SVM Regression to Assess Meat Characteristics of Bísaro Pig Loins Using NIRS Methodology

Lia Vasconcelos; Luís G Dias; Ana Leite; Iasmin Ferreira; Etelvina Pereira; Severiano Silva; Sandra Rodrigues; Alfredo Teixeira

doi:10.3390/foods12030470

SVM Regression to Assess Meat Characteristics of Bísaro Pig Loins Using NIRS Methodology

Foods. 2023 Jan 19;12(3):470. doi: 10.3390/foods12030470.

Authors

Lia Vasconcelos^{1

2}, Luís G Dias^{1

2}, Ana Leite^{1

2}, Iasmin Ferreira^{1

2}, Etelvina Pereira^{1

2}, Severiano Silva³, Sandra Rodrigues^{1

2}, Alfredo Teixeira^{1

2}

Affiliations

¹ Mountain Reserach Center (CIMO), Polytechnic Institut of Bragança, Campus de Santa Apolónia, 5300-253 Bragança, Portugal.
² Laboratory for Sustainability and Technology in Mountain Regions, Polytechnic Institut of Bragança, Campus de Santa Apolónia, 5300-253 Bragança, Portugal.
³ Veterinary and Animal Research Centre (CECAV), Associate Laboratory of Animal and Veterinary Science (AL4AnimalS), University of Trás-os-Montes e Alto Douro, 5000-801 Vila Real, Portugal.

Abstract

This study evaluates the ability of the near infrared reflectance spectroscopy (NIRS) to estimate the aW, protein, moisture, ash, fat, collagen, texture, pigments, and WHC in the Longissimus thoracis et lumborum (LTL) of Bísaro pig. Samples (n = 40) of the LTL muscle were minced and scanned in an FT-NIR MasterTM N500 (BÜCHI) over a NIR spectral range of 4000-10,000 cm^-1 with a resolution of 4 cm^-1. The PLS and SVM regression models were developed using the spectra's math treatment, DV1, DV2, MSC, SNV, and SMT (n = 40). PLS models showed acceptable fits (estimation models with RMSE ≤ 0.5% and R² ≥ 0.95) except for the RT variable (RMSE of 0.891% and R² of 0.748). The SVM models presented better overall prediction results than those obtained by PLS, where only the variables pigments and WHC presented estimation models (respectively: RMSE of 0.069 and 0.472%; R² of 0.993 and 0.996; slope of 0.985 ± 0.006 and 0.925 ± 0.006). The results showed NIRs capacity to predict the meat quality traits of Bísaro pig breed in order to guarantee its characterization.

Keywords: Bísaro pig; Longissimus thoracis et lumborum; NIR; SVM model; meat quality.

Grants and funding

This research was funded by Project PRODER SI I&DT Medida 4.1 “Cooperação para a Inovação”.The research get financial support through national funds: the Foundation for Science and Technology (FCT, Portugal), FCT/MCTES (PIDDAC) to CIMO (UIDB/00690/2020 and UIDP/00690/2020) and SusTEC (LA/P/0007/2021); and the Laboratory of Carcass and Meat Quality of the Agriculture School of the Instituto Politécnico de Bragança “Cantinho do Alfredo”. Grants of L.V., A.L., I.F. and are due to NORTE-01-0247-FEDER-072234, European Regional Development Fund (FEDER). The author (A.T.) is member of the Healthy Meat network, funded by CYTED (ref. 119RT0568).