[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-2765":3,"related-2765":74},{"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":22,"tags":24,"primary_topic":30,"secondary_topics":36,"classification":37,"search_phrases":50,"slug":53,"view_count":54,"doi":55,"paper":56,"created_at":73},2765,"Tuning the architectural flexibility and dynamic swelling boundaries of pectin-chitosan hydrogels using choline chloride-based deep eutectic solvents","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.nxmate.2026.103518","In modified biopolymers, balancing high swelling with tensile compliance remains a major challenge due to water-induced structural collapse. The study aims to systematically tuning the spatial configuration of hydrogen bond donors, HBD (ethylene glycol, glycerol, and acetic acid) in DES to modulate network properties of pectin-chitosan hydrogels (E20, G20 and A20) and their environmental responsiveness, ensuring structural integrity while permitting swelling. The network exhibiting pH and temperature-responsive swelling across pH 3–11 and temperature 30–60 °C, as well as an ionic swelling capacity that varied with valence (Na + > Ca 2+ > Fe 3+ ). By acting as a molecular wedge that competitively disrupts rigid native ionic crosslinks, the ethylene glycol-based DES (E20) reduced the gel fraction to the lowest; 13.33 ± 1.71%, creating an open skeletal framework that achieved a superior water absorption capacity of 16.02 ± 0.15 g\u002Fg at pH 7 due to the minimal size and little steric hindrance of ethylene glycol-based DES. Architectural flexibility was proven through both tensile compliance (Young's modulus of 0.26–1.44 MPa) and static compression load tolerance up to 49.05 kPa (4.91–49.05 kPa) stress range with a minimal fracture. In addition, the cyclic endurance was demonstrated through five consecutive hydration-dehydration cycles. This work establishes a physical-chemistry foundation for predictive molecular design framework that successfully decouples architectural flexibility and compressive load tolerance from swelling-induced network failure. Through this work, a smart, multi-stimuli-responsive, flexible, and high-swelling biopolymer matrix could be tailored for demanding real-world applications such as smart agriculture and soft robotics.","在改性生物聚合物中，由于水诱导的结构坍塌，平衡高溶胀性与拉伸顺应性仍然是一项重大挑战。本研究旨在系统调控低共熔溶剂（DES）中氢键供体（HBD）（乙二醇、甘油和乙酸）的空间构型，以调节果胶-壳聚糖水凝胶（E20、G20和A20）的网络特性及其环境响应性，在确保结构完整性的同时允许溶胀。该网络在pH 3–11和温度30–60 °C范围内表现出pH和温度响应性溶胀，以及随价态变化的离子溶胀能力（Na⁺ > Ca²⁺ > Fe³⁺）。基于乙二醇的DES（E20）作为分子楔子竞争性地破坏刚性天然离子交联，将凝胶分数降至最低，为13.33 ± 1.71%，形成了开放的骨架结构，由于基于乙二醇的DES尺寸最小且空间位阻小，在pH 7时实现了16.02 ± 0.15 g\u002Fg的优异吸水能力。通过拉伸顺应性（杨氏模量为0.26–1.44 MPa）和静态压缩载荷耐受性（应力范围为4.91–49.05 kPa，断裂极小）证明了结构柔韧性。此外，通过五次连续的水合-脱水循环证明了循环耐久性。本研究为预测性分子设计框架建立了物理化学基础，该框架成功地将结构柔韧性和压缩载荷耐受性与溶胀诱导的网络失效解耦。