[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-3534":3,"related-3534":102},{"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":77,"slug":80,"view_count":54,"doi":81,"paper":82,"created_at":101},3534,"From river health to sustainable irrigation water resources: a five-year integrated ecological assessment for climate-resilient food systems in semi-arid Iraq","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1968827","Freshwater degradation in semi-arid regions can simultaneously affect river ecological condition and the reliability of water resources for irrigated food production. This study integrated ecological, irrigation-water, hydroclimatic, and crop-specific assessments across the Euphrates, Shatt Al-Hillah, and Al-Diwaniyah river systems in central Iraq over 5 years (2020–2024). Fifteen stations were monitored seasonally, generating 300 station-season observations. Physicochemical variables, major ions, nutrients, irrigation-water indicators, benthic diatoms, macroinvertebrates, habitat condition, hydroclimatic variables, and crop-specific irrigation constraints were evaluated within a common analytical framework. A persistent spatial gradient was observed across the three river systems. Mean electrical conductivity increased from 855.4 ± 226.3 μS cm −1 in the Euphrates to 1295.5 ± 247.1 μS cm −1 in Shatt Al-Hillah and 1791.9 ± 375.4 μS cm −1 in Al-Diwaniyah, accompanied by increasing Na + , Cl − , nutrients, and irrigation-water restrictions. Overall, 90.3% of observations exhibited slight-to-moderate salinity restriction, whereas severe salinity occurred only in Al-Diwaniyah. Hydroclimatic variability was associated with temporal salinity risk, with the strongest EC anomalies occurring during the summers of 2022 and 2024 and significant negative associations between EC and both SPEI-3 and SPEI-6. Biological condition declined along the same gradient: diatom and macroinvertebrate diversity, EPT representation, habitat condition, and dissolved oxygen were highest in the Euphrates and lowest in Al-Diwaniyah. Principal component analysis explained 89.67% of total variance on the first two axes and clearly contrasted biological condition with salinity, ionic enrichment, and nutrient concentrations. Crop-specific assessment further showed increasing agricultural constraints, with maize being the most sensitive crop and constrained in 100% of observations at all Al-Diwaniyah stations. These findings demonstrate that river ecological condition, irrigation-water reliability, hydroclimatic variability, and crop-specific suitability are closely interconnected. Integrating these dimensions can support more adaptive water allocation and climate-resilient irrigation management in semi-arid food-production systems.","半干旱地区的淡水退化会同时影响河流生态状况与灌溉粮食生产的水资源可靠性。本研究在伊拉克中部的幼发拉底河、希拉河和迪瓦尼耶河三个河系开展了为期5年（2020—2024年）的生态、灌溉用水、水文气候和作物特异性评估的综合研究。研究对15个站点进行季节性监测，共获得300个站点-季节观测数据。在统一的分析框架内，评估了理化变量、主要离子、营养盐、灌溉水指标、底栖硅藻、大型无脊椎动物、栖息地状况、水文气候变量以及作物特异性灌溉限制。三个河系之间呈现出持续的空间梯度。平均电导率从幼发拉底河的855.4 ± 226.3 μS cm⁻¹升至希拉河的1295.5 ± 247.1 μS cm⁻¹和迪瓦尼耶河的1791.9 ± 375.4 μS cm⁻¹，同时伴随Na⁺、Cl⁻、营养盐的增加及灌溉用水限制的加剧。总体而言，90.3%的观测表现为轻度至中度盐度限制，而严重盐度仅出现在迪瓦尼耶河。水文气候变率与盐度的时间风险相关，最强的电导率异常出现在2022年和2024年夏季，且电导率与SPEI-3和SPEI-6均呈显著负相关。生物状况沿同一梯度下降：硅藻和大型无脊椎动物多样性、EPT（蜉蝣目-襀翅目-毛翅目）代表性、栖息地状况和溶解氧在幼发拉底河最高，在迪瓦尼耶河最低。主成分分析在前两个轴上解释了89.67%的总方差，清晰地将生物状况与盐度、离子富集和营养盐浓度形成对比。作物特异性评估进一步表明农业限制日益加剧，其中玉米是最敏感的作物，在迪瓦尼耶河所有站点的100%观测中均受到限制。这些发现表明，河流生态状况、灌溉水可靠性、水文气候变率和作物特异性适宜性密切相关。