The dairy industry is very dynamic and has undergone tremendous change in the last few decades.

During the 1940s and 1950s, industry leaders were touting the benefits of using purebred dairy bulls to increase milk production through genetic selection; agronomists were promoting the concept of managing soil fertility, specifically nitrogen, for better crop yields; and refrigeration and transportation technologies were improving, leading to improved dairy product acceptance and consumption by the consumer.

Today’s dairy environment is dramatically different from the 1950s. Producers now have access to genetically engineered crops, computerization to aid with crop planting, cattle feeding, milk harvest and new biotechnology tools to enhance milk production. Instead of simply relying on a purebred natural service sire, producers now have their choice of a variety of timed A.I. protocols, sexed semen and in vitro fertilization followed by embryo transfer.

During this period of rapid change, milk production in the U.S. has improved from approximately 5,000 pounds per cow in 1950 to over 18,000 pounds in 2000, based on estimates from the United States Department of Agriculture. Continued improvement in milk production efficiency has enabled the modern dairyman to remain profitable despite receiving milk prices that are not much different from 20 years ago.

Despite the vast improvements in milk production, management and overall production efficiency, one principle that has remained constant is that reproductive efficiency has a large effect on overall dairy herd profitability. Sound reproductive management benefits dairies by increasing milk production (more rapid return to more profitable and efficient phase of lactation), more culling options due to fewer late-lactation removals of non-pregnant cows, more replacement heifers and bull calves produced, fewer extended dry periods and more rapid improvement in genetic gain.

The majority of people working within the dairy industry agree that sound reproductive management can have tremendous positive effects on profitability and one of the key components of modern dairy production medicine is the analysis of reproductive records. Accurate and reliable on-farm records can help guide producers, veterinarians and consultants to make better management decisions regarding reproductive management.

The majority of cows in the U.S. dairy herd are managed using some form of computerized records system. Carefully maintained and accurate records that can be analyzed appropriately can help answer questions such as:

1. Where are we now regarding pregnancy production?
2. How have we performed historically?
3. Where are we headed in the near future?

However, before getting into specific monitors, reports or interpretation, there are some general concepts, concerns and terminology that must be considered.

Terminology

• Voluntary waiting period (VWP)
The period of time set aside after calving that allows for uterine involution and hopefully, the resumption of cyclicity, prior to the initiation of breeding. For most dairies, the VWP is 45 to 60 days in milk.

• Conception risk
The percent of services with known outcomes over a specified period of time that result in a pregnancy, or, alternatively, the number pregnant divided by number inseminated (and subsequently determined to be pregnant or not pregnant) over some time period.

• Insemination risk
The percent of eligible cows that are inseminated within a given time frame – usually 21 days. This estimate includes animals inseminated as a result of estrus detection or by timed insemination. This estimate is usually not performed for bull breeding since few are actually recording which cows are actually serviced by the bull.

• Pregnancy rate
The percentage of eligible cows that becomes pregnant within a given time frame – usually 21 days. While it is true that heat detection (or insemination risk) and conception risk dramatically impact pregnancy rate, they should not be the basis for calculating pregnancy rate. Hence, pregnancy rate can be calculated for bull pens similarly to A.I. pens once the entry date into the pen and the conception dates are estimated.

Comments regarding setting goals
Goals are target levels of performance toward which producers are trying to achieve. When setting goals, one should follow the S.M.A.R.T. approach and define goals that are specific, measurable, attainable, realistic, and timely. An important concept here is to not set goals that are too lofty and unrealistic. Dairymen should not set 30 percent as their pregnancy rate goal, at least not initially, if their herd is currently languishing at 12 percent pregnancy rate. Instead, they should pick a more reasonable improvement level, work to achieve that level of performance, celebrate that accomplishment and then set a new higher goal.

Once goals have been set, one must define the individual components or processes that impact the dairy’s ability to reach the previously defined targets and determine how performance will be evaluated. In order to achieve a high pregnancy rate, there are a multitude of processes that must all function properly. Cows must transition well from dry cow to fresh cow with limited negative impact from negative energy balance, metritis, endometritis, etc.; cows must receive their first insemination in a timely manner following the end of the voluntary waiting period and be efficiently reinseminated if pregnancy does not occur; good semen handling and breeding skills should result in a high risk of conception for each insemination; and once pregnancies are created, there should be low risk of embryonic loss or abortion.

