Reproductive Health Programs for Dairy Herds: Analysis of Records for Assessment of Reproductive Performance

CHAPTER 61 Reproductive Health Programs for Dairy Herds: Analysis of Records for Assessment of Reproductive Performance


The effective use of records is a cornerstone of modern dairy production medicine. Records provide access to the performance results of a dairy’s management and serve as a major source of diagnostic information when problems arise. As veterinary service to dairy farms has matured, practitioners have become more involved in herd-level analysis, management consulting, and problem solving. Monitoring is an essential component of any system that must respond to external influences (Fig. 61-1).13 A parameter of the system is measured and compared with standards, goals, or past performance. If the parameter does not meet the goal, then plans are made and actions are taken (usually including collection of more diagnostic information). Because of both the action taken and the external influences on the system, a result is achieved. The result becomes the new status and the cycle begins again. Even though this activity is routine in most veterinary reproductive programs, in many cases it is not as fully developed or deliberately documented as might be most useful to the client.

Although the general scheme described is consistent across all types of monitoring, it is useful to distinguish between the following four general classes of monitoring.

Viewed from another perspective, monitoring can be applied to two classes of information:

2. Processes: Monitoring can also be applied to systems in operation to discover whether the prescribed activities of the system are being done and being done properly. To be effective, this presupposes that a specific operating system is defined and the person(s) responsible are aware and properly trained. For example, in a dairy reproduction program based on estrus detection, are personnel actually taking the time to observe the breeding population of cows? Do they know what to watch for? Do they report observations to the right person in a timely manner? Are they accurate in their observations? Are enough cows bred within a specified period? The distinction between these two classes of monitoring sometimes is indistinct (e.g., are enough cows bred?), but the conceptual difference is valuable. Real beneficial changes on the dairy happen at the process level, and problems can often be most quickly detected as undesirable changes in processes. Economic impact largely happens at the outcome level. Process monitoring (oversight) is a major part of a manager’s responsibilities and is key to assuring that the right things are done in the right way. Veterinary involvement in reproductive programs may include such process monitoring, either as a trouble-shooting activity or as part of the dairy’s operating management. To be effective in the latter role, the veterinarian must be on the dairy on a consistent basis and sufficient time has to be committed to the task. Typically, such process monitoring by the veterinarian includes a training component.

As dairies become more rationalized and as science and process development advances, the connection between processes and outcomes becomes tighter and more predictable. As that development continues, more and more time and attention will be committed to process monitoring, with less focus on outcomes because they will follow more reliably (but not necessarily perfectly) from proper processes.


The practitioner should be aware of several pitfalls in status and trend monitoring that can lead to inappropriate inaction (real problems escape notice) or inappropriate action (situations are misdiagnosed as problems and the wrong action is taken). Of the two, inappropriate inaction is probably the more common in reproductive production medicine and the more costly. The major pitfalls are as follows.

1. Variation in methods of calculation: There are many sources of reproductive indices and each has arrived at its own (often undocumented) approaches to calculating reproductive indices.2 Recommendations regarding calculation have been put forth, but remain inconsistently implemented.5 Furthermore, new approaches have become more appropriate since the last time a committee met to consider standardization. Care is necessary in interpreting numbers as presented, particularly when comparing results between various recording and summarizing programs.2,5,6

2. The dangers of averages. Reproductive herd records, and therefore reproductive herd monitoring, are rife with averages (means). Average days open, average services per conception, average annual culling rate as a percent of the herd (which is neither an average nor a rate)—these and others are used daily by veterinarians as they try to track the reproductive performance of their client herds. Averages measure one type of central tendency of a distribution of individual observations. Alone, they do not describe the spread of the distribution, nor do they call attention to failures of opportunities. Average days open, for example, can be the same in different herds, but with very different distributions. One herd can have a well-managed, tightly clustered distribution around the mean, while in another herd some cows might become pregnant very early while others are extremely delayed. Both herds might have the same average number of days open.

