[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-3663":3,"related-3663":97},{"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,"primary_topic":32,"secondary_topics":38,"classification":39,"search_phrases":58,"slug":61,"view_count":47,"doi":62,"paper":63,"created_at":96},3663,"China’s changing diets improve human health but increase environmental pressures","https:\u002F\u002Fdoi.org\u002F10.1038\u002Fs43247-026-04063-0","Understanding how dietary transitions shape environmental and health outcomes across socio-economic and spatial contexts is essential for informing sustainable food system transformations. Here we investigate evolving trade-offs between environmental and health outcomes during urban and rural dietary transitions in China from 1990 to 2021, and examines how these trade-offs vary with regional development levels. Here we show that China’s dietary transition has shifted from initial health and environment synergies to trade-offs, with rising environmental pressures alongside health gains. These trade-offs are more pronounced in regions with a human development index above 0.55. Urban and rural dietary transitions show broadly similar patterns but differ in trade-off progression and associated risks: urban diets are linked to faster health improvements with rising environmental impacts, while rural diets show slower health gains alongside disproportionately high environmental burdens. Scenario analyses indicate that integrating precision agriculture, food waste reduction, and dietary optimization can substantially reduce both health and environmental burdens while narrowing urban and rural inequalities. China’s dietary transitions improve health outcomes but increase environmental pressures, with faster health gains but rising environmental impacts in urban areas and slower health gains yet higher environmental burdens in rural areas, according to analysis combining environmental and health indicators and scenario modeling","理解饮食结构转变如何在不同社会经济和空间背景下影响环境与健康结果，对于推动可持续食物系统转型至关重要。本文研究了1990年至2021年中国城乡饮食结构转变过程中环境与健康结果之间不断演变的权衡关系，并考察了这些权衡关系如何随区域发展水平而变化。研究表明，中国的饮食结构转变已从初期健康与环境的协同效应转向权衡关系，环境压力与健康收益同步上升。这些权衡关系在人类发展指数高于0.55的地区更为显著。城乡饮食结构转变呈现总体相似的模式，但在权衡关系的演进和相关风险方面存在差异：城市饮食与健康改善速度较快但环境影响上升相关，而农村饮食则表现为健康收益较慢且环境负担不成比例地偏高。情景分析表明，整合精准农业、减少食物浪费和饮食优化可大幅降低健康和环境负担，同时缩小城乡不平等。综合环境与健康指标及情景模型的分析表明，中国饮食结构转变改善了健康结果，但增加了环境压力，城市地区健康收益较快但环境影响上升，农村地区健康收益较慢但环境负担更高。",null,"Communications Earth & Environment","2026-09-25T00:00:00Z","论文",10,true,85,{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":21,"relevant":22,"comment":23},22,23,18,14,8,1,"基于1990-2021年中国城乡膳食转型的环境与健康权衡分析，数据扎实、结论明确，对可持续食物系统与农业政策有参考价值。",[25],{"name":10,"url":6},[27,28,29,30,31],"精准农业","可持续食物系统","食物浪费","膳食转型","城乡差异",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},"I1","smart-agriculture","智慧农业总论","\u002Ftopic\u002Fdigital-agriculture\u002Fsmart-agriculture","I",[],{"status":40,"locked":41,"version":42,"method":43,"evidence":44},"classified",false,"2026-10-22.2","rules",{"candidates":45,"agricultural_evidence":14},[46,52],{"code":33,"score":47,"supported":14,"title":48,"abstract":49,"tags":51},7,[],[27,50],"precision agriculture",[27],{"code":53,"score":54,"supported":41,"title":55,"abstract":56,"tags":57},"E2",2,[],[],[28,29],[59,60],"中国 膳食转型 环境影响","精准农业 食物浪费 