Biomedical subjects

J Jamrozik

Publications and source records attributed to J Jamrozik.

At least 19 recordsLinked to original sources

PubMed2006

Analysis of milk urea nitrogen and lactose and their effect on longevity in Canadian dairy cattle.

The aim of this study was to assess the phenotypic level of lactose and milk urea nitrogen concentration (MUN) and the association of these traits with functional survival of Canadian dairy cattle using a Weibull proportional hazards model. A total of 1,568,952 test-day records from 283,958 multiparous Holstein cows from 4,758 herds, and 79,036 test-day records from 26,784 multiparous Ayrshire cows from 384 herds, calving from 2001 to 2004, were used for the phenotypic analysis. The overall average lactose percentage and MUN for Ayrshires were 4.49% and 12.20 mg/dL, respectively. The corresponding figures for Holsteins were 4.58% and 11.11 mg/dL. Concentration of MUN increased with parity number, whereas lactose percentage decreased in later parities. Data for survival analysis consisted of 39,536 first-lactation cows from 1,619 herds from 2,755 sires for Holsteins and 2,093 cows in 228 herds from 157 sires for Ayrshires. Test-day lactose percentage and MUN were averaged within first lactation. Average lactose percentage and MUN were grouped into 5 classes (low, medium-low, medium, medium-high, and high) based on mean and standard deviation values. 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, lactose percentage and MUN classes, and sire. The relative culling rate was calculated for animals in each class after accounting for the remaining effects included in the model. Results showed that there was a statistically significant association between lactose percentage and MUN in first lactation with functional survival in both breeds. Ayrshire cows with high and low concentration of MUN tended to be culled at a higher than average rate. Instead, Holstein cows had a linear association, with decreasing relative risk of culling with increasing levels of MUN concentration. The relationship between lactose percentage and survival was similar across breeds, with higher risk of culling at low level of lactose, and lower risk of culling at high level of lactose percentage.

Animals↗

PubMed2006

Genetic analysis of milk production traits of polish black and white cattle using large-scale random regression test-day models.

Genetic parameters for milk, fat, and protein yield and persistency in the first 3 lactations of Polish Black and White cattle were estimated. A multiple-lactation model was applied with random herd-test-day effect, fixed regressions for herd-year and age-season of calving, and random regressions for the additive genetic and permanent environmental effects. Three data sets with slightly different edits on minimal number of days in milk and the size of herd-year class were used. Each subset included more than 0.5 million test-day records and more than 58,000 cows. Estimates of covariance components and genetic parameters for each trait were obtained by Bayesian methods using the Gibbs sampler. Due to the large size and a good structure of the data, no differences in estimates were found when additional criteria for record selection were applied. More than 95% of the genetic variance for all traits and lactations was explained by the first 2 principal components, which were associated with the mean yield and lactation persistency. Heritabilities of 305-d milk yield in the first 3 lactations (0.18, 0.16, 0.17) were lower than those for fat (0.12, 0.11, 0.12) and protein (0.13, 0.14, 0.15). Estimates of daily heritabilities increased in general with days in milk for all traits and lactations, with no apparent abnormalities at the beginning or end of lactation. Genetic correlations between yields in different lactations ranged from 0.74 (fat yield in lactations 1 and 3) to 0.89 (milk yield in lactations 2 and 3). Persistency of lactation was defined as the linear regression coefficient of the lactation curve. Heritability of persistency increased with lactation number for all traits and genetic correlations between persistency in different lactations were smaller than those for 305d yield. Persistency was not genetically correlated with the total yield in lactation.

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↗

PubMed2005

Joint international evaluation of Milking Shorthorn dairy cattle for production traits.

Pedigree information and test-day records for the first 3 parities of Milking Shorthorn dairy cattle from 5 countries were analyzed. After editing, the data included 1,018,528 test-day records from 68,653 cows. A multiple-lactation random regression test-day model with Legendre polynomials of order 4 and a Bayesian method were used to estimate variance components for both single and multiple-countries. Fixed effects included herd-test-day class and regressions on DIM within age at calving-parity-season of calving. Random effects included animal genetic, permanent environmental, and residual effects. Average daily heritabilities from single country analyses ranged from 0.33 to 0.47 for milk yield and from 0.37 to 0.45 for protein yield across lactations and countries. Common sires (66) and their daughters were identified for creating a connected data set for simultaneous (co)variance component estimation of milk yield across all 5 countries. Between-country genetic correlations were low, with values from 0.08 to 0.46 and standard deviations from 0.08 to 0.12. Estimated breeding values for milk were generated for each animal using the same test-day animal model. Correlations among country estimated breeding values were higher than genetic correlations. Top 100 bull lists were generated on the scale of each country, and genetic progress was assessed. Future evaluation with increased genetic ties among countries may facilitate international comparison of Milking Shorthorns.

