Genetic and environmental factors influencing milk, protein and fat yields of pasture-based dairy cows in Tasmania

Abstract

The objective of this study was to provide an update on milk production performance, heritability, genetic and phenotypic correlations among production traits that are valuable for management, breeding and selection decisions in pasture-based dairy systems. The study utilised a total of 106 990 lactation records of Holstein–Friesian (FF), Jersey (JJ) and their crossbreds (HF) from 428 Tasmanian dairy herds collected between 2000 and 2005. The data were analysed using the least-squares approach with a general linear model and restricted maximum likelihood approach with a linear animal model. Results indicated highly significant (P < 0.01) effects of breed, herd size, cow’s parity, season and year of calving on milk, protein and fat yields. Average milk and protein yields per cow per lactation were highest in the FF breed (5212 L and 171 kg, respectively) and lowest in the JJ breed (3713 L and 143 kg, respectively). FF cows also produced 13.5 kg more milk fat than JJ and HF cows. Furthermore, milk, fat and protein yields were highest for cows calving during spring and lowest for autumn-calving cows. It was also evident that cows in very large herds (>1110 cows/herd) outproduced those in smaller herds. Heritability was highest for milk yield and lowest for somatic cell count ranging from 0.28 to 0.41. Genetic and phenotypic correlations between milk, fat and protein yields ranged from 0.41 to 0.85, and 0.66 to 0.92, respectively. However, genetic and phenotypic correlations between the log of somatic cell count and the production traits ranged from 0.03 to 0.09 and –0.03 to –0.05. We conclude that breed, herd size, parity, season and year of calving were among the main factors correlated with the productivity of dairy cows in Tasmania and adjustments for these factors would be mandatory for any unbiased comparison of lactation performance within and between pasture-based dairy production systems. The practical application of this information would be valuable to dairy farmers for decisions related to breeding, selection and management of their herds.