膳食优化","中国膳食转型环境影响-3663","10.1038\u002Fs43247-026-04063-0",{"doi":62,"openalex_id":64,"authors":65,"venue":10,"cited_by_count":86,"oa_url":87,"card":88,"direction":94,"ingested_from":95},"W7167885329",[66,68,71,74,77,80,83],{"name":67,"orcid":9},"Yufan Shi",{"name":69,"orcid":70},"Fan Ning","https:\u002F\u002Forcid.org\u002F0009-0006-6198-8253",{"name":72,"orcid":73},"Miaomiao Liu","https:\u002F\u002Forcid.org\u002F0000-0002-9043-3584",{"name":75,"orcid":76},"Jie Yang","https:\u002F\u002Forcid.org\u002F0000-0003-4801-7162",{"name":78,"orcid":79},"Wen Fang","https:\u002F\u002Forcid.org\u002F0000-0001-7748-6772",{"name":81,"orcid":82},"Zongwei Ma","https:\u002F\u002Forcid.org\u002F0000-0003-0257-5695",{"name":84,"orcid":85},"Jun Bi","https:\u002F\u002Forcid.org\u002F0000-0001-9591-4806",0,"https:\u002F\u002Fwww.nature.com\u002Farticles\u002Fs43247-026-04063-0_reference.pdf",{"tldr":89,"method":90,"finding":91,"direction":92,"opportunity":93},"分析1990-2021年中国城乡膳食转型对健康与环境的权衡，并模拟优化路径。","结合环境与健康指标及情景模拟，分析城乡膳食转型与区域发展差异。","膳食转型由健康环境协同转为权衡，城镇健康改善快但环境压力升，农村健康慢而环境负担高。","农业绿色发展与碳","可探究精准农业、减损与膳食优化组合在缩小城乡健康环境不平等中的落地机制与政策路径。","智慧农业 \u002F 农业物联网","openalex","2026-09-28T23:30:10.187347Z",{"total":98,"page":22,"page_size":98,"items":99},6,[100,155,197,244,300,353],{"id":101,"title":102,"url":103,"summary":104,"summary_zh":9,"content":9,"source_name":105,"source_url":103,"published_at":106,"category":12,"cover_url":9,"hotness":13,"is_selected":41,"score":107,"score_detail":108,"sources":112,"tags":114,"primary_topic":119,"secondary_topics":120,"classification":121,"search_phrases":134,"slug":137,"view_count":86,"doi":138,"paper":139,"created_at":154},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":109,"substance":110,"depth":19,"authority":20,"freshness":13,"relevant":22,"comment":111},16,21,"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。",[113],{"name":105,"url":103},[115,116,27,117,118],"智慧农业","农业人工智能","机器视觉","作物行检测",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[],{"status":40,"locked":41,"version":42,"method":43,"evidence":122},{"candidates":123,"agricultural_evidence":14},[124,129],{"code":33,"score":125,"supported":14,"title":126,"abstract":127,"tags":128},5,[],[50],[115,27],{"code":130,"score":54,"supported":41,"title":131,"abstract":132,"tags":133},"I2",[],[],[116,117],[135,136],"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":138,"openalex_id":140,"authors":141,"venue":105,"cited_by_count":86,"oa_url":9,"card":9,"direction":9,"ingested_from":95},"W7223117828",[142,145,148,151],{"name":143,"orcid":144},"Esther Gascó","https:\u002F\u002Forcid.org\u002F0000-0003-1798-4483",{"name":146,"orcid":147},"Clara I. López-González","https:\u002F\u002Forcid.org\u002F0000-0002-2755-1692",{"name":149,"orcid":150},"Eva Besada-Portas","https:\u002F\u002Forcid.org\u002F0000-0001-6129-4653",{"name":152,"orcid":153},"Gonzalo Pájares","https:\u002F\u002Forcid.org\u002F0000-0003-0915-6282","2026-10-22T11:20:09.678587Z",{"id":156,"title":157,"url":158,"summary":159,"summary_zh":9,"content":9,"source_name":160,"source_url":158,"published_at":161,"category":12,"cover_url":9,"hotness":13,"is_selected":41,"score":162,"score_detail":163,"sources":166,"tags":168,"primary_topic":171,"secondary_topics":172,"classification":173,"search_phrases":186,"slug":189,"view_count":86,"doi":190,"paper":191,"created_at":196},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","OpenAlex","2026-10-19T00:00:00Z",56,{"impact":19,"substance