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Participatory Varietal Selection×Mother-Baby Trial Design×
FieldFood Agriculture StudiesFood Agriculture Studies
FamilyProcess / pipelineProcess / pipeline
Year of origin19962002
OriginatorJohn R. Witcombe and colleaguesSieglinde Snapp
TypeParticipatory experimental pipeline for cultivar identificationLinked on-farm experimental design pairing replicated and dispersed trials
Seminal sourceWitcombe, J. R., Joshi, A., Joshi, K. D., & Sthapit, B. R. (1996). Farmer Participatory Crop Improvement. I. Varietal Selection and Breeding Methods and Their Impact on Biodiversity. Experimental Agriculture, 32(4), 445-460. DOI ↗Snapp, S. (2002). Quantifying Farmer Evaluation of Technologies: The Mother and Baby Trial Design. In M. R. Bellon & J. Reeves (Eds.), Quantitative Analysis of Data from Participatory Methods in Plant Breeding (pp. 9-17). Mexico, DF: CIMMYT. link ↗
AliasesPVS, Farmer Participatory Variety Selection, Participatory Variety Selection, Client-Oriented Varietal SelectionMother and Baby Trial Design, MBT Design, Mother-Baby Trial Approach, Mother-Baby On-Farm Trials
Related44
SummaryParticipatory varietal selection (PVS) is a participatory crop-improvement method in which farmers choose, grow, and evaluate finished or near-finished cultivars on their own fields under their own management, so that the varieties identified are the ones farmers actually prefer and will adopt. Formalized by John Witcombe and colleagues in 1996 as the faster, cheaper sibling of participatory plant breeding, PVS responds to the problem that conventional varietal release — selection on research stations against breeder criteria — often produces varieties that fail in farmers' fields or ignore traits farmers value, leaving the formal seed system with low adoption in marginal, heterogeneous environments. By moving the final stage of selection onto farms and into farmers' hands, PVS rapidly screens existing genetic material for fitness to real growing conditions and real preferences.The mother-baby trial design is an on-farm experimental architecture, formalized by Sieglinde Snapp in 2002, that resolves the long-standing tension between statistical rigor and wide farmer participation in agricultural research. A small number of replicated 'mother' trials carry the complete set of treatments under good management and provide the controlled, analyzable comparison; surrounding them, a large number of simple 'baby' trials, each on a farmer's own field and each testing only a subset of the treatments against the farmer's usual practice, sample the real variation in conditions and capture farmer evaluation at scale. Linking the two — the mother for precision, the babies for breadth and realism — yields both defensible treatment estimates and credible evidence about how technologies perform and are judged across many real farms.
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