Implementation of Automated Premilking Stimulation on NYS Dairy Farms
Principal Investigator: Matthias Wieland
Co-PI: Daryl Nydam
DESCRIPTION (provided by applicant):
This study will evaluate and implement automated premilking stimulation (APS) systems on NYS dairy farms. Optimal premilking stimulation is paramount to harvest high quality milk while maintaining udder health. Traditionally, stimulation has been achieved through manual milk stripping in a labor intense process. Automated premilking stimulation systems offer unique opportunities to automate the milk harvesting process and have the potential to decrease labor costs and alleviate labor challenges. In this study, we will test if the important effects of the physiology of milk letdown are achievable by automation rather than by human labor. First, we will enroll 700 cows from a NYS dairy in a controlled trial. Cows will be randomly allocated to either manual or automated premilking stimulation. Data on milk production, milk flow parameters, teat tissue condition, and udder health will be collected over the 4-month study period. We will use statistical models to compare the efficiency of APS with traditional manual stimulation to demonstrate if APS is an equivalent method to stimulate cows at milking without compromising production parameters, teat condition, or udder health. Second, based on the results of the initial farm, we will validate the efficiency of APS with different systems represented by 5 additional farms. Thereafter we will develop educational materials to make this technical solution available for use on similar farms across NYS via a series of outreach meetings.