[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"topic-GEAIR":3},{"name":4,"kind":5,"tokens":6,"total":7,"page":7,"page_size":8,"items":9},"GEAIR","tag",[4],1,100,[10],{"id":11,"title":12,"url":13,"summary":14,"summary_zh":15,"content":16,"source_name":17,"source_url":15,"published_at":15,"category":18,"cover_url":15,"hotness":19,"is_selected":20,"score":21,"score_detail":22,"sources":29,"tags":31,"primary_topic":15,"secondary_topics":37,"classification":38,"search_phrases":64,"slug":67,"view_count":68,"doi":69,"paper":15,"created_at":70},339,"农业智能机器人发展范式转变——从\"以机适种\"到\"种机协同\"","https:\u002F\u002Fnkdb.magtechjournal.com\u002FEN\u002F10.13304\u002Fj.nykjdb.2026.0350","Tinghao ZHANG、Yue XIE、Mengze SUN、Cao XU在《中国农业科技导报》2026年第28卷第6期发表文章。提出农业智能机器人发展正经历从\"以机适种\"(Robot-to-crop Adaptation)到\"种机协同\"(Crop-robot Synergy)的范式转变,首次系统阐述BAR(Bio-inspired Agricultural Robot)模式:以番茄智能育种机器人\"GEAIR\"为代表,将作物花器官改造与机器人授粉深度结合,实现\"花-机-智\"协同;并构建智能育种工厂全流程示意图,推动农业由单一作物性状改良转向作物与机器人的系统化协同设计。该模式有望成为农业新质生产力形成的重要技术方向,为未来智能农业体系构建提供理论参考。",null,"![Image 1](https:\u002F\u002Fnkdb.magtechjournal.com\u002Fimages\u002F1008-0864\u002Fimages\u002Fb1.jpg)\n\n![Image 2](https:\u002F\u002Fnkdb.magtechjournal.com\u002Fimages\u002F1008-0864\u002Fimages\u002Fb2.jpg)\n\n![Image 3](https:\u002F\u002Fnkdb.magtechjournal.com\u002Fimages\u002F1008-0864\u002Fimages\u002Fb3.jpg)\n\n![Image 4](https:\u002F\u002Fnkdb.magtechjournal.com\u002Fimages\u002F1008-0864\u002Fimages\u002Fb4.jpg)\n\n![Image 5](https:\u002F\u002Fnkdb.magtechjournal.com\u002Fimages\u002F1008-0864\u002Fimages\u002Fb9.jpg)\n\n![Image 6](https:\u002F\u002Fnkdb.magtechjournal.com\u002Fimages\u002F1008-0864\u002Fimages\u002Fb5.jpg)\n\n![Image 7](https:\u002F\u002Fnkdb.magtechjournal.com\u002Fimages\u002F1008-0864\u002Fimages\u002Fb6.jpg)\n\n![Image 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[10.13304\u002Fj.nykjdb.2026.0350](https:\u002F\u002Fdoi.org\u002F10.13304\u002Fj.nykjdb.2026.0350)\n\n• DISRUPTIVE AND NON-CONSENSUS INNOVATIONS •\n\n### A Paradigm Shift from “Robot**-**to**-**crop Adaptation” to “Crop**-**robot Synergy” in Agricultural Intelligent Robot Development\n\nTinghao ZHANG 1,2,3([![Image 12](https:\u002F\u002Fnkdb.magtechjournal.com\u002Fimages\u002Femail.png)](mailto:thzhang@genetics.ac.cn)), Yue XIE 1,2,3, Mengze SUN 1,2, Cao XU 1,2,3([![Image 13](https:\u002F\u002Fnkdb.magtechjournal.com\u002Fimages\u002Femail.png)](mailto:caoxu@genetics.ac.cn))\n\n1.   1.State Key Laboratory of Seed Innovation，Institute of Genetics and Developmental Biology，Chinese Academy of Sciences，Beijing 100101，China\n\n2.CAS-JIC Centre of Excellence for Plant and Microbial Science，Institute of Genetics and Developmental Biology，Chinese Academy of Sciences，Beijing 100101，China\n\n3.University of Chinese Academy of Sciences，Beijing 100049，China\n\n*   `Received:`2026-05-27 `Accepted:`2026-06-10 `Online:`2026-06-15 `Published:`2026-07-07 \n*   `Contact:` Tinghao ZHANG,Cao XU \n\n### 从“以机适种”到“种机协同”的农业智能机器人研发范式转变\n\n张廷浩 1,2,3([![Image 14](https:\u002F\u002Fnkdb.magtechjournal.com\u002Fimages\u002Femail.png)](mailto:thzhang@genetics.ac.cn)), 谢跃 1,2,3, 孙萌泽 1,2, 许操 1,2,3([![Image 15](https:\u002F\u002Fnkdb.magtechjournal.com\u002Fimages\u002Femail.png)](mailto:caoxu@genetics.ac.cn))\n\n1.   1.中国科学院遗传与发育生物学研究所，种子创新全国重点实验室，北京 100101\n\n2.