通过这项工作，可以定制一种智能、多刺激响应、柔性且高溶胀的生物聚合物基质，以满足智能农业和软体机器人等严苛的实际应用需求。",null,"Next Materials","2026-09-17T00:00:00Z","论文",10,false,72,{"impact":17,"substance":18,"depth":19,"authority":17,"freshness":13,"relevant":20,"comment":21},12,21,17,1,"果胶-壳聚糖水凝胶经DES调控实现pH\u002F温度\u002F离子多重响应与高溶胀，为智慧农业与软体机器人提供新材料设计框架，方法新颖但尚处实验室阶段。",[23],{"name":10,"url":6},[25,26,27,28,29],"智慧农业","水凝胶","农业新材料","生物聚合物","软体机器人",{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},"I1","smart-agriculture","智慧农业总论","\u002Ftopic\u002Fdigital-agriculture\u002Fsmart-agriculture","I",[],{"status":38,"locked":14,"version":39,"method":40,"evidence":41},"classified","2026-10-22.2","rules",{"candidates":42,"agricultural_evidence":45},[43],{"code":31,"score":44,"supported":45,"title":46,"abstract":47,"tags":49},4,true,[],[48],"smart agriculture",[25],[51,52],"农业新材料 生物聚合物 软体机器人 智慧农业","农业新材料 生物聚合物","农业新材料生物聚合物软体机器人智慧农业-2765",5,"10.1016\u002Fj.nxmate.2026.103518",{"doi":55,"openalex_id":57,"authors":58,"venue":10,"cited_by_count":64,"oa_url":6,"card":65,"direction":71,"ingested_from":72},"W7213449544",[59,61],{"name":60,"orcid":9},"Siti Noor Atiyah Md Raffe",{"name":62,"orcid":63},"Rizana Yusof","https:\u002F\u002Forcid.org\u002F0000-0001-7080-9655",0,{"tldr":66,"method":67,"finding":68,"direction":69,"opportunity":70},"用氯化胆碱基低共熔溶剂调控果胶-壳聚糖水凝胶网络，实现高溶胀与柔性的解耦。","合成E20\u002FG20\u002FA20水凝胶，测试pH、温度、离子响应溶胀及力学性能。","乙二醇基DES作分子楔破坏刚性交联，获得最高吸水16.02 g\u002Fg且保持柔性。","农业绿色发展与碳","可探索该智能水凝胶在农业保水缓释、土壤湿度响应及可降解地膜中的应用。","智慧农业 \u002F 农业物联网","openalex","2026-09-17T23:30:10.104249Z",{"total":75,"page":20,"page_size":75,"items":76},6,[77,134,194,240,279,338],{"id":78,"title":79,"url":80,"summary":81,"summary_zh":9,"content":9,"source_name":82,"source_url":80,"published_at":83,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":84,"score_detail":85,"sources":90,"tags":92,"primary_topic":97,"secondary_topics":98,"classification":99,"search_phrases":113,"slug":116,"view_count":64,"doi":117,"paper":118,"created_at":133},5539,"Robust and transparent crop-row detection from RGB field imagery for vision-based agricultural guidance systems","https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs11119-026-10473-z","Robust and transparent crop-row detection from RGB field imagery for vision-based agricultural guidance systems。Precision Agriculture","Precision Agriculture","2026-10-22T00:00:00Z",79,{"impact":86,"substance":18,"depth":87,"authority":88,"freshness":13,"relevant":20,"comment":89},16,18,14,"核心期刊新论文，提出鲁棒且可解释的RGB作物行检测方法，对视觉导航农机具参考价值明确，但属细分技术进展，未达重大突破层级。",[91],{"name":82,"url":80},[25,93,94,95,96],"农业人工智能","精准农业","机器视觉","作物行检测",{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},[],{"status":38,"locked":14,"version":39,"method":40,"evidence":100},{"candidates":101,"agricultural_evidence":45},[102,107],{"code":31,"score":54,"supported":45,"title":103,"abstract":104,"tags":106},[],[105],"precision agriculture",[25,94],{"code":108,"score":109,"supported":14,"title":110,"abstract":111,"tags":112},"I2",2,[],[],[93,95],[114,115],"RGB 作物行检测","农业人工智能 作物行检测 智慧农业 机器视觉","RGB作物行检测-5539","10.1007\u002Fs11119-026-10473-z",{"doi":117,"openalex_id":119,"authors":120,"venue":82,"cited_by_count":64,"oa_url":9,"card":9,"direction":9,"ingested_from":72},"W7223117828",[121,124,127,130],{"name":122,"orcid":123},"Esther Gascó","https:\u002F\u002Forcid.org\u002F0000-0003-1798-4483",{"name":125,"orcid":126},"Clara I. López-González","https:\u002F\u002Forcid.org\u002F0000-0002-2755-1692",{"name":128,"orcid":129},"Eva Besada-Portas","https:\u002F\u002Forcid.org\u002F0000-0001-6129-4653",{"name":131,"orcid":132},"Gonzalo