[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-5372":3,"related-5372":99},{"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":67,"slug":70,"view_count":71,"doi":72,"paper":73,"created_at":98},5372,"Livelihood risks and resilience of rural households: evidence from Sichuan Province, China","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1934397","Rural households in flood-prone areas face overlapping livelihood risks, yet evidence remains limited on how specific risk dimensions are associated with different components of livelihood resilience. This study examined these associations among rural households in three counties of Sichuan Province, China. Cross-sectional questionnaire data were collected from 540 rural households in Gaoxian, Jiajiang, and Yuechi counties. Composite indices were constructed for health, environmental, financial, and social risks and for buffering, self-organization, and learning capacities. Fractional logit models with county fixed effects were used to estimate adjusted associations, with inference based on village-clustered wild-bootstrap procedures. Social risk was negatively associated with buffering capacity, self-organization capacity, learning capacity, and overall livelihood resilience. Health risk was negatively associated with self-organization capacity at the 10% level and with overall livelihood resilience at the 5% level, but not with buffering or learning capacity. Financial risk was positively associated with overall livelihood resilience in the baseline model, but this association was not robust to excluding loan-amount indicators. Environmental risk was not statistically associated with any resilience outcome. The associations between livelihood risk and resilience were dimension-specific and should not be interpreted as causal. The findings identify social support and access to health services as priorities for further local assessment, while financial vulnerability should be distinguished from credit access and environmental interventions should be guided by additional evidence on local hazards and program performance.","洪涝易发地区的农村家庭面临多重生计风险，但关于具体风险维度与生计韧性不同组成部分之间关联的证据仍然有限。本研究考察了中国四川省三个县农村家庭中这些关联。研究收集了高县、夹江县和岳池县540户农村家庭的横截面问卷数据，构建了健康风险、环境风险、金融风险和社会风险以及缓冲能力、自组织能力和学习能力的综合指数。采用带县级固定效应的分数对数模型估计调整后的关联，推断基于村级聚类野生自助法程序。社会风险与缓冲能力、自组织能力、学习能力及总体生计韧性呈负相关。健康风险在10%水平上与自组织能力呈负相关，在5%水平上与总体生计韧性呈负相关，但与缓冲能力或学习能力无关。金融风险在基准模型中与总体生计韧性呈正相关，但该关联在剔除贷款金额指标后不稳健。环境风险与任何韧性结果均无统计学关联。生计风险与韧性之间的关联具有维度特异性，不应被解释为因果关系。研究结果将社会支持和卫生服务可及性确定为地方进一步评估的优先事项，同时应将金融脆弱性与信贷可及性加以区分，环境干预措施应以关于地方灾害和项目绩效的更多证据为指导。",null,"Frontiers in Sustainable Food Systems","2026-10-19T00:00:00Z","论文",10,false,63,{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":21,"relevant":22,"comment":23},8,18,15,13,9,1,"基于四川三县540户问卷的实证研究，揭示社会风险对生计韧性的负向关联，方法规范但属区域案例，公共影响有限，可作参考而非精选。",[25],{"name":10,"url":6},[27,28,29,30,31],"乡村治理","农村金融","生计韧性","健康服务","农户生计",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},"H7","climate","气候适应与防灾减灾","\u002Ftopic\u002Fenvironment\u002Fclimate","H",[],{"status":40,"locked":14,"version":41,"method":42,"evidence":43},"classified","2026-10-22.2","rules",{"candidates":44,"agricultural_evidence":47},[45,52,57,62],{"code":33,"score":46,"supported":47,"title":48,"abstract":49,"tags":51},3,true,[],[50],"洪涝",[],{"code":53,"score":22,"supported":14,"title":54,"abstract":55,"tags":56},"G3",[],[],[28],{"code":58,"score":22,"supported":14,"title":59,"abstract":60,"tags":61},"G5",[],[],[27],{"code":63,"score":22,"supported":14,"title":64,"abstract":65,"tags":66},"G6",[],[],[31],[68,69],"四川 农户 生计韧性","高县 夹江 岳池 农户","四川农户生计韧性-5372",0,"10.3389\u002Ffsufs.2026.1934397",{"doi":72,"openalex_id":74,"authors":75,"venue":10,"cited_by_count":71,"oa_url":6,"card":91,"direction":95,"ingested_from":97},"W7222969600",[76,79,81,83,85,87,89],{"name":77,"orcid":78},"Tao Liu","https:\u002F\u002Forcid.org\u002F0000-0002-0506-3356",{"name":80,"orcid":9},"Ting Zhao",{"name":82,"orcid":9},"Jiahui Tian",{"name":84,"orcid":9},"Shanshan Zhao",{"name":86,"orcid":9},"Tao Zeng",{"name":88,"orcid":9},"Lijie Xu",{"name":90,"orcid":9},"Wei