The Babcock Institute University of Wisconsin Dairy Updates

Managers of high producing dairy herds have known for some time that optimizing reproductive efficiency is an essential issue in maintaining profitability of a dairy herd. A recent survey by the University of Wisconsin Center for Dairy Profitability asked a random sample of 2,700 dairy producers in Wisconsin to rank the importance of different dairy issues to the future profitability of their businesses. Herd health and reproduction were ranked as the top priority for future farm profitability out of a 52 possible items. Many of the costs associated with reproduction are readily apparent from a quick glance at the balance sheet, such as semen costs, drug costs, and veterinary fees. Most dairy producers also realize that there are major opportunity costs associated with culling a highproducing dairy cow that does not become pregnant. Other opportunity costs, such as decreased milk production due to excessive days open and decreased genetic progress in replacement heifers, are also costly on a dairy operation although they are difficult to precisely quantify. What determines reproductive efficiency on a dairy operation? There are multitudes of management, physiologic, nutritional, genetic, and disease issues that can dramatically alter reproduction. In this presentation, I will focus on improving reproductive efficiency in lactating dairy cows and will primarily use data from high-producing dairy cattle in the United States. In dairy operations that use artificial insemination (AI), reproductive efficiency depends on how efficiently cows are detected in estrus and serviced (service rate) and fertility to each service (pregnancy rate per AI [PR/AI]). Calculation of these two key rates can help in evaluating current reproductive programs and in designing and monitoring the success of new reproductive programs. In dairy operations with high producing cows, there are a variety of management and physiological factors that are having a serious impact on these two rates and this will be discussed in some detail in the subsequent section. First, it may be useful to discuss mathematically how changes in these two rates can change the dynamics of reproduction in a dairy herd. Figure 1 shows two graphs that illustrate the potential effect of management changes that affect PR/AI (Figure 1A) or service rate (Figure 1B). The top line in both graphs shows the rate of pregnancies for a herd with 40% PR/AI and 40% service rate. The herd with 40% for both rates has a median days open of 150 days. Interestingly, at 250 days there are about 20% of the cows that are still not pregnant. It should be remembered that this is a theoretical herd with all cows having the same fertility of 40%. There are no sterile or severely infertile cows in this theoretical herd. Nevertheless, it is likely that many of these "normal" cows would be culled if this situation occurred in a dairy herd. Thus, this theoretical herd illustrates that it is likely that many dairy operations may be culling cows for reproductive reasons that may have become pregnant if the pregnancy rate per AI and service rate had been optimized. The next paragraph considers how changes in these rates impact reproductive efficiency. In Figure 1A the pregnancy rate per AI is improved from 40% to 50%. This type of improvement may be possible in some herds wi th ca re fu l management decisions. Obviously, this results in some improvement in days open to 135 days; however, Improving Reproductive Efficiency