整合这些维度可支持半干旱粮食生产系统中更具适应性的水资源分配和气候韧性灌溉管理。",null,"Frontiers in Sustainable Food Systems","2026-09-25T00:00:00Z","论文",10,false,78,{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":21,"relevant":22,"comment":23},16,22,18,13,9,1,"五年跨三河水生态与灌溉水质综合评估，数据规模大、结论可靠，对半干旱区气候韧性灌溉管理有参考价值。",[25],{"name":10,"url":6},[27,28,29,30,31],"粮食安全","气候韧性","水资源管理","盐渍化","灌溉水质",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},"H3","irrigation","水资源与灌溉","\u002Ftopic\u002Fenvironment\u002Firrigation","H",[],{"status":40,"locked":14,"version":41,"method":42,"evidence":43},"classified","2026-10-22.2","rules",{"candidates":44,"agricultural_evidence":46},[45,52,60,67,72],{"code":33,"score":19,"supported":46,"title":47,"abstract":48,"tags":51},true,[34],[49,50,34],"灌溉","水资源",[29],{"code":53,"score":54,"supported":46,"title":55,"abstract":56,"tags":59},"A3",6,[],[57,58],"玉米","maize",[],{"code":61,"score":62,"supported":46,"title":63,"abstract":64,"tags":66},"H7",4,[],[65],"干旱",[28],{"code":68,"score":22,"supported":14,"title":69,"abstract":70,"tags":71},"A8",[],[],[27],{"code":73,"score":22,"supported":14,"title":74,"abstract":75,"tags":76},"H2",[],[],[30],[78,79],"伊拉克 幼发拉底河 灌溉水质","半干旱区 盐渍化 灌溉水","伊拉克幼发拉底河灌溉水质-3534","10.3389\u002Ffsufs.2026.1968827",{"doi":81,"openalex_id":83,"authors":84,"venue":10,"cited_by_count":93,"oa_url":6,"card":94,"direction":98,"ingested_from":100},"W7214391385",[85,88,90],{"name":86,"orcid":87},"Bassam M. Al-Yaseen","https:\u002F\u002Forcid.org\u002F0009-0003-6019-6447",{"name":89,"orcid":9},"Suad Ghali Kadhim Alahmed",{"name":91,"orcid":92},"Nawres Abdulkareem Hussein","https:\u002F\u002Forcid.org\u002F0009-0009-9147-1919",0,{"tldr":95,"method":96,"finding":97,"direction":98,"opportunity":99},"伊拉克半干旱区三河系五年综合评估，揭示水质退化与灌溉可靠性及作物适宜性的联动。","15站点季节性监测300次，整合理化、生物、水文气候与作物灌溉约束指标。","盐度沿河系梯度上升，90.3%观测受轻中度盐度限制，玉米在Al-Diwaniyah全部受限。","农业绿色发展与碳","可构建耦合河流生态与作物灌溉适宜性的多尺度预警模型，支撑半干旱区自适应配水。","openalex","2026-09-26T23:30:07.865370Z",{"total":54,"page":22,"page_size":54,"items":103},[104,188,261,361,449,501],{"id":105,"title":106,"url":107,"summary":108,"summary_zh":109,"content":9,"source_name":110,"source_url":107,"published_at":111,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":112,"score_detail":113,"sources":118,"tags":120,"primary_topic":124,"secondary_topics":129,"classification":131,"search_phrases":164,"slug":167,"view_count":93,"doi":168,"paper":169,"created_at":187},4887,"Farming under fire: Conflict, displacement, and the collapse of food security in south Lebanon","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.jrurstud.2026.104458","Context Lebanon's agricultural sector and food systems are facing unprecedented pressures amid overlapping crises: economic collapse, climate change, and the 2023-2025 armed conflict with Israel. Objective This paper investigates the compounded impact of conflict-induced displacement and climate stress on rural livelihoods, agricultural productivity, and food security in South Lebanon-an area marked by strategic agricultural value and climate vulnerability. Methods Drawing on 29 in-depth interviews with displaced farmers, cooperative leaders, and food producers from conflict-affected areas such as Marjayoun, Nabatieh, and Bint Jbeil, this qualitative study uncovers key disruptions in agricultural infrastructure, local markets, and household food access. Interview findings are also triangulated with published secondary quantitative data (IPC, FAO, WFP, and World Bank assessments). Results and conclusion s: The findings reveal how displacement led to the abandonment of farms, loss of livestock, contamination of crops, and collapse of cooperative models, exacerbating existing economic and climate stressors like currency depreciation, water scarcity, unpredictable rainfall, and reduced yields. Gendered impacts, informal solidarity mechanisms, and persistent energy and input shortages emerged as critical themes. The study highlights the urgent need for an integrated recovery strategy focused on smart irrigation, climate-resilient crops, market reintegration, and financial support for smallholders. The analysis is guided by a conceptual framework that treats conflict-induced displacement and climate stress as interlocking drivers of livelihood erosion, market collapse, and food and nutrition insecurity, with gendered and refugee-specific vulnerabilities at the core. Significance As Lebanon faces a worsening food insecurity crisis, with 1.17 million people in IPC Phase 3 or higher, rebuilding agriculture is no longer a developmental luxury but an existential necessity for national food security.","背景 黎巴嫩的农业部门和粮食系统在多重危机交织下面临前所未有的压力：经济崩溃、气候变化以及2023至2025年与以色列的武装冲突。