[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-1816":3,"related-1816":70},{"id":4,"title":5,"url":6,"summary":7,"summary_zh":8,"content":8,"source_name":9,"source_url":8,"published_at":10,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":14,"score_detail":15,"sources":22,"tags":24,"primary_topic":29,"secondary_topics":35,"classification":36,"search_phrases":55,"slug":58,"view_count":59,"doi":8,"paper":60,"created_at":69},1816,"The Economics of Precision Agriculture (PA) and Resource Efficiency: Digital Technologies for Sustainable and Profitable Farming（MDPI Sustainability 2026, 18(15), 7512）","https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F15\u002F7512","结构化叙事—系统综述2004—2026年Scopus\u002FWoS\u002FGoogle Scholar同行评议研究，整合技术采纳理论、资源经济学与生产效率模型解释数字技术如何产生经济价值。GPS引导机械、可变速率技术、智能灌溉系统、AI驱动决策支持工具、综合数字平台改善水肥利用率、劳动生产率、生产效率和农场盈利能力。但经济表现高度依赖情境，回报率（ROI）、净现值（NPV）、生命周期成本评估方法学不一致降低可比性。地理集中于北美、欧洲与澳大利亚，对中国、印度、巴西等理解有限。",null,"MDPI Sustainability 2026, 18(15)","2026-09-02T00:00:00Z","论文",10,false,76,{"impact":16,"substance":17,"depth":16,"authority":18,"freshness":19,"relevant":20,"comment":21},18,22,13,5,1,"系统综述揭示精准农业经济回报的情境依赖性，指出评估方法不一致及地理覆盖局限，对农业数字化投资决策有参考价值。",[23],{"name":9,"url":6},[25,26,27,28],"数字农业","精准农业","资源效率","经济效益",{"code":30,"slug":31,"name":32,"path":33,"parent_code":34},"H3","irrigation","水资源与灌溉","\u002Ftopic\u002Fenvironment\u002Firrigation","H",[],{"status":37,"locked":13,"version":38,"method":39,"evidence":40},"classified","2026-10-22.2","rules",{"candidates":41,"agricultural_evidence":44},[42,49],{"code":43,"score":12,"supported":44,"title":45,"abstract":47,"tags":48},"I1",true,[46],"precision agriculture",[],[25,26],{"code":30,"score":50,"supported":44,"title":51,"abstract":52,"tags":54},3,[],[53],"灌溉",[],[56,57],"数字农业 精准农业 经济效益 资源效率","数字农业 精准农业","数字农业精准农业经济效益资源效率-1816",0,{"doi":8,"openalex_id":8,"authors":61,"venue":8,"cited_by_count":59,"oa_url":8,"card":62,"direction":66,"ingested_from":68},[],{"tldr":63,"method":64,"finding":65,"direction":66,"opportunity":67},"系统综述2004-2026年精准农业技术经济影响，发现其提升资源效率与盈利但受情境制约。","系统综述Scopus\u002FWoS\u002FGoogle Scholar文献，整合技术采纳理论","精准农业技术改善水肥利用率和盈利能力，但经济回报高度依赖情境，评估方法不一致。","智慧农业 \u002F 农业物联网","研究中国等发展中国家的精准农业经济评估，统一ROI\u002FNPV方法学，探索小农户情境下的技术适配与价值实现。","agent","2026-09-07T00:04:41.581744Z",{"total":71,"page":20,"page_size":71,"items":72},6,[73,189,270,336,410,472],{"id":74,"title":75,"url":76,"summary":77,"summary_zh":78,"content":8,"source_name":79,"source_url":76,"published_at":80,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":81,"score_detail":82,"sources":85,"tags":87,"primary_topic":92,"secondary_topics":98,"classification":105,"search_phrases":163,"slug":166,"view_count":59,"doi":167,"paper":168,"created_at":188},5553,"Artificial Intelligence–Driven Precision Agriculture Systems: Engineering Frameworks for Climate-Resilient Food Production","https:\u002F\u002Fdoi.org\u002F10.53982\u002Fajerd.2026.01.14-j","Climate change, soil issues, water scarcity, and the increasing need for food worldwide mean we need smart farming systems that can manage resources flexibly. Old farming methods used the same inputs and simple rules for decisions. AI can help us manage resources better by adapting and optimizing them as we deal with complex environmental factors. This paper looks closely at AI-powered precision agriculture systems designed to make food production more resilient to changing weather. The authors reviewed research from 2021 to 2026 in agricultural engineering, computer engineering, and environmental systems. The authors examined how machine learning, deep learning, reinforcement learning, computer vision, robotics, and