Pájares","https:\u002F\u002Forcid.org\u002F0000-0003-0915-6282","2026-10-22T11:20:09.678587Z",{"id":135,"title":136,"url":137,"summary":138,"summary_zh":139,"content":9,"source_name":140,"source_url":137,"published_at":141,"category":12,"cover_url":9,"hotness":142,"is_selected":14,"score":143,"score_detail":144,"sources":148,"tags":152,"primary_topic":157,"secondary_topics":158,"classification":159,"search_phrases":176,"slug":179,"view_count":64,"doi":180,"paper":181,"created_at":193},5397,"The Relationship Between Nutrient Concentration and Measurable Optical Characteristics of Banana Leaves: A Quantitative Image-Based Study","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.23469780","Relationship between Nutrient Concentration and Measurable Optical Characteristics of Banana Leaves: A Quantitative Image-Based Study explores the relationship between nutrient concentrations and the optical characteristics of banana leaves using quantitative image analysis. The study focuses on measurable leaf features, including colour intensity, RGB values, and other image-derived parameters, to identify patterns associated with plant nutrient status. Digital images of banana leaves can provide valuable information about variations in leaf appearance that may reflect differences in nutrient availability. By analysing these characteristics alongside nutrient concentration measurements, the study aims to establish quantitative relationships that can support plant nutrient assessment. This approach may contribute to the development of cost-effective, non-destructive, and image-based techniques for monitoring banana plant health. The findings can be useful for precision agriculture, crop management, and future research on digital image processing for agricultural applications.","香蕉叶片养分浓度与可测量光学特征之间的关系：一项基于定量图像的研究探讨了利用定量图像分析研究香蕉叶片养分浓度与光学特征之间的关系。该研究聚焦于可测量的叶片特征，包括颜色强度、RGB值及其他图像衍生参数，以识别与植物养分状况相关的模式。香蕉叶片的数字图像可提供关于叶片外观变化的有价值信息，这些变化可能反映养分有效性的差异。通过将这些特征与养分浓度测量结果一并分析，该研究旨在建立可支持植物养分评估的定量关系。该方法可能有助于开发低成本、非破坏性且基于图像的香蕉植株健康监测技术。研究结果可用于精准农业、作物管理以及未来农业应用数字图像处理的研究。","Zenodo (CERN European Organization for Nuclear Research)","2026-10-19T00:00:00Z",25,66,{"impact":17,"substance":87,"depth":145,"authority":17,"freshness":146,"relevant":20,"comment":147},15,9,"该研究基于图像定量分析香蕉叶片营养状况，方法新颖且面向无损监测，对精准农业有参考价值，但属单作物探索性研究，影响范围有限。",[149,150],{"name":140,"url":137},{"name":140,"url":151},"https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.23470020",[25,153,154,155,156],"图像分析","香蕉","无损监测","作物营养",{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},[],{"status":38,"locked":14,"version":39,"method":40,"evidence":160},{"candidates":161,"agricultural_evidence":45},[162,167,172],{"code":31,"score":163,"supported":45,"title":164,"abstract":165,"tags":166},7,[],[94,105],[25],{"code":168,"score":20,"supported":14,"title":169,"abstract":170,"tags":171},"B2",[],[],[154],{"code":108,"score":20,"supported":14,"title":173,"abstract":174,"tags":175},[],[],[153],[177,178],"香蕉叶片 营养浓度 图像分析","香蕉 无损监测 精准农业","香蕉叶片营养浓度图像分析-5397","10.5281\u002Fzenodo.23469780",{"doi":180,"openalex_id":182,"authors":183,"venue":140,"cited_by_count":64,"oa_url":137,"card":186,"direction":192,"ingested_from":72},"W7222941290",[184],{"name":185,"orcid":9},"Anantjit