Using the Pregnancy Analytics Mobile App: Bull problems and BSEs

The Beef Cattle Institute’s Dr. Bob Larson brings you a series of “cases” employing the use of the Pregnancy Analytics mobile app. Each case will explore a unique herd and examine its reproductive efficiency, strengths, challenges and areas of improvement. The reports (linked below) will lead you through using the Pregnancy Analytics app to utilize the data and practice using it on an actual problem herd.

The case: Bull problems and BSEs

A herd of 209 commercial red-composite cows was palpated on October 7. The herd is split into three breeding pastures with bulls being turned out on June 10 and removed on August 15. The calves were being weaned on the ranch (i.e. left in their current pastures) and the cows were being trucked to a new pasture so the owner started dropping off cows at your clinic very early in the morning to be preg-checked, dewormed, and vaccinated before being taken to fall grazing on corn stalks. During the breeding season: 62 were in the “West Pasture” with two bulls, 81 were in the “North Pasture” with three bulls, and 66 were in the “Windmill Pasture” with two bulls. About 60% of the first-calf heifers were in the West Pasture –– with the rest split between the other two pastures.

Findings

Seventy-six cows were open (64% were pregnant) and only 8% of the cows were classified as being “thin” (BCS <5).

The first analysis of the preg-check data was to look at the percent of the herd that became pregnant each 21-day period of the breeding season and we find that 44.5% of the herd became pregnant in the first 21-days (pregnancies would have been 98 to 119 days), 13.9% in the second 21-day period (77-97 days), and 5.3% in the third 21-day period (56-76 days). The goal for this herd (and most herds) is to have at least 60% of the cows becoming pregnant in the first 21 days of breeding.

Another way to evaluate preg-check data is to determine the percent of the available (non-pregnant) cattle that become pregnant each 21-day period. Recognize that as the breeding season goes along, once cattle become pregnant, they are no longer available to get pregnant again, so the percent of the herd that becomes pregnant each 21 days is not the same as the percent of available cattle that become pregnant each 21 days. To display this measure of reproductive success using the Pregnancy Analytics App – select “% Preg Success”. Based on expected pregnancy success when both cow and bull fertility is optimum, the “% Preg Success” goal should be between 60%-70% for every 21-day period of the breeding season.

Looking at the percentage of open cows that became pregnant each 21-day period, we find that either cow or bull fertility (or both) was lower than desired at the start of the breeding season (44.5% settling in first 21 days) and pregnancy success did not improve and in fact got worse as the breeding season progressed (25% in the second 21 days and 12.6% in the third 21 days).

In this herd, the poor over-all percentage pregnant clearly indicates a problem and the percent pregnant by 21-day interval provides information that the poor reproductive performance continued for the entire breeding season. To begin to evaluate the herd further, the Pregnancy Analytics App provides a way to easily divide the herd into pertinent sub-groups – and when the pregnancy success by 21-days is evaluated by age group, we find that both the first-calf heifers and the mature cows had too many open cows. (1st-calf heifers are defined as those cows suckling their first calf and being bred for their second pregnancy).

More information can be found by displaying the % Preg Success and while neither the 1st-calf heifers nor the cows reached the expected reproductive performance of 60-70% of open cows becoming pregnant in a 21-day period –– the 1st calf heifers tended to perform better than cows and the performance declined over the breeding season.

The preg-check data can also be evaluated by comparing the breed-up differences between body condition score categories. We know that only 8% of the herd was classified as “thin” at the time of preg-check, so we may be justified to ignore any assessment of the association between BCS and pregnancy distribution in this herd; but to be complete, I looked at BCS and found that cows classified as being in moderate body condition performed as poorly as cows classified as being thin.

So far, the information I have looked at raises the possibility of either Trichomoniasis or bull problems being the most likely rule-outs – with cow infertility due to nutritional or late-calving being less likely because the magnitude of open cows is more compatible with bull problems or Trich and the fact that fertility does not improve as the cows have more time post-partum to resume fertile cycles as the breeding season progresses.

The most revealing information about this herd is obtained by looking at the effect of breeding pasture on reproductive performance (both the pregnancy distribution and % Preg Success).

I interpret this information as evidence that the primary problem for this herd is in the Windmill pasture. The other two pastures (West and North) perform very well early in the breeding season – indicating that the cows must have had time post-partum and adequate nutrition pre- and post-partum to resume fertile cycles by the 21st day of the breeding season. Nearly all the open cows were in the Windmill pasture and fertility was very poor throughout the breeding season. The magnitude of the infertility is worse than I would expect for Trichomoniasis and definitely worse than I would expect with a cow problem (in addition, excellent cow performance in the other pastures pretty much rules out a cow problem). The poor reproductive performance in the Windmill pasture must be due to a bull problem.

Conclusion

The primary problem in this herd is in the Windmill pasture and almost has to be due to a bull problem even though the rancher reports that all the bulls were between three and five years of age and had been successful breeders in previous years. I would recommend a BSE on both bulls from this pasture, but if one or both bulls pass the BSE, my diagnosis would not change (finding a musculoskeletal or semen problem in one or both bulls would confirm the diagnosis).

