[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-740":3,"related-740":60},{"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":22,"tags":24,"primary_topic":28,"secondary_topics":34,"classification":35,"search_phrases":54,"slug":57,"view_count":58,"doi":8,"paper":8,"created_at":59},740,"福州市农业农村局赴福建省农科院对接推进福州分院建设——聚焦茉莉花茶、蔬菜等特色产业","https:\u002F\u002Fwww.toutiao.com\u002Farticle\u002F7674815190273098294","福州市农业农村局赴福建省农业科学院对接推进福州分院建设,院地共建第八个分院,聚焦茉莉花茶、蔬菜等特色产业,推进福建省农科院系统院地合作再上新台阶。",null,"## 福州市农业农村局赴省农业科学院对接推进福州分院建设 推动院地合作走深走实\n\n为深入贯彻市委、市政府工作部署，全面落实市政府与省农业科学院《战略合作框架协议》精神，8月12日，福州市农业农村局党组书记吴志群、局长林健带队拜访省农业科学院，就加快推进省农业科学院福州分院建设开展专题座谈。省农业科学院党委书记、院长余文权主持座谈会，副院长汤浩及双方相关处所、单位负责人参加。\n\n![Image 1](https:\u002F\u002Fp3-sign.toutiaoimg.com\u002Ftos-cn-i-axegupay5k\u002Ff449f740285e422a83d0f17f39237425~tplv-tt-origin-web:gif.jpeg?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1787788712&x-signature=e2BcloE2QrKBHSMe8ke2PsgLTQo%3D)\n\n座谈会上，余文权院长首先传达了省委、省政府主要领导调研省农科院时的工作要求，并紧扣琅岐蔬菜基地提档升级、福州茉莉花茶产业高质量发展、特色农业现代化及农文旅深度融合等重点领域，明确了下一阶段院地合作的重点方向。他指出，福州分院是省农科院在省内布局建设的第8个分院，定位清晰、使命明确，核心任务是服务福州农业科技高质量发展，推动专家人才下沉一线，带动地市级农科机构能力提升。双方要依托福州分院平台，叠加资源与政策优势，强化高位统筹，建立常态化调度机制，力争早出成果、多出高水平成果，将福州分院打造成为全省分院建设的标杆样板。\n\n![Image 2](https:\u002F\u002Fp3-sign.toutiaoimg.com\u002Ftos-cn-i-6w9my0ksvp\u002F933536b015554e2fb222e3bc08f2eacc~tplv-tt-origin-web:gif.jpeg?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1787788712&x-signature=jvfXWPElZeYYaqI2M1CUh8pWx6Y%3D)\n\n吴志群、林健代表福州市农业农村局对省农科院长期以来给予福州“三农”工作的支持表示感谢。他们表示，市农业农村局将以福州分院挂牌成立为契机，坚决扛起科技兴农政治责任，充分发挥牵头抓总作用，统筹市农业科学研究所、市蔬菜科学研究所等单位力量，主动对接省农科院在科技、人才、平台等方面的优势资源。下一步，将聚焦福州茉莉花茶、福橘、枇杷、橄榄、甘薯等特色优势农产品，建立专家团队“一对一”常态化沟通机制，坚持工作项目化、项目清单化、清单责任化，扎实推进科研联合攻关、基层科技服务、专业人才培育、智慧农业平台建设等重点任务，确保各项合作事项落地见效，切实将框架协议转化为推动福州农业高质量发展的实际成效。\n\n此次对接座谈，进一步凝聚了院地合作共识，细化了福州分院建设路径，为后续项目落地、成果转化奠定了坚实基础。双方一致表示，将以此为新起点，同向发力、同题共答，共同书写福州农业科技赋能乡村全面振兴的新篇章。","福建省农业科学院\u002F福州市农业农村局 2026-08-17","2026-08-17T00:00:00Z","报道",10,false,53,{"impact":17,"substance":18,"depth":13,"authority":13,"freshness":19,"relevant":20,"comment":21},12,14,7,1,"地市级农业科技合作动态，聚焦特色产业，有一定信息量，但影响层级有限。",[23],{"name":10,"url":6},[25,26,27],"福建省农科院","福州分院","茉莉花茶",{"code":29,"slug":30,"name":31,"path":32,"parent_code":33},"B1","vegetables","蔬菜","\u002Ftopic\u002Fhorticulture\u002Fvegetables","B",[],{"status":36,"locked":14,"version":37,"method":38,"evidence":39},"classified","2026-10-22.2","rules",{"candidates":40,"agricultural_evidence":43},[41,47],{"code":29,"score":42,"supported":43,"title":44,"abstract":45,"tags":46},11,true,[31],[31],[],{"code":48,"score":49,"supported":43,"title":50,"abstract":51,"tags":53},"G1",3,[],[52],"院地合作",[],[55,56],"福建省农科院 