Abstract

Sensory beef qualities could be impacted throughout the farm-to-fork continuum. The aim of this work was to predict the sensory quality classes of Longissimus muscle established from three sensory descriptors: tenderness, juiciness and flavour intensity. The extreme classes of meat quality were: Q + class including the highest scores for tenderness and juiciness, and an intermediate score for flavour intensity and Q − class including low scores for tenderness, juiciness and flavour intensity. To predict the extreme quality classes, seven decision trees were performed using the individual data related to rearing factors (p = 50), carcase traits (p = 13) and/or aged meat traits (p = 9) of 100 Charolais heifers. The decision trees established from rearing factors and carcass trait data (RF-CARCA-Tree) allowed the highest accuracy of prediction (79.7%) with 90.7% and 66.7% of correctly classified individuals, respectively. Our results showed that different combinations of factors could produce Q + class. Three rearing factors (i.e. the calculated average of concentrates’ net energy content in the diet during the pasture period of pre-weaning period (PWP); the number of days concentrates were offered in calf diet during PWP; and the calculated average of concentrates’ crude protein content in the fattening diet) and the conformation score could be considered as action levers to improve meat quality. These three rearing factors were related to the pre-weaning and fattening periods of the heifer, slowing a possible management of the potential beef quality from rearing factors throughout the life of the heifer. Highlights Beef quality can be improved throughout the heifer’s life by rearing factors related to concentrate in the diet. Sensory beef quality classes could be managed from rearing factors and carcass traits. Raw aged meat data did not allow to improve the prediction of sensory beef quality classes.

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