What Is the Most Cost-Effective Breeding Program for Breeding Heifers—Timed AI, Estrous Detection, or a Combination of Both?1
Introduction
As any other business enterprise, the sustainability of a dairy farm is highly dependent on economics. In order to obtain a profitable return on assets, there is a constant need to maximize outputs and, oftentimes, to minimize inputs. In a conventional dairy farm, most of the cash receipts (about 88%) come from milk sales, and a smaller portion (about 12%) results from animal sales, including those destined for dairy production (Santos et al. 2010). On the other hand, feed costs of lactating dairy cows account for roughly 50% of total cost of production, whereas rearing replacement heifers account for about 23% of the cost of producing milk. Reproduction influences both milk production and number of replacement heifers available on a farm; therefore, reproductive efficiency becomes a key determinant of dairy cow profitability (Britt 1985; Meadows et al. 2005; De Vries 2006; De Vries et al. 2006).
According to a survey conducted by the National Animal Health Monitoring System, approximately 63% of the dairy farms in the United States use AI following detection of spontaneous or induced estrus in dairy heifers (NAHMS 2009). The main advantages of this program are the ease of implementation, relatively low costs, and high pregnancy per AI. However, success of programs for detection of estrus is highly dependent on efficiency and accuracy of detection, which requires daily observation. Low estrous-detection rates result in low pregnancy rates and a large variation in age at first breeding and at pregnancy, and, consequently, age at first calving, which are economically undesired (Ettema and Santos 2004). Administration of PGF2α when heifers are moved to the breeding pens is a very common strategy to induce luteolysis and formation of sexually active groups, thereby facilitating detection of estrus by concentrating estrous expression in fewer days, which improves pregnancy rates (Stevenson et al. 2008). Approximately 33% of dairy farms in the United States still use natural service as the main method to breed heifers (NAHMS 2009).
A survey completed in 2007 indicated that fewer than 4% of dairy operations used timed-AI programs as a breeding strategy for dairy heifers (NAHMS 2009). The low utilization of such programs was justified by reduced pregnancy per AI (30%–40%) obtained with standard Ovsynch protocol compared with AI at detected estrus (50%–60%). Another reason was the perception by producers that reproductive management of dairy heifers is not a concern. Nonetheless, novel timed-AI programs for dairy heifers have been developed and resulted in adequate pregnancy per AI (50%–60%; Lima et al. 2011; Lima et al. 2012). With adequate fertility, the major advantage of implementing timed-AI protocols for dairy heifers is to maximize the number of pregnant animals immediately after they become eligible to breeding, which is expected to result in younger age at pregnancy and calving, therefore reducing costs with feeding dairy heifers (Ettema and Santos 2004). Nevertheless, these programs require compliance, labor, and costs with hormone administration.
Therefore, the objective of this publication is to present information from recently published work by Ribeiro et al. (2012) that looked at the economics of different reproductive programs for breeding heifers that use timed AI only (TAI), estrus detection only (ED), or a combination of both (TAI+ED).
Economics of Different Reproductive Program for Dairy Heifers
A simulation was performed to calculate pregnancy rates, average time to pregnancy, total costs per AI (including labor, drugs, semen, and equipment required), and total costs per pregnancy for four reproductive programs when the duration of the breeding period was 84 days or approximately four estrous cycles.
Heifers were eligible to be bred starting at 400 days of age (day 0) and were subjected to one of the four breeding protocols:
Timed AI only
Detection of estrus only
Timed AI for first breeding and detection of estrus for the remaining period
Timed AI for first AI followed by insemination upon detected estrus or resynchronized insemination after non-pregnant diagnosis
Four estrous detection rates were considered of 50%, 60%, 70%, and 80%. Detection of estrus program included an injection of PGF2α on day 0 in all heifers and a second injection 14 days later for those not inseminated. Pregnancy per AI for those inseminated after estrus was assumed to be 60% for the first breeding and 54% for the remaining inseminations (Norman et al. 2010). For timed AI, nonpregnant heifers were reinseminated every 40 days for up to three AI, and pregnancies per AI were 59%, 55%, and 51% for the first, second, and third breedings, respectively (Lima et al. 2011; Lima et al. 2012). For detection of estrus, costs with labor were calculated for tail chalking and animal observation was computed. Costs per pregnancy included costs incurred to implement the breeding program and feed costs associated with the interval from beginning of breeding to pregnancy. It was assumed that each extra day to pregnancy after 400 days of age would increase feed costs when heifers consume more DM, at 23–25 months of age. Each extra day cost $2.00. Nonpregnant heifers at the end of the simulation (day 84) had an additional cost of $168 for feed.