中国科学院遗传与发育生物学研究所，CAS-JIC植物与微生物科学卓越创新中心，北京 100101\n\n3.中国科学院大学，北京 100049\n\n*   `通讯作者:` 张廷浩,许操 \n*   `作者简介:`张廷浩 E-mail：[thzhang@genetics.ac.cn](mailto:thzhang@genetics.ac.cn)； \n*   `基金资助:`北京市智能温室蔬菜创新团队项目(BAIC12-2026);北京市乡村振兴农业科技项目(NY2601580000);国家重点研发计划项目(2023YFA0914800) \n\n## [RichHTML 8](https:\u002F\u002Fnkdb.magtechjournal.com\u002FEN\u002F10.13304\u002Fj.nykjdb.2026.0350#)\n\n## [PDF 24](https:\u002F\u002Fnkdb.magtechjournal.com\u002FEN\u002F10.13304\u002Fj.nykjdb.2026.0350#1)\n\n[_![Image 16](https:\u002F\u002Fnkdb.magtechjournal.com\u002Fimages\u002Fknowledge\\_map1.png)_ ## Knowledge 0](https:\u002F\u002Fnkdb.magtechjournal.com\u002FEN\u002Flexeme\u002FshowArticleByLexeme.do?articleID=13229)\n\n#### [Abstract](https:\u002F\u002Fnkdb.magtechjournal.com\u002FEN\u002F10.13304\u002Fj.nykjdb.2026.0350)\n\n**Abstract:**\n\nDriven by demographic change， labor shortages， and climate change， conventional agriculture faces growing constraints in efficiency and resources. Meanwhile， intelligent agriculture continues to encounter major challenges， including the mismatch between crop traits and agricultural robots， and the disconnect between breeding innovation and field production， thereby limiting robotic performance in complex environments. Given this， the paper focused on the BAR model， integrating biotechnology as the foundation， artificial intelligence for empowerment， and robotics for labor， and emphasized the concept of ‘crop-robot co-design’. The application potential of BAR model was explored in key areas such as developing crop traits compatible with robots， optimizing intelligent agricultural decision-making systems， designing multi-task collaborative robots， and building smart breeding factories. Additionally， the practical challenges faced in achieving core technological breakthroughs， establishing an industrial ecosystem and promoting widespread adoption were analyzed. Finally， the agricultural trend toward transforming from ‘robot-to-crop adaptation’ to ‘crop-robot synergy’ was prospected. It was proposed that the BAR model could drive agriculture from single crop trait improvement to systematic co-design of crops and robots. This model should become a key technological direction for developing new forms of agricultural productivity， and provide theoretical guidance for building intelligent agricultural systems in the future.\n\n**Key words:**[BAR model,](https:\u002F\u002Fnkdb.magtechjournal.com\u002FEN\u002F10.13304\u002Fj.nykjdb.2026.0350#)[agricultural intelligent robot,](https:\u002F\u002Fnkdb.magtechjournal.com\u002FEN\u002F10.13304\u002Fj.nykjdb.2026.0350#)[artificial intelligence,](https:\u002F\u002Fnkdb.magtechjournal.com\u002FEN\u002F10.13304\u002Fj.nykjdb.2026.0350#)[crop-robot synergy,](https:\u002F\u002Fnkdb.magtechjournal.com\u002FEN\u002F10.13304\u002Fj.nykjdb.2026.0350#)[agricultural new quality productive forces](https:\u002F\u002Fnkdb.magtechjournal.com\u002FEN\u002F10.13304\u002Fj.nykjdb.2026.0350#)\n\n**摘要：**\n\n在人口结构变化、农业劳动力减少及全球气候变化加剧的背景下，传统高投入、依赖人工经验的农业体系面临效率瓶颈与资源约束等挑战。同时，在智能农业的推进过程中，逐渐暴露出作物农艺性状与智能装备适配性差、育种研发与生产实际脱节等痛点，严重制约了农业智能机器人在复杂场景中的作业效率与规模化推广。鉴于此，围绕生物技术（biotechnology）筑基、人工智能（artificial intelligence）赋能与机器人（robot）劳作深度融合的BAR模式，重点阐述“作物-机器人协同设计”理念，探讨了该模式在创制“机器人友好型”作物性状、优化农业智能决策系统、研发多任务协同机器人及构建智能育种工厂等关键领域的应用潜力，并分析其在核心技术突破、产业生态构建与推广应用中面临的现实挑战。