福州分院 茉莉花茶","福建省农科院 福州分院","福建省农科院福州分院茉莉花茶-740",2,"2026-08-19T23:57:29.996651Z",{"total":61,"page":20,"page_size":61,"items":62},6,[63,126,184,242,297,340],{"id":64,"title":65,"url":66,"summary":67,"summary_zh":68,"content":8,"source_name":69,"source_url":66,"published_at":70,"category":71,"cover_url":8,"hotness":13,"is_selected":14,"score":72,"score_detail":73,"sources":78,"tags":80,"primary_topic":86,"secondary_topics":87,"classification":88,"search_phrases":106,"slug":109,"view_count":110,"doi":111,"paper":112,"created_at":125},5565,"A Unified Survival-Based Energy Framework Linking Plant Color, Stress, and Productivity","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.23540961","Plant coloration, expressed through leaf greenness, floral pigmentation, and fruit color intensity, reflects the integrated outcome of pigment biosynthesis, optical absorption, metabolic regulation, and energy–mass exchange with the environment. While the biochemical pathways governing the synthesis and degradation of major pigment classes—including chlorophylls, carotenoids, and anthocyanins—are well established, existing models largely interpret color expression as a localized biochemical phenomenon. Such approaches do not explicitly account for whole-plant energy balance, transpiration-driven losses, or thermodynamic constraints, limiting their ability to explain widely observed patterns of color saturation, stress-induced fading, and species-specific stability across environmental gradients. Here we develop a unified framework for plant color generation and stability that treats pigmentation as a survival-limited energetic process embedded within the broader dynamics of absorption, transport, metabolism, and entropy production. Central to the framework is a dimensionless energy survival factor, Ψ=AE\u002FTE+ε where AE represents absorbed and retained energetic and elemental resources relevant to pigment formation, TE denotes transpiration-linked, metabolic, and environmental dissipation losses, and ε captures irreducible entropy-producing degradation inherent to non-equilibrium biological systems. By construction, 0\u003CΨ\u003C1, ensuring full compliance with the second law of thermodynamics. When combined with pigment-specific optical absorption coefficients and physiological limitation functions, the framework yields a physically interpretable