Farmers’ knowledge and perceptions of Cassava (Manihot esculenta Crantz) diseases and management

Abstract

This study aimed to examine farmers’ understanding and views on Cassava diseases and control methods. To achieve the former, k-means clustering and Principal Component Analysis (PCA) were used to identify and visualize response patterns for each group of variables relating to farmers’ understanding of Cassava diseases and control methods, and heatmaps were used to detail the characteristics of each pattern. To achieve the latter, bar plots were used to visualize variables related to farmers’ views. Out of 22 response patterns relating to causes of Cassava Mosaic Disease (CMD), 11 didn’t link a virus to CMD symptoms, while only one pattern associated CMD symptoms with a virus, the whitefly, and infected cuttings, indicating a lack of farmers’ knowledge on cassava viral diseases. Also, only 18.88% of farmers know about Cassava diseases and management technologies. This study highlights the urgent need for education and resources for farmers to safeguard their crops and livelihoods.