Modeling Associations Between Intensification Interventions And Sustainability In Smallholder Dairy Farms In The Kenyan Highlands

ABSTRACT

Increased herd productivity and incomes can be obtained with the intensification of smallholder dairy production when applying genetics, ecological and socio-economic interventions. However, intensification can also result in negative externalities including depletion of natural resources, land use changes and human health risks. This study evaluated the association of intensification interventions with herd productivity, natural resource depletion and human health risks using a set of indicator variables. Data were from a sample of 140 smallholder dairy farms in two Counties (Kiambu and Meru) benefitting from the Kenya Market Led Dairy Program. Analysis proceeded in two stages. Firstly, Principle Component Analysis (PCA) to select indicator variables for second stage regression analysis to select optimal models which quantified the contributions of each intervention to externalities. The indicator variables of herd productivity selected in PCA were milk yield (10 litres per cow/day) and margins per litre of milk (Kenya Shilling 4.2), which represent positive externalities of intensification. In the optimal model, socio-economic interventions (concentrate use, credit uptake and milk sales) had greater contribution to variations in both milk yield and margins earned compared to genetic (insemination costs) or ecological (manure recycled) interventions. The indicator variable of natural resource depletion of significance was the volume of drinking and service water on the farms (5.1 litres/ Kg of milk produced), which represent negative externality. The variations in water use were higher from socio-economic interventions (milk sales) than was from ecological intervention (manure recycling), and suggested that depletion of water would increase with sale of more milk and recycling of more manure on the farm. The indicator variable significant for human health risks was the volume of milk rejected (7.7 Kg/month), representing negative externality, but the optimal regression model had very low explanatory power (8.3%) and still, the socio-economic intervention had the largest contribution to explained variation. Results indicated that the volume of milk rejected would increase with sale of more milk, but decrease when feeding more concentrates and recycling more manure on the farm. Results imply that greater attention to socio-economic interventions is important in dairy intensification process, but require continuous monitoring to provide early warning about negative externalities that emerge.