Investigations into the applications and impacts of automation in pasture-based dairy systems

Abstract

Feed and labour together account for between 50 to 75% of the dairy farm costs in pasture-based systems. Optimised grazing management through remote (satellite-based) monitoring of pastures can potentially reduce feed costs, whereas automatic milking systems (AMS) can potentially reduce labour requirements by automating the whole milking process. The overarching objective of this thesis was to identify the limitations to the uptake of these technologies and explore opportunities to make them more efficient and productive. The literature review in Chapter 2 highlighted that low accuracy in the estimations and lack of calibration methods as key issues for remote sensing for grazing management. These issues were addressed in Chapter 3 and Chapter 4 by developing a novel approach that combines high-resolution satellite imagery calibrated with a rising plate meter. Chapter 2 also identified that the low adoption of AMS could be explained by a performance that does not justify the higher capital investment compared to conventional systems (CMS). A comprehensive world’s first research that used data from commercial farms from Australia (Chapter 5) showed that overall, AMS and CMS could achieve similar economic and physical performance. Subsequent investigation within AMS using data from Australia and overseas (Chapter 6) showed that milk harvested/robot, total labour on-farm, and cows/robot were the main factors associated with productivity and profitability in AMS. These findings were used to develop the world-first decision-support system (https://bit.ly/MilkingEdgeAMSTool) available for pasture-based AMS (Chapter 7) that helps farmers considering or operating AMS to better assess their performance and the physical and economic impact of different AMS strategies. In summary, this thesis significantly improves the state of knowledge and understanding of remote sensing and AMS and provides methodologies and tools to make them more efficient and productive.