Gamification of farmer-participatory priority setting in plant breeding: Design and validation of “AgroDuos”

Date Issued
2017-05Date Online
2017-04Language
enType
Journal ArticleReview status
Peer ReviewAccessibility
Open AccessUsage rights
CC-BY-NC-ND-4.0Metadata
Show full item recordCitation
Steinke J, van Etten J. 2017. Gamification of farmerparticipatory priority setting in plant breeding: Design and validation of “AgroDuos”. Journal of Crop Improvement 31(3): 356-378
Permanent link to cite or share this item: https://hdl.handle.net/10568/80943
Abstract/Description
Participatory methods to characterize farmers’ needs and preferences play an important role in plant breeding to ensure that new varieties fulfill the needs and expectations of end users. Different farmer-participatory methods for priority setting exist, each one responding differently to trade-offs between various requirements, such as replicability, simplicity, or granularity of the results. All available methods, however, require training, academic skill, and staff time of specially qualified professionals. Breeding and variety replacement may be accelerated by empowering non-academic organizations, such as NGOs and farmer organizations, to carry out farmer-participatory priority setting. But for this use context, currently no suitable method is available. A new method is needed that demands relatively low skill levels from enumerators and respondents, engages farmers without the need for extrinsic incentives, and gives statistically robust results. To achieve these objectives, we followed principles of “gamification” in the design of AgroDuos, a choice experiment that resembles a card game and that involves pairwise ranking of variety traits. We tested the method in a pilot with 39 farmers in Honduras to define their trait priorities for common bean (Phaseolus vulgaris L.). To validate our results, we independently carried out conjoint analysis, an established method for priority setting in plant breeding. We found that AgroDuos produced valid and useful results while enabling rapid, easy, and engaging data collection. Challenges persist concerning local adaptation and data analysis by non-specialist staff, which may be resolved in the future by providing templates and online support.
CGIAR Author ORCID iDs
Jacob van Ettenhttps://orcid.org/0000-0001-7554-2558