IoT sensors are used for predicting crop yields, spotting diseases, improving irrigation, managing nutrients, and automating field tasks. Our analysis shows that hybrid deep learning models (CNN-LSTM) are better than single models for predicting crop yields over space and time. Reinforcement learning algorithms are also better at adjusting irrigation cycles when weather is unpredictable. Using edge computing for system design reduces delays and improves real-time decision-making compared to traditional cloud-based systems. However, there are still big challenges with understanding how AI models work, having enough diverse data, ensuring cybersecurity, setting common standards, and making these systems affordable, especially in developing countries. To tackle these problems, we suggest a framework that combines AI analysis, distributed sensor networks, adaptive controls, and climate risk assessments. The authors provided critical insights into essential research gaps and outline a technological roadmap towards achieving sustainable, resilient and intelligent agricultural systems.","气候变化、土壤问题、水资源短缺以及全球日益增长的粮食需求，意味着我们需要能够灵活管理资源的智能农业系统。传统农业方法对相同的投入采用固定模式，并依赖简单规则进行决策。人工智能可以帮助我们更好地管理资源，通过适应和优化资源利用来应对复杂的环境因素。本文深入探讨了人工智能驱动的精准农业系统，旨在使粮食生产对不断变化的天气更具韧性。作者综述了2021年至2026年间农业工程、计算机工程和环境系统领域的研究。作者考察了机器学习、深度学习、强化学习、计算机视觉、机器人技术及物联网传感器如何被用于作物产量预测、病害识别、灌溉优化、养分管理和田间作业自动化。我们的分析表明，混合深度学习模型（CNN-LSTM）在时空作物产量预测方面优于单一模型。在天气不可预测的情况下，强化学习算法在调整灌溉周期方面也表现更优。与传统基于云的系统相比，采用边缘计算进行系统设计可降低延迟并改善实时决策能力。然而，在理解人工智能模型的工作原理、获取足够多样化的数据、确保网络安全、制定通用标准以及使这些系统具备可负担性方面，仍存在重大挑战，尤其是在发展中国家。为应对这些问题，我们提出了一个融合人工智能分析、分布式传感器网络、自适应控制和气候风险评估的框架。作者对关键研究空白提供了重要见解，并勾勒了实现可持续、韧性和智能农业系统的技术路线图。","ABUAD Journal of Engineering Research and Development (AJERD)","2026-10-21T00:00:00Z",80,{"impact":16,"substance":17,"depth":16,"authority":18,"freshness":83,"relevant":20,"comment":84},9,"系统综述AI驱动精准农业的工程框架与技术路线，方法梳理扎实、结论有参考价值，但属综述类论文，产业落地影响有限。",[86],{"name":79,"url":76},[88,89,90,26,91],"智慧农业","农业人工智能","物联网","气候韧性",{"code":93,"slug":94,"name":95,"path":96,"parent_code":97},"I2","agricultural-ai","农业AI与大模型","\u002Ftopic\u002Fdigital-agriculture\u002Fagricultural-ai","I",[99,104],{"code":100,"slug":101,"name":102,"path":103,"parent_code":97},"I5","agricultural-iot","物联网传感与边缘计算","\u002Ftopic\u002Fdigital-agriculture\u002Fagricultural-iot",{"code":30,"slug":31,"name":32,"path":33,"parent_code":34},{"status":37,"locked":13,"version":38,"method":39,"evidence":106},{"candidates":107,"agricultural_evidence":44},[108,119,124,131,136,144,151,157],{"code":93,"score":16,"supported":44,"title":109,"abstract":111,"tags":118},[110],"artificial intelligence",[112,113,114,115,116,117],"深度学习","机器学习","计算机视觉","machine learning","deep learning","computer vision",[89],{"code":43,"score":120,"supported":44,"title":121,"abstract":122,"tags":123},16,[46],[26,46],[88,26],{"code":100,"score":12,"supported":44,"title":125,"abstract":126,"tags":130},[],[90,127,128,129],"边缘计算","IoT","edge computing",[90],{"code":30,"score":83,"supported":44,"title":132,"abstract":133,"tags":135},[],[53,134,31],"水资源",[],{"code":137,"score":138,"supported":44,"title":139,"abstract":140,"tags":143},"H7",7,[],[141,142],"气候变化","climate change",[91],{"code":145,"score":71,"supported":44,"title":146,"abstract":147,"tags":150},"H2",[],[148,149],"土壤","soil",[],{"code":152,"score":50,"supported":44,"title":153,"abstract":154,"tags":156},"A7",[],[155],"间作",[],{"code":158,"score":50,"supported":44,"title":159,"abstract":160,"tags":162},"F3",[],[161],"养分管理",[],[164,165],"AI 精准农业 气候韧性","CNN-LSTM 