最后，展望了农业由“以机适种”向“种机协同”转型的发展趋势，提出BAR模式可推动农业由单一作物性状改良转向作物与机器人的系统化协同设计。该模式有望成为农业新质生产力形成的重要技术方向，并为未来智能农业体系构建提供理论参考。\n\n**关键词:**[BAR模式,](https:\u002F\u002Fnkdb.magtechjournal.com\u002FEN\u002F10.13304\u002Fj.nykjdb.2026.0350#)[农业智能机器人,](https:\u002F\u002Fnkdb.magtechjournal.com\u002FEN\u002F10.13304\u002Fj.nykjdb.2026.0350#)[人工智能,](https:\u002F\u002Fnkdb.magtechjournal.com\u002FEN\u002F10.13304\u002Fj.nykjdb.2026.0350#)[种机协同,](https:\u002F\u002Fnkdb.magtechjournal.com\u002FEN\u002F10.13304\u002Fj.nykjdb.2026.0350#)[农业新质生产力](https:\u002F\u002Fnkdb.magtechjournal.com\u002FEN\u002F10.13304\u002Fj.nykjdb.2026.0350#)\n\n**CLC Number:**\n\n*   [S-1](https:\u002F\u002Fnkdb.magtechjournal.com\u002FEN\u002F10.13304\u002Fj.nykjdb.2026.0350#)\n\n#### Cite this article\n\nTinghao ZHANG, Yue XIE, Mengze SUN, Cao XU. A Paradigm Shift from “Robot**-**to**-**crop Adaptation” to “Crop**-**robot Synergy” in Agricultural Intelligent Robot Development[J]. Journal of Agricultural Science and Technology, 2026, 28(6): 1-7.\n\n张廷浩, 谢跃, 孙萌泽, 许操. 从“以机适种”到“种机协同”的农业智能机器人研发范式转变[J]. 中国农业科技导报, 2026, 28(6): 1-7.\n\n#### share this article\n\n**Add to citation manager**[EndNote](https:\u002F\u002Fnkdb.magtechjournal.com\u002FEN\u002Farticle\u002FgetTxtFile.do?fileType=EndNote&id=13229)|[Ris](https:\u002F\u002Fnkdb.magtechjournal.com\u002FEN\u002Farticle\u002FgetTxtFile.do?fileType=Ris&id=13229)|[BibTeX](https:\u002F\u002Fnkdb.magtechjournal.com\u002FEN\u002Farticle\u002FgetTxtFile.do?fileType=BibTeX&id=13229)\n\n**URL:**[https:\u002F\u002Fnkdb.magtechjournal.com\u002FEN\u002F10.13304\u002Fj.nykjdb.2026.0350](https:\u002F\u002Fnkdb.magtechjournal.com\u002FEN\u002F10.13304\u002Fj.nykjdb.2026.0350)\n\n[https:\u002F\u002Fnkdb.magtechjournal.com\u002FEN\u002FY2026\u002FV28\u002FI6\u002F1](https:\u002F\u002Fnkdb.magtechjournal.com\u002FEN\u002FY2026\u002FV28\u002FI6\u002F1)\n\n#### [Figures\u002FTables 2](https:\u002F\u002Fnkdb.magtechjournal.com\u002FEN\u002F10.13304\u002Fj.nykjdb.2026.0350)\n\n[![Image 17](https:\u002F\u002Fnkdb.magtechjournal.com\u002Ffileup\u002F1008-0864\u002FFIGURE\u002F2026-28-6\u002FImages\u002F1008-0864-2026-28-6-1\u002FD1B693C9-83F1-48f0-BD0A-3F7060D8CA33-F001.jpg)](https:\u002F\u002Fnkdb.magtechjournal.com\u002FEN\u002F10.13304\u002Fj.nykjdb.2026.0350#figureClass12000)\n\n**Fig. 1**Schematic diagram of crop-robot co-design and working scenario of the intelligent breeding robot ‘GEAIR’ ［7］A： Schematic of floral modification and robotic breeding； B： Floral phenotypes of wild-type and mutant，the scale bar is 1 mm； C： Deep-learning network for flower detection； D： Robotic pollination of tomato in greenhouse \n\n![Image 18](https:\u002F\u002Fnkdb.magtechjournal.com\u002Ffileup\u002F1008-0864\u002FFIGURE\u002F2026-28-6\u002FImages\u002F1008-0864-2026-28-6-1\u002FD1B693C9-83F1-48f0-BD0A-3F7060D8CA33-F001.jpg)\n**Fig. 1**Schematic diagram of crop-robot co-design and working scenario of the intelligent breeding robot ‘GEAIR’ ［7］A： Schematic of floral modification and robotic breeding； B： Floral phenotypes of wild-type and mutant，the scale bar is 1 mm； C： Deep-learning network for flower detection； D： Robotic pollination of tomato in greenhouse\n\n[![Image 