目标 本文研究冲突导致的流离失所与气候压力对黎巴嫩南部农村生计、农业生产力和粮食安全的叠加影响——该地区具有重要的农业战略价值和气候脆弱性。方法 本定性研究基于对来自马尔杰永、纳巴蒂耶和宾特朱拜勒等受冲突影响地区的流离失所农民、合作社领导人和粮食生产者的29次深度访谈，揭示了农业基础设施、地方市场和家庭粮食获取方面的关键中断。访谈结果还与已发表的二手定量数据（IPC、FAO、WFP和世界银行的评估）进行了三角验证。结果与结论 研究结果揭示了流离失所如何导致农田弃耕、牲畜损失、作物污染和合作社模式崩溃，加剧了现有的经济和气候压力因素，如货币贬值、水资源短缺、降雨不可预测和产量下降。性别影响、非正式互助机制以及持续存在的能源和投入品短缺成为关键主题。研究强调迫切需要一项综合恢复战略，重点关注智能灌溉、气候韧性作物、市场再融入以及对小农户的财政支持。分析以一个概念框架为指导，该框架将冲突导致的流离失所和气候压力视为生计侵蚀、市场崩溃以及粮食和营养不安全的相互关联驱动因素，并将性别和难民特有的脆弱性置于核心位置。意义 随着黎巴嫩面临日益恶化的粮食不安全危机，有117万人处于IPC第3阶段或更高阶段，重建农业不再是一种发展上的奢侈，而是国家粮食安全的生存必需。","Journal of Rural Studies","2026-10-12T00:00:00Z",85,{"impact":18,"substance":114,"depth":19,"authority":115,"freshness":116,"relevant":22,"comment":117},23,14,8,"基于29个深度访谈与IPC\u002FFAO等数据的定性研究，揭示冲突叠加气候压力对南黎巴嫩农业与粮食安全的复合冲击，并提出智慧灌溉与气候韧性作物等恢复策略，对冲突地区农业重建具参考价值。",[119],{"name":110,"url":107},[27,28,121,122,123],"智慧灌溉","小农户支持","冲突与农业",{"code":68,"slug":125,"name":126,"path":127,"parent_code":128},"yield-food-security","单产提升与粮食安全","\u002Ftopic\u002Ffield-crops\u002Fyield-food-security","A",[130],{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},{"status":40,"locked":14,"version":41,"method":42,"evidence":132},{"candidates":133,"agricultural_evidence":46},[134,140,144,151,158],{"code":68,"score":135,"supported":46,"title":136,"abstract":138,"tags":139},15,[137],"food security",[27,137],[27],{"code":33,"score":13,"supported":46,"title":141,"abstract":142,"tags":143},[],[49,50,34],[121],{"code":61,"score":145,"supported":46,"title":146,"abstract":147,"tags":150},7,[],[148,149],"气候变化","climate change",[28],{"code":152,"score":153,"supported":46,"title":154,"abstract":155,"tags":157},"C",3,[],[156],"livestock",[],{"code":159,"score":153,"supported":46,"title":160,"abstract":161,"tags":163},"G2",[],[162],"小农户",[],[165,166],"南黎巴嫩 粮食安全","冲突 流离失所 生计","南黎巴嫩粮食安全-4887","10.1016\u002Fj.jrurstud.2026.104458",{"doi":168,"openalex_id":170,"authors":171,"venue":110,"cited_by_count":93,"oa_url":107,"card":180,"direction":186,"ingested_from":100},"W7221536688",[172,174,177],{"name":173,"orcid":9},"Yasmine Fakhry",{"name":175,"orcid":176},"Jasmin Lilian Diab","https:\u002F\u002Forcid.org\u002F0000-0003-4158-7728",{"name":178,"orcid":179},"Hussein F. Hassan","https:\u002F\u002Forcid.org\u002F0000-0003-4215-6815",{"tldr":181,"method":182,"finding":183,"direction":184,"opportunity":185},"通过访谈与二手数据，揭示黎巴嫩南部冲突与气候压力叠加导致农业崩溃和粮食不安全。","29份深度访谈，结合IPC、FAO、WFP和世界银行二手定量数据三角验证。","流离失所致农田废弃、牲畜损失、合作社瓦解，加剧经济与气候压力，117万人处于IPC第三阶段以上。","数字乡村与农业信息化","可探索冲突\u002F气候脆弱区智慧灌溉、气候韧性作物与市场重建的数字化恢复策略。","智慧农业 \u002F 农业物联网","2026-10-14T23:30:11.877241Z",{"id":189,"title":190,"url":191,"summary":192,"summary_zh":9,"content":9,"source_name":193,"source_url":191,"published_at":194,"category":12,"cover_url":9,"hotness":195,"is_selected":14,"score":196,"score_detail":197,"sources":201,"tags":205,"primary_topic":208,"secondary_topics":209,"classification":217,"search_phrases":244,"slug":247,"view_count":22,"doi":248,"paper":249,"created_at":260},1255,"Optimizing Water Management in Agriculture: The Role of IoT-Powered Smart Irrigation Systems in Addressing Global Food Security and Water Scarcity","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.21413238","Objective: This study aims to explore the impact of IoT-powered smart irrigation systems on optimizing water management in agriculture, with a specific focus on addressing global food security and mitigating water scarcity challenges. Materials and Methods: The research employs a mixed-methods approach, combining quantitative data analysis from