N. Künzi

Factor analysis for evaluating relationships between herd life and type traits in Swiss Brown cattle

The genetic and phenotypic correlation matrices of 18 type traits scored during the first lactation on 9224 daughters of 274 Swiss Brown test sires were used to derive uncorrelated genetic and phenotypic factors for evaluating relationships of two herd life measures with type traits. A principal component analysis was applied to the correlation matrices to choose genetic and phenotypic components which mostly account for the total variation in type traits. Five genetic and five phenotypic components, explaining 74% of the total genetic and 58% of the total phenotypic variation in type traits respectively, were retained for the subsequent analysis. New genetic and phenotypic factors were defined by principal factor analysis. The new factors were then rotated in order to determine contribution of the individual traits to the particular factors. Factor pattern coefficients were used to compute genetic and phenotypic factor scores from the original type traits. Sire PTA for genetic factor scores, and cow phenotypic factor scores were used as explanatory variables in a multiple regression analysis to model the relation between herd life and the factors. Both herd life measures considered — true and functional herd life — were influenced by genetic and phenotypic factors which include udder and teat traits, typical dairy body characteristics, and certain feet and leg traits. Sire PTA for genetic factors explained about 13 of total genetic variance in herd life. Both genetic and phenotypic factors for type traits explained only a small part of the variance in herd life. The revision of the type classification system is recommended.

Genetic relationships among longevity, milk production, and type traits in Swiss Brown cattle

Abstract The length of productive life and its relationships with production and type traits in Swiss Brown cattle was investigated using data from test sire progeny type evaluation. Data included records on 9 224 daughters of 274 sires, which had an opportunity to stay in the herd for at least 84 mo. True (TPL) and functional (FPL) productive life observed 48, 66, and 84 mo after first calving were analysed. FPL was computed by adjusting TPL for first lactation milk yield relative to herd average. Production traits included first lactation milk, fat and protein yield and fat and protein content. Type traits included measurements for wither height and heart girth and numerical scores of 16 other traits. (Co) variances were estimated with multiple-trait REML using a sire model. Heritabilities for all herd life measures ranged from 0.03 to 0.14 and were considerably higher for TPL than for FPL. Genetic correlations among TPL and corresponding FPL measures were approximately 0.8. The genetic correlations between yield traits and both TPL and FPL were positive and on the average amounted to 0.75 for TPL and 0.35 for FPL. The phenotypic correlations for FPL were all close to zero. Almost all type traits were positively correlated with productive life. The highest genetic correlations were obtained between productive life and udder and teat traits.

Comparison of models to estimate maternal effects for weaning weight of Swiss Angus cattle fitting a sire×herd interaction as an additional random effect

Field data of Swiss Angus cattle were used to explore the consequences of including in the model additional random effects, such as maternal effects and a sire×herd interaction (SH), on the estimates of genetic parameters for weaning weight. Data were analysed using Restricted Maximum Likelihood (REML), applied to animal models comprising fixed effects of herd, year of birth, month of birth, sex, birth type, age of dam and age of calf at weaning. All investigated models included a random direct genetic effect, but differed for combinations of random maternal genetic and permanent environmental effects as well as for direct-maternal genetic covariance and for sire×herd interaction. The models including SH effect fitted the data significantly better (P<0.01) than those ignoring the interaction. Ignoring SH effect resulted in a strong negative correlation between additive direct and maternal effects. The models including SH resulted in reduced estimates of direct and maternal genetic variance and of direct-maternal genetic covariance and, consequently, in a less negative correlation between direct and maternal genetic effects. With the inclusion of SH effect in the model, the direct-maternal covariance was no longer statistically significant. The SH variance represented only 7% of the phenotypic variance but accounted for a great amount of the covariance between direct and maternal genetic effects estimated ignoring SH.

Genetic evaluation of on-farm tested pigs using an animal model I. Estimation of variance components with restricted maximum likelihood

Variance components of average daily gain (ADG) and premium cuts in proportion to carcass weight (PCP) estimated from ultrasonic measurements for on-farm tested Yorkshire and Landrace pigs in Switzerland were estimated by REML (restricted maximum likelihood) using an animal model. In order to keep computing costs reasonable, three subsets of data with at least 10 000 tested animals were sampled by herd from the complete data set for each breed. The single trait model contained fixed herd × year × season, sex, and unknown parent group effects and a linear regression on live weight, as well as random litter and animal effects. The estimated variance components from the data subsets were averaged within breed. Although the estimates from the different subsets varied considerably, the mean estimates were similar for both breeds and in agreement with values reported in the literature. For ADG the estimates of heritability (h2) were 0.16 and 0.20, and the estimates of the litter variance in proportion to the phenotypic variance (c2) were 0.42 and 0.49 for the Yorkshire and Landrace breed, respectively. For PCP h2 estimates for Yorkshire and Landrace pigs were 0.44 and 0.42, respectively, and c2 estimates were 0.16 for both breeds. The values found for phenotypic, genetic and litter correlations between ADG and PCP ranged from −0.12 to −0.24.