作物产量预测","AI精准农业气候韧性-5553","10.53982\u002Fajerd.2026.01.14-j",{"doi":167,"openalex_id":169,"authors":170,"venue":79,"cited_by_count":59,"oa_url":76,"card":181,"direction":66,"ingested_from":187},"W7223121456",[171,174,176,178],{"name":172,"orcid":173},"Olumayowa J. Iyanda","https:\u002F\u002Forcid.org\u002F0000-0002-5340-9884",{"name":175,"orcid":8},"Oluwadare OYEBODE",{"name":177,"orcid":8},"Iretiayo Adelaiye",{"name":179,"orcid":180},"Ayomide Afolabi","https:\u002F\u002Forcid.org\u002F0000-0002-5171-886X",{"tldr":182,"method":183,"finding":184,"direction":185,"opportunity":186},"综述2021-2026年AI驱动精准农业系统，提出气候韧性粮食生产工程框架。","综述机器学习、深度学习、强化学习、计算机视觉、机器人与物联网在精准农业中的应用。","CNN-LSTM混合模型和强化学习在产量预测与灌溉调度上优于单一方法，边缘计算提升实时性。","农业人工智能与决策模型","可研究边缘计算与强化学习结合的轻量级灌溉决策系统，并探索发展中国家低成本部署与标准化路径。","openalex","2026-10-22T11:20:18.151376Z",{"id":190,"title":191,"url":192,"summary":193,"summary_zh":194,"content":8,"source_name":195,"source_url":192,"published_at":196,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":197,"score_detail":198,"sources":202,"tags":204,"primary_topic":209,"secondary_topics":215,"classification":217,"search_phrases":254,"slug":257,"view_count":59,"doi":258,"paper":259,"created_at":269},5381,"Climate-Smart Floriculture: Strategies for Sustainable Flower Production Under a Changing Climate","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.23467834","Floriculture is a high-value horticultural sector comprising cut flowers, potted flowering plants, foliage plants, ornamental bulbs and nursery plants. The sector is increasingly exposed to climate variability through rising temperature, drought, irregular rainfall, extreme weather events, elevated atmospheric CO₂ and changing pest and disease pressure. These stresses can influence vegetative growth, flowering, flower quality, production scheduling and postharvest performance, thereby affecting the economic value of ornamental crops. Climate-smart floriculture provides an integrated framework for improving resilience while maintaining productivity and resource-use efficiency. Key strategies include climate-resilient cultivar selection, efficient irrigation, soil-moisture conservation, protected cultivation, microclimate regulation, integrated pest management and precision technologies. Genetic improvement offers a long-term approach for developing cultivars capable of maintaining desirable ornamental traits under environmental stress, whereas protected cultivation can buffer crops against external climatic fluctuations. Efficient irrigation, rainwater harvesting and improved soil management can reduce vulnerability to water scarcity, while integrated pest management can address climate-associated changes in pest and disease pressure. Precision agriculture, controlled-environment agriculture and machine-learning-based decision systems offer additional opportunities for real-time monitoring and resource optimisation. However, technological adoption is influenced by investment costs, knowledge availability, extension services, market access and supportive policies. This article discusses the major climate-related risks to floriculture and evaluates integrated strategies for developing productive, resource-efficient and climate-resilient flower production systems.","花卉产业是一个高附加值的园艺部门，包括切花、盆栽开花植物、观叶植物、观赏球根植物和苗木。该产业日益受到气候变率的威胁，表现为气温升高、干旱、降雨不规律、极端天气事件、大气CO₂浓度升高以及病虫害压力变化。这些胁迫可影响营养生长、开花、花卉品质、生产调度和采后性能，进而影响观赏作物的经济价值。气候智慧型花卉产业提供了一个综合框架，可在保持生产力和资源利用效率的同时提高韧性。关键策略包括气候韧性品种选择、高效灌溉、土壤水分保持、设施栽培、微气候调控、病虫害综合治理和精准技术。遗传改良为培育能够在环境胁迫下保持理想观赏性状的品种提供了长期途径，而设施栽培可缓冲作物免受外部气候波动的影响。高效灌溉、雨水收集和改善的土壤管理可降低对水资源短缺的脆弱性，而病虫害综合治理可应对气候相关的病虫害压力变化。精准农业、受控环境农业和基于机器学习的决策系统为实时监测和资源优化提供了额外机会。然而，技术采用受到投资成本、知识可得性、推广服务、市场准入和支持性政策的影响。