":21,"depth":13,"authority":164,"freshness":21,"relevant":22,"comment":165},12,"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。",[167],{"name":160,"url":158},[115,169,27,170],"农业机器人","智能采收",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[],{"status":40,"locked":41,"version":42,"method":43,"evidence":174},{"candidates":175,"agricultural_evidence":14},[176,181],{"code":33,"score":177,"supported":14,"title":178,"abstract":179,"tags":180},13,[50],[50],[115,27],{"code":182,"score":22,"supported":41,"title":183,"abstract":184,"tags":185},"F6",[],[],[169],[187,188],"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":190,"openalex_id":192,"authors":193,"venue":9,"cited_by_count":86,"oa_url":158,"card":9,"direction":94,"ingested_from":95},"W7222971426",[194],{"name":195,"orcid":9},"Joydeep Dey","2026-10-20T23:30:08.600540Z",{"id":198,"title":199,"url":200,"summary":201,"summary_zh":202,"content":9,"source_name":203,"source_url":200,"published_at":161,"category":12,"cover_url":9,"hotness":13,"is_selected":41,"score":107,"score_detail":204,"sources":207,"tags":209,"primary_topic":212,"secondary_topics":213,"classification":214,"search_phrases":227,"slug":230,"view_count":86,"doi":231,"paper":232,"created_at":243},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。","Zenodo (CERN European Organization for Nuclear Research)",{"impact":19,"substance":17,"depth":19,"authority":164,"freshness":205,"relevant":22,"comment":206},9,"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。",[208],{"name":203,"url":200},[115,116,210,27,211],"数字孪生","植物表型",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[],{"status":40,"locked":41,"version":42,"method":43,"evidence":215},{"candidates":216,"agricultural_evidence":14},[217,223],{"code":33,"score":218,"supported":14,"title":219,"abstract":221,"tags":222},20,[220],"digital twin",[27,210,50],[210,115,27],{"code":130,"score":22,"supported":41,"title":224,"abstract":225,"tags":226},[],[],[116],[228,229],"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":231,"openalex_id":233,"authors":234,"venue":203,"cited_by_count":86,"oa_url":200,"card":237,"direction":241,"ingested_from":95},"W7222885652",[235],{"name":236,"orcid":9},"MOHAMMED TAHAR SAIM",{"tldr":238,"method":239,"finding":240,"direction":241,"opportunity":242},"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。","农业遥感与作物表型","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",{"id":245,"title":246,"url":247,"summary":248,"summary_zh":249,"content":9,"source_name":250,"source_url":247,"published_at":251,"category":12,"cover_url":9,"hotness":13,"is_selected":41,"score":252,"score_detail":253,"sources":255,"tags":257,"primary_topic":262,"secondary_topics":263,"classification":264,"search_phrases":276,"slug":279,"view_count":22,"doi":280,"paper":281,"created_at":299},5103,"Assessment of the efficiency of resource potential utilization in the agricultural sector of the economy under investment and innovation development","https:\u002F\u002Fdoi.org\u002F10.32782\u002Fnvlvet-e10701","Ukraine’s agricultural sector is undergoing transformation under the influence of wartime challenges, economic restructuring, European integration, digitalization, and the growing need for sustainable resource management. Improving the efficiency of resource potential utilization has become a prerequisite for strengthening the competitiveness