The accuracy of farmer-generated data in an agricultural citizen science methodology

This study tests whether farmer-generated data in agricultural citizen science are good enough to generate valid statements about the research topic. They assess the accuracy of farmer observations in trials of crowdsourced crop variety selection that use triadic comparisons of technologies (tricot). At five sites in Honduras, 35 farmers (women and men) participated in tricot experiments. They ranked three varieties of common bean (Phaseolus vulgaris L.) for Plant vigor, Plant architecture, Pest resistance, and Disease resistance. Their sample size simulation shows that low reliability can be compensated by engaging higher numbers of observers to generate statistically meaningful results, demonstrating the usefulness of the Wisdom of Crowds principle in agricultural research. This first study on data quality from a farmer citizen science methodology shows that realistic numbers of less than 200 participants can produce meaningful results for agricultural research by tricot-style trials.