本文讨论了花卉产业面临的主要气候相关风险，并评估了发展高产、资源高效和气候韧性花卉生产系统的综合策略。","Zenodo (CERN European Organization for Nuclear Research)","2026-10-19T00:00:00Z",77,{"impact":16,"substance":199,"depth":200,"authority":18,"freshness":83,"relevant":20,"comment":201},20,17,"系统综述花卉业气候风险与综合应对策略，具行业参考价值，但属综述性论文、非突破性成果。",[203],{"name":195,"url":192},[26,205,206,207,208],"病虫害防控","气候智慧农业","花卉产业","设施园艺",{"code":210,"slug":211,"name":212,"path":213,"parent_code":214},"B4","flowers","花卉与观赏植物","\u002Ftopic\u002Fhorticulture\u002Fflowers","B",[216],{"code":30,"slug":31,"name":32,"path":33,"parent_code":34},{"status":37,"locked":13,"version":38,"method":39,"evidence":218},{"candidates":219,"agricultural_evidence":44},[220,227,231,237,241,245,249],{"code":210,"score":16,"supported":44,"title":221,"abstract":223,"tags":226},[222],"floriculture",[224,225,222],"花卉","ornamental",[207],{"code":30,"score":83,"supported":44,"title":228,"abstract":229,"tags":230},[],[53,134,31],[],{"code":137,"score":138,"supported":44,"title":232,"abstract":233,"tags":236},[],[234,235],"干旱","drought",[206],{"code":43,"score":138,"supported":44,"title":238,"abstract":239,"tags":240},[],[26,46],[26],{"code":145,"score":71,"supported":44,"title":242,"abstract":243,"tags":244},[],[148,149],[],{"code":93,"score":50,"supported":44,"title":246,"abstract":247,"tags":248},[],[113],[],{"code":250,"score":20,"supported":13,"title":251,"abstract":252,"tags":253},"B7",[],[],[208],[255,256],"花卉 可持续生产 气候变化","气候智慧农业 病虫害防控 精准农业 花卉产业","花卉可持续生产气候变化-5381","10.5281\u002Fzenodo.23467834",{"doi":258,"openalex_id":260,"authors":261,"venue":195,"cited_by_count":59,"oa_url":192,"card":264,"direction":66,"ingested_from":187},"W7222973900",[262],{"name":263,"orcid":8},"Shriya Gupta1 and Harish Kumar2",{"tldr":265,"method":266,"finding":267,"direction":66,"opportunity":268},"综述气候智慧型花卉生产策略，评估气候变化风险与综合适应措施。","文献综述，整合抗逆品种、灌溉、保护地栽培、IPM与精准技术。","综合策略可提升花卉气候韧性，但技术采纳受成本、知识与政策制约。","花卉领域精准农业与机器学习决策应用少，可研究低成本智能环境调控与品种-技术协同。","2026-10-20T23:30:08.681802Z",{"id":271,"title":272,"url":273,"summary":274,"summary_zh":275,"content":8,"source_name":276,"source_url":273,"published_at":196,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":277,"score_detail":278,"sources":282,"tags":284,"primary_topic":287,"secondary_topics":288,"classification":290,"search_phrases":312,"slug":315,"view_count":59,"doi":316,"paper":317,"created_at":335},5378,"IoT-Enabled Smart Irrigation Using ESP32 and LoRa for Precision Water Management in Connectivity-Limited Regions","https:\u002F\u002Fdoi.org\u002F10.3390\u002Felectronics15204831","In this paper, a new method for irrigation systems in agriculture has been reported. This work aims to design and implement a smart irrigation system based on the ESP32 platform and Internet of Things (IoT) technologies for optimizing water usage management. With the rapid growth of Internet of Things (IoT) technologies, where devices are connected and can be controlled through the internet, it is now feasible to design smart irrigation systems based on real-time environmental data to deliver optimal water use with minimal human intervention. In Sahara areas, where communication networks and internet connections are lacking, alternative communication protocols are necessary for data transfer. LoRa technology based on the SX1278 transceiver provides long-range, low-power communication that can achieve multi-kilometer ranges (up to 10–15 km in rural areas) under ideal conditions: line-of-sight, high antenna height, low data rate, and open rural environments between distributed sensor nodes and a central gateway. However, this theoretical range cannot be assumed in practice. Field tests under standard farm deployment conditions (ground-level placement