Sampling for Socially‐Inclusive Adoption Studies (SSAS): A new interdisciplinary sampling method for DNA‐fingerprinting‐based crop varietal adoption studies
Yoselyn Hernandez Chaves, Luis A. Sanchez Chacon, Martina Occelli, Sergio Puerto, Ruth Castro‐Vásquez, Bethany F. Econopouly, Joyce Estrada‐Gamboa, Erica Lopez, Vanessa Mora, Deborah Rubin, Kelly R. Robbins, Roberto Camacho, Hale A. TufanSocietal Impact Statement
DNA fingerprinting is becoming the standard measurement procedure in crop adoption studies in the Global South, yet the lack of systematic and intentional sampling regarding which farmer to go to the plot with may bias results from these methods. We introduce a methodological innovation, Sampling for Socially Inclusive Adoption Studies (SSAS), to offer a more inclusive sampling strategy. We find that SSAS enables research around how respondent socio‐demographic differences, respondent selection approaches, and intra‐household dynamics shape DNA fingerprinting‐based adoption studies. SSAS can serve as a tool for more participatory, nuanced, and context‐sensitive research design for these studies.
Summary
The lack of intentional sampling of farmers may explain the disconnect between genomic and self‐reported data in DNA fingerprinting‐based crop varietal adoption studies. We introduce a methodological innovation, Sampling for Socially Inclusive Adoption Studies (SSAS), that interlinks socio‐demographic information, a measurement of the information endowment of a respondent, intra‐household decision making, and plot level DNA fingerprinting sampling. SSAS comprises two main parts; the first is an intra‐household survey, administered to two individual adult decision makers within a farming household, which generates an estimate of their knowledge of the crop studied to determine who will be engaged for leaf tissue sampling. The second part is collecting leaf tissue in the field with the chosen respondent. We piloted the SSAS method with a small set of common bean growers in Costa Rica. The pilot data showed that application of SSAS generated data that would guide breeding programs to identify respondents for DNA fingerprinting studies and relate their results to decision making dynamics and household headship within households. To our knowledge, this is the first DNA fingerprinting approach to be developed and piloted directly by a National Agricultural Research Institution. We provide practical guidance for applying SSAS in resource‐constrained institutions and offer a path forward for wider adoption of DNA fingerprinting methods. SSAS is a tool for exploring broader dynamics of knowledge, networks, intrahousehold dynamics, and inequality within agricultural production, opening up entry points for more participatory, nuanced, and context‐sensitive research design.