Use of lactation models to develop a cow performance monitoring tool in smallholder dairy farms
Animal performance monitoring is of enormous value for management decision-making at the individual farmer level as well as for the industry and country as a whole. The aim of the study was to develop a performance monitoring tool for existing smallholder dairy production system based on lactation curves. For this purpose three equations of Wood (1967), critical exponential and double exponential were compared to evaluate their fitting and prediction ability. The full data set comprised of 11481 daily milk records for Holstein-Friesian in various stages of lactation. Data of 84 Holstein-Friesian cows was used to develop lactation curves. Within each lactation, only milk yield from calving until 330 days post-calving were used. The three models were evaluated using three criteria which were the amount of variation accounted for by the model (coefficient of determination), b-value and distribution of residuals. Based on these criteria, the double exponential equation was selected for developing the cow performance monitoring (CPM) curve. The CPM curve was developed based on the mean lactation curve with its confidence interval generating the upper and lower limits. The CPM curve had high prediction rates (sensitivity=93% and specificity=93%) hence efficient enough to guide routine management of dairy animals in smallholder farms.