and vegetation interference) showed that the link was lost at approximately 120 m, which validates the system at the scale of a field plot. This project used Arduino (version 2.3.7) software to program the NodeMCU (ESP32) board to link the board with the Blynk cloud application. The project is used to monitor the temperature, humidity, and soil moisture and do the command for the irrigation system, with master and slave cards using LoRa technology as a communication tool to replace communication systems like WiFi or cellular networks in deserted or remote areas, which might not offer sufficient coverage or could be too expensive to build. To address this challenge, this paper presents the design and implementation of a smart irrigation system based on the ESP32 microcontroller and LoRa (SX1278) technology, with the long-term objective of helping in the modernization of traditional agriculture and environmental sustainability. Extending the coverage to larger fields and Sahara areas would require elevated antennas, optimized LoRa parameters (spreading factor and bandwidth), multi-hop relay nodes, or multiple gateways; these strategies are proposed as future work.","本文报道了一种农业灌溉系统的新方法。本工作旨在设计和实现一种基于ESP32平台和物联网（Internet of Things, IoT）技术的智能灌溉系统，以优化用水管理。随着物联网技术的快速发展，设备得以互联并可通过互联网进行控制，如今基于实时环境数据设计智能灌溉系统，以在最少人工干预下实现最优用水已成为可能。在撒哈拉地区，由于缺乏通信网络和互联网连接，数据传输需要采用替代通信协议。基于SX1278收发器的LoRa技术可提供远距离、低功耗通信，在理想条件下（视距传输、天线高度较高、低数据速率以及分布式传感器节点与中心网关之间开阔的农村环境），其通信距离可达数公里（农村地区可达10–15 km）。然而，这一理论距离在实际中并不能假定成立。在标准农田部署条件下（地面放置和植被干扰）进行的现场测试表明，链路在约120 m处即发生中断，这验证了系统在田块尺度上的可行性。本项目使用Arduino（版本2.3.7）软件对NodeMCU（ESP32）开发板进行编程，将开发板与Blynk云应用相连接。该项目用于监测温度、湿度和土壤水分，并向灌溉系统发送指令，主从卡采用LoRa技术作为通信工具，以替代WiFi或蜂窝网络等通信系统——这些系统在荒漠或偏远地区可能覆盖不足，或建设成本过高。为应对这一挑战，本文提出了基于ESP32微控制器和LoRa（SX1278）技术的智能灌溉系统的设计与实现，其长期目标是助力传统农业的现代化和环境可持续性。要将覆盖范围扩展至更大田块和撒哈拉地区，需要架高天线、优化LoRa参数（扩频因子和带宽）、采用多跳中继节点或部署多个网关；这些策略被提出作为未来工作。","Electronics",67,{"impact":279,"substance":16,"depth":120,"authority":18,"freshness":280,"relevant":20,"comment":281},12,8,"面向无网络覆盖地区的ESP32+LoRa智能灌溉系统，含实地链路测试数据，方法有参考价值但属细分技术进展，未达每日精选门槛。",[283],{"name":276,"url":273},[88,90,26,285,286],"节水灌溉","LoRa",{"code":100,"slug":101,"name":102,"path":103,"parent_code":97},[289],{"code":30,"slug":31,"name":32,"path":33,"parent_code":34},{"status":37,"locked":13,"version":38,"method":39,"evidence":291},{"candidates":292,"agricultural_evidence":44},[293,298,303,307],{"code":100,"score":16,"supported":44,"title":294,"abstract":295,"tags":297},[128],[90,296,128],"internet of things",[90],{"code":30,"score":299,"supported":44,"title":300,"abstract":301,"tags":302},15,[31],[53,31],[285],{"code":145,"score":71,"supported":44,"title":304,"abstract":305,"tags":306},[],[148,149],[],{"code":43,"score":308,"supported":13,"title":309,"abstract":310,"tags":311},2,[],[],[88,26],[313,314],"ESP32 LoRa 智能灌溉","SX1278 精准灌溉","ESP32LoRa智能灌溉-5378","10.3390\u002Felectronics15204831",{"doi":316,"openalex_id":318,"authors":319,"venue":276,"cited_by_count":59,"oa_url":273,"card":330,"direction":66,"ingested_from":187},"W7222959710",[320,322,324,327],{"name":321,"orcid":8},"Hanfoug Salah",{"name":323,"orcid":8},"Riad Saidi",{"name":325,"orcid":326},"Abdelaziz Aouiche","https:\u002F\u002Forcid.org\u002F0000-0003-1378-7941",{"name":328,"orcid":329},"Yazeed Alkhrijah","https:\u002F\u002Forcid.org\u002F0000-0001-7352-003X",{"tldr":331,"method":332,"finding":333,"direction":66,"opportunity":334},"基于ESP32与LoRa构建智能灌溉系统，在无网络覆盖区实现精准用水管理。","ESP32采集温湿度和土壤水分，经LoRa(SX1278)传输至网关并接入Bly","实际农田条件下LoRa链路仅约120米即中断，远低于理论公里级。","可研究多跳中继、天线高度与扩频参数优化，提升偏远农田LoRa组网覆盖与可靠性。","2026-10-20T23:30:08.464791Z",{"id":337,"title":338,"url":339,"summary":340,"summary_zh":341,"content":8,"source_name":342,"source_url":339,"published_at":343,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":14,"score_detail":344,"sources":347,"tags":349,"primary_topic":354,"secondary_topics":355,"classification":356,"search_phrases":390,"slug":393,"view_count":59,"doi":394,"paper":395,"created_at":409},5139,"Association