Each of these aforementioned areas could be described as monitoring parameters, i.e., each one is a measurable factor that contributes to the overall reproduction efficiency goal of a higher pregnancy rate.

Benchmarks
Benchmarks are standards by which others can be measured or compared. Benchmarks are not synonymous with goals. Instead, benchmarks are reported standards that are typically adapted from large data sets. Often, these benchmarks are simply the averages for different monitoring parameters and may be derived by lumping together herds that represent a wide variety of production levels and management philosophies.

Unfortunately, many people may use these benchmarks as herd-level goals. These benchmarks become measuring sticks to evaluate their own dairy’s performance. Commonly used benchmarks that producers use to evaluate herd reproductive status often include the use of calving interval, average days open and pregnancy rate.

For example, whole herd pregnancy rates typically average about 14 percent across the U.S. A producer that is currently at 16 percent pregnancy rate might feel good about his herd’s performance as compared to the benchmark of 14 percent, but based on economic modeling, he is incurring tremendous lost opportunity costs by his inability to achieve a more profitable, yet realistic, level of reproductive efficiency of 20 to 25 percent.

In the absence of other data, benchmarks can be useful as a starting point for comparison, but who wants to strive to be just average in an economic sense? As a general rule, generic, industry-wide benchmarks are dangerous, and should be avoided, or at the very least, used with extreme caution. A far better approach would be to evaluate their current status, and see if recent changes were harmful or beneficial. Ultimately, producers should set their own herd-specific goals.

Monitoring issues
The process of monitoring involves the routine and systematic collection and evaluation of information (monitoring parameters) from a dairy in an attempt to detect change in the process. In general, monitoring is used to measure the effect of some implemented intervention, to detect the occurrence of an unintended disruption in the system process, and to help motivate behavioral change on the dairy by identifying previously unknown or unrecognized issues. Equally important, however, is to use caution with monitoring to avoid changing something when it is not really a problem.

Of course, mistakes can be made in monitoring performance parameters and there are some clearly identified potential pitfalls that should be recognized by professionals involved with dairy performance monitoring including variation, lag, momentum and bias.

Variation
Variation is a concept referring to the amount of change over time. The different ways of calculating calving interval represents one form of variation across the different processing centers. At the herd level, variation can refer to how much difference there is in an outcome across some population. Averages are often used to measure the central tendency for a group but the amount of spread or variation is not apparent and a few outliers can dramatically skew the average.

Lag
Lag refers to the elapsed time between when an event occurs and when it is measured. Lag is inherent in many reproductive parameters such as conception risk because we must wait until we can actually determine the outcome of the insemination by either a return to estrus or by pregnancy evaluation.

Momentum
Momentum refers to the dampening or buffering effect that results from excessive influence of events from the distant past on current performance, i.e., recent changes may be obscured by the weight of historical performance. As a consequence, mistakes may be made in interpretation of performance in either direction.

Bias
The final of the four major potential pitfalls regarding interpretation of performance records is bias. A bias is a systematic error in the collection, analysis or interpretation of data that can lead to incorrect conclusions. Or, to put it in more simple terms, bias is the incorrect inclusion or exclusion of cows from the parameter calculation.

Evaluating reproductive performance
Every dairy consultant has their own approach toward evaluating reproductive performance via dairy herd records. The approach that is presented here is not meant to be all-inclusive, nor is it meant to be an “ideal” method, but rather is simply the approach that the author prefers to take when looking at reproductive records on-farm. The following outline represents one potential approach to the evaluation of reproductive performance:

• Understand the herd’s objectives regarding its reproductive program.

• Verify completeness of the available data.

• Evaluate the “true” VWP and the herd’s ability to deliver semen in a timely manner for first insemination.

