Determinants of Farm Machinery Adoption Among Small-Scale Farmers: A Statistical Case Study from Borno State, Nigeria

Abstract

This study aimed to analyze the rate and determinants of farm machinery adoption among smallscale farmers using both descriptive and inferential statistical techniques. The study revealed that only 46% of respondents had adopted at least one form of farm machinery. Education level, farm size, access to credit, and extension services were statistically significant predictors of machinery adoption. A logistic regression model indicated that access to credit increases the likelihood of adoption by 17.1%, while an additional hectare of land increases the odds by 19.6%. The ROC curve had an AUC of 0.82, showing that the model had strong classification accuracy. The correlation matrix showed positive and significant relationships between machinery use and all other independent variables. Regional disparities in adoption rates were also significant (ANOVA, p < 0.01), suggesting location-specific factors influence adoption behavior among 200 small-scale farmers in Biu, Borno State.