Optimization of The Milk Harvesting Process Through Automation and Data Integration

Adequate udder stimulation of dairy cows before milking is critical for the harvest of high-quality milk, traditionally achieved through milk stripping by hand. To date, dairy operations apply a fixed pre-milking stimulation regimen to all cows, irrespective of their physiological needs. This results in delayed milk ejection (DME) in approx. 25% of cows on New York State dairies. Delayed milk ejection leads to poor milking efficiency, impaired teat and udder health, and reduced milk yield. We estimate that DME results in an income loss of approx. $250,000/year on a 1,000-cow dairy. Accommodating the physiological requirements of individual cows in a precision dairy farming system is of utmost importance to optimal milk harvest and animal well-being. To achieve this, a new dimension for automated identification of cows with DME and providing them with additional pre-milking stimulation using automated pre-milking stimulation (APS) systems is critical.

Leave a Reply

Your email address will not be published. Required fields are marked *

Become a Fellow

Join the Cornell Institute for Digital Agriculture and become a participating member in advancing research, thought, policy and practice to advance the field of digital agriculture and help build stronger, more resilient agri-food systems.

Stay up to Date

Receive our newsletter for announcements of events, opportunities, digital ag news, Cornell news, and more.

CIDA - Cornell Institute for Digital Agriculture

If you have a disability and are having trouble accessing information on this website or need materials in an alternate format, contact [email protected] for assistance.


CIDA Copyright 2023 | CIDA is an equal opportunity employer | Terms of Use | Privacy Policy