The Lasting Impact of Calf Performance

Abstract

This thesis explores data-driven decision-making in intensive dairy farming, focusing on calf management's impact on productivity and cattle longevity. It highlights the transformative role of automated calf feeders (ACF) and the need for utilising data generated by ACF for informed decisionmaking. Based on a dataset from a 2,000-cow intensive dairy operation in New South Wales, Australia, the research examines variability in weaning weights (WWT) and proposes early intervention points. Findings reveal associations between early-life events, calf-rearing practices, and future animal productivity. Notably, calves consuming over 30 kg of milk within the first five days are more likely to be weaned at weights over 80 kg. Feeding behaviour and weaning weight are positively correlated, suggesting potential early indicators of calf-rearing performance. Lower performing calves have a reduced likelihood of achieving a second lactation, emphasizing the importance of calf performance on productivity. Additionally, preweaning factors such as birth weight, weaning weight, and days in milk significantly influence cow longevity within the herd. The thesis advocates for a holistic approach to dairy cow management, leveraging technology and researchderived farm practices to improve productivity and sustainability without increasing costs. In conclusion, it underscores the potential of data-driven decision-making and precision technology in shaping the future of intensive dairy farming, aiming to optimise calf growth, minimise calving difficulties, and enhance overall animal welfare and productivity.