Optimal Farm Enterprise Mix And Threshold Dietary Requierements For Smallholder Farmers In Semi-Arid Chamwino District, Dodoma-Tanzania

ABSTRACT

Malnutrition is among the serious health problems affecting infants, children and women of reproductive age in Tanzania. Various approaches have been adopted to address this problem. Such approaches include; importation of food, food aid and medical treatment. Despite these efforts, however, millions of Tanzanians particularly women and children continue to suffer from one or more forms of malnutrition. Agriculture has been currently taken as great measure to harness malnutrition among developing countries including Tanzania, whereas recently new attention has been given to the role of agriculture in nutrition and malnutrition. The study was conducted to determine an optimal farm enterprise mix that uses available resources to maximize profit while ensuring adequate supply of food to meet household’s macro-nutrient requirements. The study used cross sectional data from 300 farming households from two villages of Chinoje and Mzula in Chamwino District in Dodoma region of central Tanzania. A static linear programming (LP) model was used to determine optimal farm enterprise mix and threshold dietary requirements for smallholder farming households. The findings indicate that the optimal enterprise mix that maximizes profit while meeting adequate macro-nutrient food needs of the households entails a combination of 2.40 acres of millet, 0.75 acres of sunflower, 3.65 acres of groundnuts and at least 16 chickens. This nutrition sensitive optimal resource combination enables the farming household to attain global optimal solution of TZS 1 383 878. It could be concluded that with the current average farm production, most of the farming households were unable to satisfy their household food needs from farm production. In this regard, the study recommends for optimal combination of available resources to meet minimal macro-nutrient requirements while generating an optimal level of farm income.