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09:50·[怀柔融媒](https:\u002F\u002Fwww.toutiao.com\u002Fc\u002Fuser\u002Ftoken\u002FMS4wLjABAAAAXDYwUw0px2_OPdLzHWKHzibqEAcAUd4cuJXpgBvAu0E\u002F?source=tuwen_detail)\n\n近日，2026年全国智慧农业创新大赛在雄安举办。中科院自动化所自主研发的串番茄采摘机器人在设施小番茄采摘机器人赛道拔得头筹，全程无人工干预、不伤植株藤蔓，30分钟采收75串番茄，斩获总分200分、线性得分满分的优异成绩。\n\n![Image 1](https:\u002F\u002Fp3-sign.toutiaoimg.com\u002Ftos-cn-i-axegupay5k\u002Fccda56567b964d2b979671e541236190~tplv-tt-origin-web:gif.jpeg?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1787183931&x-signature=sYt1zP%2BFzhWttz0IGk1vDUFfjRg%3D)\n\n本次大赛共设置六大农业技术应用赛道，全国70余家高校、科研院所及企业队伍同台开展实景实操竞技。该赛道要求机器人在标准连栋玻璃温室内自主完成成熟果串识别定位、无损采摘、精准放置全套作业。自动化所采摘机器人高质量完成全流程作业，充分验证了AI赋能现代农业的可行性，为无人化未来农场规模化落地提供优质实践样本。\n\n针对温室果蔬果实堆叠、枝叶遮挡造成采摘难度大、传统设备易伤果漏采等问题，团队新研发柔顺剪式末端执行结构，搭配具身智能高精度采摘算法模型。这套装备融合可见光、触觉多模态感知技术，可精准判别果实成熟度、锁定最优采摘点位，真正实现低损伤、标准化智能采收，提升温室果蔬自动化作业效率。\n\n![Image 2](https:\u002F\u002Fp3-sign.toutiaoimg.com\u002Ftos-cn-i-6w9my0ksvp\u002Fb2b65c6eee6446c183baf0d8cd5b3b1f~tplv-tt-origin-web:gif.jpeg?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1787183931&x-signature=n1kTb8775ayCen6ySesJyOXEg%2B4%3D)\n\n目前这款智能采摘装备已联合中科院遗传与生物发育研究所，在北京、山西、广西多地温室、果园完成示范落地，成为高附加值果蔬采收专用智能装备。\n\n团队已于今年3月同中国科学院大学博士农场郭家坞基地达成深度技术合作，计划9月进驻基地开展实景田间试验，加速智慧农业技术落地转化。\n\n本次参赛项目由怀柔镇、国科大博士农场郭家坞基地联合推介，推动实验室前沿农业机器人技术走向赛场、落地田间。\n\n![Image 3](https:\u002F\u002Fp3-sign.toutiaoimg.com\u002Ftos-cn-i-6w9my0ksvp\u002Fc96c764faebe4f44b3d49dbfbfdcdc9f~tplv-tt-origin-web:gif.jpeg?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1787183931&x-signature=6AqYQkLb7FZSLvYRhDGfHp7szmA%3D)\n\n国科大博士农场郭家坞基地依托中科院大学科研与人才资源，以“人工智能+机器人+生态农场”为核心建设思路，目标打造国内首座全流程全自动智能机器人农场。怀柔镇相关负责人表示，后续将持续扶持博士农场基地建设，推动科技、农业、文旅融合发展，以智能农机装备为抓手打造区域智慧农业标杆。\n\n**END**\n\n【转载请注明来源：北京怀柔公众号】\n\n文字：袁靖茗\n\n编辑：魏润佳","怀柔融媒 2026-08-07","2026-08-07T00:00:00Z","报道",66,{"impact":18,"substance":17,"depth":264,"authority":20,"freshness":191,"relevant":21,"comment":265},15,"报道了智慧农业创新大赛中采摘机器人的技术突破与应用落地，具有行业进展价值，但信源为地方媒体且时效性一般。",[267],{"name":259,"url":256},[26,269,28,270],"雄安","中科院",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[273],{"code":51,"slug":162,"name":163,"path":164,"parent_code":165},{"status":39,"locked":13,"version":40,"method":41,"evidence":275},{"candidates":276,"agricultural_evidence":45},[277,281,285,289],{"code":51,"score":175,"supported":45,"title":278,"abstract":279,"tags":280},[28],[28],[28],{"code":57,"score":175,"supported":45,"title":282,"abstract":283,"tags":284},[26],[26],[26],{"code":32,"score":110,"supported":45,"title":286,"abstract":287,"tags":288},[112],[112],[],{"code":224,"score":290,"supported":45,"title":291,"abstract":292,"tags":293},3,[],[227],[],[295,296],"采摘机器人 智慧农业 中科院 雄安","采摘机器人 