No abstract

The objective of this study was to investigate the genetic relationship between body condition score (BCS) and reproduction traits for first-parity Canadian Ayrshire and Holstein cows. Body condition scores were collected by field staff several times over the lactation in herds from Québec, and reproduction records (including both fertility and calving traits) were extracted from the official database used for the Canadian genetic evaluation of those herds. For each breed, six 2-trait animal models were run; they included random regressions that allowed the estimation of genetic correlations between BCS over the lactation and reproduction traits that are measured as a single lactation record. Analyses were undertaken on data from 108 Ayrshire herds and 342 Holstein herds. Average daily heritabilities of BCS were close to 0.13 for both breeds; these relatively low estimates might be explained by the high variability among herds and BCS evaluators. Genetic correlations between BCS and interval fertility traits (days from calving to first service, days from first service to conception, and days open) were negative and ranged between −0.77 and −0.58 for Ayrshire and between −0.31 and −0.03 for Holstein. Genetic correlations between BCS and 56-d nonreturn rate at first insemination were positive and moderate. The trends of these genetic correlations over the lactation suggest that a genetically low BCS in early lactation would increase the number of days that the primiparous cow was not pregnant and would decrease the chances of the primiparous cow to conceive at first service. Genetic correlations between BCS and calving traits were generally the strongest at calving and decreased with increasing days in milk. The correlation between BCS at calving and maternal calving ease was 0.21 for Holstein and 0.31 for Ayrshire and emphasized the relationship between fat cows around calving and dystocia. Genetic correlations between calving traits and BCS during the subsequent lactation were moderate and favorable, indicating that primiparous cows with a genetically high BCS over the lactation would have a greater chance of producing a calf that survived (maternal calf survival) and would transmit the genes that allowed the calf to be born more easily (maternal calving ease) and to survive (direct calving ease).

The objective of this study was to investigate the genetic relationships of the 3 most frequently reported dairy cattle diseases (clinical mastitis, cystic ovaries, and lameness) with test-day milk yield and somatic cell score (SCS) in first-lactation Canadian Holstein cows using random regression models. Health data recorded by producers were available from the National Dairy Cattle Health System in Canada. Disease traits were defined as binary traits (0=healthy, 1=affected) based on whether or not the cow had at least one disease case recorded within 305 d after calving. Mean frequencies of clinical mastitis, cystic ovaries, and lameness were 12.7, 8.2, and 9.1%, respectively. For genetic analyses, a Bayesian approach using Gibbs sampling was applied. Bivariate linear sire random regression model analyses were carried out between each of the 3 disease traits and test-day milk yield or SCS. Random regressions on second-degree Legendre polynomials were used to model the daily sire additive genetic and cow effects on test-day milk yield and SCS, whereas only the intercept term was fitted for disease traits. Estimated heritabilities were 0.03, 0.03, and 0.02 for clinical mastitis, cystic ovaries, and lameness, respectively. Average heritabilities for milk yield were between 0.41 and 0.49. Average heritabilities for SCS ranged from 0.10 to 0.12. The average genetic correlations between daily milk yield and clinical mastitis, cystic ovaries, and lameness were 0.40, 0.26, and 0.23, respectively; however, the last estimate was not statistically different from zero. Cows with a high genetic merit for milk yield during the lactation were more susceptible to clinical mastitis and cystic ovaries. Estimates of genetic correlations between daily milk yield and clinical mastitis were moderate throughout the lactation. The genetic correlations between daily milk yield and cystic ovaries were near zero at the beginning of lactation and were highest at mid and end lactation. The average genetic correlation between daily SCS and clinical mastitis was 0.59 and was consistent throughout the lactation. The average genetic correlation between daily SCS and cystic ovaries was near zero (-0.01), whereas a moderate, but nonsignificant, correlation of 0.27 was observed between SCS and lameness. Unfavorable genetic associations between milk yield and diseases imply that production and health traits should be considered simultaneously in genetic selection.

Pregnancy has a negative impact on milk production in dairy cattle. Estimates of the effects of pregnancy are required in genetic evaluation models. Test-day records of Ayrshire, Jersey, Brown Swiss, and Guernsey breeds were analyzed phenotypically for the effect of pregnancy using 4 different models. Milk, fat, and protein yields were analyzed separately. The first model used a fourth-order Legendre polynomial regression on days in milk within classes of 10 d open. The second model fitted stage of pregnancy within days open classes to investigate the possible interaction between lactation stage and gestation stage. The third model included a fourth-order Legendre polynomial regression on days pregnant. In the fourth model, test-day records were divided into stage of pregnancy classes. Given that the effect of pregnancy was significant for all models, and that the adjusted R-squared values were consistent across the models, implying that the models for each trait fitted equally well within breeds, models were therefore compared based on the practicality of the results. Analysis of the first model indicated that milk production for cows with < or =180 d open tended to have low yields in the last part of lactation. Cows with longer days open, however, had proportionally higher milk yield throughout lactation, suggesting a possible confounding effect of production level with days open effects. Results from the analysis involving the second model illustrated that there was no apparent interaction between lactation stage and gestation stage. Results from the third and fourth models showed that milk and fat yields began to decline after about 4 mo of pregnancy for all breeds, and protein yield began to decline after about 2 mo of pregnancy for all breeds. A lack of records during the final 60 d of pregnancy (the typical dry period) severely limited the third model, as pregnancy effects could not be estimated accurately. This problem was lessened, however, with the fourth (stage of pregnancy) model, because test-day records for cows > or =210 d pregnant were grouped together, allowing for a moderate number of test-day records in the final class of days pregnant. Because the stage of pregnancy model showed a decline in production that increased as gestation progressed, and because there was not a lack of test-day records at the end of pregnancy, the fourth model provided the most realistic estimate of the effect of pregnancy on milk production. Further investigation is needed into the incorporation of stage of pregnancy effects into genetic evaluations.