Analysis of Variance↗

PubMed2005

Comparison of random regression test-day models for Polish Black and White cattle.

Test-day milk yields of first-lactation Black and White cows were used to select the model for routine genetic evaluation of dairy cattle in Poland. The population of Polish Black and White cows is characterized by small herd size, low level of production, and relatively early peak of lactation. Several random regression models for first-lactation milk yield were initially compared using the "percentage of squared bias" criterion and the correlations between true and predicted breeding values. Models with random herd-test-date effects, fixed age-season and herd-year curves, and random additive genetic and permanent environmental curves (Legendre polynomials of different orders were used for all regressions) were chosen for further studies. Additional comparisons included analyses of the residuals and shapes of variance curves in days in milk. The low production level and early peak of lactation of the breed required the use of Legendre polynomials of order 5 to describe age-season lactation curves. For the other curves, Legendre polynomials of order 3 satisfactorily described daily milk yield variation. Fitting third-order polynomials for the permanent environmental effect made it possible to adequately account for heterogeneous residual variance at different stages of lactation.

Analysis of Variance↗

PubMed2004

Random regression test-day models with residuals following a Student's-t distribution.

First-lactation milk yield test-day records of Canadian Holsteins were analyzed by single-trait random regression test-day models that assumed normal or Student's-t distribution for residuals. Objectives were to test the performance of the robust statistical models that use heavy-tailed distributions for the residual effect. Models fitted were: Gaussian, Student's-t, and Student's-t with fixed number of degrees of freedom (equal to 5, 15, 30, 100 or 1000) for the t distribution. Bayesian methods with Gibbs sampling were used to make inferences about overall model plausibility through Bayes factors, posterior means for covariance components, estimated breeding values for regression coefficients, solutions for permanent environmental regressions, and residuals of the models. Bayes factors favored Student's-t model with the posterior mean of degrees of freedom equal to 2.4 over all other models, indicating very strong departure from normality. Number of outliers in Student's-t model was reduced by 35% in comparison with the Gaussian model. Differences in covariance components for regression coefficients between models were small, and rankings of animals based on additive genetic merit for the first two regression coefficients (total yield and persistency) were similar. Results from the Gaussian and Student's-t models with fixed degrees of freedom become more alike (smaller departures from normality for Student's-t models) with increasing number of degrees of freedom for the t-distributions. For any pair of Student's-t models, the one with the smaller number of degrees of freedom for the t-distribution was shown to be superior. Similarly, number of outliers increased with increasing degrees of freedom for the t distribution.

Animals↗

PubMed2003

Estimation of genetic parameters for concentrations of milk urea nitrogen.

The objective of this study was to use field data collected by dairy herd improvement programs to estimate genetic parameters for concentrations of milk urea nitrogen (MUN). Edited data were 36,074 test-day records of MUN and yields of milk, fat, and protein obtained from 6102 cows in Holstein herds in Ontario, Canada. Data were divided into three sets, for the first three lactations. Two analyses were performed on data from each lactation. The first procedure used ANOVA to estimate the significance of the effects of several environmental factors on MUN. Herd-test-day effects had the most significant impact on MUN. Effects of stage of lactation were also important, and MUN levels tended to increase from the time of peak yield until the end of lactation. The second analysis used a random regression model to estimate heritabilities and genetic correlations of MUN and the yield traits. Heritability estimates for MUN in lactations one, two, and three were 0.44, 0.59, and 0.48, respectively. Heritabilities for the yield traits were of a similar magnitude. Little relationship was observed between MUN and yield. Raw phenotypic correlations were all <0.10 (absolute value). Genetic correlations with production traits were close to zero in lactations one and three and only slightly positive in lactation two. The results indicate that selection on MUN is possible, but relationships between MUN and other economically important traits such as metabolic disease and fertility are needed.

Animals↗

PubMed2002

Two-step and random regression analyses of weight gain of station-tested beef bulls.

