Genetic correlations among body condition score, yield, and fertility in first-parity cows estimated by random regression models

Citation
Rf. Veerkamp et al., Genetic correlations among body condition score, yield, and fertility in first-parity cows estimated by random regression models, J DAIRY SCI, 84(10), 2001, pp. 2327-2335
Citations number
39
Categorie Soggetti
Food Science/Nutrition
Journal title
JOURNAL OF DAIRY SCIENCE
ISSN journal
00220302 → ACNP
Volume
84
Issue
10
Year of publication
2001
Pages
2327 - 2335
Database
ISI
SICI code
0022-0302(200110)84:10<2327:GCABCS>2.0.ZU;2-O
Abstract
Twenty type classifiers scored body condition (BCS) of 91,738 first-parity cows from 601 sires and 5518 maternal grandsires. Fertility data during fir st lactation were extracted for 177,220 cows, of which 67,278 also had a BC S observation, and first-lactation 305-d milk, fat, and protein yields were added for 180,631 cows. Heritabilities and genetic correlations were estim ated using a sire-maternal grandsire model. Heritability of BCS was 0.38. H eritabilities for fertility traits were low (0.01 to 0.07), but genetic sta ndard deviations were substantial, 9 d for days to first service and calvin g interval, 0.25 for number of services, and 5% for first-service conceptio n. Phenotypic correlations between fertility and yield or BCS were small (- 0.15 to 0.20). Genetic correlations between yield and all fertility traits were unfavorable (0.37 to 0.74). Genetic correlations with BCS were between -0.4 and -0.6 for calving interval and days to first service. Random regre ssion analysis (RR) showed that correlations changed with days in milk for BCS. Little agreement was found between variances and correlations from RR, and analysis including a single month (mo 1 to 10) of data for BCS, especi ally during early and late lactation. However, this was due to excluding da ta from the conventional analysis, rather than due to the polynomials used. RR and a conventional five-traits model where BCS in mo 1, 4, 7, and 10 wa s treated as a separate traits (plus yield or fertility) gave similar resul ts. Thus a parsimonious random regression model gave more realistic estimat es for the (co)variances than a series of bivariate analysis on subsets of the data for BCS. A higher genetic merit for yield has unfavorable effects on fertility, but the genetic correlation suggests that BCS (at some stages of lactation) might help to alleviate the unfavorable effect of selection for higher yield on fertility.