Unfolding Factors Influencing Pineapple Production: Evidence From Bagamoyo In Tanzania

This paper examined factors that influence pineapple production in Bagamoyo using cross-sectional data collected during the harvesting season of 2023/2024. A sample of 150 smallholder pineapple farmers was randomly selected using a systematic random sampling procedure. We used the Ordinary Least Squares with a Cobb- Douglas function to estimate the parameters after log- linearize the Cobb- Douglas function. The coefficient of determination 𝑅 ଶ = 0.81 showed that the explanatory variables were fit for the model as 81% of the variation in the production of pineapples is explained by the selected seven factors. Further results revealed that out of the seven predictors, labour, age and farming experience were statistically significant ( p-values: 0.000, 0.003 and 0.000) respectively, all of which the p-value was less than a 5 per cent level of significance. The other variables namely education level, soil quality, technology use and farm size were insignificantly explaining pineapple production. We conclude that labour (family and hired), age and farming experience are positively correlated to the quantity of pineapple production. We recommend that the policy on agriculture should insist on the provision of extension services to be offered timely to ensure quality yield for both local consumption as well as exports. Encouraging exports through promotion to address the challenge of untapped potential for exports of the pineapple which in turn encourages production and lastly, investment in agricultural research would steer up the need for further research into pineapple seed breeding, pest control and post-harvest technology. Such initiatives would promote crop production and thereby improve the livelihood of the smallholder farmers.