Our objectives were to compare a two-step model and a joint procedure via random regression model for evaluating weight gain of beef bulls, weighed every 28 d on 140-d test, and to estimate genetic, environmental, and phenotypic parameters. Two-step analysis consisted of fitting fixed linear regressions to weights of each bull to determine weight gain on test. In the second step, gain on test was analyzed by a mixed model that included fixed effects of breed, test group, and starting age and random effects of weaning herd-year group and animal (additive genetic). The random regression model included the same effects as the two-step mixed-model analysis with an additional random animal permanent environment effect. Fourth-order Legendre polynomials of days on test were fitted for all fixed and random effects in the random regression model, except for breed. Breed effects and residual variances varied for each measurement period. Variance components and EBV for gain were obtained from the covariance function and estimates of random regression coefficients for weight, respectively. Random regression heritability estimates for gain on test increased over time, being maximum at end of test (0.38) and equal to two-step estimate. Permanent environment variance ratio estimates also increased over time and were greater than heritability estimates. Estimate of weaning herd-year variance ratio was approximately constant over time, being equal to 0.07 at end of test and similar to two-step estimate. Genetic correlations between gain through different periods on test given by random regression model were high (from 0.81, between 28 and 140-d gain on test, to 0.99, between 112 and 140-d gain on test). Genetic correlations between gain on discrete 28-d intervals were moderate to high (e.g., 0.49 and 0.99 between the last 28 d on test and the first and fourth 28 d, respectively). Rank correlations between EBV for 140-d gain by the two procedures were 0.98, 0.84, and 0.73 for all bulls and the 5% and 1% of bulls with highest random regression EBV, respectively. Results indicated that the two procedures rank top bulls quite differently for 140-d gain on test. Random regression model accounted for changes over time of genetic and environmental effects on the test weight gain curve of the bulls. Use of 112-d instead of a 140-d test provided similar ranking of bulls on the basis of EBV for gain on test.

Animals↗

PubMed2002

Genetic evaluation of bulls and cows with single- and multiple-country test-day models.

First-lactation milk yield test-day records on cows from Australia, Canada, Italy, and New Zealand were analyzed by single- and multiple-country random regression models. Models included fixed effects of herd-test day and breed composition-age at calving-season of calving by days in milk, and random regressions with Legendre polynomials of order four for animal genetic and permanent environmental effects. Milk yields in different countries were defined as genetically different traits for the purpose of multiple-trait model. Estimated breeding values of bulls and cows from single- and multiple-trait models were compared within and across countries for two traits: total milk yield in lactation and lactation persistency, defined as the linear coefficient of animal genetic curve. Correlations between single- and multiple-trait evaluations within country for total yield were higher than 0.95 for bulls and close to 1 for cows. Correlations for lactation persistency were lower than respective correlations for total yield. Between country correlations for lactation yield ranged from 0.93 to 0.96, indicating different ranking of bulls on different country scales under multiple-trait model. Lactation persistency had in general lower between-country correlations, with the highest values for Canada-Italy and Australia-New Zealand pairs, for both single- and multiple-country models. Although multiple-country random regression test-day model was computationally feasible for four countries, the same would not be true for routine international genetic evaluation in the near future.

Age Factors↗

PubMed2002

Estimates of genetic parameters for single- and multiple-country test-day models.

Single- and multiple-country random regression models were applied to estimate genetic parameters for first-lactation test-day milk yield of cows from four countries: Australia, Canada, Italy, and New Zealand. Selected countries represented a wide range of production systems and environments. Milk production in Canada and Italy is based mainly on intensive management systems, while Australia and New Zealand are largely based on rotational grazing. Legendre polynomials with five coefficients were used to model genetic and environmental lactation curves. Covariance components of lactation curve coefficients within and across countries, and selected functions of those, were estimated by Bayesian methods with Gibbs sampling, on selected subsets of data. Countries differed in both phenotypic and genetic parameters of lactation curves between d 5 and 305 of lactation. Principal component analysis of single-trait genetic and environmental covariance matrices showed, however, that the pattern of variability in test-day milk yield was very similar between countries. General level of milk production in lactation and persistency components accounted for more than 90% of the total variance. Estimated genetic correlations between countries for total yield in lactation ranged from 0.65 (Italy and New Zealand) to 0.83 (Australia and New Zealand), indicating a possibility of genotype by environment interaction for some pairs of countries.

Animal Husbandry↗

PubMed2000

New spirans containing a 1,5-benzodithiepine system, derived from methylbenzenes. Conformational transmission

[structure: see text] A synthesis of three new spirans, derived from methylbenzenes, containing the 1,5-benzodithiepine system is reported. X-ray structure proved the identity of model monospiran 9. In the solid and liquid state, the conformation of the seven-membered ring is chair, and the five-membered ring has the envelope conformation. The effect of conformational transmission in spirans 9 and 10 was observed. The synthesis of trispirans from hexamethylbenzene using the proposed scheme is also possible.

Journal Article↗

PubMed2000

Strategies for estimating the parameters needed for different test-day models.

