Abstract
The tendency to fight is a well-known behavior in Valdostana cattle, and noncruel traditional contests are organized yearly by farmers to identify the most dominant cow. Cow battles consist of elimination matches that have important economic implications for both tourism and farmers. The aims of this study are 1) to validate a scoring system to express fighting ability, and 2) to carry out a genetic analysis for this trait using different data sets and models. A data set accounting for 16,509 fighting records of 5,981 cows relevant to contests over 6 yr was retained after editing (data set 1). Data on placements were used to compute a placement score accounting for wins, tournament size, and difficulty, and differentiating the 20 preliminary battles each year from the final match. A second data set was created using only the individual best yearly placement scores, that is, deleting repeats with a smaller placement score for the same animal within each year (data set 2; n = 10,367 records, corresponding to a single datum per year per cow). Compared with the placement or position of each cow, the placement score proved to be less skewed (−1.45 for placement position and 1.25 for placement score, respectively) and exhibited better coefficients for the probability of a normal distribution. An animal model REML method analysis (accounting for 13,456 animals in the pedigree) was carried out, with consideration given to different combinations of fixed and random nongenetic factors other than the random animal and permanent environmental effects. Results indicated that random factors other than additive genetic and permanent environment effects did not improve the model fit; therefore, it was not useful to take them into account. Heritability estimates obtained with the model showing the best fit were 0.078 (data set 1) and 0.098 (data set 2). Results of this study indicate that selection for fighting ability in Valdostana cattle using data on battle performance is possible. Copyright © 2010. American Society of Animal Science .