farticles\u002F10.3389\u002Ffpls.2026.1925867\u002Fpdf",{"tldr":128,"method":129,"finding":130,"direction":86,"opportunity":131},"提出轻量混合架构SpatioFormer，提升复杂环境下农作物病虫害检测的空间感知能力。","设计PDR跨层动态路由、SA-SHMA大核注意力与CGA-GLU门控，在PDDD","在极低参数量下恢复浅层空间细节并抑制背景噪声，边缘设备延迟具竞争力。","可探索将空间感知增强机制迁移至多作物多病害场景，并研究边缘端实时部署的能效优化。","智慧农业 \u002F 农业物联网","2026-09-17T23:30:14.148727Z",{"id":135,"title":136,"url":137,"summary":138,"summary_zh":139,"content":9,"source_name":10,"source_url":137,"published_at":63,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":98,"score_detail":140,"sources":142,"tags":144,"search_phrases":149,"slug":152,"view_count":36,"doi":153,"paper":154,"created_at":184},2755,"Sustainable postharvest preservation of mangoes using antagonistic bacterial pellets through regulation of reactive oxygen species metabolism","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1877440","Introduction Losses caused by diseases after harvesting can reach 30%–60%, severely restricting the sustainable development of the mango industry. This study investigated the effects of different antagonistic bacterial pellets on postharvest mango preservation and the regulation of reactive oxygen species (ROS) metabolism. Methods Mangoes were sprayed separately with bacterial suspensions of four antagonistic pellets: GsBa-1, GHY-1, JQ-1, and GHY-3. Results The results showed that all four antagonistic bacterial pellets enhanced the postharvest preservation of mangoes to varying degrees, with JQ-1 exhibiting the most significant effect. On the 24th day, the mangoes in the JQ-1 treatment group showed significantly higher firmness and titratable acidity content than those in the other groups. The malondialdehyde (MDA), hydrogen peroxide (H 2 O 2 ), and superoxide anion radical (O 2 −· ) contents were reduced by 30.9, 31.2, and 46.9%, respectively, compared with those of the CK. The activities of catalase (CAT), peroxidase (POD), and glutathione peroxidase (GPx), and glutathione (GSH) content increased by 38.5, 75.2, 68.9, and 66.9%, respectively, compared with the CK. Discussion JQ-1 treatment effectively reduced the accumulation of reactive oxygen species (ROS) and delayed the decline in the activities of key antioxidant enzymes, including SOD, CAT, APX and POD. This treatment not only preserved the quality and nutritional value of mangoes but also significantly extended their storage life, providing a scientific basis and feasible approach for the development of new mango preservation technologies.","引言 采后病害造成的损失可达30%–60%，严重制约了芒果产业的可持续发展。本研究探讨了不同拮抗菌菌剂对芒果采后保鲜及活性氧（ROS）代谢调控的影响。方法 分别用4种拮抗菌剂GsBa-1、GHY-1、JQ-1和GHY-3的菌悬液喷洒芒果。结果 结果表明，4种拮抗菌剂均不同程度地提高了芒果的采后保鲜效果，其中JQ-1效果最为显著。