description of both pigment concentration and color stability. Empirical ranges for absorbed photosynthetically active radiation (≈45–70%), excitation survival (≈85–95%), and respiratory and transpiration losses (≈30–60% of assimilated resources) naturally constrain Ψ, predicting observed limits on sustained pigment accumulation without invoking biochemical inefficiency or ad hoc correction factors. The analysis demonstrates that increased light availability or enhanced biosynthetic capacity alone does not intensify coloration unless absorbed resources survive transport and loss processes. Stress-induced chlorosis, transient anthocyanin accumulation, and saturation of greenness under high irradiance emerge as direct consequences of reduced energy survival rather than impaired pigment synthesis. By explicitly separating survival from synthesis, the framework reconciles molecular-scale pigment biochemistry with whole-plant and ecosystem-scale color dynamics. This survival-based formulation provides a unified physical basis for interpreting plant color variation across species and environments and offers a scalable foundation for crop stress diagnostics, remote-sensing interpretation, and comparative plant phenotyping. More broadly, it extends survival-limited energy principles to visible plant traits, advancing plant science beyond isolated biochemical descriptions toward a systems-level understanding of how energy governs phenotypic expression.","植物色泽通过叶片绿色度、花色苷着色和果实颜色强度体现，反映了色素生物合成、光学吸收、代谢调控以及与环境的能量-物质交换的综合结果。尽管主要色素类别——包括叶绿素、类胡萝卜素和花青素——的合成与降解生化途径已较为明确，但现有模型大多将颜色表达解释为局部生化现象。此类方法未明确考虑整株植物能量平衡、蒸腾驱动的损耗或热力学约束，限制了其解释广泛观察到的颜色饱和度、胁迫诱导褪色以及跨环境梯度的物种特异性稳定性等模式的能力。本文构建了一个统一的植物颜色生成与稳定性框架，将色素沉着视为一种受生存限制的能量过程，并将其嵌入吸收、运输、代谢和熵产生的更广泛动力学之中。该框架的核心是一个无量纲能量生存因子Ψ=AE\u002FTE+ε，其中AE代表与色素形成相关的被吸收并保留的能量和元素资源，TE表示与蒸腾相关的、代谢的和环境的耗散损失，ε则捕捉非平衡生物系统固有的不可约熵产生降解。根据构建方式，0\u003CΨ\u003C1，确保完全符合热力学第二定律。当与色素特异性光学吸收系数和生理限制函数相结合时，该框架可对色素浓度和颜色稳定性给出具有物理可解释性的描述。吸收性光合有效辐射（约45–70%）、激发能存活率（约85–95%）以及呼吸和蒸腾损失（约占同化资源的30–60%）的经验范围自然约束了Ψ，从而预测出所观察到的持续色素积累限度，而无需引入生化低效性或特设校正因子。分析表明，仅增加光照可用性或增强生物合成能力并不会加深颜色，除非被吸收的资源能够在运输和损失过程中存活下来。胁迫诱导的黄化、瞬时花青素积累以及高辐照下绿色度饱和，均表现为能量生存率降低而非色素合成受损的直接后果。