Comparing the Performance of Automatic Milking Systems through Dynamic Testing Also Helps to Identify Potential Risk Factors for Mastitis.

Simple Summary: The performance of milking machines, whether in conventional or automated systems, can be evaluated using new-generation vacuum meters (dynamic testing). Access to data from these tests on automatic milking systems (AMSs) from various manufacturers and herds enabled the design of a retrospective study aimed at describing and comparing key milk emission parameters for different AMS brands, while also identifying potential mastitis risk factors. In total, 4878 individual quarter milkings were evaluated from cows in 48 different dairy herds. The findings revealed that factors such as milk yield and brand significantly influenced the variability of milking parameters. These results suggest that the interaction between AMSs and cows, along with the related milk emission physiology, plays a crucial role, similar to conventional milking. The observed differences in main milking parameters also correspond to parameters considered to predispose cows to mastitis. The most surprising result was the high frequency of two major mastitis risk factors (bimodality and irregular vacuum fluctuations). Automatic milking systems (AMSs) are revolutionizing the dairy industry by boosting herd efficiency, primarily through an increased milk yield per cow and reduced labor costs. The performance of milking machines, whether traditional or automated, can be evaluated using advanced vacuum meters through dynamic testing. This process involves scrutinizing the system and milking routine to identify critical points, utilizing the VaDia™ logger (BioControl AS, Rakkestad, Norway). Vacuum recordings were downloaded and analyzed using the VaDia Suite™ software under the guidance of a milking specialist. Access to data from AMSs across various manufacturers and herds facilitated a retrospective study aimed at describing and comparing key milk emission parameters for different AMS brands while identifying potential mastitis risk factors. Using the proper statistical procedures of SPSS 29.1 (IBM Corp., Armonk, NY, USA), researchers analyzed data from 4878 individual quarter milkings from cows in 48 dairy herds. Results indicated a significant variability in milking parameters associated with quarter milk yield and AMS brand. Notably, despite AMSs standardizing teat preparation and stimulation, this study revealed a surprisingly high frequency of two major mastitis risk factors—bimodality and irregular vacuum fluctuations—occurring more frequently than in conventional milking systems. This study, one of the few comparing different AMS brands and their performance, highlights the crucial role of dynamic testing in evaluating AMS performance under real-world conditions. [ABSTRACT FROM AUTHOR]