Comparison of models with a fixed or a random contemporary group effect for the genetic evaluation for litter size in pigs

Abstract This paper compares alternative models with respect to the accuracy of prediction of randomly chosen observations excluded from the genetic evaluation. REML variance components were estimated with a linear mixed model for number of piglets born alive of Swiss Landrace (SL) and Swiss Large White (LW) sows. The two alternative models assume a fixed herd ∗ time period ( h × t ) effect and a random h × t effect, respectively. For two additional random models the variance ratios of the fixed model were used, but the ratio of residual to h × t variance varied. Repeatedly, a small set of randomly chosen observations were excluded from the data and predicted based on estimates obtained from the remaining data. The random models predicted excluded observations more accurately than the fixed model but there was nearly no difference between the models to predict observations from h × t with more records. Differences between the random models were small. Due to a better structure of the LW data, differences between models to predict observations were considerably smaller than for SL. For the analysed data a model with a random h × t effect is recommended.

Genetic evaluation of on-farm tested pigs using an animal model II. Prediction of breeding values with a multiple trait model

Abstract The aim of this study was to examine the application of best linear unbiased prediction (BLUP)with a multiple trait animal model for the genetic evaluation of on-farm tested pigs. The analysis was based on test results of 197 949 Yorkshire (Y) and 70 550 Landrace (L) pigs tested in Switzerland from 1976 to 1987. The two traits considered were average daily gain (ADG) and premium cuts in proportion to carcass weight (PCP) estimated from ultrasonic measurements. The model contained fixed herd × year × season, sex, unknown parent group effects and the linear regression on live weight, as well as random litter and animal effects. The mixed model equations with 582 698 (Y) and 211 768 (L) unknowns were solved by ‘iteration on the data’. Inbreeding was taken into account. The average inbreeding coefficient of parents born in 1986 was 1% and 1.5% in the Y and L breed, respectively. On the supercomputer CRAY X-MP/28 all the data were kept in memory. The computing time (CPU time) required for one round of iteration was 2.5 (Y) and 0.9 (L) seconds. 100 rounds of iteration were sufficient for the estimation of genetic trend. In both traits genetic trend was positive for both breeds. During the 12 years considered, ADG improved genetically by 6.5 g/day and 10.3 g/day, and PCP by 1.9% and 1.2% in the Y and L breed respectively. The effect of ignoring inbreeding on predicted breeding values was small.

Multiple trait model combining random regressions for daily feed intake with single measured performance traits of growing pigs

A random regression model for daily feed intake and a conventional multiple trait animal model for the four traits average daily gain on test (ADG), feed conversion ratio (FCR), carcass lean content and meat quality index were combined to analyse data from 1 449 castrated male Large White pigs performance tested in two French central testing stations in 1997. Group housed pigs fed ad libitum with electronic feed dispensers were tested from 35 to 100 kg live body weight. A quadratic polynomial in days on test was used as a regression function for weekly means of daily feed intake and to escribe its residual variance. The same fixed (batch) and random (additive genetic, pen and individual permanent environmental) effects were used for regression coefficients of feed intake and single measured traits. Variance components were estimated by means of a Bayesian analysis using Gibbs sampling. Four Gibbs chains were run for 550 000 rounds each, from which 50 000 rounds were discarded from the burn-in period. Estimates of posterior means of covariance matrices were calculated from the remaining two million samples. Low heritabilities of linear and quadratic regression coefficients and their unfavourable genetic correlations with other performance traits reveal that altering the shape of the feed intake curve by direct or indirect selection is difficult.

Relative carcass value of Simmental, Holstein and their crosses based on veal calves, fattening bulls and culled cows in Switzerland

Abstract Retail carcass values of Simmental, Holstein Friesians and their crosses were determined using full dissection of the left carcass side. Alternative dairy by dual purpose breed crosses were fattened on contract farms (calves and bulls) or sampled from commercial abattoirs (cows). The carcass fat percentages of the different genotypes were not significantly different within calves, bulls and young cows. For older cows, fat percentages were standardized to 7.5%. The carcass values significantly decreased with increasing Holstein Friesian gene percentage within all categories. The decrease in the deviations per kg of cold carcass weight from pure Simmental to Black and White Holsteins amounts to 3.81% in calves, 4.38% in bulls, 21.87% in young cows and 8.54% in old cows. Prediction equations for carcass values across genotypes were best using lean percentage and premium cut percentage. It was concluded that pricing systems should focus on these traits.

Relationship between own performance test and progeny test for beef production traits in Swiss dual-purpose cattle

Abstract In Switzerland, selection of dual-purpose bulls for beef traits is based on individual and progeny performance. Bulls with satisfactory development in the performance test may later be progeny tested for beef characteristics. Genetic parameters were estimated for daily gain in two consecutive periods of the individual performance test and for the traits carcass gain, carcass score and thigh volume in the progeny test. From the 992 Braunvieh and 1154 Simmental bulls, about 25% had results in both tests. The pedigree was traced back to the grandparents of the tested bulls. Parameters were estimated separately for each breed using an animal model for the performance-test traits and a sire model for the progeny-test traits. Two- and three-trait models were applied to estimate (co) variances. For the Simmental breed, parameters among the three growth traits agree well with the literature. In comparison, the estimated heritability for Braunvieh was lower for the daily gain of the individual performance and higher for the carcass gain. For both breeds, clear positive correlations were found between carcass score and gain traits. Thigh volume is less heritable and only weakly, but positively, correlated with the other traits.