通过明确分离生存","Zenodo (CERN European Organization for Nuclear Research)","2026-10-21T00:00:00Z","论文",79,{"impact":74,"substance":75,"depth":74,"authority":17,"freshness":76,"relevant":20,"comment":77},18,22,9,"提出以能量生存因子统一解释植物颜色与胁迫的物理框架，方法新颖且对遥感解译和作物诊断有潜在价值，但属预印本理论模型，尚缺田间验证。",[79],{"name":69,"url":66},[81,82,83,84,85],"智慧农业","遥感监测","植物表型","作物胁迫诊断","能量平衡",{"code":29,"slug":30,"name":31,"path":32,"parent_code":33},[],{"status":36,"locked":14,"version":37,"method":38,"evidence":89},{"candidates":90,"agricultural_evidence":43},[91,96,101],{"code":29,"score":49,"supported":43,"title":92,"abstract":93,"tags":95},[],[94],"萝卜",[],{"code":97,"score":20,"supported":14,"title":98,"abstract":99,"tags":100},"I1",[],[],[81],{"code":102,"score":20,"supported":14,"title":103,"abstract":104,"tags":105},"I3",[],[],[82],[107,108],"植物颜色 能量生存因子","作物胁迫 遥感诊断","植物颜色能量生存因子-5565",0,"10.5281\u002Fzenodo.23540961",{"doi":111,"openalex_id":113,"authors":114,"venue":69,"cited_by_count":110,"oa_url":66,"card":118,"direction":122,"ingested_from":124},"W7223098474",[115],{"name":116,"orcid":117},"Mokhdum Azam Mashrafi","https:\u002F\u002Forcid.org\u002F0009-0002-1801-1130",{"tldr":119,"method":120,"finding":121,"direction":122,"opportunity":123},"提出基于生存的能量框架，用能量存活因子解释植物颜色生成与稳定性。","构建无量纲能量存活因子Ψ=AE\u002F(TE+ε)，结合色素吸收系数与生理限制函数。","颜色深浅取决于吸收资源经运输损耗后的存活率，而非单纯合成能力。","农业遥感与作物表型","可将Ψ因子与冠层光谱\u002F表型遥感结合，发展胁迫早期诊断与生产力预测模型。","openalex","2026-10-22T11:20:31.195819Z",{"id":127,"title":128,"url":129,"summary":130,"summary_zh":8,"content":8,"source_name":131,"source_url":8,"published_at":70,"category":71,"cover_url":8,"hotness":13,"is_selected":14,"score":132,"score_detail":133,"sources":139,"tags":141,"primary_topic":146,"secondary_topics":151,"classification":153,"search_phrases":170,"slug":173,"view_count":110,"doi":8,"paper":174,"created_at":183},5536,"日光温室番茄全生育期环境特征解析与智能调控决策支持方法","https:\u002F\u002Fpaper.sciencenet.cn\u002Fhtmlpaper\u002F2026\u002F10\u002F20261021145441802156759.shtm","研究解析日光温室番茄全生育期环境特征，发现该类温室气候缓冲能力较强、有效积温与番茄生理需求呈双峰匹配，但相对增益指标揭示单位时间热量供给失衡、深冬热量不足以及光能结构性不足、湿度调控昼夜失衡等问题。作者建议构建温度—光照—湿度耦合的智能闭环控制系统。","Agriculture 2026-10-21",77,{"impact":134,"substance":135,"depth":136,"authority":137,"freshness":13,"relevant":20,"comment":138},16,21,17,13,"论文解析日光温室番茄全生育期环境特征并提出温光湿耦合智能调控方案，结论有新意，对设施农业信息化有参考价值。",[140],{"name":131,"url":129},[81,142,143,144,145],"设施农业","环境调控","温室番茄","智能决策",{"code":147,"slug":148,"name":149,"path":150,"parent_code":33},"B7","protected-horticulture","设施园艺与植物工厂","\u002Ftopic\u002Fhorticulture\u002Fprotected-horticulture",[152],{"code":29,"slug":30,"name":31,"path":32,"parent_code":33},{"status":36,"locked":14,"version":37,"method":38,"evidence":154},{"candidates":155,"agricultural_evidence":43},[156,161,166],{"code":147,"score":137,"supported":43,"title":157,"abstract":159,"tags":160},[158],"温室",[158],[144,143],{"code":29,"score":42,"supported":43,"title":162,"abstract":164,"tags":165},[163],"番茄",[163],[],{"code":97,"score":20,"supported":14,"title":167,"abstract":168,"tags":169},[],[],[81],[171,172],"日光温室 