and sustainability of agricultural enterprises. The purpose of this study is to provide a comprehensive assessment of the efficiency of resource potential utilization in the agricultural sector of the economy under investment and innovation development and to substantiate organizational and economic measures for its improvement. The research is based on a systems approach using economic-statistical, comparative, analytical, economic-mathematical, graphical, forecasting, and composite assessment methods. The empirical analysis covers agricultural enterprises in the Poltava region during 2015–2025. Resource potential utilization efficiency was comprehensively assessed by integrating economic, investment, innovation, environmental, and managerial indicators. The results show that technological modernization, digital transformation, investment activity, and strategic management are the principal drivers of efficient resource utilization and sustainable enterprise development. An integrated organizational and economic model for resource potential development is proposed, combining precision agriculture, digital monitoring, resource-saving technologies, and human capital development. Forecasting confirms the positive impact of the proposed measures on labour productivity, capital productivity, profitability, investment activity, digitalization, and the integrated indicator of resource utilization efficiency. The scientific novelty lies in improving a comprehensive methodological approach to assessing the efficiency of resource potential utilization in the agricultural sector of the economy through integrating economic, investment, innovation, environmental, and managerial components. The practical significance lies in applying the proposed approach to strategic planning for agricultural enterprise development, investment decision-making, and improving resource management efficiency.","乌克兰农业部门正处在战时挑战、经济结构调整、欧洲一体化、数字化以及可持续资源管理需求日益增长等多重因素影响下的转型进程之中。提高资源潜力利用效率已成为增强农业企业竞争力和可持续性的先决条件。本研究旨在对投资与创新发展背景下经济中农业部门的资源潜力利用效率进行综合评估，并为其改进提供组织与经济措施的依据。研究基于系统方法，运用了经济统计、比较、分析、经济数学、图形、预测及综合评估等方法。实证分析涵盖2015—2025年波尔塔瓦地区的农业企业。通过整合经济、投资、创新、环境和管理指标，对资源潜力利用效率进行了综合评估。结果表明，技术现代化、数字化转型、投资活动和战略管理是高效资源利用与企业可持续发展的主要驱动力。研究提出了一个资源潜力发展的综合组织与经济模型，将精准农业、数字监测、资源节约技术和人力资本开发相结合。预测结果证实了所提措施对劳动生产率、资本生产率、盈利能力、投资活动、数字化以及资源利用效率综合指标的积极影响。本研究的科学新颖性在于，通过整合经济、投资、创新、环境和管理等组成部分，改进了评估经济中农业部门资源潜力利用效率的综合方法论。其实践意义在于将所提方法应用于农业企业发展的战略规划、投资决策以及提高资源管理效率。","Scientific Messenger of LNU of Veterinary Medicine and Biotechnologies","2026-10-15T00:00:00Z",63,{"impact":21,"substance":19,"depth":109,"authority":164,"freshness":205,"relevant":22,"comment":254},"区域实证研究，方法综合但影响限于乌克兰波尔塔瓦地区，对国内三农信息化参考价值有限。",[256],{"name":250,"url":247},[258,27,259,260,261],"数字农业","农业投资","乌克兰农业","农业资源利用",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[],{"status":40,"locked":41,"version":42,"method":43,"evidence":265},{"candidates":266,"agricultural_evidence":14},[267,271],{"code":33,"score":21,"supported":14,"title":268,"abstract":269,"tags":270},[],[27,50],[258,27],{"code":272,"score":22,"supported":41,"title":273,"abstract":274,"tags":275},"G3",[],[],[259],[277,278],"波尔塔瓦 农业企业 资源潜力","乌克兰 数字化 投资","波尔塔瓦农业企业资源潜力-5103","10.32782\u002Fnvlvet-e10701",{"doi":280,"openalex_id":282,"authors":283,"venue":250,"cited_by_count":86,"oa_url":247,"card":293,"direction":297,"ingested_from":95},"W7221969015",[284,287,290],{"name":285,"orcid":286},"Olena