Economics of peri-urban zero-grazing in Uganda: the case of Mpigi district
This study was conducted using 73 zero-grazing farm units selected randomly in the environs of Kampala City. It aimed at (I) describing the socio-economic characteristics of zerograzing farmers in the area; (2) identifying their production constraints; (3) estimating variable cost components of zero-grazing and (4) assessing the economic viability of zero-grazing enterprises in semi-urbanised environments. Cross sectional data collected on structured questionnaire was used. Descriptive statistics, analysis of variance (ANOVA), gross margin calculations and Linear regression were utilised to analyze the data. Descriptive statistics provided the mean estimated values of inputs and outputs used by individual study farms. Gross margins gave a measure of the - returns to fanners' fixed capital, management and risk. The ANDVA determined whether the established value differences were statistically significant. Linear regression in a causal relationship identified variable farm level factors that explained the significant differences. Constraints identified by farmers through score board ranking were as follows: Labour requirements (17.0%), Marketing of milk (15.0%), Cost of inputs: Concentrates (12.6%), livestock diseases (12.0%), poor milk yield (11.7%), Periodic fodder shortage (9.0%), Veterinary extension services (9.0%), poor reproductive performance (7.2%), water shortage (2.7%), credit facilities (1.3%), in security oflivestock (1.3%), and manure disposal (0.9%). The provision of concentrate feeds at 35.1 percent of the total variable costs was found to be the biggest farm variable cost component. This was followed by labour at 28.3 percent, forage at 16.8 percent, animal health at 13.4 percent and routine farm services at 6.4 percent. Dairy enterprise gross margins per year were established to range from Ush. -314,214 to Ush. 5,600,026, with a mean of Ush. 1,493,259 (±752,900). Altogether there were fifty-seven farms (80%) with positive gross margins. ANOYA indicated that hTfOSS margins significantly differed depending on farmers' access to off-farm sources of income (p=0.005), type of acaricide used on the farm (p=0.009), farmers' education standard (p=0.014), initial source of capital (p=0.028), and distance of the farm from the urban centre (p=0.034). Enterprise hTfOSS margins were, however, not significantly different (p>0.05) for sex of the farm owner, breeding method used by the farm, method of manure disposal, land tenure systems, farmers' experience, herd sizes, family size, farm area(s) under forage, total number of milking cows on the farm, farm mean lactation length, labour input in man-hours, and the farm mean daily milk yields. Modelling revealed that profit (EGM) for a given farm was dependant upon the volume of milk produced per lactating cow per day (p<O.OO1), milk prices (p<O.OOI), number of lactating cows on the farm (p=O.OOI),market channel used to sell offrnilk (p=O.013), distance of farm from urban centre (p=0.019) and whether farmer used home grown forages or not (p<O.OOI). The study concluded that zero-grazing was a profitable farm enterprise (EGM>O) for farmers dwelling in the study area. a possibility of farmers to in crease their profit margins was also established. It is recommended that farmers in peri-urban areas should take up zero-grazing as an alternative source of household income.