The adoption of Automated activity monitoring (AAM) systems and protocols for synchronization of ovulation and timed AI (TAI) on commercial dairy farms have led to an improvement in reproductive performance over the last two decades. These systems are not mutually exclusive but can act synergistically.
Automated activity monitors enable the producer to not only improve their heat detection rate but also offer additional information on estrous expression that are currently unused. Of particular importance seems to be the intensity of an estrus event and the expression of estrus within the voluntary waiting period (VWP). Both traits seem to be robust predictors for fertility of individual cows and might serve as selection criteria for a targeted reproductive management (TRM) approach (Giordano et al., 2022).
While there are preliminary results for an intervention to restore fertility in cows with reduced estrous expression at AI and anestrous cows within the VWP numerous challenges remain before the dairy industry can take full advantage of a TRM approach. There will be cows not detected in estrus due to technical difficulties of the system (e.g., device failures, algorithm) or physiological limitations of cows to display estrous behavior (Stangaferro and Giordano, 2019).
Two recent studies evaluating AAM systems reported that 35 to more than 50% of cows not detected in estrus by the AAM system ovulated without showing signs of estrus, thus underwent silent ovulations (Sauls et al., 2017; Valenza et al., 2012). In addition, a certain proportion of cows will be anovular at the end of the VWP.
The prevalence of anovulation was 23.3% (ranging from 7.3 to 41.7%) within 8 US herds including 5,818 cows (Bamber et al., 2009). In a Canadian survey including 1,341 cows from 18 herds, the overall prevalence of anovulation was 19.5%, ranging from 5 to 45% within herds (Walsh et al., 2007).
An advanced understanding of the underlying physiology of TAI protocols and appropriate modifications have led to an improvement in fertility in response to these protocols to a level that is similar or even better compared with cows that receive AI after spontaneous estrus. The prerequisites for achieving excellent fertility outcomes in TAI protocols for lactating dairy cows are:
Although it has been shown that herds can achieve exceptional reproductive performance using 100% TAI approach, alternative strategies can be considered.
Nevertheless, these protocols can help to overcome compromised fertility in a subgroup of cows that have been identified using data from AAM systems in a TRM approach. This represents an opportunity to merge the two technologies, without compromising reproductive performance.
The outline proposes a reproductive management strategy that can be used to combine AAM and TAI to optimize reproductive performance. For first service, producers should include transition health and estrus expression within the VWP into their decision-making process as outlined in Figure 1.
So far, two different strategies have been tested using either a Double-Ovsynch protocol or an Ovsynch protocol with P4 supplementation. Similar to anovular cows, it is very likely that these cows will not respond well to a standard Ovsynch protocol. Therefore, optimizing progesterone concentration during follicular growth in these cows seems necessary by either presynchronization using a combination of GnRH and PGF or supplementation of progesterone (P4). In addition, adding a second PGF treatment will improve luteal regression in these cows as they are more prone to incomplete luteal regression by starting the protocol in a low P4 environment.
Figure 1. Proposed scheme for managing the first service in cows using targeted reproductive management. Panel A: cows expressing estrus within the voluntary waiting period (VWP). Panel B: cows with no estrus expression within the VWP.
Non-pregnant cows need to be identified quickly in order to re-inseminate them. Therefore, a systematic approach has been recommended.
Accurate identification of cows returning to estrus from 18 to 32 days after AI is the easiest and least costly method for determining non-pregnancy early after insemination. This assumption, however, is being challenged by new research:
There are timed AI protocols available (called Resynch) that can be used to reduce interbreeding intervals (Lopes et al., 2013). The first GnRH injection of these protocols can be given to all cows one week before pregnancy check without any negative effect in cows that are pregnant (Figure 2). This approach is only recommended if it becomes a weekly farm routine and pregnancy examinations are done on the same day of the week.
Figure 2. Management of non-pregnant cows at pregnancy diagnosis in order to re-inseminate them quickly. CL = Corpus luteum. P4 = Progesterone.
For non-pregnant cows, there are 2 distinct situations (Pérez et al., 2020):
Combining AAM data and a targeted use of timed AI protocols in a systematic manner as outlined above allows dairy producers to have superior reproductive performance with a targeted use of hormones.
References
Bamber, R. L., G. E. Shook, M. C. Wiltbank, J. E. P. Santos, and P. M. Fricke. 2009. Genetic parameters for anovulation and pregnancy loss in dairy cattle. Journal of dairy science 92(11):5739–5753. https://doi.org/10.3168/jds.2009-2226
Giordano, J. O., M. L. Stangaferro, R. Wijma, W. C. Chandler, and R. D. Watters. 2015. Reproductive performance of dairy cows managed with a program aimed at increasing insemination of cows in estrus based on increased physical activity and fertility of timed artificial inseminations. Journal of dairy science 98(4):2488–2501. https://doi.org/10.3168/jds.2014-8961
Giordano, J. O., E. M. Sitko, C. Rial, M. M. Pérez, and G. E. Granados. 2022. Symposium review: Use of multiple biological, management, and performance data for the design of targeted reproductive management strategies for dairy cows. Journal of dairy science 105(5):4669–4678. https://doi.org/10.3168/jds.2021-21476
Lopes, G., J. O. Giordano, A. Valenza, M. M. Herlihy, J. N. Guenther, M. C. Wiltbank, and P. M. Fricke. 2013. Effect of timing of initiation of resynchronization and presynchronization with gonadotropin-releasing hormone on fertility of resynchronized inseminations in lactating dairy cows. Journal of dairy science 96(6):3788–3798. https://doi.org/10.3168/jds.2012-6429
Pérez, M. M., R. Wijma, M. Scarbolo, E. Cabrera, F. Sosa, E. M. Sitko, and J. O. Giordano. 2020. Lactating dairy cows managed for second and greater artificial insemination services with the Short-Resynch or Day 25 Resynch program had similar reproductive performance. Journal of dairy science 103(11):10769–10783. https://doi.org/10.3168/jds.2020-18607
Sauls, J. A., B. E. Voelz, S. L. Hill, L. G. D. Mendonça, and J. S. Stevenson. 2017. Increasing estrus expression in the lactating dairy cow. Journal of dairy science 100(1):807–820. https://doi.org/10.3168/jds.2016-11519
Stangaferro, M. L., and J. O. Giordano. 2019. Pregnant! AABP Proceedings:146–149. https://doi.org/10.21423/aabppro20197117.
Valenza, A., J. O. Giordano, G. Lopes, L. Vincenti, M. C. Amundson, and P. M. Fricke. 2012. Assessment of an accelerometer system for detection of estrus and treatment with gonadotropin-releasing hormone at the time of insemination in lactating dairy cows. Journal of dairy science 95(12):7115–7127. https://doi.org/10.3168/jds.2012-5639
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