Beyond “Women's Traits”: Exploring How Gender, Social Difference, and Household Characteristics Influence Trait Preferences

Abstract

Demand-led breeding strategies are gaining importance in public sector breeding globally. While borrowing approaches from the private sector, public sector programs remain mainly focused on food security and social impact related outcomes. This necessitates information on specific user groups and their preferences to build targeted customer and product profiles for informed breeding decisions. A variety of studies have identified gendered trait preferences, but do not systematically analyze differences related to or interactions of gender with other social dimensions, household characteristics, and geographic factors. This study integrates 1000minds survey trait trade-off analysis with the Rural Household Multi-Indicator Survey to study cassava trait preferences in Nigeria related to a major food product, gari. Results build on earlier research demonstrating that women prioritize food product quality traits while men prioritize agronomic traits. We show that food product quality traits are more important for members from food insecure households and gender differences between men and women increase among the food insecure. Furthermore, respondents from poorer households prioritize traits similar to respondents in non-poor households but there are notable trait differences between men and women in poor households. Women in female headed household prioritized quality traits more than women living with a spouse. Important regional differences in trait preferences were also observed. In the South East region, where household use of cassava is important, and connection to larger markets is less developed, quality traits and in ground storability were prioritized more than in other states. These results reinforce the importance of recognizing social difference and the heterogeneity among men and women, and how individual and household characteristics interact to reveal trait preference variability. This information can inform trait prioritization and guide development of breeding products that have higher social impact, which may ultimately serve the more vulnerable and align with development goals.