Abstract
Efficiency of data transformation strategies is evaluated to correct heterogeneity among cattle in the genetic evaluation of bulls, cows and progenies. Four data structures of bovine weaning weights were simulated: herds with and without heterogeneity for means and variances, and herds with and without genetic connectedness. In the genetic evaluations, data were used in the original scale and transformed (Logarithmic, Square root, standardization and ratio by phenotypic standard deviation). The evaluated data transformation strategies were not efficient in eliminating the negative effects of heterogeneity among cattle in the genetic evaluation of bulls, cows and progenies.
Highlights
Cattle herds undergoing genetic evaluations do not generally present the same means and the same genetic and phenotype variances
When there is no heterogeneity among the herds and for simulated data without any genetic linkage, order correlation among genetic rates was close to 1 and varied between 82 and 96% (Table 3)
Regardless of the scale used, heterogeneity among the herds had a great influence on the genetic evaluation of steers, cows and progenies
Summary
Cattle herds undergoing genetic evaluations do not generally present the same means and the same genetic and phenotype variances. In other words, they present heterogeneity for such parameters. Heterogeneity among cattle herds reduce the efficiency of genetic evaluations and impair genetic progress. Variance heterogeneity among cattle herds for production characteristics in dairy cattle and for performance in beef cattle is amply documented (CAMPELO et al, 2003; TORRES et al, 2000). Variance heterogeneity was even found within the same cattle herd with regard to fixed effects of gender, year and date of birth, age of cow at birth, pregnancy of the animal and randomized effect of steers for data on growth rate and scrotum circumference of Canchin breed animals (FREITAS, 2000). Variance heterogeneity was even found within the same cattle herd with regard to fixed effects of gender, year and date of birth, age of cow at birth, pregnancy of the animal and randomized effect of steers for data on growth rate and scrotum circumference of Canchin breed animals (FREITAS, 2000). Carneiro et al (2008), who
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