番茄 环境调控","温室番茄 智能闭环控制","日光温室番茄环境调控-5536",{"doi":8,"openalex_id":8,"authors":175,"venue":8,"cited_by_count":110,"oa_url":8,"card":176,"direction":180,"ingested_from":182},[],{"tldr":177,"method":178,"finding":179,"direction":180,"opportunity":181},"解析日光温室番茄全生育期环境特征并提出智能调控决策支持方法。","基于全生育期环境监测数据，分析积温匹配与相对增益指标。","温室缓冲力强但深冬热量不足、光能结构性不足、湿度昼夜失衡。","智慧农业 \u002F 农业物联网","可研发温度—光照—湿度耦合的智能闭环控制算法，并验证其对番茄产量与能耗的协同优化效果。","agent","2026-10-22T00:07:10.129353Z",{"id":185,"title":186,"url":187,"summary":188,"summary_zh":8,"content":8,"source_name":189,"source_url":8,"published_at":190,"category":71,"cover_url":8,"hotness":13,"is_selected":14,"score":191,"score_detail":192,"sources":195,"tags":197,"primary_topic":203,"secondary_topics":204,"classification":205,"search_phrases":229,"slug":232,"view_count":110,"doi":8,"paper":233,"created_at":241},5533,"基于低成本遥操作机械臂模仿学习的草莓果柄定点采摘","https:\u002F\u002Farxiv.org\u002Fabs\u002F2610.22765","该研究构建视觉运动模仿学习流程，统一感知、运动规划与接触操作，从人工遥操作演示训练基于ResNet-50骨干的动作分块Transformer策略，并在Jetson AGX Orin边缘平台以15赫兹自主部署。策略在130条演示、十万梯度步内损失由2.84降至0.091，数据集与模型权重已开源。预印本，已被IROS农业机器人研讨会接收。","arXiv 预印本 2026-10-16","2026-10-16T00:00:00Z",68,{"impact":134,"substance":135,"depth":74,"authority":76,"freshness":193,"relevant":20,"comment":194},4,"方法新颖、数据与开源材料扎实，但属预印本且已过一周，适合作为细分技术进展收录而非头条精选。",[196],{"name":189,"url":187},[198,199,200,201,202],"农业人工智能","农业机器人","边缘计算","模仿学习","草莓采摘",{"code":29,"slug":30,"name":31,"path":32,"parent_code":33},[],{"status":36,"locked":14,"version":37,"method":38,"evidence":206},{"candidates":207,"agricultural_evidence":43},[208,214,219,224],{"code":29,"score":209,"supported":43,"title":210,"abstract":212,"tags":213},8,[211],"草莓",[],[],{"code":215,"score":193,"supported":43,"title":216,"abstract":217,"tags":218},"F6",[],[199],[199],{"code":220,"score":20,"supported":14,"title":221,"abstract":222,"tags":223},"I2",[],[],[198],{"code":225,"score":20,"supported":14,"title":226,"abstract":227,"tags":228},"I5",[],[],[200],[230,231],"草莓果柄 定点采摘 机械臂","Jetson AGX Orin 采摘 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项科研成果集中亮相，4 家企业现场发布需求，8 个项目签约金额合计 705 万元。签约项目包括水稻品种「申优331」十五年独占许可（全国）、「上研1820」金针菇品种权转让、「申香1726」香菇品种两年普通使用许可（山西）、「珍珠蜜1号」甜瓜品种转让、远缘杂交创制口感型花苔类蔬菜新种源技术等，合作辐射上海、安徽、山西、山东、湖北等多地。","  日前，以“科技赋能 农科‘芯’势力”为主题的“金科育绿”上海农业科技成果路演——上海市农业科学院成果专场活动在南上海科创中心举行。