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First experiences with a novel farmer citizen science approach: crowdsourcing participatory variety selection through on-farm triadic comparisons of technologies (TRICOT)

机译:首次体验新农民公民科学方法:通过农场三元技术比较(TRICOT)众包参与式多样性选择

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摘要

Rapid climatic and socio-economic changes challenge current agricultural R&D capacity. The necessary quantum leap in knowledge generation should build on the innovation capacity of farmers themselves. A novel citizen science methodology, triadic comparisons of technologies or tricot, was implemented in pilot studies in India, East Africa, and Central America. The methodology involves distributing a pool of agricultural technologies in different combinations of three to individual farmers who observe these technologies under farm conditions and compare their performance. Since the combinations of three technologies overlap, statistical methods can piece together the overall performance ranking of the complete pool of technologies. The tricot approach affords wide scaling, as the distribution of trial packages and instruction sessions is relatively easy to execute, farmers do not need to be organized in collaborative groups, and feedback is easy to collect, even by phone. The tricot approach provides interpretable, meaningful results and was widely accepted by farmers. The methodology underwent improvement in data input formats. A number of methodological issues remain: integrating environmental analysis, capturing gender-specific differences, stimulating farmers' motivation, and supporting implementation with an integrated digital platform. Future studies should apply the tricot approach to a wider range of technologies, quantify its potential contribution to climate adaptation, and embed the approach in appropriate institutions and business models, empowering participants and democratizing science.
机译:快速的气候和社会经济变化挑战了当前的农业研发能力。知识创造中必不可少的飞跃应该建立在农民自身的创新能力上。在印度,东非和中美洲的试点研究中,采用了一种新颖的公民科学方法,即对技术或经编的三重比较。该方法涉及向个体农民分配以三种不同组合的一组农业技术,这些农民在农场条件下观察这些技术并比较其绩效。由于三种技术的组合重叠,因此统计方法可以将整个技术库的整体性能排名汇总在一起。特里科特方法可提供广泛的应用范围,因为分发试用包和指导课程相对容易,农民无需组织协作小组,并且即使通过电话也很容易收集反馈。特里科特方法提供了可解释的,有意义的结果,并被农民广泛接受。该方法在数据输入格式上得到了改进。仍然存在许多方法学问题:整合环境分析,捕捉性别差异,激发农民的积极性以及通过整合的数字平台支持实施。未来的研究应将Tricot方法应用于更广泛的技术,量化其对气候适应的潜在贡献,并将该方法嵌入适当的机构和商业模型中,以增强参与者的能力并使科学民主化。

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