Liu",{"tldr":92,"method":93,"finding":94,"direction":95,"opportunity":96},"分析四川三县540户农户生计风险各维度与生计韧性各成分的关联。","入户问卷构建风险与韧性指数，用分数logit模型加县固定效应和村级聚类野生自助法","社会风险与各韧性成分及总体韧性负相关，健康风险与总体韧性负相关，环境风险无显著关联。","数字乡村与农业信息化","可结合数字乡村建设，研究社会支持网络与医疗可及性等信息化服务如何提升农户生计韧性。","openalex","2026-10-20T23:30:06.775370Z",{"total":100,"page":22,"page_size":100,"items":101},6,[102,159,222,306,368,481],{"id":103,"title":104,"url":105,"summary":106,"summary_zh":107,"content":9,"source_name":10,"source_url":105,"published_at":108,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":109,"score_detail":110,"sources":114,"tags":116,"primary_topic":121,"secondary_topics":122,"classification":123,"search_phrases":141,"slug":144,"view_count":71,"doi":145,"paper":146,"created_at":158},4874,"Estimating the level of rural household resilience to food insecurity: evidence from Rushinga Rural District in northern Zimbabwe","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1875364","Introduction Rural households in semi-arid Zimbabwe face recurrent food insecurity because their livelihoods depend heavily on climate-sensitive agriculture, limited assets, and weak rural service systems. However, household-level evidence on the dimensions that construct resilience to food insecurity in Southern Africa remains limited. The study estimates multidimensional rural household resilience to food insecurity in Rushinga District, Zimbabwe; identifies the relative contributions of eight livelihood-related resilience dimensions; and examines resilience patterns by livelihood orientation and household headship, using cross-sectional survey data from 300 households collected across three wards. Methods The study applied a two-stage procedure informed by the multidimensional structure of the FAO-RIMA-II framework. In the first stage, observable household indicators were grouped a priori into eight theoretically informed resilience dimensions, such as assets, income and food access, social protection, access to basic services, access to natural resources, adaptive capacity, support services, and stability. PCA was used within each dimension to reduce the observed indicators into dimension-level component scores. In the second stage, the retained dimension scores were entered into a factor analysis to examine their joint structure and construct the multidimensional household resilience index. Results The second-order factor analysis retained three factors explaining 59.28% of the variance, with comparatively high absolute loadings for income and food access (0.891), assets (0.793), adaptive capacity (-0.777), stability (0.783), basic services (0.623) and support services (0.813). Access to natural resources did not load strongly on the retained factors, indicating a comparatively weaker contribution within the estimated multidimensional structure. Non-farming households recorded a higher mean resilience score relative to farming households, while female-headed households recorded a lower mean resilience score compared to male-headed households. Conclusion The findings suggest that strengthening rural resilience to food insecurity in Zimbabwe may require a policy approach that supports productive assets, non-farm livelihood diversification, access to basic services, and gender-responsive support systems, alongside agricultural interventions.","引言 津巴布韦半干旱地区的农村家庭面临反复出现的粮食不安全问题，因为其生计高度依赖对气候敏感的农业、资产有限且农村服务体系薄弱。然而，关于南部非洲粮食不安全复原力构成维度的家庭层面证据仍然有限。本研究利用在三个选区收集的300户家庭的横截面调查数据，评估津巴布韦Rushinga区农村家庭多维粮食不安全复原力；识别八个与生计相关的复原力维度的相对贡献；并按生计取向和户主性别考察复原力模式。方法 本研究采用基于FAO-RIMA-II框架多维结构的两阶段程序。第一阶段，将可观测的家庭指标先验地归入八个具有理论依据的复原力维度，如资产、收入与食物获取、社会保护、基本服务获取、自然资源获取、适应能力、支持服务和稳定性。在每个维度内使用PCA将观测指标降维为维度层面的成分得分。第二阶段，将保留的维度得分纳入因子分析，以考察其联合结构并构建多维家庭复原力指数。结果 二阶因子分析保留了三个因子，解释了59.28%的方差，其中收入与食物获取（0.891）、资产（0.793）、适应能力（-0.777）、稳定性（0.783）、基本服务（0.623）和支持服务（0.813）的绝对载荷相对较高。自然资源获取在保留因子上的载荷不强，表明其在所估计的多维结构中贡献相对较弱。非农业家庭的平均复原力得分高于农业家庭，而女性户主家庭的平均复原力得分低于男性户主家庭。