活动旨在贯彻落实《关于加快推进本市农业科技创新的实施意见》《关于加快培育我市涉农科技企业的实施方案》等文件精神，持续强化企业创新主体地位，推动成果供给端与产业需求端精准对接，加快培育农业新质生产力。来自市农业农村委、市农科院、区农业农村委、涉农高校科研院所、农业科技企业、金融机构等约180名代表参加。\n\n  “科技成果只有走出实验室、走向市场，才能真正转化为现实生产力。”上海市农业科学院党委委员、副院长沈晓晖表示，上海农业体量虽小，但农业科技进步贡献率已超过80%。\n\n  本次活动重点聚焦特色种源、农业生物制造和现代设施农业三个新赛道。在成果路演环节，10项科研成果集中亮相，覆盖粮油良种、特色果蔬、食药用菌、智慧农业装备等多个领域，集中展现了市农科院的创新成果。\n\n  在需求路演环节，康码（上海）生物科技有限公司、上海泰缘生物科技股份有限公司、上海青禾上谷智能科技有限公司、上海农本安科技有限公司等4家企业现场发布蛋白营养液及无细胞蛋白产业化、农业废弃物生物新材料产业化、AI智能农业设施及数据驱动育种、智能立体有机植物工厂建设等金融和技术需求。活动还集中发布了5家企业需求，推动产业需求与科研供给、金融资本精准对接。\n\n  签约仪式上，8个合作项目现场签约，涵盖品种权转让、技术独占许可、普通实施许可、技术开发等多种模式，合作辐射上海、安徽、山西、山东、湖北等多地。签约项目包括水稻品种“申优331”十五年独占许可（全国）、“拮抗稻瘟病菌和产γ-聚谷氨酸的贝莱斯芽孢杆菌及其应用”专利三年普通实施许可（上海地区）、金针菇新品种“上研1820”品种权转让、香菇新品种“申香1726”两年普通使用许可（山西省）、“一种复合多种营养物质饲用添加剂生物制造技术体系”转让、甜瓜品种“珍珠蜜1号”转让、黑木耳系列产品加工工艺与配方开发、远缘杂交创制口感型花苔类新蔬菜种源技术等，签约金额合计705万元及提成。活动还通过视频展示了上海农业科技企业金融服务成效。","上海市农业农村委员会 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国内首款华南型黄瓜育种芯片落地青岛","https:\u002F\u002Fwww.farmer.com.cn\u002F2026\u002F10\u002F20\u002F991031341.html","青岛市农科院联合山东极智生物科技发布华南型黄瓜专用5K液相育种芯片V1.0，是国内首款针对华南型黄瓜遗传背景设计的专用育种芯片，筛选5300多个核心位点（含78个功能前景位点），整体检出率97.57%。依托40份核心种质资源全基因组重测序构建，芯片把瓜类回交转育周期从5至6代约三年缩短到2至3代、一年半，育种周期整体有望缩短一半。这是国产分子工具替代外来方案、支撑种业自主可控的关键一步，也说明AI与基因数据结合正在把传统育种推向精准化。","在青岛市农科院的大棚里，黄瓜幼苗绿意正浓。科研人员弯下腰，用镊子轻轻夹起一片嫩叶，剪下零点几克，送进实验室。别小看这片叶子，它很快就能换来一份黄瓜的“基因体检报告”。\n\n日前，在青岛市华南型黄瓜育种技术创新与产业发展研讨会暨专用育种芯片推介会上，由青岛市农科院联合山东极智生物科技有限公司研发的华南型黄瓜专用5K液相育种芯片V1.0正式发布。这是国内首款针对华南型黄瓜遗传背景设计的专用育种芯片，标志着我国华南型黄瓜生物育种在自主可控的国产化工具上迈出关键一步。\n\n“育种芯片，其实就是一把给黄瓜做体检的尺子。”青岛市农科院蔬菜研究所副研究员、黄瓜课题负责人张功臣介绍，这款芯片针对华南型黄瓜量身设计，“5K”代表5000多个位点，实际筛选了5300多个核心位点，液相芯片相当于把多把“分子尺子”集成在一起。只需取零点几克叶片提取DNA，就能判断材料是否抗病、品质如何、有没有刺瘤、带不带苦味——尤其苦味，可以在早期直接筛掉，种到田里的都是目标材料。\n\n省下的时间，账算得清楚。过去传统育种要把大量材料种进大棚，1万份材料需要很多地，从播种到长成耗时漫长；如今在实验室短时间内即可完成成千上万份材料的检测，精筛后再下田。张功臣以瓜类回交转育为例：过去完成一个回交转育过程需要5至6代、约三年，芯片辅助背景选择后只需2至3代，缩短到一年至一年半，育种周期有望整体缩短一半。\n\n为何要专门为华南型黄瓜研发芯片？张功臣解释，青岛拥有特色华南型黄瓜种质资源，本地产业在国内占比高、地位重要，聚集了不少育种企业，青岛特色蔬菜“鲁黄瓜3号”正是其中代表。然而华南型黄瓜育种长期依赖表型经验选择，周期长、效率低；现有高通量分子检测工具多依赖外来技术方案，成本高、部分标记位点与华南型遗传背景适配度不足。加之市场对品质、营养的要求越来越高，传统杂交育种育成一个品种往往需要5至8年，把现代生物育种与传统育种相结合，成为必然选择。\n\n芯片的“硬核”，藏在一组数据里。研发依托40份遗传差异显著的华南型黄瓜核心种质资源，通过全基因组重测序结合生物信息学分析，筛选获得5373个高质量核心标记位点，其中含78个功能前景位点、5295个背景位点。经多批次材料实测，芯片整体检出率达97.57%，分型精准、稳定性优异，突破了传统分子标记通量低、靶向性差的技术瓶颈。\n\n与会专家指出，这款芯片填补了华南型黄瓜高通量分子检测工具的技术短板。依托产学研协同模式，科研成果转化为可落地的商业化技术服务，对保护黄瓜种质资源、提升我国华南型黄瓜育种自主创新能力具有重要现实意义。\n\n在种业企业看来，芯片的价值同样直接。山东极智生物科技有限公司育种事业部总监荆鑫介绍，芯片可通过材料检测判断遗传背景、亲缘关系，帮助育种单位评估产量、品质、抗性等潜力。相比部分高密度芯片，这款5K液相芯片既满足位点需求，检测速度更快、分析周期更短，成本也有望降低，更适合规模化育种应用。\n\n“芯片一定要被使用，才能发挥更大价值。”张功臣说。