Publication",{"tldr":187,"method":188,"finding":189,"direction":190,"opportunity":191},"用定量图像分析探究香蕉叶片养分浓度与可测光学特征的关系。","采集香蕉叶片数字图像，提取颜色强度、RGB值等参数，与养分浓度做定量关联分析。","叶片图像光学特征与养分浓度存在可量化的关联，可支撑无损养分评估。","农业遥感与作物表型","可扩展到多品种、多生育期与田间光照校正，并构建图像-养分反演模型与便携诊断工具。","数字乡村与农业信息化","2026-10-20T23:30:22.619634Z",{"id":195,"title":196,"url":197,"summary":198,"summary_zh":9,"content":9,"source_name":199,"source_url":197,"published_at":141,"category":12,"cover_url":9,"hotness":142,"is_selected":14,"score":200,"score_detail":201,"sources":204,"tags":208,"primary_topic":212,"secondary_topics":213,"classification":214,"search_phrases":222,"slug":225,"view_count":64,"doi":226,"paper":227,"created_at":239},5396,"Understanding the Digital Agriculture Landscape in Central Africa: 2000-2026 Systematic Review.","https:\u002F\u002Fdoi.org\u002F10.13140\u002Frg.2.2.22601.71520","Understanding the Digital Agriculture Landscape in Central Africa: 2000-2026 Systematic Review.。OpenAlex","OpenAlex",37,{"impact":202,"substance":75,"depth":202,"authority":75,"freshness":146,"relevant":20,"comment":203},8,"中非数字农业系统综述，主题相关但摘要信息极少，仅题录级元数据，增量与权威性有限，不建议进入每日精选。",[205,206],{"name":199,"url":197},{"name":199,"url":207},"https:\u002F\u002Fdoi.org\u002F10.13140\u002Frg.2.2.16146.41922",[209,25,210,211],"数字农业","农业信息化","中非",{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},[],{"status":38,"locked":14,"version":39,"method":40,"evidence":215},{"candidates":216,"agricultural_evidence":45},[217],{"code":31,"score":88,"supported":45,"title":218,"abstract":220,"tags":221},[219],"digital agriculture",[219],[210,209,25],[223,224],"中非 数字农业","农业信息化 数字农业 智慧农业 中非","中非数字农业-5396","10.13140\u002Frg.2.2.22601.71520",{"doi":226,"openalex_id":228,"authors":229,"venue":9,"cited_by_count":64,"oa_url":197,"card":9,"direction":192,"ingested_from":72},"W7222930115",[230,232,234,237],{"name":231,"orcid":9},"Anani Ogou",{"name":233,"orcid":9},"Henry Chotangui",{"name":235,"orcid":236},"Honoré Beyegue-Djonko","https:\u002F\u002Forcid.org\u002F0009-0004-6447-5889",{"name":238,"orcid":9},"Christopher Mubeteneh Tankou","2026-10-20T23:30:22.542913Z",{"id":241,"title":242,"url":243,"summary":244,"summary_zh":9,"content":9,"source_name":199,"source_url":243,"published_at":141,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":245,"score_detail":246,"sources":248,"tags":250,"primary_topic":253,"secondary_topics":254,"classification":255,"search_phrases":268,"slug":271,"view_count":64,"doi":272,"paper":273,"created_at":278},5380,"Automation, Robotics, and Precision Agriculture Transformation Through Smart Harvest Systems","https:\u002F\u002Fdoi.org\u002F10.13140\u002Frg.2.2.17987.98089","Automation, Robotics, and Precision Agriculture Transformation Through Smart Harvest Systems。OpenAlex",56,{"impact":87,"substance":202,"depth":13,"authority":17,"freshness":202,"relevant":20,"comment":247},"主题契合智慧农业，但摘要仅为标题重复、缺乏方法与数据细节，信息增量有限，暂不建议进入每日精选。",[249],{"name":199,"url":243},[25,251,94,252],"农业机器人","智能采收",{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},[],{"status":38,"locked":14,"version":39,"method":40,"evidence":256},{"candidates":257,"agricultural_evidence":45},[258,263],{"code":31,"score":259,"supported":45,"title":260,"abstract":261,"tags":262},13,[105],[105],[25,94],{"code":264,"score":20,"supported":14,"title":265,"abstract":266,"tags":267},"F6",[],[],[251],[269,270],"农业机器人 智慧农业 智能采收 精准农业","农业机器人 智慧农业","农业机器人智慧农业智能采收精准农业-5380","10.13140\u002Frg.2.2.17987.98089",{"doi":272,"openalex_id":274,"authors":275,"venue":9,"cited_by_count":64,"oa_url":243,"card":9,"direction":71,"ingested_from":72},"W7222971426",[276],{"name":277,"orcid":9},"Joydeep