结论 研究结果表明，加强津巴布韦农村粮食不安全复原力可能需要一种政策路径，在农业干预措施之外，支持生产性资产、非农生计多样化、基本服务获取和性别响应型支持体系。","2026-10-13T00:00:00Z",66,{"impact":17,"substance":111,"depth":112,"authority":20,"freshness":21,"relevant":22,"comment":113},20,16,"基于FAO-RIMA-II框架的300户实证研究，方法规范、结论具体，但属津巴布韦地方性案例，对国内三农信息化参考价值有限，可作国际比较素材。",[115],{"name":10,"url":105},[117,118,31,119,120],"粮食安全","非农就业","农村抗逆力","性别差异",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[],{"status":40,"locked":14,"version":41,"method":42,"evidence":124},{"candidates":125,"agricultural_evidence":47},[126,131,136],{"code":33,"score":46,"supported":47,"title":127,"abstract":128,"tags":130},[],[129],"干旱",[],{"code":63,"score":132,"supported":14,"title":133,"abstract":134,"tags":135},2,[],[],[31,118],{"code":137,"score":22,"supported":14,"title":138,"abstract":139,"tags":140},"A8",[],[],[117],[142,143],"津巴布韦 Rushinga 农户抗逆力","FAO-RIMA-II 粮食安全","津巴布韦Rushinga农户抗逆力-4874","10.3389\u002Ffsufs.2026.1875364",{"doi":145,"openalex_id":147,"authors":148,"venue":10,"cited_by_count":71,"oa_url":105,"card":153,"direction":95,"ingested_from":97},"W7221657887",[149,151],{"name":150,"orcid":9},"Onismo Muzah",{"name":152,"orcid":9},"Tafadzwa Mabhaudhi",{"tldr":154,"method":155,"finding":156,"direction":95,"opportunity":157},"基于津巴布韦300户调查，用FAO-RIMA-II框架估算农村家庭粮食不安全恢复力指数。","两阶段法：各维度内PCA降维，再对维度得分做二阶因子分析构建综合指数。","收入与食物获取、资产、支持服务贡献最大；非农家庭恢复力更高，女性户主家庭更低。","可将恢复力指数与农户数字服务可及性、移动支付等信息化指标结合，检验数字赋能对恢复力的调节作用。","2026-10-14T23:30:07.234699Z",{"id":160,"title":161,"url":162,"summary":163,"summary_zh":164,"content":9,"source_name":165,"source_url":162,"published_at":166,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":167,"score_detail":168,"sources":171,"tags":173,"primary_topic":178,"secondary_topics":179,"classification":180,"search_phrases":203,"slug":206,"view_count":132,"doi":207,"paper":208,"created_at":221},4342,"GREEN FINANCE AND CAPITAL CIRCULATION IN SMART AGRICULTURE: AI-DRIVEN INSIGHTS","https:\u002F\u002Fdoi.org\u002F10.24412\u002F2411-0450-2026-7-114-120","This scientific article examines the role of digitalization and smart agriculture in advancing green finance, AI-driven innovation, and inclusive rural investment. The main objective of the study is to assess how integrating digital technologies and AI systems into agricultural finance can enhance productivity and support sustainable community development. Drawing on the theoretical foundations of digital finance, green finance, and development policy, the research explores the relationship between traditional credit systems and innovative technological solutions to drive structural transformations in rural economies. The analysis shows that conventional agricultural finance mechanisms are often constrained by limited access to funds, high transaction costs, and insufficient risk management. Digital tools, including mobile banking, fintech platforms, and AI-based credit scoring, improve financial accessibility, optimize investment decisions, and increase transparency, while smart agricultural technologies enhance efficiency, productivity, and climate resilience. The study also discusses long-term trends in global agro-food trade and regional structural characteristics reflecting uneven import and export flows across regions. Overall, the research demonstrates that combining digitalization, AI, and targeted finance can significantly foster more sustainable and productive agricultural development, increasing both efficiency and financial inclusion while supporting long-term resilience in rural communities.","本文考察了数字化与智慧农业在推动绿色金融、人工智能驱动的创新以及包容性农村投资中的作用。研究的主要目标是评估将数字技术和人工智能系统融入农业金融，如何能够提升生产力并支持可持续的社区发展。基于数字金融、绿色金融和发展政策的理论基础，研究探讨了传统信贷体系与创新技术解决方案之间的关系，以推动农村经济的结构性转型。分析表明，传统农业金融机制往往受限于资金获取渠道有限、交易成本高以及风险管理不足。数字工具，包括移动银行、金融科技平台和基于人工智能的信用评分，改善了金融可及性，优化了投资决策，并提高了透明度，而智慧农业技术则提升了效率、生产力和气候韧性。研究还讨论了全球农食产品贸易的长期趋势以及反映各区域进出口流量不均衡的区域结构特征。总体而言，研究表明，将数字化、人工智能和有针对性的金融相结合，能够显著促进更可持续、更具生产力的农业发展，在提高效率和金融包容性的同时，支持农村社区的长期韧性。","cyberleninka.ru","2026-10-06T00:00:00Z",72,{"impact":18,"substance":111,"depth":169,"authority":17,"freshness":21,"relevant":22,"comment":170},17,"论文从数字金融与AI信贷视角切入智慧农业与绿色金融，结论具参考价值，但来源为俄语开放期刊，权威性一般，适合作为主题聚合素材而非头条精选。",[172],{"name":165,"url":162},[174,175,176,28,177],"智慧农业","农业人工智能","数字普惠金融","绿色金融",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[],{"status":40,"locked":14,"version":41,"method":42,"evidence":181},{"candidates":182,"agricultural_evidence":47},[183,189,193,198],{"code":184,"score":19,"supported":47,"title":185,"abstract":187,"tags":188},"I1",[186],"smart