Investigations into system and cow performance efficiency in pasture-based automatic milking systems

Abstract

Although previous research has demonstrated that AMS can be successfully integrated with pasture-based systems, performance and efficiency levels observed in pasture-based AMS present greater variability and are lower in comparison to indoor AMS. Therefore, the general aim of this thesis was to identify strategies on how to improve system performance in pasture-based AMS operating with voluntary traffic. The literature review explored the current situation in regards to system and cow performance on pasture-based AMS. Gaps in knowledge and potential ways of increasing productivity were identified. The demonstrated effect that the number of cows milked per robot had a greater effect than milking frequency on robot performance (Chapter 3), together with the high degree of variability regarding individual cow performance (Chapter 2), led to developing a methodology to identify Efficient and Inefficient cows based on their combined effect of milking frequency and milk yield (Chapter 4). The hypothesis that differences in cow behaviour could explain, at least in part, the differences observed between levels of efficiency in cow performance was confirmed after a field study was conducted for that purpose (Chapter 6). A validation of a recently commercially released version of an activity and rumination monitoring system was conducted (Chapter 5) to allow differences in cow behaviour to be determined. The potential to manipulate robot utilisation at whole herd level was then explored in Chapter 7, in which the results of a field study conducted to evaluate if experienced cows could quickly adapt to a short period of voluntary-batch milking, without cow performance being affected, were summarised. In summary this thesis makes a significant contribution based on novel, original, and scientifically-generated knowledge, that together, will help to advance systems and cow performance and efficiency on pasture-based AMS in the future.