Biomedical subjects

G J Kistemaker

Publications and source records attributed to G J Kistemaker.

8 recordsLinked to original sources

PubMed2006

Analysis of inbreeding and its relationship with functional longevity in Canadian dairy cattle.

The aim of this study was to assess the level of inbreeding and its relationship to the functional survival of Canadian dairy breeds by using a Weibull proportional hazard model. Data consisted of records from 72,385 cows in 1,505 herds from 2,499 sires for Jerseys, 112,723 cows in 1,482 herds from 2,926 sires for Ayrshires, and 1,977,311 cows in 17,182 herds from 8,261 sires for Holsteins. Longevity was defined as the number of days from first calving to culling, death, or censoring. Inbreeding coefficients (F) were grouped into 7 classes (F = 0, 0 < F < 3.125, 3.125 < or = F < 6.25, 6.25 < or = F <12.5, 12.5 < or = F < 18.25, 18.25 < or = F < 25.0, and F > or = 25.0%). The statistical model included the effects of stage of lactation, season of production, the annual change in herd size, type of milk recording supervision, age at first calving, effects of milk, fat, and protein yields calculated as within herd-year-parity deviations, herd-year-season of calving, inbreeding, and sire. The relative culling rate was calculated for animals in each class after accounting for the above-mentioned effects. A trend toward increased risk of culling among more inbred animals was observed for all breeds. Little difference in survival was observed for cows with 0 < F <12.5%. The relative risk ratios (relative to F = 0) for cows with inbreeding coefficients up to 12.5% were 1.19, 1.16, and 1.14 for Jersey, Ayrshire, and Holstein cows, respectively. Greater effects of inbreeding were seen, however, when F increased beyond 12.5%.

Aging↗

PubMed2006

Analysis of the relationship between somatic cell score and functional longevity in Canadian dairy cattle.

The aim of this study was to assess the level of somatic cell count (SCC) and to explore the impact of somatic cell score (SCS) on the functional longevity of Canadian dairy cattle by using a Weibull proportional hazards model. Data consisted of 1,911,428 cows from 15,970 herds sired by 7,826 sires for Holsteins, 80,977 cows in 2,036 herds from 1,153 sires for Ayrshires, and 53,114 cows in 1,372 herds from 1,758 sires for Jerseys. Functional longevity was defined as the number of days from the first calving to culling, death, or censoring. The test-day SCC was transformed to a linear score, and the resulting SCS were averaged within each lactation. The average SCS were grouped into 10 classes. The statistical model included the effects of stage of lactation; season of production; annual change in herd size; type of milk recording supervision; age at first calving; effects of milk, fat, and protein yields, calculated as within-herd-year-parity deviations; herd-year-season of calving; SCS class; and sire. The relative culling rate was calculated for animals in each SCS class after accounting for the aforementioned effects. The overall average SCC for Holsteins was 167,000 cells/mL, for Ayrshires was 155,000 cells/mL, and for the Jerseys was 212,000 cells/mL. In all breeds there were no appreciable differences in the relative risk of culling among classes of SCS breed averages (i.e., up to a SCS of 5). However, as the SCS increased beyond the breed average, the relative risk of cows being culled increased considerably. For instance, Holstein, Ayrshire, and Jersey cows with the highest classes of SCS had, respectively, a 4.95, 6.73, and 6.62 times greater risk of being culled than cows with average SCS.

Age Factors↗

PubMed2005

Genetic analysis of herd life in Canadian dairy cattle on a lactation basis using a Weibull proportional hazards model.