between digital agricultural technology promotion and farmers’ adoption of extreme climate adaptation technologies: evidence from chili pepper farmers in Guizhou Province, China","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1914305","Adaptation technologies are important for reducing the risks associated with extreme climatic events, particularly in mountainous areas where complex topography can increase agricultural vulnerability. Digital Agricultural Technology Promotion (DATP) provides an increasingly important channel through which farmers access information related to climate adaptation technologies. However, empirical evidence on the association between DATP and farmers’ adoption of such technologies in mountainous areas remains limited. Using survey data from 846 chili pepper farmers in Guizhou Province, China, this study employs baseline regression, mediation analysis, moderation analysis, and heterogeneity analysis to examine the association between DATP and farmers’ adoption of extreme climate adaptation technologies. The results show that DATP is significantly and positively associated with both adoption degree and sustained adoption willingness. Mediation analysis identifies three potential pathways consistent with this association: broader information access channels, greater information trust, and stronger information application ability. Moderation analysis further shows that benefit and risk expectation confirmation significantly condition the association between DATP and adaptation behavior. Heterogeneity analysis indicates that the positive association is strongest for water resource management and biological control technologies and is relatively stronger among pure farmers, farmers with higher digital literacy, and large-scale chili farmers. These findings highlight the relevance of information access, information credibility, digital capabilities, and farmer heterogeneity in understanding digital approaches to climate adaptation in mountainous agricultural areas. The findings provide empirical evidence for developing differentiated digital strategies to support farmers’ climate adaptation.","适应技术对于降低极端气候事件相关风险具有重要意义，在复杂地形加剧农业脆弱性的山区尤为如此。数字农业技术推广（Digital Agricultural Technology Promotion，DATP）为农户获取气候适应技术相关信息提供了日益重要的渠道。然而，关于DATP与山区农户采纳此类技术之间关联的实证证据仍然有限。本研究利用来自中国贵州省846户辣椒种植户的调查数据，采用基准回归、中介分析、调节分析和异质性分析，考察DATP与农户极端气候适应技术采纳之间的关联。结果表明，DATP与采纳程度和持续采纳意愿均呈显著正相关。中介分析识别出与该关联相符的三条潜在路径：更广泛的信息获取渠道、更高的信息信任以及更强的信息应用能力。调节分析进一步表明，收益与风险预期确认显著调节DATP与适应行为之间的关联。异质性分析表明，该正向关联在水资源管理和生物防治技术中最为显著，且在纯农户、数字素养较高的农户和规模化辣椒种植户中相对更强。上述发现凸显了信息获取、信息可信度、数字能力和农户异质性在理解山区农业气候适应数字化路径中的相关性。研究结果为制定差异化数字策略以支持农户气候适应提供了实证依据。","Frontiers in Sustainable Food Systems","2026-10-16T00:00:00Z",{"impact":120,"substance":345,"depth":200,"authority":18,"freshness":83,"relevant":20,"comment":346},21,"基于846户贵州椒农调查的实证研究，揭示数字农技推广与气候适应技术采纳的关联机制，数据扎实、结论有政策参考价值，值得入选。",[348],{"name":342,"url":339},[25,350,351,352,353],"农户采纳","气候适应","贵州农业","辣椒种植",{"code":30,"slug":31,"name":32,"path":33,"parent_code":34},[],{"status":37,"locked":13,"version":38,"method":39,"evidence":357},{"candidates":358,"agricultural_evidence":44},[359,364,369,373,379,385],{"code":30,"score":71,"supported":44,"title":360,"abstract":361,"tags":363},[],[134,362],"water