Editor’s note: This article is the first in a two-part series about how to monitor and, if necessary, change a herd’s reproductive management. Click here to read the second and final part in this two-part series. As the U.S. dairy industry continues to consolidate into fewer but larger farms, the demands for effective management and leadership skills have increased. Owners have historically run their dairies via a hands-on approach, providing much of the labor necessary, but with increases in herd size and efforts to maximize the return on their milking parlor by milking around the clock, owners have had to make the transition to more of a role as administrator and supervisor.
As milk production per cow has increased, there have been some challenges with achieving good reproductive performance.
Physiologically, there are significant differences between Holstein dairy cows producing large volumes of milk and those producing below-average volumes, and these differences include a reduction in the duration of estrus, decreased estrus detection efficiency, potential declines in conception risk (CR, defined as the percentage of matings that result in a diagnosed pregnancy, i.e., the number of new pregnancies diagnosed divided by the total number of cows inseminated) as a consequence of prolonged luteinizing hormone stimulation and delayed ovulation, as well as declines in CR due to inaccuracies around estrus detection.
However, well-managed herds have been able to continue to get cows pregnant in a very timely manner by reducing the impact of metabolic and uterine health challenges and by placing more emphasis on a well-structured reproductive program.
In an effort to improve reproductive performance, a number of new tools and technologies have been developed and research is constantly ongoing. The use of timed artificial insemination (TAI) protocols has mitigated much of the impact of high milk production and feed intake on the ability to detect estrus and inseminate cows in a timely manner.
Technology in the form of activity monitoring systems and radio frequency identification (RFID) can help to reduce the risk of human error and improve compliance within the breeding management program when implemented and used appropriately.
In addition, there has been a shift away from placing genetic selection pressure predominantly on milk production to increased selective pressure for other important traits including reproduction.
Each of these changes places an additional burden on management – dairy managers must hone their economic decision-making skills to select the correct technology to match their herd’s abilities and goals.
No therapeutic intervention or new technology can compensate for poor management, a lack of appropriate training or for inaccurate record keeping.
Evolution of timed-A.I. protocols
For many herds, the use of TAI has reduced or eliminated the need for estrus detection when implemented with an appropriate voluntary waiting period and good animal health monitoring practices and has provided economically positive results for most herds, despite some of the management challenges.
In the authors’ opinions, the widespread adoption and implementation of TAI has been a large contributor toward the improvement in reproductive performance that appears to have occurred in the past few years. During the late 1990s, two large data sets, one from California containing 80 herds and 100,000 cows and one from the upper Midwest containing over 2,200 herds and 250,000 cows, were assembled.
In these reports, the average pregnancy rate (PR), defined as the percentage of eligible cows that became pregnant within a given time frame (usually 21 days), was 14 to 16 percent. During the last 10 years, herd numbers have decreased, herd size has increased, adoption of TAI and other reproductive technologies has increased, and the general consensus is that dairy cattle reproductive performance has improved.
Now, our expectations are that herds should have PR of at least 18 to 20 percent with many Holstein herds achieving high levels of milk production while maintaining annual PR of 24 to 26 percent.
Each of the TAI approaches (see Figure 1) has its own advantages and disadvantages including differences in efficiency at recruiting cows into ovulation cohorts and the number and type of injections required and utilization of TAI may allow more efficient use of labor while also providing improved reproductive efficiency.
Click here or on the image at right to view it at full size in a new window.
The choice of whether to use a TAI program and which program to use should be determined by the management’s assessment of labor, facility and cow health constraints, as well as the current level of reproductive performance.
Each of the successful TAI protocols is based upon some variation or derivative of Ovsynch, as shown in Figure 1. Conception risk for Ovsynch typically ranges from the upper 20s to mid-40s, depending upon the cyclicity status of cows at the start of the program, the presence or absence of some presynchronization strategy, the timing of the interval between the PGF2α injection and the second GnRH and whether the Ovsynch is for first service or as part of a resynchronization approach.
Many herds utilize once-daily estrus detection during the morning hours via the use of visual assessment of tail chalk status and will inseminate at this time. One frustration regarding Ovsynch for some dairies is the requirement for either an afternoon injection or an afternoon insemination, depending on the program version used.
Administering the GnRH in the afternoon at 56 to 60 hours after PGF2α shifts the insemination back to the morning period and slightly improves CR as compared to the morning injection of the second GnRH at 48 hours, followed by an afternoon or evening insemination in 12 to 16 hours.
In order to eliminate some of the compliance issues associated with Ovsynch, Cosynch-72 was developed (Figure 1) with each of the steps performed during the morning breeding management period, facilitating greater potential compliance. However, the expected CR for Cosynch-72 is expected to be lower than Ovsynch.