在第24天时，JQ-1处理组芒果的硬度和可滴定酸含量显著高于其他各组。与CK相比，丙二醛（MDA）、过氧化氢（H₂O₂）和超氧阴离子自由基（O₂⁻·）含量分别降低了30.9%、31.2%和46.9%。过氧化氢酶（CAT）、过氧化物酶（POD）和谷胱甘肽过氧化物酶（GPx）活性及谷胱甘肽（GSH）含量分别较CK提高了38.5%、75.2%、68.9%和66.9%。讨论 JQ-1处理有效减少了活性氧（ROS）的积累，并延缓了包括SOD、CAT、APX和POD在内的关键抗氧化酶活性的下降。该处理不仅保持了芒果的品质和营养价值，还显著延长了其贮藏期，为开发新型芒果保鲜技术提供了科学依据和可行途径。",{"impact":66,"substance":100,"depth":19,"authority":20,"freshness":13,"relevant":22,"comment":141},"以拮抗细菌颗粒调控活性氧代谢延长芒果货架期，数据翔实、结论可靠，对果蔬采后减损与绿色保鲜技术有实质参考价值。",[143],{"name":10,"url":137},[29,145,146,147,148],"芒果保鲜","采后减损","活性氧代谢","农产品贮藏",[150,151],"农产品贮藏 活性氧代谢 生物防治 芒果保鲜","农产品贮藏 活性氧代谢","农产品贮藏活性氧代谢生物防治芒果保鲜-2755","10.3389\u002Ffsufs.2026.1877440",{"doi":153,"openalex_id":155,"authors":156,"venue":10,"cited_by_count":36,"oa_url":137,"card":179,"direction":50,"ingested_from":52},"W7213473131",[157,159,161,163,165,167,170,172,175,177],{"name":158,"orcid":9},"Tian Peiyi",{"name":160,"orcid":9},"Dong Ying",{"name":162,"orcid":9},"Duan Jiaying",{"name":164,"orcid":9},"Cheng Qinyang",{"name":166,"orcid":9},"Sun Jing",{"name":168,"orcid":169},"Bangdi Liu","https:\u002F\u002Forcid.org\u002F0000-0003-2302-3830",{"name":171,"orcid":9},"Zhang Min",{"name":173,"orcid":174},"Zhengrong Wang","https:\u002F\u002Forcid.org\u002F0000-0001-7471-5904",{"name":176,"orcid":9},"Maha Abdullah Alwaili",{"name":178,"orcid":9},"Nawal Al-Hoshani",{"tldr":180,"method":181,"finding":182,"direction":50,"opportunity":183},"四种拮抗细菌丸处理芒果，JQ-1通过调控活性氧代谢显著延长保鲜期。","四种拮抗细菌悬浮液喷施芒果，测定ROS代谢与抗氧化酶指标。","JQ-1处理降低MDA、H2O2和O2−·，提高CAT、POD、GPx活性及GSH，保鲜最佳。","可探索拮抗细菌丸在采后保鲜中的分子机制及与其他绿色保鲜技术的协同应用。","2026-09-17T23:30:07.723677Z",{"id":186,"title":187,"url":188,"summary":189,"summary_zh":190,"content":9,"source_name":191,"source_url":188,"published_at":97,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":192,"score_detail":193,"sources":197,"tags":199,"search_phrases":202,"slug":205,"view_count":36,"doi":206,"paper":207,"created_at":235},2741,"A tomato maturity detection method against occlusion and variable illumination","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.compag.2026.112423","A tomato maturity detection method against occlusion and variable illumination。Computers and Electronics in Agriculture","一种抗遮挡和可变光照的番茄成熟度检测方法","Computers and Electronics in Agriculture",68,{"impact":194,"substance":68,"depth":66,"authority":195,"freshness":17,"relevant":22,"comment":196},12,14,"核心期刊论文，针对遮挡与光照变化下的番茄成熟度检测提出新方法，属农业人工智能细分领域实质进展，但应用范围有限，未达重大突破层级。",[198],{"name":191,"url":188},[73,74,200,28,201],"目标检测","作物表型",[203,204],"农业人工智能 作物表型 智慧农业 目标检测","农业人工智能 作物表型","农业人工智能作物表型智慧农业目标检测-2741","10.1016\u002Fj.compag.2026.112423",{"doi":206,"openalex_id":208,"authors":209,"venue":191,"cited_by_count":36,"oa_url":9,"card":230,"direction":86,"ingested_from":52},"W7213429689",[210,213,216,219,222,225,227],{"name":211,"orcid":212},"Hao