New technologies have become available in recent years to improve reproductive success. These technologies include improvements to traditional approaches to reproductive management (heat detection and AI) as well as to approaches that synchronize AI so that all cows and/or heifers are inseminated at one time (timed-AI programs).
Combinations of traditional and timed-AI programs also are used on many farms. Regardless of the approach, a focused effort on reproductive management has been shown to increase pregnancy rates, translating to greater reproductive efficiency on the dairy.
Synchronization protocols evolve rapidly as newer procedures are tested and improvements are made. To help dairy producers, veterinarians and industry professionals deal with rapid change and make informed decisions related to synchronization protocols, the Dairy Cattle Reproduction Council (DCRC) has created synchronization protocol sheets for dairy cows and dairy heifers. The documents outline established synchronization protocols that may help dairy producers improve on-farm reproductive performance.
The protocol sheets were developed by an ad-hoc committee of scientists and veterinarians at academic institutions. Members of the original committee included Matt Lucy (University of Missouri), Ricardo Chebel (University of Minnesota), Paul Fricke (University of Wisconsin), Joe Dalton (University of Idaho) and Scott Poock (University of Missouri). A large number of dairy professionals, veterinarians and scientists also evaluated and helped revise the information.
This document is intended for educational purposes as consultants work with their dairy producer clients to make reproductive management decisions. The DCRC does not endorse one protocol over another, nor does DCRC endorse synchronization protocols over any of the other approaches to dairy cattle reproduction. The protocol sheets will be reviewed annually by representatives from the DCRC. New protocols will be included when they are validated in controlled studies.
Source – Dairy Herd