Understanding the Key to Successful Reproduction
Service
rate is defined as the percentage of eligible cows bred during a 21-day period.
In herds using AI, the service rate directly reflects estrus detection efficiency
because a cow must first be detected in estrus before she can be bred. Unfortunately,
less than 50% of all estrus periods are accurately detected on an average
dairy farm in the United States (Senger, 1994). This inefficiency in estrus
detection not only increases time to first AI but can increase the average
interval between services to 40 to 50 days (Stevenson and Call, 1983). Many
dairy managers choose to focus on improving PR/AI in their herds; however,
over three times as much of the variation in average days open among farms
is due to differences in service rate as is due to differences in PR/AI (Barr,
1975). Economic cost analysis of improving the estrus detection rate (i.e.,
service rate) by 20 to 30%, and assuming a 50% AI conception rate, resulted
in an estimated annual benefit of $83 per cow (Pecsok et al., 1994). Similarly,
increasing the estrus detection rate from 35 to 55% reduced average days open
from 136 to 119 days, resulting in a net return per cow of $60 per year (Oltenacu
et al., 1981). Thus, management strategies that improve the service rate in
an operation result in a net profit to the producer.
Figure
1 graphically illustrates the potential effect of management strategies that
improve either PR/AI (left panel) or service rate (right panel) in a theoretical
herd with normal fertility and having no sterile or severely infertile cows.
The top line in both graphs represents the pregnancy rate for a herd with
a PR/AI of 40% and a service rate of 40%. In this scenario, the herd has a
median days open of 150 days, and by 250 DIM nearly 20% of cows in the herd
are not pregnant. The left panel of Figure 1 illustrates the effect of improving
PR/AI from 40% to 50% while maintaining a 40% service rate. In this scenario,
median days open is reduced to 135 days, however, nearly 12% of cows in the
herd are not pregnant by 250 DIM. In contrast, the right panel of Figure 1
illustrates the effect of improving service rate from 40% to 90% while maintaining
a PR/AI of 40%. In this scenario, median days open is reduced to about 100
days, and by 200 DIM nearly all cows in the herd are pregnant. Thus, although
managers should strive to maximize PR/AI, increasing service rate has a greater
impact on improving reproductive performance of a herd.
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Figure 1. Graphical illustration of the potential effect of
management strategies that improve PR/AI (left panel) or service rate (right
panel) in a theoretical herd with normal fertility and having no sterile or
severely infertile cows. The top line in both graphs represents the pregnancy
rate for a herd with a PR/AI of 40% and a service rate of 40%. The left panel
illustrates the effect of improving PR/AI from 40% to 50% while maintaining a 40% service rate.
The right panel illustrates the effect of improving service rate from 40%
to 90% while maintaining a PR/AI of 40%.
Figure
1 illustrates the key to successful reproduction in a dairy herd. First, dairy
managers should strive to maximize PR/AI in their herds by managing the factors
they can control (Table 1) while realizing that PR/AI in high-producing dairy
cows is low. The most effective key to maximizing pregnancy rate in a dairy
herd is to strive to improve the AI service rate. Before discussing strategies
to improve the AI service rate, we must first understand the factors that
determine estrus expression in lactating dairy cows.