智慧农业","采摘机器人智慧农业中科院雄安-456","2026-08-12T23:57:22.928534Z",{"id":300,"title":301,"url":302,"summary":303,"summary_zh":304,"content":8,"source_name":305,"source_url":302,"published_at":306,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":92,"score_detail":307,"sources":309,"tags":311,"primary_topic":316,"secondary_topics":317,"classification":318,"search_phrases":335,"slug":338,"view_count":73,"doi":339,"paper":340,"created_at":353},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",{"impact":18,"substance":94,"depth":18,"authority":175,"freshness":96,"relevant":21,"comment":308},"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。",[310],{"name":305,"url":302},[26,312,313,314,315],"遥感监测","植物表型","作物胁迫诊断","能量平衡",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":13,"version":40,"method":41,"evidence":319},{"candidates":320,"agricultural_evidence":45},[321,326,330],{"code":32,"score":290,"supported":45,"title":322,"abstract":323,"tags":325},[],[324],"萝卜",[],{"code":57,"score":21,"supported":13,"title":327,"abstract":328,"tags":329},[],[],[26],{"code":331,"score":21,"supported":13,"title":332,"abstract":333,"tags":334},"I3",[],[],[312],[336,337],"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","10.5281\u002Fzenodo.23540961",{"doi":339,"openalex_id":341,"authors":342,"venue":305,"cited_by_count":73,"oa_url":302,"card":346,"direction":350,"ingested_from":352},"W7223098474",[343],{"name":344,"orcid":345},"Mokhdum Azam Mashrafi","https:\u002F\u002Forcid.org\u002F0009-0002-1801-1130",{"tldr":347,"method":348,"finding":349,"direction":350,"opportunity":351},"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":355,"title":356,"url":357,"summary":358,"summary_zh":8,"content":8,"source_name":359,"source_url":8,"published_at":306,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":360,"score_detail":361,"sources":365,"tags":367,"primary_topic":372,"secondary_topics":376,"classification":378,"search_phrases":393,"slug":396,"view_count":73,"doi":8,"paper":397,"created_at":404},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":16,"substance":362,"depth":363,"authority":19,"freshness":12,"relevant":21,"comment":364},21,17,"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。",[366],{"name":359,"url":357},[26,368,369,370,371],"设施农业","环境调控","温室番茄","智能决策",{"code":224,"slug":373,"name":374,"path":375,"parent_code":36},"protected-horticulture","设施园艺与植物工厂","\u002Ftopic\u002Fhorticulture\u002Fprotected-horticulture",[377],{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},{"status":39,"locked":13,"version":40,"method":41,"evidence":379},{"candidates":380,"agricultural_evidence":45},[381,385,389],{"code":224,"score":19,"supported":45,"title":382,"abstract":383,"tags":384},[227],[227],[370,369],{"code":32,"score":110,"supported":45,"title":386,"abstract":387,"tags":388},[112],[112],[],{"code":57,"score":21,"supported":13,"title":390,"abstract":391,"tags":392},[],[],[26],[394,395],"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":398,"venue":8,"cited_by_count":73,"oa_url":8,"card":399,"direction":78,"ingested_from":80},[],{"tldr":400,"method":401,"finding":402,"direction":78,"opportunity":403},"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。","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。","2026-10-22T00:07:10.129353Z"]