resource",[],{"code":137,"score":365,"supported":44,"title":366,"abstract":367,"tags":368},4,[],[351],[351],{"code":43,"score":365,"supported":44,"title":370,"abstract":371,"tags":372},[],[25],[25],{"code":374,"score":50,"supported":44,"title":375,"abstract":376,"tags":378},"B1",[],[377],"辣椒",[],{"code":380,"score":50,"supported":44,"title":381,"abstract":382,"tags":384},"F4",[],[383],"生物防治",[],{"code":386,"score":20,"supported":13,"title":387,"abstract":388,"tags":389},"G2",[],[],[350],[391,392],"贵州 辣椒 农户 数字农业","数字农业技术推广 气候适应","贵州辣椒农户数字农业-5139","10.3389\u002Ffsufs.2026.1914305",{"doi":394,"openalex_id":396,"authors":397,"venue":342,"cited_by_count":59,"oa_url":402,"card":403,"direction":407,"ingested_from":187},"W7222443624",[398,400],{"name":399,"orcid":8},"Hongjuan Gao",{"name":401,"orcid":8},"Han Huiqing","https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fsustainable-food-systems\u002Farticles\u002F10.3389\u002Ffsufs.2026.1914305\u002Fpdf",{"tldr":404,"method":405,"finding":406,"direction":407,"opportunity":408},"基于贵州846户椒农调查，分析数字农业技术推广与农户极端气候适应技术采纳的关联。","贵州椒农问卷数据，基线回归、中介、调节与异质性分析。","数字推广显著正向关联采纳程度与持续意愿，信息获取、信任、应用能力为中介路径。","数字乡村与农业信息化","可延伸研究数字推广对不同作物、不同地形区农户气候适应行为的差异化机制与长期效果。","2026-10-17T23:30:06.590477Z",{"id":411,"title":412,"url":413,"summary":414,"summary_zh":415,"content":8,"source_name":195,"source_url":413,"published_at":416,"category":11,"cover_url":8,"hotness":417,"is_selected":13,"score":418,"score_detail":419,"sources":422,"tags":427,"primary_topic":431,"secondary_topics":432,"classification":433,"search_phrases":455,"slug":458,"view_count":308,"doi":459,"paper":460,"created_at":471},5073,"INCREASING REGIONAL ADDED VALUE THROUGH THE PROCESSING OF AGRICULTURAL PRODUCTS IN THE REPUBLIC OF KARAKALPAKSTAN","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.23383466","This article examines the economic and environmental significance of using digital innovations to develop green agriculture in the Republic of Karakalpakstan. It analyzes challenges related to water scarcity, soil salinity, production costs, and the efficiency of natural resource utilization. The article highlights the potential of digital monitoring, smart irrigation, remote sensing, and data-driven management to improve agricultural production outcomes.","本文探讨了在卡拉卡尔帕克斯坦共和国利用数字创新发展绿色农业的经济与环境意义。文章分析了与水资源短缺、土壤盐渍化、生产成本以及自然资源利用效率相关的挑战。文章强调了数字监测、智能灌溉、遥感以及数据驱动管理在改善农业生产成效方面的潜力。","2026-10-15T00:00:00Z",25,63,{"impact":279,"substance":120,"depth":420,"authority":279,"freshness":83,"relevant":20,"comment":421},14,"聚焦乌兹别克斯坦卡拉卡尔帕克斯坦地区数字农业与盐碱地治理，属区域案例研究，对国内智慧农业与盐碱地改良有参考价值，但影响层级与信息增量有限。",[423,424],{"name":195,"url":413},{"name":425,"url":426},"SAMARALI TA’LIM VA BARQAROR INNOVATSIYALAR JURNALI","https:\u002F\u002Finnovativepublication.uz\u002Findex.php\u002Fjelsi\u002Farticle\u002Fview\u002F6404",[25,88,428,429,430],"智能灌溉","盐碱地治理","遥感监测",{"code":30,"slug":31,"name":32,"path":33,"parent_code":34},[],{"status":37,"locked":13,"version":38,"method":39,"evidence":434},{"candidates":435,"agricultural_evidence":44},[436,440,444,451],{"code":30,"score":12,"supported":44,"title":437,"abstract":438,"tags":439},[],[53,134,31],[428],{"code":145,"score":138,"supported":44,"title":441,"abstract":442,"tags":443},[],[148,149],[429],{"code":445,"score":138,"supported":44,"title":446,"abstract":447,"tags":450},"I3",[],[448,449],"遥感","remote sensing",[430],{"code":43,"score":308,"supported":13,"title":452,"abstract":453,"tags":454},[],[],[25,88],[456,457],"卡拉卡尔帕克斯坦 数字农业","咸海地区 盐碱地 智能灌溉","卡拉卡尔帕克斯坦数字农业-5073","10.5281\u002Fzenodo.23383466",{"doi":459,"openalex_id":461,"authors":462,"venue":195,"cited_by_count":59,"oa_url":413,"card":465,"direction":66,"ingested_from":187},"W7221970206",[463],{"name":464,"orcid":8},"Sholpan