Abstract
This study aimed to verify the effect of age of dam on the performance of male and female Nellore calves, using the following variables: average daily gain (ADG), adjusted weight for 205 days of age (W205), and number of days to reach 160 kg (D160). Information were collected from a commercial herd consisting of 1,122 calves and 1,009 heifers and their mothers. To classify animals with similar performance based on the cows’ calving orders (age of dam), the multivariate cluster analysis was adopted through the complete linkage hierarchical method. The best performance was observed in the calves of cows in their sixth calving at most; for heifers, the best performance was seen in those born to cows in their eighth calving at most. Cows in their eighth calving should be discarded.
Highlights
According to Boligon, Albuquerque, Mercadante and Lôbo (2009), increased weight gain in the preweaning phase has a positive effect on slaughter age reduction
The most commonly used ways to assess the performance of animals in this phase are average daily gain (ADG), adjusted weight at a pre-established age, and number of days to reach a certain weight (Pilau & Lobato, 2009; Souza et al, 2010; Lopes, Santos, Marques, Silva, & Ferreira, 2012)
The objective of this study was to assess the performance of Nellore calves and heifers as a function of the cows’ age of dam, using as criteria the ADG, weight for 205 days of age (W205) and days to reach 160 kg (D160) variables, through cluster analysis
Summary
According to Boligon, Albuquerque, Mercadante and Lôbo (2009), increased weight gain in the preweaning phase has a positive effect on slaughter age reduction. The most commonly used ways to assess the performance of animals in this phase are average daily gain (ADG), adjusted weight at a pre-established age, and number of days to reach a certain weight (Pilau & Lobato, 2009; Souza et al, 2010; Lopes, Santos, Marques, Silva, & Ferreira, 2012). Performance from birth to weaning is one of the first indications of genetic potential for an animal to gain weight. The expression of this quantitative phenotypic characteristic is due to its genes, and influenced by month of birth, the cow’s gestational age, the calf’s weaning age, the matrix’s maturity weight, the mother’s racial composition, the calf’s sex, and correlations between these variables (Castro-Pereira, Alencar, & Barbosa, 2007; Bocchi, Oliveira, Ferraz, & Eler, 2008; Queiroz, Costa, Oliveira, & Fries, 2009; Barichello, Alencar, Torres Jr., & Silva, 2011; Fialho et al, 2015). With the advent of computers, more complex analyses have emerged that can present solutions to problems in a more consistent way, with highlight to multivariate statistical methods, which are exploratory analyses that allow generating hypotheses on the object studied, using several variables simultaneously (Ferreira, 2008; Silva et al, 2011)
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