برآورد پارامترها و روندهای ژنتیکی و فنوتیپی صفات تولید مثلی گاوهای ماده و نرخ باروری گاوهای نر هلشتاین ایران

Abstract
Introduction: Fertility is considered an important economic trait in cattle, yet despite its importance, reproductive efficiency of dairy cattle has decreased dramatically in the past decades and is of increasing concern to farmers and the dairy industry (Ghiasi et al. 2011; Pryce et al. 2010). The decline in the reproductive efficiency of dairy cattle has become a challenging problem worldwide. Genetic response for fertility traits is expected to be small due to low heritabilities as shown in many studies. In the past decades, more attention has been placed on milk production in selection programs worldwide, which has caused a decline in female fertility due to the antagonistic genetic relationship between milk production and fertility (Pryce et al. 2010; Toghiani 2012). Therefore, it is necessary to include fertility traits in the breeding programs for improving fertility or stopping its downward genetic trend (Penagaricano et al. 2012). It is well documented that bull fertility is influenced by genetic factors. Semen production traits, such as volume and sperm concentration, were found to have moderate heritabilities (from 0.15 to 0.30), whereas some of the semen quality traits, such as motility and percentage of abnormal sperm, had moderate to high heritabilities (close to 0.60) (Rezende et al. 2018). The objective of this study was to assess genetic parameters for fertility traits in Holstein dairy cows and sire conception rate (SCR) a new phenotypic evaluation of bull fertility.
Materials and method: In this study information's related to heifers and cows 1 to 3 parity, 1992 to 2018, by the National Animal Breeding center and promotion of Animal Products of Iran and sire conception rate (SCR) 2008 to 2018, a phenotypic evaluation of bull fertility, has been provided to dairy producers the Council of Dairy Cattle Breeding (CDCB) were used. Traits included: sire conception rate (SCR), age at first service (AFS), age at first calving (AFC), days open (DO), calving interval (CI), gestation length (GL), Pregnancy rate (PR), Interval between first and last
insemination (IFL), Days from calving to first service (DFS) and number of services per conception (NS). Edited data included the following: SCR between 7.6 % to -16 %, AFS between 320 and 900 days, AFC between 630 to 1350 days, CI between 300 and 700 days, IFL less than 290, GL between 260 and 290 days, DFS between 20 and 300 days, DO between 40 and 350 days, PR between -28 and 55 and NS between 1 and 10. Select the model equations and fixed effects were optimized using GLM procedure in SAS package. Subsequently, the multi-variate animal model analyses was carried out in order to estimate of direct additive genetic and phenotypic correlations between fertility traits. Estimation of genetic parameters using animal model in REML methodology was done by REMLF90 program.
Results and Discussion: Heritability estimates for all fertility traits were low, minimum heritability were estimated for IFL trait by heifers (0.002) and maximum amount for SCR trait (0.303). Heritability were estimated for other fertility traits 0.033, 0.005, 0.052, 0.048, 0.085, 0.108, 0.095, 0.059, 0.031, 0.025, 0.023, 0.017, 0.018, 0.013, 0.009, 0.013, 0.032, 0.028 and 0.018 for AFS, AFC, CI, OD, PR, GL_H, GL, DFS_1, DFS_2, DFS_3, IFL_1, IFL_2, IFL_3, IFL_123, NS_H, NS_1, NS_2 and NS_3, respectively. These estimates are in agreement with the results obtained by Ghiasi et al. (2011) and Rahbar et al. (2016) in Holstein cows. Heritability estimates obtained in this study were larger than the ones obtained by Toghiani Pozveh et al. (2009) for CI, DFS and DO in the previous study of Iranian Holsteins. The heritability estimates obtained for interval traits (DO, CI, and GL) were higher than those obtained for categorical (NS) or binary traits. However interval traits may be affected by management decisions such as the length of the voluntary waiting period or estrus synchronization applied in some farms (Ghiasi et al. 2011). In general, negative and moderate additive genetic and phenotypic correlations estimates were obtained between fertility traits. Estimated additive genetic correlations in the range of -0.56 (between GL and AFC) and 0.83 (between IFL and NS). However, estimated phenotypic correlations in the range of -0.80 (between PR and OD) and 0.85 (between GL and OD). The first one is formed by the traits that measure overall fertility of the cow (i.e. CI, OD and PR) which can be obtained directly from calving dates. In particular, OD and PR showed additive genetic (-0.39) and phenotypic (-0.80) correlation estimates which indicates that these two traits are genetically the same as expected because PR is a linear function of OD. The same results were found by VanRaden et al. (2004) and Ghiasi et al. (2011) in Holstein cattle. The mean breeding values were estimated -0.31 to 0.38, -4.14 to -3.34, -6.70 to -5.64, -0.0435 to -0.0064, -2.20 to -1.93, 9.16 to 10.73, 8.72 to 10.15, 3.29 to 4.21 and 4.34 to 5.84 for SCR, AFC, AFS, GL, PR, CI, OD, IFL DFS, respectively. However, the mean phenotypic values was positive, except SCR (range -0.62 to 0.66). These results were in agreement with reported Aghajari et al. (2015); Ansari-Lari et al. (2009) and Shirmoradi et al. (2010). Were estimated negative genetic trend for SCR (-2.22), AFS (-4.02 %), AFC (-2.66 %), GL (-0.07) and PR (-0.83) traits. Subsequently, for CI, DO, IFL and DFS traits, positive phenotypic trends were obtained. These estimated genetic and phenotypic trend agreed with other reports (Faraji-Arough et al. 2011; Rahbar et al. 2016).
Conclusion: Genetic parameters (heritabilities and genetic correlations) have been estimated for fertility traits in heifers and cows and fertility bulls. The results of this study indicated that breeding programs have paid little attention to reproductive traits in Iranian Holstein cows, and therefore it is recommended to pay more attention to these traits in order to improve the performance of Holstein cows. According to the results suggest that the genetic prediction of dairy bull fertility is feasible. This could have a positive effect on the dairy industry, for example, the early culling of bull calves with very low SCR predictions.