According to whom? Spousal, household, and plot differences in improved cassava variety adoption in Nigeria

Societal Impact Statement Agricultural innovations underpin most investments that aim to increase agricultural productivity globally. Improved crop varieties have historically constituted the bulwark of agricultural innovation outputs and are credited with the success of large‐scale interventions such as the Green Revolution. Much research has shown, however, that gender shapes agricultural technology adoption, increasingly understood in relation to the age, race, and ethnicity of the respondent. Our study shows how decisions made by researchers when designing crop varietal adoption studies, including who in a farming household is asked and how they are asked about adoption, significantly shape reported adoption rates, highlighting potential errors in reported crop varietal adoption rates. Summary Accurately measuring agricultural technology adoption rates underpins impact claims made for new technologies. While numerous studies have documented gender‐based differences in the adoption of agricultural technologies, there remains an urgent need to understand how study design and respondent selection within households shape these reported differences. We explore the case of improved cassava varieties (ICV) in Nigeria to examine differences in reporting on varietal adoption rates based on sampling method, level of analysis, and household position. We compare intrahousehold (spousal), household, and plot‐level data for self‐reported rates of ICV adoption and compare these to data from DNA fingerprinting. We identify significant disparities in reported rates of ICV adoption at the household, spousal, and plot levels, most of which were different from DNA fingerprinting data collected from respondents' plots. Our findings shed light on the importance of participant selection in varietal adoption studies and raise questions around self‐reported adoption rates in the literature. Varietal adoption rates are used to measure a breeding program's success and impact. However, this study shows that estimated rates can differ significantly depending on adoption study design–including unit of analysis, selection of data source, and how the questions are asked. We call for more data feminism around crop varietal adoption studies, study designs that minimize bias, expanded design standards to include multiple respondents within each household, and multiple data analysis methods that reflect the plurality of experiences with adoption among farmers.