Location: Coastal Plain Soil, Water and Plant Conservation Research
Title: Food security and agricultural challenges in West African rural communities: a machine learning analysisAuthor
AHN, JAEHYUN - Texas A&M University | |
BRIERS, GARY - Texas A&M University | |
BAKER, MATHEW - Texas A&M University | |
PRICE, EDWIN - Texas A&M University | |
Sohoulande, Clement | |
STRONG, ROBERT - Texas A&M University | |
PIÑA, MANUEL - Texas A&M University | |
KIBRIYA, SHAHRIAR - Texas A&M University |
Submitted to: International Journal of Food Properties
Publication Type: Peer Reviewed Journal Publication Acceptance Date: 4/9/2022 Publication Date: 4/17/2022 Citation: Ahn, J., Briers, G., Baker, M., Price, E., Sohoulande Djebou, D.C., Strong, R., Piña, M., Kibriya, S. 2022. Food security and agricultural challenges in West African rural communities: a machine learning analysis. International Journal of Food Properties. 25:827-844. https://doi.org/10.1080/10942912.2022.2066124. DOI: https://doi.org/10.1080/10942912.2022.2066124 Interpretive Summary: This article investigated household-level food security for Ghana, Liberia, and Senegal. Different agroclimatic, ecological, social, and farming conditions in West Africa were represented. The study used a machine learning approach to classify 644 Ghanaian, 323 Liberian, and 510 Senegalese households for comparison and interpretation on food security. Results for Liberia and Senegal imply community support, diverse selling channels outside villages, resolving the dispute over farmland, and increasing community-level investment for food availability and access demonstrate household food security. Results for Ghana highlighted the role of independent producers and food suppliers toward stability. Household food security or insecurity was distinguished by location-specific and gender-led households in Liberia and Senegal. Practically, the results presented a need to step-up agricultural education and extension based on an empirical field survey and its interpretations. The results can add considerations to the role of farming households as independent and individual suppliers and consumers to long-standing dimensions of food security, i.e., food availability, access, and stability. Technical Abstract: This article investigated household-level food security for Ghana, Liberia, and Senegal. Different agroclimatic, ecological, social, and farming conditions in West Africa were represented. Using data-driven Random Forest and Chi-Square Automatic Interaction Detection (CHAID) decision tree methodology, this study classified 644 Ghanaian, 323 Liberian, and 510 Senegalese households for comparison and interpretation on food security. The predictors growing Liberian and Senegalese decision trees imply community support, diverse selling channels outside villages, resolving the dispute over farmland, and increasing community-level investment for food availability and access demonstrate household food security. Predictor importance on food security for Ghana highlighted the role of independent producers and food suppliers toward stability. Household food security or insecurity was distinguished by location-specific and gender-led households in Liberia and Senegal. Practically, the results presented a need to step-up agricultural education and extension based on an empirical field survey and its interpretations. The results can add considerations to the role of farming households as independent and individual suppliers and consumers to long-standing dimensions of food security, i.e., food availability, access, and stability. |