agricultural case studies and qualitative interviews with farmers and agricultural experts. The study assesses the effectiveness of smart irrigation technologies, including soil moisture sensors, weather forecasting tools, and automated irrigation systems, in improving water use efficiency and crop yields. Results and Discussion: The findings indicate that IoT-powered smart irrigation systems significantly enhance water management practices in agriculture. These systems result in a reduction of up to 30% in water usage, while simultaneously increasing crop productivity by 15-20%. Additionally, the integration of real-time data analytics allows for more precise irrigation scheduling, which contributes to sustainable agricultural practices and improved food security. Conclusions: This research contributes to the existing literature by providing empirical evidence of the benefits of IoT technologies in agriculture. It highlights the potential of smart irrigation systems as a viable solution to the dual challenges of food security and water scarcity. The findings emphasize the need for policy interventions and investment in technology to facilitate the adoption of these systems in farming practices worldwide.","Zenodo (CERN European Organization for Nuclear Research)","2026-08-30T00:00:00Z",25,70,{"impact":19,"substance":18,"depth":17,"authority":198,"freshness":199,"relevant":22,"comment":200},12,2,"论文实证智能灌溉节水30%增产20%，对农业水资源管理有参考价值，但时效性较低。",[202,203],{"name":193,"url":191},{"name":193,"url":204},"https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.21413237",[206,27,207,29],"智慧农业","智能灌溉",{"code":68,"slug":125,"name":126,"path":127,"parent_code":128},[210,211],{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},{"code":212,"slug":213,"name":214,"path":215,"parent_code":216},"I5","agricultural-iot","物联网传感与边缘计算","\u002Ftopic\u002Fdigital-agriculture\u002Fagricultural-iot","I",{"status":40,"locked":14,"version":41,"method":42,"evidence":218},{"candidates":219,"agricultural_evidence":46},[220,224,228,234,239],{"code":33,"score":20,"supported":46,"title":221,"abstract":222,"tags":223},[34],[34],[207,29],{"code":68,"score":198,"supported":46,"title":225,"abstract":226,"tags":227},[137],[137],[27],{"code":212,"score":229,"supported":46,"title":230,"abstract":232,"tags":233},11,[231],"IoT",[231],[],{"code":73,"score":153,"supported":46,"title":235,"abstract":236,"tags":238},[],[237],"soil",[],{"code":240,"score":22,"supported":14,"title":241,"abstract":242,"tags":243},"I1",[],[],[206],[245,246],"水资源管理 智慧农业 智能灌溉 粮食安全","水资源管理 智慧农业","水资源管理智慧农业智能灌溉粮食安全-1255","10.5281\u002Fzenodo.21413238",{"doi":248,"openalex_id":250,"authors":251,"venue":193,"cited_by_count":93,"oa_url":191,"card":255,"direction":186,"ingested_from":100},"W7169531097",[252],{"name":253,"orcid":254},"Mahdi Sabati Gavgani","https:\u002F\u002Forcid.org\u002F0000-0002-4585-9199",{"tldr":256,"method":257,"finding":258,"direction":186,"opportunity":259},"研究物联网智能灌溉系统优化农业用水，提升粮食安全与缓解水资源短缺。","混合方法：案例定量分析与农户专家定性访谈，评估传感器、天气预报和自动灌溉技术。","智能灌溉节水30%，增产15-20%，实时数据分析优化灌溉调度。","可探索智能灌溉系统在不同作物、气候和农户采纳障碍下的适应性，以及政策激励对推广的影响。","2026-09-01T04:03:11.304099Z",{"id":262,"title":263,"url":264,"summary":265,"summary_zh":266,"content":9,"source_name":267,"source_url":264,"published_at":268,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":269,"score_detail":270,"sources":272,"tags":274,"primary_topic":278,"secondary_topics":283,"classification":286,"search_phrases":336,"slug":339,"view_count":93,"doi":340,"paper":341,"created_at":360},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":19,"substance":18,"depth":19,"authority":20,"freshness":21,"relevant":22,"comment":271},"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。",[273],{"name":267,"url":264},[206,275,276,277,28],"农业人工智能","物联网","精准农业",{"code":279,"slug":280,"name":281,"path":282,"parent_code":216},"I2","agricultural-ai","农业AI与大模型","\u002Ftopic\u002Fdigital-agriculture\u002Fagricultural-ai",[284,285],{"code":212,"slug":213,"name":214,"path":215,"parent_code":216},{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},{"status":40,"locked":14,"version":41,"method":42,"evidence":287},{"candidates":288,"agricultural_evidence":46},[289,300,305,311,315,319,324,330],{"code":279,"score":19,"supported":46,"title":290,"abstract":292,"tags":299},[291],"artificial