• Evaluate the pregnancy rate, ideally from a variety of ways – Whole herd performance over the last year (calendar date, days in milk, A.I. herd versus natural service (if bulls are used), first lactation versus 2+ lactation cows)

• Evaluate breeding submission risk using the previous approach (except for bulls)

• Evaluate conception risk – Service number, breeding type or code, technician, day of the week, and via a stratified approach if cow numbers allow

• Pregnancy check evaluation – frequency, compliance

• Pregnancy hard count

• Pregnancy losses

• Transition health and management (if data is available)

The first step mentioned in the outline (evaluate the herd’s objectives) sounds a bit like an academic issue, but is critical in order to understand the herd’s goals, expectations, and willingness to work to improve. For example, some herds want to have the highest possible pregnancy rate and are willing to do whatever it takes to achieve it, while other herds don’t want to do anything more than deliver one to two A.I. services prior to dumping cows into bull pens. These latter herds do not want to be bothered with the intricacies of managing a timed A.I. program or investing additional management time or resources towards YOUR reproductive goal for THEIR dairy. If you try to evaluate and manage them toward a very high level of performance, the result is often a painful lesson learned (and a bloodied forehead from constantly hitting the wall!).

The next step is to verify the completeness of the data. Screening data for accuracy and completeness may involve reviewing lists of cows, examining histograms or scattergraphs, or by evaluating summary tables. Some key items to consider:

1. Are there at least 365 days worth of culled cow records available?
2. Has the recent insemination and pregnancy confirmation information been recorded?
3. Are A.I. and bull pens individually and accurately defined?
4. Are the records under consideration limited to only the herd of interest?
5. Have there been any new cows merged into the database recently?

Prior to examining the herd’s pregnancy rate, one must determine what the true voluntary waiting period is for the herd in order to know when to start “counting.” Many herds will state that their voluntary waiting period is “60 days”, but in reality, the records show something entirely different.

Once the true VWP has been established, one can then dig deeper to evaluate the efficiency of delivering the first insemination, either by visual assessment of graphs or by calculation using other commands. In A.I. herds, I like to determine what percent of cows receive an insemination within a specified period of time following the VWP. For example, if a herd is using total timed A.I. on a weekly basis and a VWP of 70 days, I would like to see 90 to 95 percent of cows that are 81 DIM or greater with a first insemination between 70 and 77, excluding reproductive culls and cows starting a lactation by abortion.

Once the VWP and efficiency for first service has been evaluated, I like to look at the pregnancy rate. While no single monitor is perfect, I feel that pregnancy rate, when performed correctly, is the single best tool for assessing both historical and ongoing reproductive efficiency in a dairy herd.

Pregnancy rate is a metric that evaluates the speed at which cows become pregnant and is calculated most commonly on a 21-day basis by dividing the number of cows that became pregnant during that time by the number of cows considered eligible to become pregnant over the same time period.

The final area for consideration when evaluating reproductive performance should probably be the first area considered after verifying that the records are complete. This critical area is transition cow management. In order to obtain high pregnancy rates, herds must do an excellent job of transitioning cows from far dry to lactating. Care should be taken to minimize the risk of an assortment of periparturient diseases such as milk fever, metritis, displaced abomasums, ketosis, etc. Unfortunately, this is an area that is most inconsistently recorded across farms. Farms need to emphasize the accurate recording of the major transition disorders.

Monitoring dairy herd reproductive performance need not be a complicated, daunting task, but a little preparation can ensure that the correct performance indicators are used correctly. Of course, this may mean changing the monitoring parameters that have been used in the past.

Short (low) calving intervals and reduced days open are legitimate goals for dairies, but these outcomes should not be used as key monitoring parameters due to the previously mentioned problems such as lag, momentum, bias and variation. Instead, focus on a few key areas such as first- service insemination efficiency, re-insemination of non-pregnant cows in a timely manner, optimizing rather than maximizing conception risk and transitioning cows in a healthy manner.

With an eye on these key areas, carefully maintained and accurate records that can be analyzed appropriately can determine historical reproductive performance, current status of pregnancy generation and may help give some guidance to where the dairy is headed in the near future.

Although there is no one perfect reproductive parameter, whole herd pregnancy rate, when calculated and used correctly, provides the most information regarding overall performance and should be the basis for evaluating dairy herd reproductive efficiency. PD

References omitted but are available upon request at editor@progressivedairy.com

—Excerpts from 2007 Western Dairy Management Conference Proceedings

Michael W. Overton, DVM, MPVM, College of Veterinary Medicine, University of Georgia