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Contribution to Characterizing the Meat Quality of Protected Designation of Origin Serrana and Preta de Montesinho Kids Using the Near-Infrared Reflectance Methodology

Authors :
Lia Vasconcelos
Luís G. Dias
Ana Leite
Etelvina Pereira
Severiano Silva
Iasmin Ferreira
Javier Mateo
Sandra Rodrigues
Alfredo Teixeira
Source :
Foods, Vol 13, Iss 10, p 1581 (2024)
Publication Year :
2024
Publisher :
MDPI AG, 2024.

Abstract

The aims of this study were to describe and compare the meat quality characteristics of male and female kids from the “Serrana” and “Preta de Montesinho” breeds certified as “Cabrito Transmontano” and reinforce the performance of near-infrared reflectance (NIR) spectra in predicting these quality characteristics and discriminating among breeds. Samples of Longissimus thoracis (n = 32; sixteen per breed; eight males and eight females) were used. Breed significantly affected meat quality characteristics, with only color and fatty acid (FA) (C12:0) being influenced by sex. The meat of the “Serrana” breed proved to be more tender than that of the “Preta de Montesinho”. However, the meat from the “Preta de Montesinho” breed showed higher intramuscular fat content and was lighter than that from the “Serrana” breed, which favors its quality of color and juiciness. The use of NIR with the linear support vector machine regression (SVMR) classification model demonstrated its capability to quantify meat quality characteristics such as pH, CIELab color, protein, moisture, ash, fat, texture, water-holding capacity, and lipid profile. Discriminant analysis was performed by dividing the sample spectra into calibration sets (75 percent) and prediction sets (25 percent) and applying the Kennard–Stone algorithm to the spectra. This resulted in 100% correct classifications with the training data and 96.7% accuracy with the test data. The test data showed acceptable estimation models with R2 > 0.99.

Details

Language :
English
ISSN :
23048158
Volume :
13
Issue :
10
Database :
Directory of Open Access Journals
Journal :
Foods
Publication Type :
Academic Journal
Accession number :
edsdoj.2d17a51c76f54417b8a52bc652712cdf
Document Type :
article
Full Text :
https://doi.org/10.3390/foods13101581