intelligence",[293,294,295,296,297,298],"深度学习","机器学习","计算机视觉","machine learning","deep learning","computer vision",[275],{"code":240,"score":17,"supported":46,"title":301,"abstract":303,"tags":304},[302],"precision agriculture",[277,302],[206,277],{"code":212,"score":13,"supported":46,"title":306,"abstract":307,"tags":310},[],[276,308,231,309],"边缘计算","edge computing",[276],{"code":33,"score":21,"supported":46,"title":312,"abstract":313,"tags":314},[],[49,50,34],[],{"code":61,"score":145,"supported":46,"title":316,"abstract":317,"tags":318},[],[148,149],[28],{"code":73,"score":54,"supported":46,"title":320,"abstract":321,"tags":323},[],[322,237],"土壤",[],{"code":325,"score":153,"supported":46,"title":326,"abstract":327,"tags":329},"A7",[],[328],"间作",[],{"code":331,"score":153,"supported":46,"title":332,"abstract":333,"tags":335},"F3",[],[334],"养分管理",[],[337,338],"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":340,"openalex_id":342,"authors":343,"venue":267,"cited_by_count":93,"oa_url":264,"card":354,"direction":186,"ingested_from":100},"W7223121456",[344,347,349,351],{"name":345,"orcid":346},"Olumayowa J. Iyanda","https:\u002F\u002Forcid.org\u002F0000-0002-5340-9884",{"name":348,"orcid":9},"Oluwadare OYEBODE",{"name":350,"orcid":9},"Iretiayo Adelaiye",{"name":352,"orcid":353},"Ayomide Afolabi","https:\u002F\u002Forcid.org\u002F0000-0002-5171-886X",{"tldr":355,"method":356,"finding":357,"direction":358,"opportunity":359},"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。","2026-10-22T11:20:18.151376Z",{"id":362,"title":363,"url":364,"summary":365,"summary_zh":366,"content":9,"source_name":367,"source_url":364,"published_at":368,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":369,"score_detail":370,"sources":374,"tags":376,"primary_topic":379,"secondary_topics":383,"classification":385,"search_phrases":430,"slug":433,"view_count":93,"doi":9,"paper":434,"created_at":448},5312,"Agricultural Production under Climate Change in Afghanistan: Impacts, Challenges and Adaptation Options (A Review)","https:\u002F\u002Fesrj.edu.af\u002Fesrj\u002Farticle\u002Fview\u002F123","Climate change poses serious challenges to agriculture in Afghanistan, a country largely dependent on rainfed farming and highly vulnerable to water scarcity, drought, and temperature extremes. Understanding the impacts of climate variability and identifying effective adaptation strategies are essential to sustain agricultural productivity and ensure food security. This systematic review synthesizes empirical, modeling, and review studies on climate change effects on Afghan agriculture, assesses adaptation measures, and integrates regional experiences from Pakistan, Iran, Tajikistan, and Uzbekistan. A structured literature search was conducted using peer-reviewed articles, institutional reports, and regional studies published between 2000 and 2025. Studies were selected based on relevance to Afghan agro-ecological systems, climate stressors, and adaptation strategies. We extracted data using a structured table format following PRISMA guidelines, combining national and regional evidence. Findings indicate that water scarcity, prolonged drought, rising temperatures, and erratic precipitation are the main stressors affecting major crops, including wheat, barley, chickpea, maize, and cotton. Yield reductions ranged from 12% to 25% across provinces. Adaptation strategies such as Climate-Smart Agriculture (CSA), efficient irrigation (drip and sprinkler), rainwater harvesting, mulching, and drought- or heat-tolerant crop varieties were most effective. Regional evidence confirms the transferability of these measures under similar agro-climatic conditions. In conclusion, climate change significantly threatens agricultural productivity in Afghanistan. Evidence-based adaptation strategies, supported by coordinated policy and capacity-building initiatives, can enhance resilience, protect rural livelihoods, and ensure sustainable food security.","气候变化对阿富汗农业构成严峻挑战，该国农业在很大程度上依赖雨养耕作，极易受到水资源短缺、干旱和极端温度的影响。理解气候变异的影响并确定有效的适应策略，对于维持农业生产力和保障粮食安全至关重要。本系统综述综合了关于气候变化对阿富汗农业影响的实证研究、模拟研究和综述研究，评估了适应措施，并整合了巴基斯坦、伊朗、塔吉克斯坦和乌兹别克斯坦的区域经验。采用结构化文献检索方法，检索了2000年至2025年间发表的同行评审论文、机构报告和区域研究。研究依据其与阿富汗农业生态系统、气候胁迫因子和适应策略的相关性进行筛选。我们遵循PRISMA指南，采用结构化表格格式提取数据，综合了国家层面和区域层面的证据。研究结果表明，水资源短缺、持续干旱、气温上升和降水不稳定是影响主要作物（包括小麦、大麦、鹰嘴豆、玉米和棉花）的主要胁迫因子。各省产量降幅在12%至25%之间。气候智慧型农业（CSA）、高效灌溉（滴灌和喷灌）、雨水收集、覆盖栽培以及耐旱或耐热作物品种等适应策略最为有效。区域证据证实了这些措施在相似农业气候条件下的可推广性。总之，气候变化显著威胁阿富汗的农业生产力。以协调政策和能力建设举措为支撑的循证适应策略能够增强韧性、保护农村生计并确保可持续的粮食安全。","ESRJ","2026-10-16T00:00:00Z",73,{"impact":19,"substance":371,"depth":372,"authority":198,"freshness":54,"relevant":22,"comment":373},20,17,"系统综述整合2000-2025年证据，量化减产12%-25%并提出可迁移的适应策略，对区域农业气候韧性研究有参考价值，但非国内三农政策或产业事件，时效性一般。",[375],{"name":367,"url":364},[206,27,148,377,378],"适应性策略","水资源短缺",{"code":61,"slug":380,"name":381,"path":382,"parent_code":37},"climate","气候适应与防灾减灾","\u002Ftopic\u002Fenvironment\u002Fclimate",[384],{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},{"status":40,"locked":14,"version":41,"method":42,"evidence":386},{"candidates":387,"agricultural_evidence":46},[388,393,397,401,408,412,419,424],{"code":61,"score":19,"supported":46,"title":389,"abstract":390,"tags":392},[149],[148,65,149,391],"drought",[148],{"code":33,"score":21,"supported":46,"title":394,"abstract":395,"tags":396},[],[49,50,34],[],{"code":68,"score":145,"supported":46,"title":398,"abstract":399,"tags":400},[],[27,137],[27],{"code":402,"score":54,"supported":46,"title":403,"abstract":404,"tags":407},"A2",[],[405,406],"小麦","wheat",[],{"code":53,"score":54,"supported":46,"title":409,"abstract":410,"tags":411},[],[57,58],[],{"code":413,"score":54,"supported":46,"title":414,"abstract":415,"tags":418},"A6",[],[416,417],"棉花","cotton",[],{"code":240,"score":62,"supported":46,"title":420,"abstract":421,"tags":423},[],[422],"smart agriculture",[206],{"code":425,"score":153,"supported":46,"title":426,"abstract":427,"tags":429},"H6",[],[428],"农业生态",[],[431,432],"阿富汗 气候变化","气候智慧型农业 灌溉","阿富汗气候变化-5312",{"doi":9,"openalex_id":435,"authors":436,"venue":367,"cited_by_count":93,"oa_url":364,"card":443,"direction":186,"ingested_from":100},"W7222907396",[437,439,441],{"name":438,"orcid":9},"Mohammad Shafiq Faieq",{"name":440,"orcid":9},"Mustafa Abid",{"name":442,"orcid":9},"Abdul khalil Afghani",{"tldr":444,"method":445,"finding":446,"direction":98,"opportunity":447},"系统综述气候变化对阿富汗农业的影响、挑战与适应策略。","按PRISMA检索2000-2025年文献，整合阿富汗及周边四国区域证据。","水资源短缺与干旱致主要作物减产12%-25%，气候智慧型农业与节水灌溉最有效。","可研究气候智慧型农业措施在阿富汗及周边干旱区的本地化适配与推广机制。","2026-10-19T23:30:11.285828Z",{"id":450,"title":451,"url":452,"summary":453,"summary_zh":454,"content":9,"source_name":455,"source_url":456,"published_at":457,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":458,"score_detail":459,"sources":461,"tags":463,"primary_topic":467,"secondary_topics":468,"classification":470,"search_phrases":482,"slug":485,"view_count":22,"doi":486,"paper":487,"created_at":500},4914,"Water Optimizer: A Tool for Decision Support and Policy Analysis","https:\u002F\u002Fdoi.org\u002F10.22004\u002Fag.econ.413426","Water Optimizer is a tool for analyzing alternative water management strategies when the available water supply is limited. It can be used by producers to determine the profit maximizing crops to produce and the optimum amount of water to apply to each crop, given a particular water supply. It can also be used to evaluate the economic consequences of public policies which expand or reduce the amount of irrigation.","水资源优化器是一种在可用供水有限时分析替代水资源管理策略的工具。