Currently, most analyses of parameters in test-day models involve two types of models: random regression, where various functions describe variability of (co)variances with regard to days in milk, and multiple traits, where observations in adjacent days in milk are treated as one trait. The methodologies used for estimation of parameters included Bayesian via Gibbs sampling, and REML in the form of derivative-free, expectation-maximization, or average-information algorithms. The first method is simpler and uses less memory but may need many rounds to produce posterior samples. In REML, however, the stopping point is well established. Because of computing limitations, the largest estimations of parameters were on fewer than 20,000 animals. The magnitude and pattern of heritabilities varied widely, which could be caused by simplifications in the model, overparameterization, small sample size, and unrepresentative samples. Patterns of heritability differ among random regression and multiple-trait models. Accurate parameters for large multi-trait random regression models may be difficult to obtain at the present time. Parameters that are sufficiently accurate in practice may be obtained outside the complete prediction model by a constructive approach, where parameters averaged over the lactation would be combined with several typical curves for (co)variances for days in milk. Obtained parameters could be used for any model, and could also aid in comparison of models.

Analysis of Variance↗

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

Estimates of genetic parameters for a test day model with random regressions for yield traits of first lactation Holsteins.

A model that contains both fixed and random linear regressions is described for analyzing test day records of dairy cows. Estimation of the variances and covariances for this model was achieved by Bayesian methods utilizing the Gibbs sampler to generate samples from the marginal posterior distributions. A single-trait model was applied to yields of milk, fat, and protein of first lactation Holsteins. Heritabilities of 305-d lactation yields were 0.32, 0.28, and 0.28 for milk, fat, and protein, respectively. Heritabilities of daily yields were greater than for 305-d yields and varied from 0.40 to 0.59 for milk yield, 0.34 to 0.68 for fat yield, and 0.33 to 0.69 for protein yield. The highest heritabilities were within the first 10 d of lactation for all traits. Genetic correlations between daily yields were higher as the interval between tests decreased, and correlations of daily yields with 305-d yields were greatest during midlactation.

Algorithms↗

PubMed1997

Genetic evaluation of dairy cattle using test day yields and random regression model.

A model for analyzing test day records that contains both fixed and random regression coefficients was applied to the genetic evaluation of first lactation data for Canadian Holstein dairy cows. Data were 5.1 million test day records with milk, fat, and protein yields from calvings between 1988 and 1995 from herds in four regions of Canada. Each evaluated animal received five predictions for each trait representing the random regression coefficients. From these solutions, a range of estimated breeding values for various parts of the lactation could be calculated. Three genetic measures of persistency were compared. Bulls could be selected for both yields and persistency of their daughters in whatever combination was desirable. Test day analyses could result in monthly genetic evaluations for yield traits.

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↗

PubMed1996

Factors influencing international comparisons of dairy sires.

A method of dairy sire evaluation across multiple countries is described. Factors influencing this method are overestimation of genetic trends within countries, inclusion of evaluations of imported bulls, years of birth of the bulls included in the analysis, and estimates of genetic correlations between countries. Fall 1994 evaluations for milk, fat, and protein yields from Canada (4559 bulls), Germany (5894 bulls), and France (8419 bulls) were used to study the effect of these factors. After inclusion of ancestors there were 21,555 bulls in total. Eight data files were created based on combinations of three factors: 1) bulls born from 1970 to present versus bulls born from 1979 to present, 2) all bulls included versus imported bulls omitted, and 3) official Canadian evaluations for all lactations versus Canadian evaluations for first lactation only. Separate evaluations for two of the data files assumed a uniform genetic correlation of 0.995 between countries. Rankings of top bulls from analyses were affected by all factors to various degrees, depending on the country. Evaluations of imported bulls have an effect on bull rankings and probably should not be included. An assumed uniform genetic correlation between countries of 0.995 may not be appropriate. Proper methods and data for estimation of the genetic correlation between countries should be sought.

Animals↗

PubMed1996

Multiple-trait prediction of lactation yields for dairy cows.

A multiple-trait procedure is described for predicting 305-d lactation yields for milk, fat, and protein that incorporates information about standard lactation curves and covariances between yields for milk, fat, and protein. Test day yields are weighted by their relative variances, and standard lactation curves of cows from similar breed, region, lactation number, age, and season of calving are used for the estimation of lactation curve parameters for each cow. Accuracies of the test interval method and the multiple-trait procedure were comparable. In addition, the multiple-trait procedure can handle long intervals between test days as well as test days with milk only recorded and can make 305-d predictions on the basis of just one test day record per cow. The procedure also lends itself to the calculation of peak yield, day of peak yield, yield persistency, and expected test-day yields, which could be useful management tools for a producer on a milk recording program.

Animals↗