Publikationsdatenbank

High milk production and good fertility:
can we select for both? (2023)

Art

Vortrag

Autoren

Borchardt, Stefan (WE 19)

Madureira, Augusto

Kongress

European Buiatrics Congress and ECBHM Jubilee Symposium

Berlin, 24. – 26.08.2023

Quelle

Kontakt

Tierklinik für Fortpflanzung

Königsweg 65
Haus 27
14163 Berlin
+49 30 838 62618
fortpflanzungsklinik@vetmed.fu-berlin.de

Abstract / Zusammenfassung

Objectives
In the past, high milk production has been associated with a decrease in fertility of lactating dairy cows. However, since early 2000 there has be an increase in the phenotypic reproductive performance of Holstein cows. Part of this has been associated with the implementation of activity monitoring systems and fertility programs for timed AI. Since 2000, several fertility traits have been emphasized for genetic selection. Genomic daughter pregnancy rate (gDPR) is calculated using the risk of pregnancy of a bull's daughters and predicts the genetic improvement in pregnancy rates for a future daughter of a bull. The improvement of genomic prediction for gDPR gives the opportunity to use the gDPR as selection criteria to improve fertility of lactating dairy cows. The objective of this study was to assess the relationship between gDPR and pregnancy at first AI and pregnancy losses (PL).

Materials and methods
A total of 6,739 Holstein cows (Parity 1: n = 2,636; Parity 2: n = 2,057; Parity 3+: n = 2,046) from one commercial dairy farm in Brazil were included. Most lactating cows were bred following a timed AI protocol for first service at d 60 ± 3 d based on estradiol and progesterone. Hair samples were collected from the tail switch and cows were genotyped using a SNP platform (Clarifide, Zoetis). Pregnancy diagnosis was performed at d 32 and 60 after AI using ultrasonography. Pregnancy loss was defined as a pregnant cow on d 32 that was nonpregnant on d 60. Cows in each parity were grouped based on their median for gDPR and genomic merit for milk yield (gMilk) into 4 groups: 1) Low gDPR and low gMilk (LgDPR_LgMilk); 2) High gDPR and low gMilk (HgDPR_LgMilk); 3) Low gDPR and high gMilk (LgDPR_HgMilk); 4) High gDPR and high gMilk (HgDPR_HgMilk).

Results
There was a mild negative correlation between gDPR and gMilk (r = - 0.191; P = 0.001). Pregnancy per AI was affected by a combination of gDPR and gMilk (P = 0.001). Pregnancy per AI was 40.6 ± 1.5 %, 50.4 ± 1.4 %, 43.1 ± 1.4 %, and 53.3 ± 1.6 % for cows in LgDPR_LgMilk, HgDPR_LgMilk, LgDPR_HgMilk, and HgDPR_HgMilk, respectively. Pregnancy loss was not associated with gMilk (P = 0.497) but there was a tendency for an association with gDPR (P = 0.100). Cows with high gDPR tended to have reduced PL compared with low gDPR cows (13.8 ± 0.8 % vs 17.5 ± 1.0 %).
There was a clear association of gDPR and gMilk on milk production at d 60 with 44.4 ± 0.16 kg, 44.9 ± 0.15 kg, 48.7 ± 0.15 kg, and 48.4 ± 0.17 kg for cows in LgDPR_LgMilk, HgDPR_LgMilk, LgDPR_HgMilk, and HgDPR_HgMilk, respectively.

Conclusions
An increase in GDPR was associated with greater odds of pregnancy per AI and a tendency towards lower odds of PL. The fact that cows could have high GDPR, and high expected milk production suggests that both genotypes could be selected for. These results provide further evidence that GDPR is associated with better reproduction outcomes.