从实验室到田间，这把国产“分子尺子”正在加速落地，为“以国产芯育中国种”注入新动能，也让黄瓜品种更快更新迭代，端上百姓餐桌。","农民日报 2026-10-20",84,{"impact":75,"substance":306,"depth":74,"authority":17,"freshness":76,"relevant":20,"comment":307},23,"国内首款华南型黄瓜专用育种芯片发布，含位点规模、检出率等实质数据与多方信源，产业价值明确，值得进入每日精选。",[309],{"name":303,"url":300},[257,311,312,313,314],"生物育种","黄瓜","育种芯片","分子标记",{"code":29,"slug":30,"name":31,"path":32,"parent_code":33},[],{"status":36,"locked":14,"version":37,"method":38,"evidence":318},{"candidates":319,"agricultural_evidence":43},[320,324,330],{"code":29,"score":17,"supported":43,"title":321,"abstract":322,"tags":323},[312],[312],[312],{"code":284,"score":19,"supported":43,"title":325,"abstract":326,"tags":329},[],[327,328],"种业","种质资源",[257],{"code":331,"score":58,"supported":14,"title":332,"abstract":333,"tags":334},"F2",[],[],[311,313],[336,337],"青岛农科院 华南型黄瓜 育种芯片","鲁黄瓜3号 育种芯片","青岛农科院华南型黄瓜育种芯片-5411","2026-10-21T00:09:54.078438Z",{"id":341,"title":342,"url":343,"summary":344,"summary_zh":345,"content":8,"source_name":346,"source_url":343,"published_at":347,"category":71,"cover_url":8,"hotness":13,"is_selected":14,"score":348,"score_detail":349,"sources":351,"tags":353,"primary_topic":357,"secondary_topics":358,"classification":364,"search_phrases":383,"slug":386,"view_count":110,"doi":387,"paper":388,"created_at":402},5387,"LIGHTWEIGHT FEATURE FUSED ATTENTION DRIVEN MULTI LEVEL HYBRID MOBILENET V2 FRAMEWORK FOR EARLY TOMATO LEAF DISEASE DETECTION","https:\u002F\u002Fdoi.org\u002F10.62441\u002Factainnovations.vi.1918","It is crucial to find and treat tomato crop diseases early and accurately to improve crop efficiency and make sure there is no scarcity of crop. However, computerized analysis is provocative due to lighting differences, compound backgrounds, and graphic likenesses among infection regions. Research work proposed a lightweight Attention Driven Multi Level Hybrid MobileNet-V2 algorithm that fuses the handcrafted texture structures with Deep Learning (DL) features, then image preprocessing is incorporated using Gaussian, Bilateral, and Guided filters to minimize noise by preserving the disease lesions. LAB color model along with Contrast Limited Adaptive Histogram Equalization (CLAHE) are used to improve the contrast. Otsu thresholding is involved to effectively separate the leaf segment from diseased parts. Local Binary Pattern (LBP) and Gray Level Co-occurrence Matrix (GLCM) descriptors are used to obtain fine-grained features, while high level features are gained by pretrained MobileNet-V2 model. Features fusion is fed to the fully connected layers of deep learning model for training and validation purpose. Results have revealed that the suggested model attains better classification performance as compared to existing models, making it an effective explanation for real time tomato leaf disease detection for smart agriculture applications.","早期准确发现并治疗番茄作物病害，对于提高作物效率、确保作物不短缺至关重要。