The objectives of this study were to identify the most important factors that influence functional survival and to estimate the genetic parameters of functional survival for Canadian dairy cattle. Data were obtained from lactation records extracted for the May 2002 genetic evaluation of Holstein, Jersey, and Ayrshire breeds that calved between July 1, 1985 and April 5, 2002. Analysis was performed using a Weibull proportional hazard model, and the baseline hazard function was defined on a lactation basis instead of the traditional analysis of the whole length of life. The statistical model included the effects of stage of lactation; season of production; the annual change in herd size; type of milk recording supervision; age at first calving; effects of milk, fat, and protein yields calculated within herd-year-parity deviations; and the random effects of herd-year-season of calving and sire. All effects fitted in the model had a significant effect on functional survival of cows in all breeds. Milk yield was by far the most important factor influencing survival, and the hazard increased as the milk production of the cows decreased. The hazard also increased as the fat content increased compared with the average group. Heifers that were older at calving were at higher risk of being culled, and expanding herds were at lower risk of being culled compared with stable herds. More culling was found in unsupervised herds than in supervised herds. The heritability values obtained were 0.14, 0.10, and 0.09 for Holstein, Jersey, and Ayrshire, respectively. Rank correlation between estimated breeding values (EBV) obtained from the current national genetic evaluation of direct herd life and the survival kit used in this study ranged from 0.65 to 0.87, depending on the number of daughters per sire. Estimated genetic trend obtained using the survival kit was overestimated.

Animals↗

PubMed2005

Relationship between type traits and longevity in Canadian Jerseys and Ayrshires using a Weibull proportional hazards model.

The aim of this study was to use a Weibull proportional hazards model to explore the impact of type traits on the functional survival of Canadian Jersey and Ayrshire cows. The data set consisted of 49,791 registered Jersey cows from 900 herds calving from 1985 to 2003. The corresponding figures for Ayrshire were 77,109 cows and 921 herds. Functional survival was defined as the number of days from first calving to culling, death, or censoring. Type information consisted of phenotypic type scores for 8 composite traits and 19 linear descriptive traits. The statistical model included the effects of stage of lactation; season of production; annual change in herd size; type of milk recording supervision; age at first calving; effects of milk, fat, and protein yields calculated as within herd-year-parity deviations; herd-year-season of calving; each type trait; and the animal's sire. Analysis was done one trait at a time for each of 27 type traits in each breed. The relative culling risk was calculated for animals in each class after accounting for the previously mentioned effects. Among the composite type traits with the greatest contribution to the likelihood function was final score followed by mammary system for Jersey breed, while in Ayrshire breed feet and legs was the second most important trait next to final score. Cows classified as Poor for final score in both breeds were >5 times more likely to be culled compared with the cows classified as Good Plus. In both breeds, cows classified as Poor for feet and legs were 5 times more likely to be culled than were cows classified as Excellent, and cows classified as Excellent for mammary system were >9 times more likely to survive than were cows classified as Poor.

Animals↗

PubMed2005

Estimates of genetic parameters for Canadian Holstein female reproduction traits.

Age at first insemination, days from calving to first insemination, number of services, first-service nonreturn rate to 56 d, days from first service to conception, calving ease, stillbirth, gestation length, and calf size of Canadian Holstein cows were jointly analyzed in a linear multiple-trait model. Traits covered a wide spectrum of aspects related to reproductive performance of dairy cows. Other frequently used fertility characteristics, like days open or calving intervals, could easily be derived from the analyzed traits. Data included 94,250 records in parities 1 to 6 on 53,158 cows from Ontario and Quebec, born in the years 1997 to 2002. Reproductive characteristics of heifers and cows were treated as different but genetically correlated traits that gave 16 total traits in the analysis. Repeated records for later parities were modeled with permanent environmental effects. Direct and maternal genetic effects were included in linear models for traits related to calving performance. Bayesian methods with Gibbs sampling were used to estimate covariance components of the model and respective genetic parameters. Estimates of heritabilities for fertility traits were low, from 3% for nonreturn rate in heifers to 13% for age at first service. Interval traits had higher heritabilities than binary or categorical traits. Service sire, sire of calf, and artificial insemination technician were important (relative to additive genetic) sources of variation for nonreturn rate and traits related to calving performance. Fertility traits in heifers and older cows were not the same genetically (genetic correlations in general were smaller than 0.9). Genetic correlations (both direct and maternal) among traits indicated that different traits measured different aspects of reproductive performance of a dairy cow. These traits could be used jointly in a fertility index to allow for selection for better fertility of dairy cattle.

