Non-invasive meat quality assessment: Exploring the potential of ocular infrared thermography to predict ultimate pH in Nellore beef cattle.

Autor: Ferreira GA; Departament of Animal Science, State University of Londrina (UEL), Rodovia Celso Garcia Cid PR 445 km 380, 86.057-970, Londrina, Brazil., Barro AG; Departament of Animal Science, State University of Londrina (UEL), Rodovia Celso Garcia Cid PR 445 km 380, 86.057-970, Londrina, Brazil., Bueno CEM; Departament of Animal Science, State University of Londrina (UEL), Rodovia Celso Garcia Cid PR 445 km 380, 86.057-970, Londrina, Brazil., Terto DK; Departament of Animal Science, State University of Londrina (UEL), Rodovia Celso Garcia Cid PR 445 km 380, 86.057-970, Londrina, Brazil., Dos Santos ÉR; Departament of Animal Science, State University of Londrina (UEL), Rodovia Celso Garcia Cid PR 445 km 380, 86.057-970, Londrina, Brazil., Ogawa NN; Departament of Animal Science, State University of Londrina (UEL), Rodovia Celso Garcia Cid PR 445 km 380, 86.057-970, Londrina, Brazil., de Carvalho RH; Departament of Animal Science, State University of Londrina (UEL), Rodovia Celso Garcia Cid PR 445 km 380, 86.057-970, Londrina, Brazil., Bridi AM; Departament of Animal Science, State University of Londrina (UEL), Rodovia Celso Garcia Cid PR 445 km 380, 86.057-970, Londrina, Brazil. Electronic address: ambridi@uel.br.
Jazyk: angličtina
Zdroj: Meat science [Meat Sci] 2024 Jul; Vol. 213, pp. 109483. Date of Electronic Publication: 2024 Mar 11.
DOI: 10.1016/j.meatsci.2024.109483
Abstrakt: This study investigated the use of infrared thermography (IRT) to identify the dark, firm, and dry (DFD) phenomenon in Brazilian beef, which is a significant concern for the industry because of its inferior quality and reduced shelf life. This study examined 113 Nellore bulls and analyzed their minimum and maximum ocular temperatures using IRT. The results highlight the efficacy of thermal images (IRTmax) as a significant predictor, with R 2 values ranging from 0.84 to 0.88 for calibration models. The inclusion of parameters such as glucose and lactate further enhanced prediction accuracy. The models also revealed that the combination of features, such as lightness (L*), redness (a*), and yellowness (b*), contributed to the precise prediction of pHu, with an R 2 of 0.88. In model validation, RMSEP ranged from 0.104 to 0.158, indicating good generalization capability. The RPD, ranging from 1.7 to 2.6, suggests satisfactory quantitative prediction. The statistical significance of all models, evidenced by P-values <0.001, strengthens the reliability of the results. In conclusion, the models support the use of IRT as a tool for identifying pHu alterations in carcasses. When combined with blood parameters, they may exhibit even greater efficiency in predicting pHu in Nelore cattle carcasses, highlighting the potential applicability of these methods in the beef industry.
Competing Interests: Declaration of competing interest The authors declare no competing interests in relation to the study.
(Copyright © 2024 Elsevier Ltd. All rights reserved.)
Databáze: MEDLINE
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