Pre- and post-slaughter data can be used to discriminate sensory beef quality clusters in cull cows

Abstract

Using data from 91 Charolais cull cows, 7 decision trees were performed to discriminate extreme sensory Longissimus muscle (LM) quality clusters (Q+ and Q-). The decision trees were established from different groups of available data (60 variables in the rearing-factor group; 13 variables in the carcass-trait group; 9 variables in aged meat data group) and their combinations. Clusters of sensory quality were established from 3 sensory descriptors: overall tenderness, overall juiciness, and flavor intensity. The Q+ cluster had the highest tenderness, juiciness, and flavor intensity scores, and the Q- cluster had the lowest scores. The decision trees established from either carcass traits only (CARCA-Tree) or rearing factors and carcass traits combined (RF-CARCA-Tree) had the highest rates of success (> 74 %) in discriminating the quality clusters. This study identified various combinations of rearing factors and/or carcass traits that can help improve meat quality. The rearing factors and carcass traits selected were: presence of concentrate in the diet during the outside pre-weaning period, duration of forage supplementation during the outside breeding period, average crude protein content of the concentrate across the fattening period, ultimate pH (pHu), and collagen score. Carcass pHu and collagen score, which are readily accessible data, had the highest rate of success (74.7 %) in successfully discriminating the meat quality clusters in the CARCA-Tree. Our results showed that 76.8 % of carcasses were categorized as Q+ when cull cow carcass had a pHu value > 5.3 and a collagen score ≤ 1.5.