Animals↗

PubMed2004

Analysis of the relationship between type traits and functional survival in Canadian Holsteins using a Weibull proportional hazards model.

The aim of this study was to explore the impact of type traits on the functional survival of Canadian Holstein cows using a Weibull proportional hazards model. The data set consisted of 1,130,616 registered cows from 13,606 herds calving from 1985 to 2003. Functional survival was defined as the number of days from first calving to culling, death, or censoring. Type information consisted of phenotypic type scores for 8 composite traits (with 18 classes of each) and 23 linear descriptive traits (with 9 classes of each). The statistical model included the effects of stage of lactation, season of production, the annual change in herd size, type of milk recording supervision, age at first calving, effects of milk, fat and protein yields calculated within herd-year-parity deviations, herd-year-season of calving, each type trait, and the sire. Analysis was done one at a time for each of 31 type traits. The relative culling risk was calculated for animals in each class after accounting for the previously mentioned effects. Among the composite type traits with the greatest contribution to the likelihood function were final score, mammary system, and feet and legs, all having a strong relationship with functional survival. Cows with low scores for these traits had higher risk of culling compared with higher scores. For instance, cows classified as poor plus 1 vs. excellent plus 1 have a relative risk of culling 3.66 and 0.28, respectively. The corresponding figures for mammary system are 4.19 and 0.46 and for feet and legs are 2.34 and 0.50. Linear type traits with the greatest contribution to the likelihood function were fore udder attachment, udder texture, udder depth, rear udder attachment height, and rear udder attachment width. Stature and size had no strong relationship with functional survival.

Animals↗

PubMed2000

Experience with a test-day model.

The Canadian Test-Day Model is a 12-trait random regression animal model in which traits are milk, fat, and protein test-day yields, and somatic cell scores on test days within each of first three lactations. Test-day records from later lactations are not used. Random regressions (genetic and permanent environmental) were based on Wilmink's three parameter function that includes an intercept, regression on days in milk, and regression on an exponential function to the power -0.05 times days in milk. The model was applied to over 22 million test-day records of over 1.4 million cows in seven dairy breeds for cows first calving since 1988. A theoretical comparison of test-day model to 305-d complete lactation animal model is given. Each animal in an analysis receives 36 additive genetic solutions (12 traits by three regression coefficients), and these are combined to give one estimated breeding value (EBV) for each of milk, fat, and protein yields, average daily somatic cell score and milk yield persistency (for bulls only). Correlation of yield EBV with previous 305-d lactation model EBV for bulls was 0.97 and for cows was 0.93 (Holsteins). A question is whether EBV for yield traits for each lactation should be combined into one overall EBV, and if so, what method to combine them. Implementation required development of new methods for approximation of reliabilities of EBV, inclusion of cows without test day records in analysis, but which were still alive and had progeny with test-day records, adjustments for heterogeneous herd-test date variances, and international comparisons. Efforts to inform the dairy industry about changes in EBV due to the model and recovering information needed to explain changes in specific animals' EBV are significant challenges. The Canadian dairy industry will require a year or more to become comfortable with the test-day model and to realize the impact it could have on selection decisions.

Analysis of Variance↗

PubMed1997

Comparison of possible covariates for use in a random regression model for analyses of test day yields.

Random regression models have been proposed for the genetic evaluation of dairy cattle using test day records. Random regression models contain linear functions of fixed and random coefficients and a set of covariates to describe the shapes of lactation curves for groups of cows and for individual cows. Previous work has used a linear function of five covariates to describe lactation shape. This study compared the function of five covariates with a function of only three covariates in three random regression models. Comparisons of estimates of components of variances and covariances, as well as comparisons of EBV and their prediction errors for milk yield, were made among models. Small practical differences existed between models in all respects. The model using regressions with five covariates had a slight advantage for comparison of prediction error variances of daily yields.

Animals↗