Herd size can have a dramatic effect on the variation and computation of averages. In a 50-cow herd with 25 confirmed pregnant animals, a single cow with 350 days open increases the average days open of the currently pregnant cows by 10 days. If this cow is then sold, the average of the remaining 24 will drop by 10 days (example assumes average days open of 100 days). If the dairy farmer is unaware of this, false credit for a positive result may be given to an irrelevant intervention. Conversely, two animals conceiving at 37 days would drop the average of the 27 pregnant animals by 5 days. At the other extreme of herd size, in very large herds with many cows contributing to the parameter, the average in any time period will tend to regress toward the long-term mean, obscuring problem cows that as individuals can be quite costly. Herd size effects cannot be avoided when averages are calculated; the practitioner must be aware of the possible pitfalls and use judgment when analyzing reproductive records.

6. Bias. Bias can be introduced in many ways into the calculation of parameters that monitor status and trends on dairy farms. Bias exists when a systematic error is made in the selection of animals used in the calculation, the information used is incomplete or inaccurate, or the assumptions made about the biology are wrong. Bias distorts the parameter’s true representation of reality. Some of the causes of such bias in reproductive parameters are as follows.

Although the preceding list of pitfalls may seem long, it should not deter practitioners from working with records to analyze a herd’s reproductive performance. Instead, knowing these pitfalls should lead to a healthy skepticism about the number presented, a determination to increase accuracy and completeness of the underlying data, and a fuller understanding of the conditions under which parameters may not truly represent herd status.


It has long been known that there is an important economic advantage to be gained by efficient reproduction in dairy herds.812 The economic effects of a sound reproductive program include increased milk by returning cows sooner to the earlier, more profitable phase of their lactation, increased numbers of replacement heifers and bull calves born, reduced costs of reproductive disease and reduced costs from culling, reduced nonproductive days due to extended dry periods, and increased rate of genetic gain.

On a biologic basis, the goal of a reproductive health program on a commercial dairy can be summarized as follows: Throughout her herd life, a cow should calve without difficulty and deliver a live calf, experience little or no postpartum reproductive disease, begin to cycle soon after calving, be inseminated soon after the voluntary waiting period, conceive to a high genetics bull within an optimal time period (or conceive at the right age as a heifer), and carry each fetus to term. This is not to imply that the goal is elimination of all pathologic events; to do so would be biologically impossible and economically inefficient. Rather, the goal is to have a minimum of pathologic events and a maximum of productivity within the constraints of practical biologic and economic reality. This general goal can be subdivided into sections, as follows.

2. Genetic return. Genetic return on the investment in semen or bulls should be optimized. Some computer packages can calculate optimal bull profiles for selection for artificial insemination, given the farmer’s goals for genetic gain and variability.13 It is worth noting that the genetic return on the investment in semen occurs only if the insemination results in a live female calf that subsequently conceives, calves, and has a productive lactation. Genetic improvement on a dairy farm is a long-term and somewhat risky investment. Assuming a 40% conception rate, 44% of females not born co-twin to a bull, a 10% abortion rate after pregnancy diagnosis, and a 20% loss of replacements from parturition until the end of a productive first lactation (includes stillbirths), only 13% of inseminations actually return any appreciable value in genetic gain to the producer. This means it takes at least 7 straws of semen just to produce a first lactation animal. On many farms, they need to purchase well over 10 straws to produce a complete first lactation.


Many parameters are used to monitor reproductive status and trends on the dairy farm. Some of these goals are shown in Table 61-1. For the most part, these are the traditional monitoring parameters for dairy reproduction. These herd goal levels must be applied with caution and may not be the appropriate alerting levels for management intervention on an individual cow basis. Several reviews of these parameters and their application have been written, so what follows is only a brief outline of the major parameters.5,1420

Sep 3, 2016 | Posted by in SUGERY, ORTHOPEDICS & ANESTHESIA | Comments Off on Reproductive Health Programs for Dairy Herds: Analysis of Records for Assessment of Reproductive Performance

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