High-fertility, High-producing Cows -- An
|Figure 1: Distribution of the estimated correlation between 305d milk yield and calving interval for Michigan DHIA herds from 1998 to 2007. A total of 4627 herd by year combinations (referred to as herd-years) are represented in the figure. VWP = Voluntary Waiting Period.|
Connecting Milk Yield with Reproduction
Aiming at this question, we set out to study the nature of the relationship between milk yield and reproductive performance of Michigan dairy cows, and how it might be associated with management practices and herd-related factors. This preliminary study, which was presented at the 2009 American Dairy Science Association conference, was based on 776,957 lactation records from 851 Michigan Dairy Herd Improvement Association (DHIA) dairy herds recorded from 1998 to 2007. Criteria for inclusion in this study were a minimum herd size of 25 cows and a maximum testing interval of 45 d. Also, given the low representation (< 5%) of dairy breeds other than Holstein, we restricted our analysis to Holstein herds.
We used cow data to estimate the within-herd correlation between 305-d milk yield and projected calving interval for each year from 1998 to 2007. Figure 1 depicts the frequency distribution of the correlation between 305-d milk and calving interval for every herd by year combination (termed a herd-year unit or contemporary group). Correlation is a measure of linear association and it can range from -1 through 0 to 1 but what does it mean? In our case, a correlation of 1 (right end of Figure 1) would indicate a perfect relationship by which any unit increase in 305-d milk would be predicted to correspond to a consistently uniform increase in calving intervals. In turn, a correlation of -1 (left end of Figure 1) would suggest a perfect relationship in the opposite direction; that is, more milk would lead to consistently shorter calving intervals and thus, improved reproductive performance.
As a middle ground, a correlation of 0 would indicate that calving interval would be completely independent of milk production. Now, keep in mind that correlation means association but does not necessarily indicate direct cause and effect between milk yield and calving interval. A correlation between milk yield and calving interval could just indicate common causal factors to both traits.
So, back to Figure 1, between 1998 and 2007, the average correlation between 305-d milk and calving interval for Michigan herds was 0.26, meaning that, on average, more milk per 305-d lactation was associated with longer calving intervals across the state. Moreover, 50% of Michigan herds had correlations between 0.19 and 0.33, again indicating an antagonistic milk production-reproduction relationship for most cases. Actually, in some herds, the situation was even worse, with strongly positive (i.e., undesirable) correlations above 0.80.
Now, at the opposite end of the curve (left of Figure 1), some herds apparently managed to have no relationship between milk yield from reproductive performance (correlation = 0) and some had even reverted the trend and showed a strongly negative (i.e. favorable) correlation of -0.46. Clearly, the relationship between milk yield and reproduction is not a one-size-fits-all relationship. Rather, there seems to be a variation among dairy herds in terms of the link between calving interval and high milk yield. One might then ask: is this variation just by sheer chance? Or, is it something real and manageable, so that it would be possible to drive the correlation between 305-d milk and calving interval to a more favorable condition? We evaluated 16 herd performance indicators and management practices, and how they may relate to the production-reproduction correlation.
Result of the Research
Good news first: management factors such as milking frequency, use of rbST administration, herd expansion and voluntary waiting period were significantly associated with the production-reproduction correlation. Herds with more frequent milking schedules (3X or greater) and with intensive rbST supplementation (>50% of the herd enrolled) had more favorable production-reproduction relationships than herds on 2X milking or with no rbST use. Although no longer used in Michigan, results on rbST are reported due to its main interest in understanding the production-reproduction relationship regardless of industry circumstances.
Also, the correlation between 305-d milk and calving interval decreased (that is, improved the relationship) in herds with longer voluntary waiting periods. Interestingly, herd size was not associated with the production-reproduction relationship, thus implying that small and large herds alike can do as good a job of successfully getting high-producing cows pregnant.
However, if a herd was expanding, the correlation between 305-d milk and calving interval increased and the relationship became more unfavorable. This could be partially explained by expanding farms holding on to open late lactation cows that would otherwise be culled from the herd, thus artificially inflating calving interval. In addition, expansion usually puts a considerable amount of pressure on cows and people. As a result, intensive management may suffer and careful attention to detail may temporarily slip away during herd expansion.
Not as Simple as It Seems
Now, here is the catch: the magnitude of the effect of each individual management practice on the correlation was very small, thus indicating the complex multifactorial nature of the relationship between milk production and reproduction. In other words, no single management strategy is a silver bullet for successful pregnancies in high producing cows.
Furthermore, DHIA data allow us only to identify factors influencing correlations between management and production-reproduction but there may not necessarily be cause-effect implications. This is particularly relevant when considering that 1) rbST is not currently in use in Michigan, and 2) rbST herds may be more likely to also implement other management-intensive practices, such as synchronized breeding schedules or targeted nutrition programs.
DHIA data on nutrition and reproductive herd management are very limited. More research will certainly be needed in this regard. We are currently working with more sophisticated methods to study these relationships from a more comprehensive perspective. Still, our results are consistent in indicating that milk yield and reproductive efficiency can be jointly optimized under conditions of intensive management along with careful attention to management detail.
In summary, milk yield and timely pregnancies of dairy cows do not necessarily play against each other. In fact, production and reproduction can be disconnected from each other or even correlate favorably, as attested to by real case herds in our Michigan dairy industry. Management strategies lay at the core of the production-reproduction relationship in a somewhat complex and intertwined manner. Understanding the mechanisms that drive this relationship can provide insightful information 1) to be aware of and stay away from undesirable scenarios, and more importantly, 2) to accurately target highly profitable management practices that optimize both milk yield and pregnancy success in the herd. Our goal is to continue to work on this subject to provide practical evidence-based insight that will help to guide on-farm management decisions towards an optimal balance between milk production and reproductive performance of Michigan dairy herds.
We are grateful to the Elwood Kirkpatrick Dairy Research Endowment, in association with Michigan Milk Producers Association, the College of Agriculture and Natural Resources and the Department of Animal Science at Michigan State University, for
partially funding this research.
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