agriculture",[174,186],[174],{"code":53,"score":46,"supported":14,"title":190,"abstract":191,"tags":192},[],[],[28,176,177],{"code":33,"score":46,"supported":47,"title":194,"abstract":195,"tags":197},[],[196],"climate resilience",[],{"code":199,"score":22,"supported":14,"title":200,"abstract":201,"tags":202},"I2",[],[],[175],[204,205],"智慧农业 绿色金融","AI 农业信贷 数字金融","智慧农业绿色金融-4342","10.24412\u002F2411-0450-2026-7-114-120",{"doi":207,"openalex_id":209,"authors":210,"venue":165,"cited_by_count":71,"oa_url":162,"card":215,"direction":220,"ingested_from":97},"W7220700804",[211,213],{"name":212,"orcid":9},"A.V. Mardoyan",{"name":214,"orcid":9},"H.A. Sargsyan",{"tldr":216,"method":217,"finding":218,"direction":95,"opportunity":219},"研究数字化与智慧农业如何推动绿色金融、AI创新与农村包容性投资。","基于数字金融、绿色金融与发展政策理论，分析移动银行、金融科技与AI信用评分。","数字工具与AI可提升金融可及性、优化投资并增强农业气候韧性。","可实证检验AI信用评分对农户信贷可得性与绿色投资决策的因果影响。","智慧农业 \u002F 农业物联网","2026-10-07T23:30:08.959053Z",{"id":223,"title":224,"url":225,"summary":226,"summary_zh":227,"content":9,"source_name":228,"source_url":225,"published_at":229,"category":12,"cover_url":9,"hotness":13,"is_selected":47,"score":230,"score_detail":231,"sources":237,"tags":239,"primary_topic":245,"secondary_topics":251,"classification":253,"search_phrases":285,"slug":288,"view_count":71,"doi":289,"paper":290,"created_at":305},5569,"A four-decadal (1981–2024) quality-assured ground-based soybean phenology dataset from Northeast China: a FAIR-compliant resource for climate impact and agricultural adaptation studies","https:\u002F\u002Fdoi.org\u002F10.1080\u002F20964471.2026.2735138","Although satellite remote sensing has been widely used to monitor land surface phenology, long-term, high-quality ground-based observations are essential for validating and calibrating these products, particularly for understanding agricultural ecosystem responses to climate change. However, such ground-truth datasets remain scarce, limiting the full potential of Earth system data applications. Here we present a comprehensive ground-based soybean phenology dataset for Northeast China, a region critical to national food security. The dataset integrates historical paper-based logs (1980s–1990s) with modern electronic records (2000s onwards) from 43 national agrometeorological stations operated by the China Meteorological Administration (CMA), spanning a 15° latitudinal gradient (38–53°N) across Heilongjiang, Jilin, and Liaoning provinces over 44 years (1981–2024). It provides the timing (day of year, DOY) of eight key phenophases (sowing, emergence, three-leaf, branching, flowering, pod formation, seed filling, maturity) and the durations of six intervening growth intervals. A multi-tiered quality assurance framework combining automated consistency checks, statistical outlier detection, and expert arbitration against agronomic principles and auxiliary climate data ensures high data integrity and completeness (>99%; paper era: 93.8%; electronic era: 98.1%). To facilitate reuse, we provide pre-computed kernel density estimates (probability distributions) and univariate linear regression trends for each station and phenological variable, along with 656 diagnostic plots. The dataset is openly available in the Science Data Bank under a CC BY 4.0 license as primary data tables (XLSX) and diagnostic plots (JPEG, 1200 dpi) (https:\u002F\u002Fdoi.org\u002F10.57760\u002Fsciencedb.37245). As a long-term, spatially explicit, FAIR-compliant ground-truth resource, this dataset is valuable for validating satellite-derived phenology products, calibrating crop modules, and investigating climate-driven impacts on agricultural systems.","尽管卫星遥感已被广泛用于监测地表物候，但长期、高质量的地面观测对于验证和校准这些产品至关重要，尤其是对于理解农业生态系统对气候变化的响应而言。然而，此类地面真值数据集仍然稀缺，限制了地球系统数据应用潜力的充分发挥。本文介绍了一套面向中国东北地区的综合性大豆物候地面数据集，该地区对国家粮食安全至关重要。该数据集整合了中国气象局（CMA）运营的43个国家农业气象站的历史纸质记录（20世纪80—90年代）与现代电子记录（2000年代至今），覆盖黑龙江、吉林和辽宁三省跨越15°纬度梯度（38—53°N）、时间跨度44年（1981—2024年）。数据集提供了8个关键物候期（播种、出苗、三叶、分枝、开花、结荚、鼓粒、成熟）的发生时间（年积日，DOY）以及6个中间生长间隔的持续时间。一套多层质量保证框架结合了自动一致性检查、统计异常值检测以及依据农学原理和辅助气候数据进行的专家仲裁，确保了高数据完整性和完整性（>99%；纸质时代：93.8%；电子时代：98.1%）。为便于重复使用，我们提供了每个站点和物候变量的预计算核密度估计（概率分布）和单变量线性回归趋势，以及656幅诊断图。