Meng","https:\u002F\u002Forcid.org\u002F0000-0001-7511-2910",{"name":214,"orcid":215},"Wenzhe Li","https:\u002F\u002Forcid.org\u002F0009-0008-1630-4697",{"name":217,"orcid":218},"Di Wang","https:\u002F\u002Forcid.org\u002F0000-0002-3911-8159",{"name":220,"orcid":221},"Hui Zhao","https:\u002F\u002Forcid.org\u002F0009-0005-4192-5776",{"name":223,"orcid":224},"Ximing Li","https:\u002F\u002Forcid.org\u002F0000-0003-4022-1273",{"name":226,"orcid":9},"Dongdong Cui",{"name":228,"orcid":229},"Fernando Auat Cheein","https:\u002F\u002Forcid.org\u002F0000-0002-6347-7696",{"tldr":231,"method":232,"finding":233,"direction":86,"opportunity":234},"提出一种抗遮挡和光照变化的番茄成熟度检测方法。","基于深度学习的图像检测，针对遮挡与光照变化优化。","该方法在遮挡和变光照下仍能准确检测番茄成熟度。","可探索多模态融合与轻量化部署，提升田间复杂场景实时检测鲁棒性。","2026-09-17T23:30:01.491379Z",{"id":237,"title":238,"url":239,"summary":240,"summary_zh":9,"content":9,"source_name":241,"source_url":9,"published_at":9,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":242,"score_detail":243,"sources":248,"tags":250,"search_phrases":254,"slug":257,"view_count":36,"doi":9,"paper":258,"created_at":266},2735,"面向2035:中国农业的未来业态与战略路径——生态化、智能化、定制化、设施化、工程化与韧性化","https:\u002F\u002Fwww.sohu.com\u002Fa\u002F1076373354_120052222","中国农业科学院科技管理局、油料作物研究所、农业经济与发展研究所、战略研究中心联合发表,文章基于国家中长期发展战略视野,梳理我国农业面临的内在制约、外部机遇与发展动力,探讨未来农业发展生态化、智能化、定制化、设施化、工程化与韧性化六大战略趋势,并提出以科技创新为核心引擎、制度政策为重要保障、现代设施为物质基础、市场机制为调节导向的四位一体协同支撑框架。","中国科学院院刊 2026年第7期",84,{"impact":244,"substance":67,"depth":68,"authority":245,"freshness":246,"relevant":22,"comment":247},26,15,3,"国家级科研机构在核心期刊提出的农业中长期战略框架，六大趋势与四位一体支撑体系具有全国性指导价值，虽时效性偏弱但值得进入每日精选。",[249],{"name":241,"url":239},[73,27,251,252,253],"农业科技","未来农业","农业战略",[255,256],"农业战略 农业科技 智慧农业 未来农业","农业战略 农业科技","农业战略农业科技智慧农业未来农业-2735",{"doi":9,"openalex_id":9,"authors":259,"venue":9,"cited_by_count":36,"oa_url":9,"card":260,"direction":264,"ingested_from":88},[],{"tldr":261,"method":262,"finding":263,"direction":264,"opportunity":265},"梳理中国农业未来六大战略趋势并提出四位一体协同支撑框架。","基于国家中长期战略视野的战略研判与趋势分析。","农业将走向生态化、智能化、定制化、设施化、工程化与韧性化。","数字乡村与农业信息化","六大趋势的量化评价指标与区域差异化落地路径尚缺实证研究。","2026-09-17T00:04:40.789315Z",{"id":268,"title":269,"url":270,"summary":271,"summary_zh":9,"content":272,"source_name":273,"source_url":9,"published_at":97,"category":274,"cover_url":9,"hotness":13,"is_selected":14,"score":64,"score_detail":275,"sources":278,"tags":280,"search_phrases":283,"slug":286,"view_count":36,"doi":9,"paper":9,"created_at":287},2729,"WAFI2026世界农业科技创新大会在京举行——辽宁省农科院等亮相","https:\u002F\u002Fwww.toutiao.com\u002Farticle\u002F7686105927610630691\u002F","2026世界农业科技创新大会(WAFI2026)9月16—19日在北京平谷举行。