Bukhalo","https:\u002F\u002Forcid.org\u002F0000-0001-7776-6715",{"name":288,"orcid":289},"Андрій Петрович Дорошенко","https:\u002F\u002Forcid.org\u002F0000-0002-6314-1586",{"name":291,"orcid":292},"Yuri Nesterenko","https:\u002F\u002Forcid.org\u002F0009-0000-5831-4465",{"tldr":294,"method":295,"finding":296,"direction":297,"opportunity":298},"评估乌克兰波尔塔瓦地区农业企业资源潜力利用效率并提出改进措施。","系统方法结合经济统计、比较、预测与复合评估，分析2015-2025年农业企业数据","技术现代化、数字化、投资与战略管理是资源高效利用和可持续发展的主要驱动力。","数字乡村与农业信息化","可延伸至战后或转型期农业数字化投资对资源效率的因果机制与动态监测研究。","2026-10-16T23:30:33.662938Z",{"id":301,"title":302,"url":303,"summary":304,"summary_zh":9,"content":9,"source_name":305,"source_url":303,"published_at":306,"category":12,"cover_url":9,"hotness":13,"is_selected":41,"score":307,"score_detail":308,"sources":311,"tags":313,"primary_topic":315,"secondary_topics":316,"classification":317,"search_phrases":333,"slug":336,"view_count":54,"doi":337,"paper":338,"created_at":352},5082,"Entomopathogenic nematode recent applications in precision agriculture: Methods, challenges, and future perspectives","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.jip.2026.108765","Entomopathogenic nematode recent applications in precision agriculture: Methods, challenges, and future perspectives。Journal of Invertebrate Pathology","Journal of Invertebrate Pathology","2026-10-14T00:00:00Z",67,{"impact":164,"substance":109,"depth":309,"authority":20,"freshness":21,"relevant":22,"comment":310},17,"核心期刊综述，聚焦昆虫病原线虫在精准农业中的应用方法与挑战，专业性强但属细分领域，产业影响有限。",[312],{"name":305,"url":303},[115,116,27,314],"生物防治",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[],{"status":40,"locked":41,"version":42,"method":43,"evidence":318},{"candidates":319,"agricultural_evidence":14},[320,324,329],{"code":33,"score":177,"supported":14,"title":321,"abstract":322,"tags":323},[50],[50],[115,27],{"code":325,"score":22,"supported":41,"title":326,"abstract":327,"tags":328},"F4",[],[],[314],{"code":130,"score":22,"supported":41,"title":330,"abstract":331,"tags":332},[],[],[116],[334,335],"昆虫病原线虫 精准农业","Journal of Invertebrate Pathology 线虫","昆虫病原线虫精准农业-5082","10.1016\u002Fj.jip.2026.108765",{"doi":337,"openalex_id":339,"authors":340,"venue":305,"cited_by_count":86,"oa_url":9,"card":9,"direction":94,"ingested_from":95},"W7221746877",[341,344,347,349],{"name":342,"orcid":343},"Alperen Kaan Bütüner","https:\u002F\u002Forcid.org\u002F0000-0002-2121-3529",{"name":345,"orcid":346},"Hilal Erdoğan","https:\u002F\u002Forcid.org\u002F0000-0002-0387-2600",{"name":348,"orcid":9},"İsmail Alper Susurluk",{"name":350,"orcid":351},"Edwin E. Lewis","https:\u002F\u002Forcid.org\u002F0000-0002-8825-1562","2026-10-16T23:30:09.556034Z",{"id":354,"title":355,"url":356,"summary":357,"summary_zh":358,"content":9,"source_name":203,"source_url":356,"published_at":359,"category":12,"cover_url":9,"hotness":13,"is_selected":41,"score":360,"score_detail":361,"sources":363,"tags":365,"primary_topic":369,"secondary_topics":370,"classification":371,"search_phrases":378,"slug":381,"view_count":86,"doi":382,"paper":383,"created_at":397},4905,"Impact of Digital Technologies on Quality Learning Engagement in Agricultural Science Among Students in Secondary Schools in Rivers State","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.23342866","This study examined the impact of digital technologies on quality learning engagement