Multivariate modelling to estimate carcase characteristics and commercial cuts of Boer goats

Abstract

The objective was to establish a multivariate model using two complementary multivariate statistical techniques, factor analysis and multiple stepwise regression to predict carcase characteristics, carcase cuts, internal fat, viscera and loin eye area from body measurements of goats Boer mestizos. Thirty-two goats were used, with initial average weights of 3.3 ± 0.61 kg and final average weights of 16 ± 2.5 kg. Before slaughter and after 16 h of fasting, body weight was measured along with the biometric measurements (BMs) of each animal: body length, withers height, croup height, chest width, croup width, croup perimeter, thoracic perimeter, leg length and thigh circumference. The half carcases were sectioned in six anatomical regions that made up the commercial cuts: neck, palette, rib, handsaw, loin and ham. BMs showed a high correlation with a few exceptions; most of the correlations are above 50%. What also happens with the Carcass weight and cuts were also correlated above 50% with BMs. The data presented an index for the Kaiser–Meyer–Olkin test of 0.80, demonstrating the adequacy of the factor analysis. Through factor analysis, it was possible to observe that the first two factors extracted accumulated 75.47% of the total variance of the studied characteristics. Moderate to high and positive correlations of morphological characteristics with body weight, carcase characteristics and primary carcase cuts suggested the adequacy of morphological characteristics as criteria for early selection of crossbred Boer goats for their body weight and carcase characteristics without slaughter.

Canonical discriminant analysis on the characterization of the goat carcass

“…However, this technique is a specialty of discriminant analysis and is used to represent several populations in a small subspace (Guedes, Ribeiro, & Carvalho, 2018). Some studies have already been carried out using the discriminant analysis with carcass characteristics of other species (Almeida et al, 2015), and sheep carcass characteristics (Paim et al, 2013;Notter et al, 2014;Camacho, 2015) however, work with goats is still scarce (Macena et al, 2022) mainly to identify the essential variables that discriminate groups according to the sex and age of the animals. Therefore, the objective of this work is to identify which carcass and cut characteristics have the best discriminatory power, between sexes and slaughter weights, through discriminant analysis.…”

Multivariate modeling to estimate the composition of carcass tissues of Santa Inês sheep

“…Önk, Sari, and Gürcan (2018), Tahtali (2019) and Tariq et al (2012) also used factor scores to estimate body weights in lambs. In a recent study, factor analysis and multiple stepwise regression were used to predict carcass characteristics, carcass cuts, internal fat, viscera and loin eye area from body measurements of crossbred Boer goats (Macena et al, 2022).…”