中国农业大学校长孙其信指出,人工智能已经从过去的示范,变成了部分大型新型经营主体的主要生产方式。中国农业大学王耀君副教授介绍神农大模型3.0已在非洲落地。北京数智京园智慧设施管控技术体系亮相。","潮新闻 记者 沈爱群 侴雪妍\n\n2026世界农业科技创新大会，正在北京举行。\n\n9月16日上午，在大会举行的“人工智能与农业论坛”上，潮新闻记者捕捉到了一个话题：人工智能如何造福农民？\n\n这个话题，由中国农业大学全球食物经济与政策研究院院长樊胜根教授在论坛致辞中提出。\n\n会上，与会国内外专家学者、业界代表见仁见智给出了答案：通过农业人工智能，可以让农民种得好、种得起、种得稳、种得赚。其中，深谙东方智慧的“中国方案”得到了与会嘉宾的点赞与关注。\n\n世界农业科技创新大会（英文缩写WAFI），是以“创新农业 共享未来”为宗旨的世界农业盛会，致力于打造农业“达沃斯”。自2023年成功举办以来，WAFI赢得了国内外同行的高度认可，被誉为世界三大农业盛会之一。\n\n![Image 1](https:\u002F\u002Fp3-sign.toutiaoimg.com\u002Ftos-cn-i-axegupay5k\u002F59a79b9b009545259d6d2d50486c2167~tplv-tt-origin-web:gif.jpeg?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1790208715&x-signature=Mbp32uTVtyQxX7rWipDc9RKtXnU%3D)\n活动现场（记者 沈爱群 摄）\n\n在这个世界级农业盛会上，与会嘉宾为何特别关注“人工智能与农民”？\n\n答案，可以从人工智能时代全球农民、小农户面临的挑战找到。\n\n农业人工智能论坛上，中国农业大学校长、中国工程院院士陈卫就谈到：当前全球农食系统面临前所未有的挑战，气候变化加剧了农业生产的风险，土地、水资源和生物多样性承受着越来越大的压力。“我们必须生产更多更有营养的食物，降低农业对环境的影响，为农村地区创造更好的发展机会。然而这些挑战在不同地区的分布并不均衡，一端是资本和技术高度密集的现代化农场，另一边是数以亿计、以有限的资源支撑全球重要粮食供给的农民与小农户。”\n\n挑战面前，人工智能为农业转型注入了新动能。正如与会嘉宾在本次论坛上提及，人工智能正在推动智能育种、精准种植和农业生产全产业链系统发生新的变化，以卫星遥感数据、气象预警数据、土壤变化数据、种子种植数据以及营销数据分析等，帮助农民实现种植方案自动生成、无人机出苗率检测、卫星遥感旱涝、摄像头自动巡田、智能拼车等农业生产及农事经营。\n\n推动这些新变化的“中国方案”中，有着力农业教育的中国高校，有从事农业生产的中国农业企业，也有站在消费端的中国城市设施农业。\n\n先看中国高校。会上，中国农业大学信息与电子工程学院副教授王耀君和中国农业大学全球食物经济与政策研究院教授张玉梅，分别在主旨演讲中提到了“神农大模型”以及“农业食物经济与政策AI模型”。\n\n神农大模型，去年就已做到了3.0版。作为国内首个实现农业系统智能的大模型，神农1.0版于2023年问世，可以实现农业专业知识的精准查询与问答。2024年迭代的神农2.0版，拓展了技术边界，可以整合文本、图像等多模态数据进行分析决策。2025年全球首发的神农3.0版，打破了农业学科壁垒，让AI成为汇聚农业智慧的载体。\n\n神农大模型3.0是“小麦育种智能助手”。它融合了国家级种质资源与专家知识，可以赋能育种决策，实现从“田间试错”到“精准育种”。\n\n神农3.0还是个农业病虫害智能体。可以识别70类、600余种病虫害，实现用一部手机就能获得如同多个专业植保专家的指导。\n\n值得一提的是，神农3.0还可以让全球农业科技人员和从业者自主构建，以最低成本推动AI应用，让农业AI在科研院所和田间地头普惠落地。“经过过去一年的推广，神农大模型已经跨越千山万水，在非洲落地了。”神农大模型团队负责人王耀君说。\n\n农业食物经济与政策AI模型，不仅面向政府、科研机构和企业，也面向广大农业生产者，旨在将数据、经济模型与人工智能相结合，为农业市场研判和科学决策提供支持。为此，张玉梅教授提醒：“对于农民和小农户来说，这个模型提供的国内外农产品价格监测与异常预警、农业生产成本收益分析、膳食营养评价和国际市场动态分析，可以帮助他们及时了解市场变化 、比较政策方案、评估生产经营收益与营养状况。”\n\n其次，看看农业企业端。会上，北大荒信息有限公司总经理任荣荣向大家介绍了“未来农场”这个各项农艺技术集成平台。以深耕智慧农业培育发展新动能为己任的北大荒信息有限公司，既自主研发了智能装备管理平台覆盖111个农场、接入8.4万台智能装备；也让“未来农场”为60万种植户提供产前、产中、产后服务，实现农业资金交易1000亿元。\n\n再看城市设施农业。会上，北京市数字农业农村促进中心副主任、正高级农艺师芦天罡，向大家展示了北京市“数智京园”智慧设施管控技术体系和连栋温室“赛马制”中试熟化场景。\n\n据芦天罡介绍，北京市目前正通过AI+城市设施农业，实现了连栋温室的国产化技术攻关和日光温室的数智场景改造，快速推动农业产业智能化。“从系统到装备到模型，人工智能可以帮助农户解放劳动力、提高精细化生产水平，还可以调节生产周期，助推农户增收。”芦天罡表示。\n\n“转载请注明出处”","今日头条 2026年9月16日","报道",{"impact":276,"substance":18,"depth":19,"authority":17,"freshness":21,"relevant":22,"comment":277},24,"世界级农业盛会现场报道，汇聚神农大模型3.0、未来农场、数智京园等多方实质进展，信息增量足，值得进入每日精选。",[279],{"name":273,"url":270},[73,74,27,281,282],"神农大模型","智能育种",[284,285],"农业人工智能 神农大模型 智慧农业 智能育种","农业人工智能 神农大模型","农业人工智能神农大模型智慧农业智能育种-2729","2026-09-17T00:04:39.330857Z"]