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Improving Crop Variety Recommendations using Citizen Science

Through a farmer citizen science approach, researchers at Bioversity International successfully scaled on-farm crop trials in three countries and improved crop variety recommendations.

Jacob van Etten, Kauê de Sousa, Allan Coto, Brandon Madriz, Carlos F. Quiros, and Jonathan Steinke (Bioversity International) co-authored a new paper on the suitability mapping of crop varieties using information digitally crowdsourced from farmers. Published in PNAS, the study designed on-farm participatory crop trials based on the tricot methodology and successfully developed a unique crop variety performance dataset from 12,409 plots in three countries: Nicaragua, Ethiopia, and India. This dataset was systemically analyzed using the Plackett-Luce tree ranking algorithm to improve crop variety recommendations in each climatic condition.

Abstract

Crop adaptation to climate change requires accelerated crop variety introduction accompanied by recommendations to help farmers match the best variety with their field contexts. Existing approaches to generate these recommendations lack scalability and predictivity in marginal production environments. We tested if crowdsourced citizen science can address this challenge, producing empirical data across geographic space that, in aggregate, can characterize varietal climatic responses. We present the results of 12,409 farmer-managed experimental plots of common bean (Phaseolus vulgaris L.) in Nicaragua, durum wheat (Triticum durum Desf.) in Ethiopia, and bread wheat (Triticum aestivum L.) in India. Farmers collaborated as citizen scientists, each ranking the performance of three varieties randomly assigned from a larger set. We show that the approach can register known specific effects of climate variation on varietal performance. The prediction of variety performance from seasonal climatic variables was generalizable across growing seasons. We show that these analyses can improve crop variety recommendations in four aspects: reduction of climate bias, incorporation of seasonal climate forecasts, risk analysis, and geographic extrapolation. Variety recommendations derived from the citizen science trials led to important differences with previous recommendations.

van Etten, J., de Sousa, K., Aguilar, A., Barrios, M., Coto, A., Dell’Acqua, M., Fadda, C., Gebrehawaryat, Y., van de Gevel, J., Gupta, A. and Kiros, A.Y., 2019. Crop variety management for climate adaptation supported by citizen science. Proceedings of the National Academy of Sciences, p.201813720.

Article: https://doi.org/10.1073/pnas.1813720116
Data: https://doi.org/10.7910/DVN/4ICF6W

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