生产者可用其确定在特定供水量下能实现利润最大化的作物种类及每种作物的最优灌溉水量，也可用于评估扩大或减少灌溉面积的公共政策的经济后果。","Lincoln (University of Nebraska)","https:\u002F\u002Fdigitalcommons.unl.edu\u002Fageconworkpap\u002F43","2026-10-13T00:00:00Z",67,{"impact":198,"substance":19,"depth":17,"authority":20,"freshness":116,"relevant":22,"comment":460},"内布拉斯加大学开发的灌溉决策支持工具，方法实用但属细分领域工具类论文，公共影响有限。",[462],{"name":455,"url":456},[464,29,465,466],"决策支持系统","灌溉决策","农业政策分析",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[469],{"code":279,"slug":280,"name":281,"path":282,"parent_code":216},{"status":40,"locked":14,"version":41,"method":42,"evidence":471},{"candidates":472,"agricultural_evidence":46},[473,477],{"code":33,"score":229,"supported":46,"title":474,"abstract":475,"tags":476},[],[49,50,34],[29,465],{"code":279,"score":21,"supported":46,"title":478,"abstract":480,"tags":481},[479],"decision support",[],[464],[483,484],"Water Optimizer 灌溉决策","内布拉斯加大学 水资源管理","WaterOptimizer灌溉决策-4914","10.22004\u002Fag.econ.413426",{"doi":486,"openalex_id":488,"authors":489,"venue":455,"cited_by_count":93,"oa_url":494,"card":495,"direction":358,"ingested_from":100},"W38113320",[490,492],{"name":491,"orcid":9},"Derrel L. Martin",{"name":493,"orcid":9},"Ray Supalla","http:\u002F\u002Fdigitalcommons.unl.edu\u002Fageconworkpap\u002F43",{"tldr":496,"method":497,"finding":498,"direction":358,"opportunity":499},"开发了Water Optimizer工具，在有限供水下优化作物种植与灌溉量以最大化利润。","基于优化模型与决策支持工具，分析不同供水策略及政策的经济影响。","该工具能帮助生产者选择利润最大化作物和最优灌溉量，并评估灌溉政策的经济后果。","可结合实时气象与土壤数据，开发动态灌溉决策模型，并拓展至多目标（经济-环境）优化。","2026-10-14T23:30:55.832240Z",{"id":502,"title":503,"url":504,"summary":505,"summary_zh":506,"content":9,"source_name":507,"source_url":504,"published_at":508,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":458,"score_detail":509,"sources":511,"tags":513,"primary_topic":518,"secondary_topics":523,"classification":530,"search_phrases":557,"slug":560,"view_count":93,"doi":561,"paper":562,"created_at":578},4753,"Mapping groundwater potential zones using GIS, remote sensing and analytical hierarchy process (AHP) in Pader and Kitgum Districts, Uganda","https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs43621-026-04943-7","Groundwater is a crucial source of freshwater in semi-arid regions, particularly in water-stressed areas, such as northern Uganda, where the surface water is scarce and unreliable precipitation patterns changes. This province lacks sufficient clean water for human consumption and only 20% of the water for agriculture extracted from the ground due to inaccessibility and insufficient information regarding the groundwater. With regard to these difficulties in water that are faced by the local communities, it has not been yet studied the distribution of groundwater in Kitgum and Pader districts. Therefore, the result of this research contributes preliminary groundwater investigation for contacting this indispensable source of water. The study employed a geospatial approach integrated with multi-criteria analysis to identify groundwater potential zones in Kitgum and Pader districts of Acholi subregion. The Utilization of Geographic Information Systems (GIS), remote sensing, and the Analytic Hierarchy Process (AHP) and six thematic layers; rainfall, drainage density, slope, soil type, geology, and land use\u002Fland cover were selected based on their hydrogeological influence and the accessibility of the data. After standardizing, and assigning normalized weights,a weighted overlay analysis in ArcGIS Pro version 3.1.0 was used to synthesize these layers into a comprehensive groundwater potential zonation map. The result categorized the study area into five zones; very low, low, medium, high, and very high