As expected, results of programs using detection of estrous were highly dependent of estrous detection rates (Table 1). As efficiency of estrous detection increased from 50% to 80%, more heifers were pregnant early and at the end of the breeding period, which reduced age at pregnancy. These improvements in reproduction also affected the cost per AI and the feed cost per pregnancy, which decreased the total cost per pregnancy with higher estrus detection. Incorporation of timed AI for first AI was beneficial to reduce cost per pregnancy compared with estrous detection alone, although the benefits decline at the high estrous detection rate (Table 1). When additional timed AI were incorporated in the breeding program to resynchronize nonpregnant heifers that had not been detected in estrus, it had a further benefit—but only at the low estrous detection efficiency (50%–60%)—not when estrous detection was greater than 60%. Timed AI only was equivalent to a program based on detection of estrus when efficiency was at least 70%. Incorporating detection of estrus after timed AI was superior to timed AI only. Most of the changes in costs per pregnancy are the result of additional feed costs with heifers becoming pregnant later in the breeding period.
Conclusion
In summary, most dairy farms breed heifers using detection of estrus. There is little justification to incorporate timed AI programs when detection of estrus is excellent; above 70%. However, for farms with detection of estrus below 60%, either timed AI for first AI followed by detection of estrus or timed AI alone improves reproductive performance and reduces the cost per pregnancy. The combination of timed AI and estrous detection between timed AIs resulted in the lowest cost per pregnancy among all programs evaluated.
References
Britt, J. H. 1985. "Enhanced reproduction and its economic implications." J. Dairy Sci.68: 1585–1592.
De Vries, A. 2006. "Economic value of pregnancy in dairy cattle." J Dairy Sci 89: 3876–3885.
De Vries, A., M. B. Crane, J. A. Bartolome, P. Melendez, C. A. Risco, and L. F. Archbald. 2006. "Economic comparison of timed artificial insemination and exogenous progesterone as treatments for ovarian cysts." J Dairy Sci 89: 3028–3037.
Ettema J, and Santos JEP. 2004. "Impact of age at calving on lactation, reproduction, health, and income in first-parity Holsteins on commercial farms." J Dairy Sci 87: 2730–2742.
Lima FS, Ayres H, Favoreto MG, Bisinotto RS, Greco LF, Ribeiro ES, Baruselli PS, Risco CA, Thatcher WW, and Santos JEP. 2011. "Effects of the GnRH at initiation of the 5-d timed AI program and timing of induction of ovulation relative to AI on ovarian dynamics and fertility of dairy heifers." J Dairy Sci 94: 4997–5004.
Lima FS, Ribeiro ES, Bisinotto RS, Martinez N, Greco LF, Galvão KN, Risco CA, Thatcher WW, Amstalden M, and Santos JEP. 2012. "Effects of GnRH and administering number of PGF2α doses in the 5-d timed AI program on ovarian responses and fertility of dairy heifers." J Dairy Sci 95 (Suppl. 2): 576–577. (Abstr.)
Meadows, C., P. J. Rajala-Schultz, and G. S. Frazer. 2005. "A spreadsheet-based model demonstrating the nonuniform economic effects of varying reproductive performance in Ohio dairy herds." J Dairy Sci 88: 1244–1254.
NAHMS. 2009. Dairy 2007, Part IV: Reference of Dairy Cattle Health and Management Practices in the United States, 2007. #N494.0209. Centers for Epidemiology and Animal Health, USDA: APHIS: VS, Fort Collins, CO.
Norman HD, Hutchison JL, Miller RH. 2010. "Use of sexed semen and its effect on conception rate, calf sex, dystocia, and stillbirth of Holsteins in the United States." J Dairy Sci 93: 3880–3890.
Ribeiro ES, KN Galvao, WW Thatcher, and JEP Santos. 2012. "Economic aspects of applying reproductive technologies to dairy herds." Anim Reprod 9: 370–387.
Santos JE, Bisinotto RS, Ribeiro ES, Lima FS, Greco LF, Staples CR, and Thatcher WW. 2010. "Applying nutrition and physiology to improve reproduction in dairy cattle." Soc Reprod Fertil Suppl 67: 387–403.
Stevenson, JL, JC Dalton, JEP Santos, R Sartori, A Ahmadzadeh, and RC Chebel. 2008. "Effect of synchronization protocols on follicular development and estradiol and progesterone concentrations of dairy heifers." J Dairy Sci 91: 3045–3056.
