Many smallholder farmers produce maize for both consumption and income purposes. Despite the role played by maize, its income production is low, especially in developing countries. In order to formulate policies targeting maize productivity, it was necessary to have knowledge of the determinants of maize production income. As such, this study aimed at determining the level of income and its determinants from maize farmers. Consequently, data was collected from 220 maize farmers using structured questionnaires. The ordinary least squares model was used to determine the determinants. The results showed that the farmers earned a mean of 372,207 Ugandan shillings (105.18 USD) from maize production. Accordingly, farm size, access to credit and household size had a significant positive influence on income from maize production, while gender (female) of the household heads had a significant negative relationship with income from maize production. It is based on these results that this study recommended that the government should offer training programs targeting female-headed households. These trainings should incorporate farm production as well as marketing. Additionally, farmers should be encouraged to access various sources of agricultural credit including financial institutions that offer agricultural loans at low-interest rates.

This study aimed at analyzing technical efficiency and its determinants among tobacco producers in Uganda. To achieve this, primary data were drawn from 200 tobacco farmers using semi-structured questionnaires. In order to determine the technical efficiency and its determinants, Data envelopment analysis and Tobit regression model were used for the analysis respectively. From the results, we observed that the mean TE was 49%, implying that the farmers were 51% inefficient. Furthermore, input prices, land size, farmers’ age, farm income and farm location were found to be the determinants of technical efficiency. This study recommended that the government should subsidize farm inputs as well as training the farmers on input combinations in order to increase technical efficiency level. Int. J. Agril. Res. Innov. Tech. 12(1): 24-29, June 2022