[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-2138":3},{"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,"view_count":32,"doi":33,"paper":34,"created_at":55},2138,"Biostimulants for sustainable intensification of agriculture: understanding farmers’ adoption behavior for their scaling-up","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1901923","Understanding how farmers integrate novel agricultural inputs into their production systems is important for promoting more sustainable input-use strategies. Although biostimulants have received increasing agronomic and policy attention, farm-level evidence on the extent and distribution of their use remains limited. This paper provides micro-level evidence on biostimulant adoption intensity among 193 biostimulant-aware and experienced farmers in two contrasting agricultural settings: Nagaur, a rainfed district in Rajasthan, and Moradabad, an irrigated district in Uttar Pradesh. This study addressed a dimension of adoption behavior: how deeply and unevenly farmers use a new input rather than whether they adopt it. The study finds that biostimulants were applied to two-thirds of the cultivated area. Biostimulant use was strongly crop-selective: vegetables (89%), spices (84%), and other commercial crops (78–86%) received comparatively high treatment share. Employing fractional logit model, the study find that market orientation and awareness of biostimulant benefits were positively associated with adoption intensity, while farm size was negatively associated with the treated-area share. The positive association between the composite adoption constraints index and adoption intensity may indicate that more intensive users have greater exposure to and recognition of barriers concerning product quality, price, availability, and technical information. The association between commercial-crop share and adoption intensity was more than twice as strong in Moradabad, Uttar Pradesh, as in Nagaur, Rajasthan, highlighting the importance of local production and market conditions. Strikingly, less than 10% of farmers recognize “biostimulants” generically, while over 97% recognize a specific branded product, and 88% identified input dealers as their main source of information. These findings show that biostimulant use among smallholders is shaped by crop value, farm scale, perceived benefits, adoption constraints, information channels, and farming-system context. Scaling appropriate biostimulant use therefore requires independent field demonstrations, crop-specific technical guidance, stronger product-quality verification, and extension strategies that engage with dealer networks while ensuring reliable and unbiased information.","理解农民如何将新型农业投入品整合进其生产系统，对于推动更可持续的投入品使用策略具有重要意义。尽管生物刺激素（biostimulants）已日益受到农艺学界和政策层面的关注，但关于其使用程度和分布的农场层面证据仍然有限。本文提供了两个对比鲜明的农业环境中193位了解生物刺激素且有使用经验的农户的微观层面证据：拉贾斯坦邦的雨养地区纳高尔（Nagaur）和北方邦的灌溉地区莫拉达巴德（Moradabad）。本研究关注的是采纳行为的一个维度：农民使用一种新投入品的深度和不均衡程度，而非是否采纳。研究发现，生物刺激素被施用于三分之二的耕地面积。生物刺激素的使用具有强烈的作物选择性：蔬菜（89%）、香料作物（84%）和其他经济作物（78%–86%）的施用面积占比较高。采用分数逻辑模型（fractional logit model），研究发现市场导向和对生物刺激素益处的认知与采纳强度呈正相关，而农场规模与施用面积占比呈负相关。综合采纳约束指数与采纳强度之间的正相关关系可能表明，使用强度更高的农户对产品质量、价格、可获得性和技术信息方面的障碍有更多的接触和认知。经济作物占比与采纳强度之间的关联在北方邦莫拉达巴德是拉贾斯坦邦纳高尔的两倍以上，凸显了当地生产和市场条件的重要性。值得注意的是，不到10%的农民能够识别“生物刺激素”这一通用名称，而超过97%的农民能识别某一具体品牌产品，88%的农民将农资经销商确定为其主要信息来源。这些发现表明，小农户对生物刺激素的使用受到作物价值、农场规模、感知效益、采纳约束、信息渠道和农业系统背景的共同影响。因此，推广适当的生物刺激素使用需要独立的田间示范、针对特定作物的技术指导、更强的产品质量验证，以及能够与经销商网络对接同时确保可靠和公正信息的推广策略。",null,"Frontiers in Sustainable Food Systems","2026-09-10T00:00:00Z","论文",10,false,75,{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":21,"relevant":22,"comment":23},15,22,17,13,8,1,"基于印度两地区193户微观调查，揭示生物刺激素采纳强度受作物价值、农场规模与经销商信息渠道影响，对农资推广与农业绿色转型有参考价值，但属区域性实证研究，公共影响层级有限。",[25],{"name":10,"url":6},[27,28,29,30,31],"农户采纳","小农户","生物刺激素","可持续集约化","农资经销",0,"10.3389\u002Ffsufs.2026.1901923",{"doi":33,"openalex_id":35,"authors":36,"venue":10,"cited_by_count":32,"oa_url":6,"card":48,"direction":52,"ingested_from":54},"W7212195082",[37,40,43,45],{"name":38,"orcid":39},"Dinesh Chand Meena","https:\u002F\u002Forcid.org\u002F0000-0002-4503-5376",{"name":41,"orcid":42},"Pratap S. Birthal","https:\u002F\u002Forcid.org\u002F0000-0002-7287-6269",{"name":44,"orcid":9},"Kiran Kumara TM",{"name":46,"orcid":47},"Iti Sharma","https:\u002F\u002Forcid.org\u002F0000-0001-7508-4606",{"tldr":49,"method":50,"finding":51,"direction":52,"opportunity":53},"基于印度两县193户农户调查，分析生物刺激素采用强度及其影响因素。","对193户有经验农户调查，用分数logit模型分析采用强度。","生物刺激素用于三分之二耕地，作物选择性强，市场导向和认知正向影响采用强度。","数字乡村与农业信息化","可研究经销商网络与品牌认知对农户采用新型农资的影响，及数字化信息渠道的替代作用。","openalex","2026-09-11T23:30:08.518376Z"]