该数据集以CC BY 4.0许可在Science Data Bank公开提供，包括主数据表（XLSX）和诊断图（JPEG，1200 dpi）（https:\u002F\u002Fdoi.org\u002F10.57760\u002Fsciencedb.37245）。作为一个长期、空间明确、符合FAIR原则的地面真值资源，该数据集对于验证卫星反演的物候产品、校准作物模块以及研究气候驱动对农业系统的影响具有重要价值。","Big Earth Data","2026-10-21T00:00:00Z",89,{"impact":232,"substance":233,"depth":234,"authority":235,"freshness":13,"relevant":22,"comment":236},22,24,19,14,"覆盖东北44年、43站的大豆物候地面观测数据集，质控严格且FAIR开放，对遥感验证与气候影响研究有实质价值，值得入选。",[238],{"name":228,"url":225},[240,241,242,243,244],"大豆","气候变化","东北农业","物候数据","遥感验证",{"code":246,"slug":247,"name":248,"path":249,"parent_code":250},"A4","soybean-oilseeds","大豆与油料","\u002Ftopic\u002Ffield-crops\u002Fsoybean-oilseeds","A",[252],{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},{"status":40,"locked":14,"version":41,"method":42,"evidence":254},{"candidates":255,"agricultural_evidence":47},[256,261,267,272,279],{"code":246,"score":19,"supported":47,"title":257,"abstract":259,"tags":260},[258],"soybean",[240,258],[240],{"code":33,"score":13,"supported":47,"title":262,"abstract":263,"tags":266},[],[241,264,265],"农业气象","climate change",[241],{"code":137,"score":100,"supported":47,"title":268,"abstract":269,"tags":271},[],[117,270],"food security",[],{"code":273,"score":100,"supported":47,"title":274,"abstract":275,"tags":278},"I3",[],[276,277],"遥感","remote sensing",[],{"code":280,"score":46,"supported":47,"title":281,"abstract":282,"tags":284},"H6",[],[283],"农业生态",[],[286,287],"东北 大豆 物候 数据集","大豆 物候 遥感 验证","东北大豆物候数据集-5569","10.1080\u002F20964471.2026.2735138",{"doi":289,"openalex_id":291,"authors":292,"venue":228,"cited_by_count":71,"oa_url":225,"card":299,"direction":303,"ingested_from":97},"W7223091615",[293,296],{"name":294,"orcid":295},"Quanjun Zhang","https:\u002F\u002Forcid.org\u002F0000-0001-6087-3928",{"name":297,"orcid":298},"Dongli Wu","https:\u002F\u002Forcid.org\u002F0000-0003-1676-2264",{"tldr":300,"method":301,"finding":302,"direction":303,"opportunity":304},"发布东北大豆1981–2024年44年地面物候数据集，含8个物候期与6个间隔期。","整合43个农气站纸质与电子记录，经自动校验、统计离群检测和专家仲裁质控。","数据完整度超99%，并提供核密度分布、线性趋势与656张诊断图。","农业遥感与作物表型","可基于该地面真值校准遥感物候产品与作物模型，量化气候变化对大豆物候的影响。","2026-10-22T11:20:39.146445Z",{"id":307,"title":308,"url":309,"summary":310,"summary_zh":9,"content":9,"source_name":311,"source_url":9,"published_at":229,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":312,"score_detail":313,"sources":315,"tags":317,"primary_topic":322,"secondary_topics":327,"classification":334,"search_phrases":355,"slug":358,"view_count":22,"doi":9,"paper":359,"created_at":367},5535,"基于无人机多光谱图像与VGG21模型的小麦渍害调控效果识别","https:\u002F\u002Ffinance.sina.cn\u002F2026-10-16\u002Fdetail-inivmprm8363597.d.html","江苏省农科院农业信息研究所联合中国农科院环发所与湖北省农科院粮作所，在小麦拔节至抽穗、抽穗至灌浆两个阶段设置对照、渍水胁迫、硅肥与氨基酸调控试验，用大疆精灵4采集冠层多光谱影像。VGG21模型对硅肥调控识别正确率超91%，精度96.42%、召回率89.53%。","智慧农业（中英文）2026-10-21",82,{"impact":18,"substance":232,"depth":18,"authority":235,"freshness":13,"relevant":22,"comment":314},"省级科研机构联合攻关，方法新颖、数据扎实，对渍害遥感识别与调控评估有实质参考价值，值得入选。",[316],{"name":311,"url":309},[174,318,319,320,321],"农业遥感","作物表型","无人机多光谱","小麦渍害",{"code":323,"slug":324,"name":325,"path":326,"parent_code":250},"A2","wheat","小麦","\u002Ftopic\u002Ffield-crops\u002Fwheat",[328,333],{"code":273,"slug":329,"name":330,"path":331,"parent_code":332},"remote-sensing","遥感与农情监测","\u002Ftopic\u002Fdigital-agriculture\u002Fremote-sensing","I",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},{"status":40,"locked":14,"version":41,"method":42,"evidence":335},{"candidates":336,"agricultural_evidence":47},[337,342,346,351],{"code":323,"score":338,"supported":47,"title":339,"abstract":340,"tags":341},11,[325],[325],[],{"code":273,"score":338,"supported":47,"title":343,"abstract":344,"tags":345},[320],[],[319,318,320],{"code":33,"score":17,"supported":47,"title":347,"abstract":349,"tags":350},[348],"渍害",[],[],{"code":184,"score":22,"supported":14,"title":352,"abstract":353,"tags":354},[],[],[174],[356,357],"江苏省农科院 小麦渍害 多光谱","VGG21 小麦 