19](https:\u002F\u002Fnkdb.magtechjournal.com\u002Ffileup\u002F1008-0864\u002FFIGURE\u002F2026-28-6\u002FImages\u002F1008-0864-2026-28-6-1\u002FD1B693C9-83F1-48f0-BD0A-3F7060D8CA33-F002.jpg)](https:\u002F\u002Fnkdb.magtechjournal.com\u002FEN\u002F10.13304\u002Fj.nykjdb.2026.0350#figureClass12001)\n\n**Fig. 2**Schematic diagram of intelligent breeding factory process integrated with BAR model［7］ \n\n![Image 20](https:\u002F\u002Fnkdb.magtechjournal.com\u002Ffileup\u002F1008-0864\u002FFIGURE\u002F2026-28-6\u002FImages\u002F1008-0864-2026-28-6-1\u002FD1B693C9-83F1-48f0-BD0A-3F7060D8CA33-F002.jpg)\n**Fig. 2**Schematic diagram of intelligent breeding factory process integrated with BAR model［7］\n\n#### [References 25](https:\u002F\u002Fnkdb.magtechjournal.com\u002FEN\u002F10.13304\u002Fj.nykjdb.2026.0350)\n\n[1]LI G, AN L, YANG W, et al.. 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[Study on the Development of Pork Freshness Detection Techniques](https:\u002F\u002Fnkdb.magtechjournal.com\u002FEN\u002F)[J]. , 2009, 11(S1): 72-74.\n\n#### [Recommended Articles](https:\u002F\u002Fnkdb.magtechjournal.com\u002FEN\u002F10.13304\u002Fj.nykjdb.2026.0350)\n\n#### [Metrics](https:\u002F\u002Fnkdb.magtechjournal.com\u002FEN\u002F10.13304\u002Fj.nykjdb.2026.0350)\n\nViewed\n\n**Full text**\n\n32**HTML****PDF** **Just accepted****Online first****Issue****Just accepted****Online first****Issue** 0 0 8 0 0 24 **From****Others****local** **Times**0 32 **Rate**0%100%\n\n**Abstract**\n\n83**Just accepted****Online first****Issue** 0 0 83 **From****local** **Times**83 **Rate**100%\n\n*   [Abstract](javascript:;)\n*   [Figures\u002FTables](javascript:;)\n*   [References](javascript:;)\n*   [Related Articles](javascript:;)\n*   [Recommended Articles](javascript:;)\n*   [Metrics](javascript:;)\n\n[TOP](https:\u002F\u002Fnkdb.magtechjournal.com\u002FEN\u002F10.13304\u002Fj.nykjdb.2026.0350#goTop \"TOP\")\n\n[京ICP备05021913号-17](https:\u002F\u002Fbeian.miit.gov.cn\u002F)![Image 21](https:\u002F\u002Fnkdb.magtechjournal.com\u002Fimages\u002F1008-0864\u002Fimages\u002Fbeian.png)[京公网安备11010802021197号](http:\u002F\u002Fwww.beian.gov.cn\u002Fportal\u002FregisterSystemInfo?recordcode=11010802021197)\n\n Copyright © Journal of Agricultural Science and Technology, All Rights Reserved.\n\n Tel: 010-82109848 E-mail: nykjdb@163.com; nkdb@caas.cn\n\n Powered by [Beijing Magtech Co., Ltd.](http:\u002F\u002Fwww.magtech.com.cn\u002FCN\u002Fmodel\u002Findex.shtml)","中国农业科技导报 2026, 28(6): 1-7","论文",10,false,84,{"impact":23,"substance":24,"depth":25,"authority":26,"freshness":27,"relevant":7,"comment":28},25,22,18,15,4,"核心期刊论文提出农业机器人研发范式转变，具有前瞻性和产业影响，但发表时间较早，时效性不足。",[30],{"name":17,"url":13},[32,33,34,35,4,36],"智能育种","农业智能机器人","种机协同","BAR模式","中国农业科技导报",[],{"status":39,"locked":20,"version":40,"method":41,"evidence":42},"needs_review","2026-10-22.2","rules",{"candidates":43,"agricultural_evidence":47,"reason":63},[44,52,58],{"code":45,"score":46,"supported":47,"title":48,"abstract":49,"tags":51},"B1",3,true,[],[50],"番茄",[],{"code":53,"score":46,"supported":47,"title":54,"abstract":55,"tags":57},"F6",[],[56],"agricultural robot",[],{"code":59,"score":7,"supported":20,"title":60,"abstract":61,"tags":62},"F2",[],[],[32],"多个产业证据相当，需要确认主归属",[65,66],"中国农业科技导报 农业智能机器人 智能育种 种机协同","中国农业科技导报 农业智能机器人","中国农业科技导报农业智能机器人智能育种种机协同-339",2,"10.13304\u002Fj.nykjdb.2026.0350","2026-08-09T23:54:49.567114Z"]