Vis-NIRS as an auxiliary tool in the classification of bovine carcasses
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.
Authors
- Saulo da Luz e Silva (ORCID: https://orcid.org/0000-0002-0849-9948)
- Gabriella Augusto Pereira (ORCID: https://orcid.org/0009-0002-1558-8196)
- GC Pereira (ORCID: https://orcid.org/0000-0001-5200-9283)
- Melissa Amin (ORCID: https://orcid.org/0000-0002-1898-7056)
- Marília Williani Filgueira Pereira (ORCID: https://orcid.org/0000-0003-1395-8368)
- G. L. D. Feijó (ORCID: https://orcid.org/0000-0003-0278-1755)
- Jaqueline Rodrigues Ferreira Cara (ORCID: https://orcid.org/0000-0002-4938-1970)
- G. R. de O. Menezes (ORCID: https://orcid.org/0000-0002-2221-1525)
- Lucy Mery Antonia Surita (ORCID: https://orcid.org/0000-0003-0501-6063)
- Luís Carlos Vinhas Ítavo (ORCID: https://orcid.org/0000-0001-6895-8483)
- Marina de Nadai Bonin Gomes (ORCID: https://orcid.org/0000-0002-6910-9368)
- Rodrigo da Costa Gomes (ORCID: https://orcid.org/0000-0001-8410-7216)
Institutions
- Universidade Federal de Mato Grosso do Sul (BR)
- Universidade de São Paulo (BR)
- Brazilian Agricultural Research Corporation (BR)
- Universidade Federal Rural do Semi-Árido (BR)
Publication Details
- Journal
- PLoS ONE
- Published
- 2025-01-23
- DOI
- https://doi.org/10.1371/journal.pone.0317434
- Primary Topic
- Identification and Quantification in Food
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
- Conselho Nacional de Desenvolvimento Científico e Tecnológico
- Fundação de Apoio ao Desenvolvimento do Ensino, Ciência e Tecnologia do Estado de Mato Grosso do Sul
- Universidade Federal de Mato Grosso do Sul