Dey","2026-10-20T23:30:08.600540Z",{"id":280,"title":281,"url":282,"summary":283,"summary_zh":284,"content":9,"source_name":285,"source_url":282,"published_at":141,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":286,"score_detail":287,"sources":291,"tags":293,"primary_topic":298,"secondary_topics":299,"classification":300,"search_phrases":307,"slug":310,"view_count":64,"doi":311,"paper":312,"created_at":337},5375,"Triboelectric Nanogenerator Based on All‐Cellulose Triboelectric Layer for Droplet Energy Harvesting and Self‐Powered Agriculture Monitoring","https:\u002F\u002Fdoi.org\u002F10.1002\u002Fsmll.76354","Cellulose-based triboelectric nanogenerators (TENGs) attract increasing attention; however, developing high-performance all-cellulose-based triboelectric layer TENGs remains challenging. In this study, a regenerated cellulose nanofiber film (R-CNF) is used as a substrate, and an aminosilane intermediate layer is introduced. By utilizing the silanol groups on the silane chains as compatible reactive sites for fluorination grafting, and simultaneously enhancing the bonding strength between modified layers through N-H···F-C hydrogen-bond interactions between amino and fluorine groups, a fluorinated regenerated cellulose nanofiber film (F-R-CNF) is successfully prepared. The degradation rate of F-R-CNF within 13 days is approximately 0.96%. When assembled into a TENG with an ethyl cellulose nanofiber film(ECNF), the output voltage of the resulting TENG is ten times higher than that of the R-CNF-based TENGs, while maintaining 85% of its output performance at 80% relative humidity. Furthermore, a droplet energy harvesting TENG (DE-TENG) is constructed to harvest energy from falling water droplets, demonstrating the potential of the DE-TENG to power agricultural micro-sensors. This study provides a feasible strategy for designing high-performance all-cellulose-based triboelectric layer triboelectric nanogenerators and reveals the great potential of F-R-CNF for self-powered devices and smart agriculture applications.","纤维素基摩擦纳米发电机（TENGs）日益受到关注，然而开发高性能全纤维素基摩擦电层TENG仍面临挑战。本研究以再生纤维素纳米纤维膜（R-CNF）为基底，引入氨基硅烷中间层，利用硅烷链上的硅醇基团作为氟化接枝的相容反应位点，同时通过氨基与含氟基团之间的N-H···F-C氢键相互作用增强改性层间的结合强度，成功制备了氟化再生纤维素纳米纤维膜（F-R-CNF）。F-R-CNF在13天内的降解率约为0.96%。将其与乙基纤维素纳米纤维膜（ECNF）组装成TENG后，所得TENG的输出电压比基于R-CNF的TENG高十倍，同时在80%相对湿度下仍保持85%的输出性能。此外，构建了液滴能量收集TENG（DE-TENG）以收集下落水滴的能量，展示了DE-TENG为农业微传感器供电的潜力。本研究为设计高性能全纤维素基摩擦电层摩擦纳米发电机提供了可行策略，并揭示了F-R-CNF在自供电器件和智慧农业应用中的巨大潜力。","Small",81,{"impact":87,"substance":288,"depth":289,"authority":88,"freshness":202,"relevant":20,"comment":290},22,19,"全纤维素摩擦纳米发电机实现液滴能量收集并驱动农业微传感器，方法新颖、数据扎实，属智慧农业自供电传感的实质进展，值得入选。",[292],{"name":285,"url":282},[25,294,295,296,297],"摩擦纳米发电","液滴能量收集","自供电传感","纤维素材料",{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},[],{"status":38,"locked":14,"version":39,"method":40,"evidence":301},{"candidates":302,"agricultural_evidence":45},[303],{"code":31,"score":163,"supported":45,"title":304,"abstract":305,"tags":306},[],[25,48],[25],[308,309],"全纤维素 摩擦纳米发电机 液滴能量收集","F-R-CNF 自供电 农业监测","全纤维素摩擦纳米发电机液滴能量收集-5375","10.1002\u002Fsmll.76354",{"doi":311,"openalex_id":313,"authors":314,"venue":285,"cited_by_count":64,"oa_url":9,"card":332,"direction":71,"ingested_from":72},"W7222917387",[315,317,320,322,324,327,329],{"name":316,"orcid":9},"Hengwei