Vis-NIRS as an auxiliary tool in the classification of bovine carcasses - Gabriela Zardo Pereira; Gabriel de Morais Pereira; Rodrigo da Costa Gomes; Gelson Luís Dias Feijó; Lucy Mery Antonia Surita; Marília Williani Filgueira Pereira; Gilberto Romeiro de Oliveira Menezes; Jaqueline Rodrigues Ferreira Cara; Luis Carlos Vinhas Ítavo; Saulo da Luz e Silva; Melissa Amin; Marina De Nadai Bonin Gomes (PLoS ONE, 2025)
This work aimed to evaluate the use of Visible and Near-infrared Spectroscopy (Vis-NIRS) as a tool in the classification of bovine carcasses. A total of 133 animals (77 females, 29 males surgically castrated and 27 males immunologically castrated) were used. Vis-NIRS spectra were collected in a chilling room 24 h postmortem directly on the hanging carcasses over the longissimus thoracis between the surface of the 5th and 6th ribs. The data were evaluated by principal component analysis (PCA) and the partial least squares regression (PLSR) method. For the prediction of sex, the best model was the Standard Normal Variate (SNV) because it presented a relatively high coefficient of determination for prediction, presenting a percentage of correctness of 75.51% and an error of 24.49%. Regarding age, none of the models were able to differentiate the samples through Vis-NIRS. The findings confirm that Vis-NIRS prediction models are a valuable tool for differentiating carcasses based on sex. To further enhance the precision of these predictions, we recommend using Vis-NIRS equipment with the full infrared wavelength range to collect and predict sex and age in intact beef samples.