Another variation to the traditional Ovsynch program has been the insertion of a CIDR into the protocol starting at day 0 (Figure 1). Cows that begin the Ovsynch protocol without a corpus luteum present, whether due to being in an anovulatory condition or due to starting the protocol in metestrus or proestrus, have a reduced expected CR.
However, the addition of the CIDR, a vaginal drug insert containing 1.38 g of progesterone, has been shown to improve the CR in these animals by 5 to 10 percent.
Ovulatory response to the first GnRH of Ovsynch is a very critical determinant for successful synchronization of ovulation in dairy cows and, as a consequence, various presynchronization options have been developed. A presynchronization protocol utilizing two injections of PGF2α given 14 days apart and 10 to 14 days prior to starting Ovsynch (Presynch-Ovsynch, as shown in Figure 1) has proven very successful for many herds.
In addition to improving the consistency of the ovulatory response to the first GnRH of Ovsynch in cycling cows, other benefits include an improvement in uterine health and the ability to “cherry pick” cows and breed them via estrus detection following PGF2α administration. With a Presynch-Ovsynch program, cows may be inseminated at the detected estrus or be started into an Ovsynch protocol 10-14 days after the second PGF2α, but optimal results appear to result from the use of an 11-day interval.
Changing approaches to monitoring and management of reproduction
In order to gauge the progress of a dairy, proper and timely recording and evaluation of key data is essential. Dairy reproductive monitoring involves the regular observation and recording of activities, events and outcomes that occur for the purposes of observing and evaluating the degree of change, intended or unintended, positive or negative, within a herd.
It should include a systematic approach to data collection, evaluation and provision of feedback about the changes detected. Routine and systematic monitoring should allow for the recognition of “normal” performance, should aid the herd manager in evaluating the impact of intentional change in management or performance, should facilitate the discovery of unintended drifts or declines in procedures or performance over time and should help determine the potential causes or sources of abnormal performance.
Goals are target levels of performance toward which producers are trying to achieve and every operation should have simple, specific, measurable and timely goals. However, it is rarely a good idea to use the goal metric itself as a monitor of performance since it usually represents the end result of many different processes.
For example, consider a herd that has an average age-at-calving for replacement heifers of 27 months. Most herds have a goal for age-at-calving of 24 months or less.
Using the herd’s current age-at-calving to establish a reasonable goal is appropriate, but relying on it as a monitor of changes in performance is very problematic since it is the cumulative result of many processes such as appropriate feeding, housing, vaccination, breeding, culling, etc. Changes in any of these areas today would not result in a measurable change in age-at-calving for months.
A manager could cull out the oldest, poorly growing heifers at some point prior to calving by selling them to his neighbor, thus reducing his average age-at-calving, but he really hasn’t changed the true performance of his replacements.
Conversely, he could initiate dramatic changes to the feeding and management of his youngest calves, but the impact of this change will not be measured using this metric until approximately two years into the future.
Evaluating a system such as heifer reproductive management by examining the age-at-first-calving utilizes an animal-based outcome, but the results are a consequence of animal performance (response to the housing and nutrition program, genetic potential for growth and fertility, breed, etc.), management’s efforts (level of metabolizable protein and energy provided at various stages of growth, promptness of movement of animals into an A.I. pen, training or hiring of breeding technicians, sire selection, etc.) and worker competence and adherence to the management plan (delivery of the proper feed to the correct pen, correct and timely identification of animals in estrus, semen handling, adherence to TAI protocols, proper identification and recording of procedures, etc.).
Whenever possible, the focus for performance analysis should be on monitoring the key steps of the process versus simply monitoring outcomes. While outcome monitoring is important and has its place, monitoring key processes and labor’s contribution to these processes gives an earlier indication of problems or improvements, thus allowing more timely correction or celebration.
Instead of merely devising ways to catch employees failing, management should focus on an active and ongoing training process that includes the following five points: explain, show, practice, observe and praise.
In the case of teaching TAI, managers should have an employee demonstrate how they will draw up the required amount of GnRH and then to administer it to a cow, observe how the employee performed the task and repeat the previous steps as needed to ensure that the correct product is administered accurately.
Was a 1.5-inch 18 ga needle that was attached to an appropriately sized syringe used to administer the GnRH in an appropriate muscle plane? If so, the manager should praise him for a job well done. If not, he should praise him for the steps performed correctly and then help the individual to modify the incorrect ones. PD
References omitted due to space but are available upon request to editor@progressivedairy.com.
—Adapted from 2011 Society for Theriogenology Conference proceedings
Overton is a professor at the University of Georgia’s College of Veterinary Medicine. Heins is a veterinarian completing a master’s degree in food animal medicine at the same institution.
Michael W. Overton
Professor of Veterinary Medicine
University of Georgia
moverton@uga.edu
