Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Can NIR Replace a Panel of Tasters in Sensory Analysis of Dry-Cured Bísaro Loin?

Lia Vasconcelos
ORCID logo ,
Luís G. Dias
ORCID logo ,
Ana Leite
ORCID logo ,
Iasmin Ferreira
,
Etelvina Pereira
,
Evandro Bona
ORCID logo ,
Javier Mateo
ORCID logo ,
Sandra Rodrigues
ORCID logo ,
And Alfredo Teixeira
* ORCID logo
Version 1 : Received: 3 November 2023 / Approved: 6 November 2023 / Online: 6 November 2023 (10:27:04 CET)

A peer-reviewed article of this Preprint also exists.

Vasconcelos, L.; Dias, L.G.; Leite, A.; Ferreira, I.; Pereira, E.; Bona, E.; Mateo, J.; Rodrigues, S.; Teixeira, A. Can Near-Infrared Spectroscopy Replace a Panel of Tasters in Sensory Analysis of Dry-Cured Bísaro Loin? Foods 2023, 12, 4335. Vasconcelos, L.; Dias, L.G.; Leite, A.; Ferreira, I.; Pereira, E.; Bona, E.; Mateo, J.; Rodrigues, S.; Teixeira, A. Can Near-Infrared Spectroscopy Replace a Panel of Tasters in Sensory Analysis of Dry-Cured Bísaro Loin? Foods 2023, 12, 4335.

Abstract

This study involved a comprehensive examination of sensory attributes in Bísaro dry-cured loins, including odor, androsterone, scatol, color, fat color, hardness, juiciness, chewiness, flavor intensity, and flavor persistence. Analysis of 40 samples revealed a wide variation in these attributes, ensuring a robust margin for multivariate calibration purposes. The respective near-infrared (NIR) spectra unveil distinct peaks associated with significant components such as protein, lipid, and water. Support Vector Regression (SVR) models were methodically calibrated for all sensory attributes, with optimal results using multiplicative scattering correction pre-treatment, MinMax normalization, and radial base kernel (non-linear SVR model). The predictive models exhibited acceptable results, characterized by R-squared values close to 1 (0.9616 - 0.9955) and low RMSE values (0.0400 – 0.1031). The prediction set's relative standard deviation (RSD) remained under 5%. Comparisons with prior research revealed significant improvements in prediction accuracy, particularly when considering attributes like pig aroma, hardness, fat color, and flavor intensity. This research underscores the potential of advanced analytical techniques to improve the precision of sensory evaluations in food quality assessment.

Keywords

dry-cured Bísaro loin; NIR analysis; sensory attributes; non-linear SVR models.

Subject

Biology and Life Sciences, Food Science and Technology

Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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