硅肥调控","江苏省农科院小麦渍害多光谱-5535",{"doi":9,"openalex_id":9,"authors":360,"venue":9,"cited_by_count":71,"oa_url":9,"card":361,"direction":303,"ingested_from":366},[],{"tldr":362,"method":363,"finding":364,"direction":303,"opportunity":365},"用无人机多光谱图像和VGG21模型识别小麦渍害后硅肥与氨基酸调控效果。","大疆精灵4采集冠层多光谱影像，构建VGG21深度学习分类模型。","VGG21对硅肥调控识别正确率超91%，精度96.42%、召回率89.53%。","可扩展多生育期、多调控组合与轻量化模型，探索渍害胁迫等级与调控效果的同步识别。","agent","2026-10-22T00:07:10.070916Z",{"id":369,"title":370,"url":371,"summary":372,"summary_zh":373,"content":9,"source_name":374,"source_url":371,"published_at":375,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":109,"score_detail":376,"sources":379,"tags":381,"primary_topic":386,"secondary_topics":387,"classification":398,"search_phrases":452,"slug":455,"view_count":71,"doi":456,"paper":457,"created_at":480},5483,"Soil Salinity under Climate Change in Pakistan: Emerging Challenges and Sustainable Management Approaches for Agriculture","https:\u002F\u002Fdoi.org\u002F10.71317\u002Fkjard.2.10.2026.883","Soil salinity is a major constraint to agricultural productivity, soil health, and food security in Pakistan, particularly under changing climatic conditions. Rising temperatures, increased evapotranspiration, irregular precipitation, droughts, flooding, and sea-level rise can intensify salt accumulation and alter soil–water interactions. This review examines the emerging challenges associated with climate change and soil salinity in Pakistan, focusing on their impacts on soil properties, crop physiology, agricultural production, and rural livelihoods. It discusses the mechanisms of soil salinity and sodicity, their spatial distribution, and the interactions among climate variability, irrigation practices, groundwater quality, and secondary salinization. Furthermore, sustainable management approaches are evaluated, including gypsum application, organic amendments, integrated nutrient management, efficient irrigation, drainage improvement, and appropriate leaching strategies. Climate-resilient approaches, such as conventional crop breeding, modern biotechnology, halophyte utilization, plant growth-promoting microorganisms, and mycorrhizal associations, are also explored. The review highlights the potential of remote sensing, geographic information systems, precision agriculture, and predictive modelling to support salinity monitoring and site-specific management. Despite these opportunities, important challenges remain, including insufficient long-term monitoring, limited region-specific data, economic constraints, and gaps in farmer awareness and institutional coordination. Addressing these challenges requires integrated research, effective agricultural policies, improved extension services, and collaboration among researchers, policymakers, and farming communities. Prioritizing locally adapted, economically feasible, and environmentally sustainable interventions can strengthen agricultural resilience, restore salt-affected soils, and protect freshwater resources. Overall, integrating climate adaptation with sustainable soil and water management is essential for maintaining agricultural productivity and improving long-term food security in Pakistan.","土壤盐渍化是制约巴基斯坦农业生产力、土壤健康和粮食安全的主要因素，在气候变化条件下尤为突出。气温升高、蒸散加剧、降水不规律、干旱、洪水以及海平面上升可能加剧盐分积累并改变土壤—水相互作用。本文综述了巴基斯坦气候变化与土壤盐渍化相关的新兴挑战，重点关注其对土壤性质、作物生理、农业生产和农村生计的影响。文章讨论了土壤盐渍化和钠质化的机制、其空间分布，以及气候变率、灌溉实践、地下水质量和次生盐渍化之间的相互作用。此外，评估了可持续管理途径，包括施用石膏、有机改良、综合养分管理、高效灌溉、排水改良和适宜的淋洗策略。还探讨了气候韧性方法，如常规作物育种、现代生物技术、盐生植物利用、植物促生微生物和菌根共生。本文强调了遥感、地理信息系统、精准农业和预测建模在支持盐渍化监测和因地制宜管理方面的潜力。尽管存在这些机遇，重要挑战依然存在，包括长期监测不足、区域特定数据有限、经济制约以及农民意识和制度协调方面的差距。应对这些挑战需要综合研究、有效的农业政策、改进的推广服务以及研究人员、政策制定者和农业社区之间的协作。优先采取适应当地、经济可行且环境可持续的干预措施，可增强农业韧性、修复盐渍化土壤并保护淡水资源。总体而言，将气候适应与可持续水土管理相结合，对于维持巴基斯坦农业生产力和改善长期粮食安全至关重要。","Kashmir Journal of Academic Research and Development","2026-10-20T00:00:00Z",{"impact":20,"substance":18,"depth":19,"authority":377,"freshness":17,"relevant":22,"comment":378},12,"综述性论文，系统梳理气候变化下巴基斯坦土壤盐渍化成因与可持续治理路径，兼具遥感与精准农业视角，对盐碱地治理议题有参考价值，但属区域性综述、非突破性成果。",[380],{"name":374,"url":371},[241,382,383,384,385],"盐碱地治理","遥感监测","智慧灌溉","土壤盐渍化",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[388,393],{"code":389,"slug":390,"name":391,"path":392,"parent_code":37},"H2","soil","土壤健康与改良","\u002Ftopic\u002Fenvironment\u002Fsoil",{"code":394,"slug":395,"name":396,"path":397,"parent_code":37},"H3","irrigation","水资源与灌溉","\u002Ftopic\u002Fenvironment\u002Firrigation",{"status":40,"locked":14,"version":41,"method":42,"evidence":399},{"candidates":400,"agricultural_evidence":47},[401,406,411,418,423,427,433,440,446],{"code":33,"score":18,"supported":47,"title":402,"abstract":403,"tags":405},[265],[241,404,129,265],"气候适应",[241],{"code":389,"score":19,"supported":47,"title":407,"abstract":408,"tags":410},[390],[409,390],"土壤",[382],{"code":394,"score":13,"supported":47,"title":412,"abstract":413,"tags":417},[],[414,415,395,416],"灌溉","水资源","evapotranspiration",[384],{"code":273,"score":419,"supported":47,"title":420,"abstract":421,"tags":422},7,[],[276,277],[383],{"code":137,"score":100,"supported":47,"title":424,"abstract":425,"tags":426},[],[117,270],[],{"code":184,"score":100,"supported":47,"title":428,"abstract":429,"tags":432},[],[430,431],"精准农业","precision agriculture",[],{"code":434,"score":100,"supported":47,"title":435,"abstract":436,"tags":439},"I4",[],[437,438],"地理信息","geographic information",[],{"code":441,"score":46,"supported":47,"title":442,"abstract":443,"tags":445},"F3",[],[444],"养分管理",[],{"code":447,"score":46,"supported":47,"title":448,"abstract":449,"tags":451},"J1",[],[450],"农业政策",[],[453,454],"巴基斯坦 土壤盐渍化","盐碱地 遥感监测","巴基斯坦土壤盐渍化-5483","10.71317\u002Fkjard.2.10.2026.883",{"doi":456,"openalex_id":458,"authors":459,"venue":374,"cited_by_count":71,"oa_url":371,"card":475,"direction":303,"ingested_from":97},"W7222999158",[460,462,464,466,468,470,473],{"name":461,"orcid":9},"Asifa Naz",{"name":463,"orcid":9},"Muhammad Abu Baker Siddiq",{"name":465,"orcid":9},"Syed Asghar Hussain Shah",{"name":467,"orcid":9},"Shahrish Nawaz",{"name":469,"orcid":9},"Muhmmad Irfan",{"name":471,"orcid":472},"Rizwana Kausar","https:\u002F\u002Forcid.org\u002F0000-0002-1339-3312",{"name":474,"orcid":9},"Muhammad Nouman Khalid",{"tldr":476,"method":477,"finding":478,"direction":303,"opportunity":479},"综述气候变化下巴基斯坦土壤盐渍化的挑战与可持续管理途径。","文献综述，整合盐渍化机制、空间分布及遥感GIS与预测模型应用。","需将气候适应与水土管理结合，优先本地化、经济可行的干预措施。","可填补长期盐渍化监测与区域数据空白，发展遥感+预测模型的精准分区治理。","2026-10-21T23:30:23.059448Z",{"id":482,"title":483,"url":484,"summary":485,"summary_zh":486,"content":9,"source_name":487,"source_url":484,"published_at":375,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":488,"score_detail":489,"sources":491,"tags":493,"primary_topic":498,"secondary_topics":502,"classification":510,"search_phrases":549,"slug":552,"view_count":71,"doi":553,"paper":554,"created_at":570},5478,"Characterisation of Food Security Situation for Smallholder Farmers in Zvimba","https:\u002F\u002Fdoi.org\u002F10.71458\u002Frx0qpm30","This study provides a comprehensive analysis of the food security situation among smallholder farmers (SHFs) in Zvimba District, Zimbabwe. Smallholder agriculture is the bedrock of Zimbabwe's food system, yet it remains highly vulnerable to a complex array of shocks and stressors. Using a mixed-methods approach, this research investigates the prevalence, drivers and lived experiences of food insecurity within this community. A structured survey was administered to 412 randomly selected smallholder households across the district's wards. The quantitative data were supplemented by 12 Focus Group Discussions (FGDs) and 24 Key Informant Interviews (KIIs) with farmers, community leaders and agricultural extension officers to capture qualitative nuances. The study is grounded in the Food Security Theory (FST), which conceptualises food security through its four pillars: food availability, food access, food utilisation and food stability. Findings reveal a precarious food security situation. Quantitatively, 78.4% of households were found to be food insecure, with an average Hunger Months Index of 4.7 months per year. The study identifies a significant disconnect between maize production, the national staple and household consumption, with over 65% of households failing to produce enough maize to meet their annual requirements. Qualitative data illuminated the multi-faceted drivers of this insecurity. Key points to note include climate change whereby erratic rainfall and prolonged mid-season dry spells were consistently reported as the primary production challenges, limited access to farming inputs whereby high costs and unreliable supplies of certified seeds, fertilizers and agro[1]chemicals constrain