potential. The analysis revealed that Kitgum District is predominantly characterized by very low to low groundwater potential zones of 67.24% when it is combined both, constrained by factors such as higher drainage density, and steeper slopes. Conversely, Pader District showed favorable conditions, with 85.5% of its area classified as high to very high groundwater potential, attributed to gentle slopes, and higher rainfall, that enhance infiltration capacity. Validation against yield data from 18 existing boreholes demonstrated a 75.0% alignment between the model and actual well performance, confirming the model’s reliability at acceptable result. This study demonstrated the effectiveness of GIS-based and AHP as a cost-effective tool for preliminary groundwater exploration in data-scarce environments. The resulting groundwater potential map provides a vital scientific foundation for sustainable water resource management, enabling targeted borehole siting, informed aquifer development, and resilience-building strategies to enhance water security for communities and livelihoods in the Acholi sub-region.","地下水是半干旱地区重要的淡水来源，尤其是在乌干达北部等水资源紧张地区，那里地表水稀缺且降水模式变化不可靠。该地区缺乏足够的清洁饮用水供人类消费，由于地下水难以获取且信息不足，仅有20%的农业用水来自地下开采。鉴于当地社区面临这些水资源困难，基特古姆和帕德尔地区的地下水分布尚未得到研究。因此，本研究结果为接触这一不可或缺的水源提供了初步的地下水调查。本研究采用地理空间方法与多准则分析相结合，识别阿乔利次区域基特古姆和帕德尔地区的地下水潜力区。利用地理信息系统（GIS）、遥感技术和层次分析法（AHP），基于其水文地质影响和数据可获取性，选取了六个主题图层：降雨量、河网密度、坡度、土壤类型、地质和土地利用\u002F土地覆盖。经过标准化和归一化权重赋值后，使用ArcGIS Pro 3.1.0版本中的加权叠加分析将这些图层综合成一张全面的地下水潜力分区图。结果将研究区划分为五个区域：极低、低、中等、高和极高潜力。分析表明，基特古姆区主要以极低至低地下水潜力区为主，两者合计占67.24%，受较高河网密度和较陡坡度等因素制约。相反，帕德尔区表现出有利条件，其85.5%的面积被归类为高至极高地下水潜力，这归因于平缓的坡度和较高的降雨量，增强了入渗能力。利用18口现有钻孔的出水量数据进行验证，模型与实际井表现之间的一致率达到75.0%，证实了模型在可接受结果范围内的可靠性。本研究证明了基于GIS和AHP的方法作为数据稀缺环境中初步地下水勘探的成本效益工具的有效性。所生成的地下水潜力图为可持续水资源管理提供了重要的科学基础，有助于有针对性地选址钻孔，为知情决策提供依据。","Discover Sustainability","2026-10-10T00:00:00Z",{"impact":116,"substance":371,"depth":372,"authority":20,"freshness":21,"relevant":22,"comment":510},"基于GIS、遥感与AHP的乌干达北部地下水潜力制图研究，方法成熟、验证可靠，对缺水地区农业水资源规划有参考价值，但属区域性初步研究，公共影响有限。",[512],{"name":507,"url":504},[514,29,515,516,517],"遥感","GIS","地下水潜力","乌干达农业",{"code":519,"slug":520,"name":521,"path":522,"parent_code":216},"I4","gis","GIS与空间分析","\u002Ftopic\u002Fdigital-agriculture\u002Fgis",[524,529],{"code":525,"slug":526,"name":527,"path":528,"parent_code":216},"I3","remote-sensing","遥感与农情监测","\u002Ftopic\u002Fdigital-agriculture\u002Fremote-sensing",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},{"status":40,"locked":14,"version":41,"method":42,"evidence":531},{"candidates":532,"agricultural_evidence":46},[533,539,544,549,553],{"code":519,"score":19,"supported":46,"title":534,"abstract":535,"tags":538},[515],[536,515,537],"地理信息","geographic information",[515],{"code":525,"score":135,"supported":46,"title":540,"abstract":542,"tags":543},[541],"remote sensing",[514,541],[514],{"code":33,"score":116,"supported":46,"title":545,"abstract":546,"tags":548},[],[50,547],"water resource",[516,29],{"code":73,"score":54,"supported":46,"title":550,"abstract":551,"tags":552},[],[322,237],[],{"code":61,"score":153,"supported":46,"title":554,"abstract":555,"tags":556},[],[65],[],[558,559],"乌干达 Kitgum Pader 地下水","GIS AHP 地下水潜力","乌干达KitgumPader地下水-4753","10.1007\u002Fs43621-026-04943-7",{"doi":561,"openalex_id":563,"authors":564,"venue":507,"cited_by_count":93,"oa_url":504,"card":572,"direction":576,"ingested_from":100},"W7221339030",[565,568,570],{"name":566,"orcid":567},"Ahmed Abdirizak Dirie","https:\u002F\u002Forcid.org\u002F0009-0002-8109-0724",{"name":569,"orcid":9},"Abdulkadir Ahmed Mohamed",{"name":571,"orcid":9},"Ambiga Kannapiran",{"tldr":573,"method":574,"finding":575,"direction":576,"opportunity":577},"用GIS、遥感和AHP制图评估乌干达两区地下水潜力并验证。","GIS与遥感结合AHP，加权叠加6个主题图层，用18口井数据验证。","Kitgum区67.24%为低潜力，Pader区85.5%为高潜力，模型与井数据吻合75%。","农业遥感与作物表型","可将该地下水潜力制图方法迁移到其他数据稀缺区，并结合农业灌溉需求优化井位。","2026-10-12T23:30:24.761508Z"]