Xiong",{"name":318,"orcid":319},"Qiaonan Yang","https:\u002F\u002Forcid.org\u002F0000-0002-9365-0867",{"name":321,"orcid":9},"Weijie Li",{"name":323,"orcid":9},"Kangwen Shi",{"name":325,"orcid":326},"Xinyan Sun","https:\u002F\u002Forcid.org\u002F0009-0008-6901-8977",{"name":328,"orcid":9},"Wenpeng Fan",{"name":330,"orcid":331},"Youqiang Zhang","https:\u002F\u002Forcid.org\u002F0009-0006-9129-8050",{"tldr":333,"method":334,"finding":335,"direction":71,"opportunity":336},"制备全纤维素摩擦电层TENG，收集水滴能量为农业微传感器供电。","再生纤维素纳米纤维膜经氨基硅烷中间层氟化接枝，与乙基纤维素膜组装TENG。","输出达R-CNF基TENG的10倍，80%湿度下保持85%性能，13天降解约0.96%。","可探索全纤维素TENG在田间高湿环境下的长期稳定性及与无线传感节点的集成供电。","2026-10-20T23:30:08.252085Z",{"id":339,"title":340,"url":341,"summary":342,"summary_zh":343,"content":9,"source_name":140,"source_url":341,"published_at":141,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":84,"score_detail":344,"sources":346,"tags":348,"primary_topic":351,"secondary_topics":352,"classification":353,"search_phrases":366,"slug":369,"view_count":64,"doi":370,"paper":371,"created_at":381},5316,"PLANT-GPK v2.7: Spatial Heterogeneity and Predictive Digital Twin for Plant Phenotyping","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.23460273","Traditional image-based plant phenotyping assumes spatial homogeneity, estimating a single set of physiological parameters for the entire plant. This paper introduces a novel extension to the PLANT-GPK framework: Spatial Physiological Heatmaps and Predictive Digital Twins. By dividing the plant image into a 3x3 grid and solving the inverse ODE problem for each spatial patch, we reveal the hidden spatial heterogeneity of resource allocation. Furthermore, the recovered parameters are extrapolated to predict the exact day of harvest using a continuous smooth-physics model, providing a powerful prescriptive tool for precision agriculture.","传统的基于图像的植物表型分析假设空间同质性，即对整个植株估计单一组生理参数。本文提出了对PLANT-GPK框架的一种新颖扩展：空间生理热图与预测性数字孪生。通过将植物图像划分为3×3网格并针对每个空间区块求解逆常微分方程（ODE）问题，我们揭示了资源分配中隐藏的空间异质性。此外，利用连续光滑物理模型对所恢复的参数进行外推，以预测确切的收获日期，为精准农业提供了强有力的规范性工具。",{"impact":87,"substance":288,"depth":87,"authority":17,"freshness":146,"relevant":20,"comment":345},"该论文提出植物表型空间异质性建模与预测性数字孪生方法，方法新颖、结论有实用价值，但属细分领域预印本成果，未达重大突破层级。",[347],{"name":140,"url":341},[25,93,349,94,350],"数字孪生","植物表型",{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},[],{"status":38,"locked":14,"version":39,"method":40,"evidence":354},{"candidates":355,"agricultural_evidence":45},[356,362],{"code":31,"score":357,"supported":45,"title":358,"abstract":360,"tags":361},20,[359],"digital twin",[94,349,105],[349,25,94],{"code":108,"score":20,"supported":14,"title":363,"abstract":364,"tags":365},[],[],[93],[367,368],"PLANT-GPK 植物表型","空间生理热图 数字孪生","PLANT-GPK植物表型-5316","10.5281\u002Fzenodo.23460273",{"doi":370,"openalex_id":372,"authors":373,"venue":140,"cited_by_count":64,"oa_url":341,"card":376,"direction":190,"ingested_from":72},"W7222885652",[374],{"name":375,"orcid":9},"MOHAMMED TAHAR SAIM",{"tldr":377,"method":378,"finding":379,"direction":190,"opportunity":380},"将植物图像分3x3网格反演ODE参数，构建空间生理热图与预测数字孪生。","基于PLANT-GPK框架，分块求解逆ODE问题，并用连续平滑物理模型外推。","揭示了植物资源分配的空间异质性，可预测精确收获日。","可探索更细粒度网格与多模态表型融合，提升数字孪生预测精度与田间适用性。","2026-10-19T23:30:19.414490Z"]