in agricultural science among students in secondary schools in Rivers State, Nigeria. A descriptive survey design was used. Through multi-stage sampling, 400 respondents (112 teachers and 288 students) were drawn from 24 public secondary schools in six Local Government Areas across the three senatorial zones. Data were collected with a self-constructed four-point questionnaire, validated by three experts, with an overall Cronbach’s alpha of 0.77, and analyzed using means, standard deviations and the z-test at the 0.05 level of significance. The study revealed that digital technologies had a positive impact on students’ learning engagement. Instructional technologies such as virtual simulation software, precision agriculture tools and virtual laboratory technology are perceived to enhance quality learning engagement of students in agricultural science. The z-tests showed no significant difference between the groups for any technology. The results show that teachers and students hold similarly favourable views of these technologies, which supports their planned integration into Agricultural Science teaching, particularly where physical laboratory and farm facilities are limited. The study concludes that the adoption of digital technologies into the teaching and learning process of agricultural science has considerable potential to improving the quality of learning engagement and can bridge the gap between theoretical instruction and practical agricultural experiences. the study thus recommends the integration of digital technologies into agricultural science instruction and that schools should organize professional development on its effective use, to enable teachers provide realistic practical experiences.","本研究考察了数字技术对尼日利亚河流州中学生农业科学优质学习投入的影响。研究采用描述性调查设计。通过多阶段抽样，从三个参议员选区六个地方政府区域的24所公立中学中抽取了400名受访者（112名教师和288名学生）。数据采用自行编制的四点式问卷收集，该问卷经三位专家验证，总体Cronbach's alpha系数为0.77，并使用均值、标准差和0.05显著性水平下的z检验进行分析。研究发现，数字技术对学生的学习投入产生了积极影响。虚拟仿真软件、精准农业工具和虚拟实验室技术等教学技术被认为能够提升农业科学学生的优质学习投入。z检验表明，各组在任何技术方面均无显著差异。结果表明，教师和学生对上述技术持相似的良好看法，这支持将其有计划地整合到农业科学教学中，尤其是在实体实验室和农场设施有限的情况下。研究得出结论，将数字技术纳入农业科学的教学过程具有相当大的潜力，能够提高学习投入的质量，并弥合理论教学与实践农业经验之间的差距。因此，研究建议将数字技术整合到农业科学教学中，学校应组织关于其有效使用的专业发展培训，以使教师能够提供真实的实践体验。","2026-10-13T00:00:00Z",61,{"impact":21,"substance":19,"depth":20,"authority":164,"freshness":205,"relevant":22,"comment":362},"尼日利亚地区性实证研究，样本与方法规范，结论支持数字技术融入农业科学教学，对农业信息化教育应用有参考价值，但影响范围限于地方。",[364],{"name":203,"url":356},[115,366,27,367,368],"数字技术","农业教育","虚拟仿真",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[],{"status":40,"locked":41,"version":42,"method":43,"evidence":372},{"candidates":373,"agricultural_evidence":14},[374],{"code":33,"score":205,"supported":14,"title":375,"abstract":376,"tags":377},[],[27,50],[366,115,27],[379,380],"Rivers State 农业科学 数字技术","尼日利亚 中学 农业科学 学习投入","RiversState农业科学数字技术-4905","10.5281\u002Fzenodo.23342866",{"doi":382,"openalex_id":384,"authors":385,"venue":203,"cited_by_count":86,"oa_url":356,"card":392,"direction":297,"ingested_from":95},"W7221595725",[386,388,390],{"name":387,"orcid":9},"P.O. Chukwuocha",{"name":389,"orcid":9},"A.U. Nnodim",{"name":391,"orcid":9},"N.S. Amadi",{"tldr":393,"method":394,"finding":395,"direction":297,"opportunity":396},"研究数字技术对尼日利亚河流州中学农业科学学习投入的影响。","对400名师生问卷调查，用均值、标准差和z检验分析。","数字技术正向提升学习投入，虚拟仿真、精准农业工具等受认可，师生观点无显著差异。","可探究数字技术在农业实践教学中的长期效果及资源匮乏地区的适配模式。","2026-10-14T23:30:34.199346Z"]