然而，由于光照差异、复杂背景以及感染区域之间的图形相似性，计算机化分析具有挑战性。研究提出了一种轻量级注意力驱动多层混合MobileNet-V2算法，该算法将手工纹理结构与深度学习（DL）特征相融合，然后结合高斯、双边和引导滤波器进行图像预处理，以在保留病害病变的同时最小化噪声。采用LAB颜色模型和对比度受限自适应直方图均衡化（CLAHE）来提高对比度。引入Otsu阈值分割以有效分离叶片片段与病害部分。使用局部二值模式（LBP）和灰度共生矩阵（GLCM）描述符获取细粒度特征，同时通过预训练的MobileNet-V2模型获取高层特征。特征融合后输入深度学习模型的全连接层进行训练和验证。结果表明，与现有模型相比，所提出的模型取得了更好的分类性能，使其成为智慧农业应用中实时番茄叶片病害检测的有效解决方案。","Acta Innovations","2026-10-18T00:00:00Z",64,{"impact":17,"substance":74,"depth":134,"authority":13,"freshness":209,"relevant":20,"comment":350},"提出融合手工纹理特征与MobileNet-V2的轻量番茄叶病检测方法，有一定方法新颖性，但属单篇论文、应用范围有限，未达每日精选门槛。",[352],{"name":346,"url":343},[81,198,354,355,356],"深度学习","番茄病害","图像识别",{"code":29,"slug":30,"name":31,"path":32,"parent_code":33},[359],{"code":220,"slug":360,"name":361,"path":362,"parent_code":363},"agricultural-ai","农业AI与大模型","\u002Ftopic\u002Fdigital-agriculture\u002Fagricultural-ai","I",{"status":36,"locked":14,"version":37,"method":38,"evidence":365},{"candidates":366,"agricultural_evidence":43},[367,373,378],{"code":29,"score":368,"supported":43,"title":369,"abstract":371,"tags":372},15,[370],"tomato",[163,370],[355],{"code":220,"score":76,"supported":43,"title":374,"abstract":375,"tags":377},[],[354,376],"deep learning",[198,356,354],{"code":97,"score":19,"supported":43,"title":379,"abstract":380,"tags":382},[],[81,381],"smart agriculture",[81],[384,385],"MobileNet-V2 番茄叶片病害","番茄叶病 深度学习 检测","MobileNet-V2番茄叶片病害-5387","10.62441\u002Factainnovations.vi.1918",{"doi":387,"openalex_id":389,"authors":390,"venue":346,"cited_by_count":110,"oa_url":396,"card":397,"direction":180,"ingested_from":124},"W7222977034",[391,393],{"name":392,"orcid":8},"Mrs. Vijetalaxmi A Hegde",{"name":394,"orcid":395},"Abhay Ramakant Kasetwar","https:\u002F\u002Forcid.org\u002F0000-0002-5800-8764","https:\u002F\u002Factainnovations.com\u002Findex.php\u002Fpub\u002Farticle\u002Fdownload\u002F1918\u002F981",{"tldr":398,"method":399,"finding":400,"direction":239,"opportunity":401},"提出轻量注意力多级混合MobileNet-V2框架，融合手工纹理与深度学习特征实现番茄叶片病害早期检","高斯\u002F双边\u002F引导滤波去噪，LAB+CLAHE增强，Otsu分割，LBP与GLCM","所提模型分类性能优于现有模型，可有效用于智慧农业实时番茄叶片病害检测。","可探索多作物跨域泛化、田间复杂光照下轻量模型部署与可解释性，及病害早期分级检测。","2026-10-20T23:30:10.424511Z"]