Eshimova",{"tldr":466,"method":467,"finding":468,"direction":469,"opportunity":470},"研究卡拉卡尔帕克斯坦通过农产品加工与数字创新提升区域附加值。","分析水资源短缺、土壤盐渍化等挑战，评估数字监测、智能灌溉、遥感和数据管理潜力。","数字创新可提高农业生产效率并促进绿色农业发展。","农业绿色发展与碳","可量化数字技术对盐碱地农业附加值及资源效率的贡献，探索适配干旱区的智慧农业模式。","2026-10-16T23:30:07.817464Z",{"id":473,"title":474,"url":475,"summary":476,"summary_zh":477,"content":8,"source_name":478,"source_url":479,"published_at":480,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":481,"score_detail":482,"sources":484,"tags":486,"primary_topic":490,"secondary_topics":491,"classification":492,"search_phrases":513,"slug":516,"view_count":20,"doi":517,"paper":518,"created_at":535},4913,"Factors Influencing the Adoption of Precision Agriculture Technologies by Nebraska Producers","https:\u002F\u002Fdoi.org\u002F10.22004\u002Fag.econ.413436","An ever-increasing world population and increasingly-volatile commodity prices have charged producers with the task of becoming more efficient. To combat this, precision agriculture technologies aimed at increasing production efficiency are continually being developed, but their adoption is not yet widespread. A survey regarding the usage of these technologies was distributed to a sample of row crop producers across the state of Nebraska and a Poisson regression was used to determine the factors influencing adoption. Results of the study indicate that larger, more tech-savvy producers and those using irrigation are more likely to adopt a higher number of precision agriculture technologies, while operator age and gross farm income were found to be noninfluential factors.","世界人口不断增长以及大宗商品价格日益波动，使生产者肩负起提高效率的任务。为应对这一挑战，旨在提高生产效率的精准农业（precision agriculture）技术不断被开发出来，但其采用尚未普及。本研究向内布拉斯加州大田作物生产者样本发放了关于这些技术使用情况的调查问卷，并采用泊松回归（Poisson regression）确定影响采用的因素。研究结果表明，规模更大、更精通技术的生产者以及使用灌溉的生产者更可能采用更多数量的精准农业技术，而经营者年龄和农场总收入则被发现在影响因素中不起作用。","Lincoln (University of Nebraska)","https:\u002F\u002Fdigitalcommons.unl.edu\u002Fageconworkpap\u002F49","2026-10-13T00:00:00Z",75,{"impact":120,"substance":345,"depth":200,"authority":18,"freshness":280,"relevant":20,"comment":483},"基于内布拉斯加州种植者调查的实证研究，用泊松回归揭示规模、技术素养与灌溉对精准农业技术采纳的影响，对国内智慧农业推广有参考价值。",[485],{"name":478,"url":479},[88,26,487,488,489],"农业技术采纳","灌溉农业","玉米大豆",{"code":30,"slug":31,"name":32,"path":33,"parent_code":34},[],{"status":37,"locked":13,"version":38,"method":39,"evidence":493},{"candidates":494,"agricultural_evidence":44},[495,499,503,508],{"code":43,"score":120,"supported":44,"title":496,"abstract":497,"tags":498},[46],[26,46],[88,26],{"code":30,"score":138,"supported":44,"title":500,"abstract":501,"tags":502},[],[53,31],[488],{"code":504,"score":20,"supported":13,"title":505,"abstract":506,"tags":507},"A3",[],[],[489],{"code":509,"score":20,"supported":13,"title":510,"abstract":511,"tags":512},"G1",[],[],[487],[514,515],"内布拉斯加 精准农业 采纳","精准农业技术 采纳因素","内布拉斯加精准农业采纳-4913","10.22004\u002Fag.econ.413436",{"doi":517,"openalex_id":519,"authors":520,"venue":478,"cited_by_count":528,"oa_url":529,"card":530,"direction":185,"ingested_from":187},"W2326051080",[521,523,525],{"name":522,"orcid":8},"Michael H Castle",{"name":524,"orcid":8},"Bradley Lubben",{"name":526,"orcid":527},"Joe D. Luck","https:\u002F\u002Forcid.org\u002F0000-0002-8278-9812",32,"http:\u002F\u002Fdigitalcommons.unl.edu\u002Fcgi\u002Fviewcontent.cgi?article=1050&context=ageconworkpap",{"tldr":531,"method":532,"finding":533,"direction":407,"opportunity":534},"基于内布拉斯加州调查，用泊松回归分析影响精准农业技术采纳的因素。","对行作物生产者问卷调查，采用泊松回归模型分析采纳数量。","规模大、技术熟练及有灌溉的生产者更易采纳更多精准农业技术，年龄和收入无显著影响。","可探究小规模或非灌溉农户采纳障碍，以及技术熟练度的中介机制与干预策略。","2026-10-14T23:30:55.751323Z"]