productivity. Morelso, socio-economic factors such as poverty, lack of viable alternative livelihoods and limited access to formal credit perpetuate a cycle of vulnerability. In addition, institutional weaknesses, for example, challenges with agricultural extension services and market inefficiencies, exacerbate the situation. The study concludes that food insecurity in Zvimba is not merely a problem of food production, but is deeply rooted in structural issues affecting food access, food utilisation, as well as food stability. Recommendations are proposed for a multi-sectoral approach, including promoting Climate-Smart Agriculture (CSA) and drought-resistant crops, strengthening input support systems and rural finance, diversifying livelihood strategies and enhancing the capacity of extension services. This research contributes to a deeper understanding of the localised dynamics of food security and provides evidence-based guidance for policymakers, development practitioners and the farmers of Zvimba themselves.","本研究对津巴布韦兹维姆巴区小农户（smallholder farmers, SHFs）的粮食安全状况进行了全面分析。小农农业是津巴布韦粮食体系的基石，但仍极易受到一系列复杂冲击和压力的影响。本研究采用混合方法，考察了该社区粮食不安全的普遍程度、驱动因素及生活体验。研究对该区各选区随机抽取的412户小农户进行了结构化问卷调查。定量数据辅以12次焦点小组讨论（FGDs）和24次关键知情人访谈（KIIs），访谈对象包括农民、社区领袖和农业推广人员，以捕捉定性层面的细微差异。本研究以粮食安全理论（Food Security Theory, FST）为基础，该理论通过四大支柱界定粮食安全：粮食可供性、粮食获取、粮食利用和粮食稳定性。研究结果揭示了严峻的粮食安全形势。定量数据显示，78.4%的家庭存在粮食不安全，年均饥饿月份指数为4.7个月。研究发现，玉米产量——该国主粮——与家庭消费之间存在显著脱节，超过65%的家庭生产的玉米不足以满足其年度需求。定性数据揭示了这一不安全状况的多重驱动因素。值得注意的要点包括：气候变化，即降雨不稳定和持续的中期干旱被一致报告为主要生产挑战；农业投入品获取受限，即认证种子、化肥和农用化学品成本高昂且供应不可靠，制约了生产力。此外，贫困、缺乏可行的替代生计以及正规信贷获取受限等社会经济因素使脆弱性循环持续存在。此外，制度薄弱环节，例如农业推广服务面临的挑战和市场效率低下，加剧了这一状况。研究得出结论，兹维姆巴的粮食不安全不仅仅是粮食生产问题，而是深深植根于影响粮食获取、粮食利用以及粮食稳定性的结构性问题。研究提出了采取多部门方法的建议，包括推广气候智能型农业（Climate-Smart Agriculture, CSA）和抗旱作物、加强投入品支持体系和农村金融、多样化生计策略以及增强","Ngenani The Zimbabwe Ezekiel Guti Journal of Community Engagement and Societal Transformations",55,{"impact":17,"substance":18,"depth":19,"authority":100,"freshness":17,"relevant":22,"comment":490},"基于412户调查与混合方法的扎实实证研究，但属津巴布韦地方性案例，公共影响与信源权威度有限，可作参考而非每日精选。",[492],{"name":487,"url":484},[117,494,495,496,497],"小农户","气候智慧农业","农业推广","津巴布韦",{"code":137,"slug":499,"name":500,"path":501,"parent_code":250},"yield-food-security","单产提升与粮食安全","\u002Ftopic\u002Ffield-crops\u002Fyield-food-security",[503,509],{"code":504,"slug":505,"name":506,"path":507,"parent_code":508},"G2","farm-services","社会化服务与规模经营","\u002Ftopic\u002Frural-services\u002Ffarm-services","G",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},{"status":40,"locked":14,"version":41,"method":42,"evidence":511},{"candidates":512,"agricultural_evidence":47},[513,517,522,527,533,540,545],{"code":137,"score":19,"supported":47,"title":514,"abstract":515,"tags":516},[270],[117,270],[117],{"code":504,"score":19,"supported":47,"title":518,"abstract":520,"tags":521},[519],"smallholder",[494,519],[494],{"code":33,"score":13,"supported":47,"title":523,"abstract":524,"tags":526},[],[241,129,265,525],"drought",[495],{"code":528,"score":419,"supported":47,"title":529,"abstract":530,"tags":532},"G1",[],[496,531],"agricultural extension",[496],{"code":534,"score":100,"supported":47,"title":535,"abstract":536,"tags":539},"A3",[],[537,538],"玉米","maize",[],{"code":53,"score":100,"supported":47,"title":541,"abstract":542,"tags":544},[],[28,543],"rural finance",[],{"code":184,"score":46,"supported":47,"title":546,"abstract":547,"tags":548},[],[186],[],[550,551],"Zvimba 小农户 粮食安全","津巴布韦 小农 玉米","Zvimba小农户粮食安全-5478","10.71458\u002Frx0qpm30",{"doi":553,"openalex_id":555,"authors":556,"venue":487,"cited_by_count":71,"oa_url":9,"card":565,"direction":220,"ingested_from":97},"W7223029383",[557,560,563],{"name":558,"orcid":559},"Casper Myambo","https:\u002F\u002Forcid.org\u002F0009-0007-8625-7526",{"name":561,"orcid":562},"Chipo Plaxedes Mubaya","https:\u002F\u002Forcid.org\u002F0000-0002-4123-0238",{"name":564,"orcid":9},"Patience Mutopo",{"tldr":566,"method":567,"finding":568,"direction":95,"opportunity":569},"调查津巴布韦Zvimba小农户粮食安全状况，分析其普遍性、成因与实际体验。","混合方法：412户问卷、12场焦点小组、24个关键人物访谈，基于粮食安全四支柱理","78.4%家庭粮食不安全，年均饥饿月4.7个月，主因是气候、投入、社会经济与制度等结构性问题。","可探索用移动端问卷与遥感产量监测构建小农户粮食安全动态预警与精准干预系统。","2026-10-21T23:30:08.937079Z"]