To prevent this problem in the future, I would strongly recommend a BSE for all bulls before the start of breeding and frequent assessment of bull musculoskeletal health and amount of estrus activity throughout the breeding season.

Download the report here.

Using the Pregnancy Analytics Mobile App: Evaluating data

The Beef Cattle Institute’s Dr. Bob Larson brings you a series of “cases” employing the use of the Pregnancy Analytics mobile app. Each case will explore a unique herd and examine its reproductive efficiency, strengths, challenges and areas of improvement. The reports (linked below) will lead you through using the Pregnancy Analytics app to utilize the data and practice using it on an actual problem herd.

The case: Diagnosing poor fertility

A herd of 187 commercial cows was palpated on September 19. The herd was split into three breeding pastures and bulls were turned out on May 30. All cows were moved to a new pasture on August 1 to run together with bulls removed. During the breeding season 38 were in the “South Pasture,” 47 were in the “Home Pasture,” and 102 were in the “Webster Pasture.” All  heifers and about half the first-calf heifers were in the Webster Pasture.

At preg-check, 59 cows were open (68.5% were pregnant) and 80% of the cows were in moderate body condition (BCS 5 up to 6) while 17% were classified as being in thin body condition. 10.4% of the herd became pregnant in the first 21 days (pregnancies would have been 91 to 112 days), 23.6% in the second 21-day period (79-90 days), 17.6% in the third 21-day period (49-89 days), and 18.7% in the fourth 21-day period (28-48 days). The goal for this herd (and for most herds) is to have at least 60% of the cows becoming pregnant in the first 21 days of breeding.

Q_whole.png

Something isn’t right here. The poor overall percentage pregnant clearly indicates a problem and the percent pregnant by 21-day interval provides information that the poor reproductive performance continued for the entire breeding season.

To evaluate further, the Pregnancy Analytics App provides a way to easily divide the herd into pertinent sub-groups. When the pregnancy success by 21 days is evaluated by age group, we find that none of the age groups perform well, and the heifers perform particularly poorly. (First-calf heifers are defined as those cows suckling their first calf and being bred for their second pregnancy.)

Q_age

More information can be found by displaying % Preg Success and finding that while neither the 1st-calf heifers nor the cows performed well the first, second, and third 21-day periods, both these age groups improved slightly the forth 21 days, but still were below the expected 60-70% pregnancy success expected. In addition, the heifers performed very poorly throughout the breeding season.

Q_success_whole.png

So far, the information doesn’t narrow the rule-out list. Problems with heifer development, a similar calving pattern last year that results in many cows not calving until after the breeding season has started, and poor bull fertility or Trichomoniasis are all possible contributors to this herd’s poor performance.

Click to download and read the full case report.

 

Using the Pregnancy Analytics Mobile App: Analyzing a problem herd

The Beef Cattle Institute’s Dr. Bob Larson brings you a series of “cases” employing the use of the Pregnancy Analytics mobile app. Each case will explore a unique herd and examine its reproductive efficiency, strengths, challenges and areas of improvement. The reports (linked below) will lead you through using the Pregnancy Analytics app to utilize the data and practice using it on an actual problem herd.

The case: Efficient, but there’s room for improvement in first-calf heifers

The first report examines data from a herd of 274 commercial cows palpated on Sept. 4. The herd was turned out onto one pasture with 9 bulls on May 20. One hundred eighteen of the cows were predominantly Angus, 69 were black white-faced Hereford and Angus cross, and 87 cows were a mix of mostly Angus breeds and composites.

At pregnancy checking, 92.7% of the cows were pregnant, with only 20 cows open. The majority of cows were in moderate body condition score (BCS). The goal of this herd (and for most herds) was for 60% of the cows to become pregnant in the first 21 days of breeding. It succeeded, with 62.6%. That’s considered a win, and the herd is considered to have very good reproductive overall efficiency. However, the Pregnancy Analytics app can divide the herd into valuable sub-groups, including age, revealing that the herd’s first-calf heifers did not breed up as well in the first 21 days (31%) as in the second 21 days (46.6%).

2_Pregnancy distribution_by age

Another point illustrated by graphs automatically generated by the app is that cow breed-up in the third 21 days was lower, which may indicate a problem late in the breeding season.

1_Pregnancy distribution_whole herd

Click to download and view the full report.

Dr. Larson’s follow-up questions:

Are heifers in this herd bred to calve ahead of the mature cows? Do you have calving dates for the heifers?
I encourage producers to breed heifers to calve ahead of the cows so that they have additional time to resume fertile cycles between calving and the start of the next breeding season. Some herds are able to breed heifers to calve at the same time as the cows and not experience a drop in pregnancy success for young cows getting bred for their second pregnancy (1st calf heifers) compared to the mature cows – but if this age group has poorer breed-up than the mature cows during the first 21 days of the breeding season, then I think a strong suggestion to move heifer breeding earlier is justified.

Starting about the end of June or the first of July (this would coincide with the end of the 2nd 21-day period), did any of the bulls have any problems? If not, what were pasture conditions and cow health like starting in late June?
Act on the information you receive from these questions.