five

Data_Sheet_1_Consumer Preference Testing of Boiled Sweetpotato Using Crowdsourced Citizen Science in Ghana and Uganda.docx

收藏
NIAID Data Ecosystem2026-03-12 收录
下载链接:
https://figshare.com/articles/dataset/Data_Sheet_1_Consumer_Preference_Testing_of_Boiled_Sweetpotato_Using_Crowdsourced_Citizen_Science_in_Ghana_and_Uganda_docx/13705906
下载链接
链接失效反馈
官方服务:
资源简介:
Crowdsourced citizen science is an emerging approach in plant sciences. The triadic comparison of technologies (tricot) approach has been successfully utilized by demand-led breeding programmes to identify varieties for dissemination suited to specific geographic and climatic regions. An important feature of this approach is the independent way in which farmers individually evaluate the varieties on their own farms as “citizen scientists.” In this study, we adapted this approach to evaluate consumer preferences to boiled sweetpotato [Ipomoea batatas (L.) Lam] roots of 21 advanced breeding materials and varieties in Ghana and 6 released varieties in Uganda. We were specifically interested in evaluating if a more independent style of evaluation (home tasting) would produce results comparable to an approach that involves control over preparation (centralized tasting). We compiled data from 1,433 participants who individually contributed to a home tasting (de-centralized) and a centralized tasting trial in Ghana and Uganda, evaluating overall acceptability, and indicating the reasons for their preferences. Geographic factors showed important contribution to define consumers' preference to boiled sweetpotato genotypes. Home and centralized tasting approaches gave similar rankings for overall acceptability, which was strongly correlated to taste. In both Ghana and Uganda, it was possible to robustly identify superior sweetpotato genotypes from consumers' perspectives. Our results indicate that the tricot approach can be successfully applied to consumer preference studies.
创建时间:
2021-02-03
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作