RT info:eu-repo/semantics/article
T1 Can Near-Infrared Spectroscopy Replace a Panel of Tasters in Sensory Analysis of Dry-Cured Bísaro Loin?
A1 Vasconcelos, Lia
A1 Dias, Luis G
A1 Leite, Ana
A1 Ferreira, Iasmin
A1 Pereira, Etelvina
A1 Bona, Evandro
A1 Mateo Oyagüe, Javier
A1 Rodrigues, Sandra
A1 Teixeira, Alfredo
A1 
A2 Tecnologia de los Alimentos
K1 Tecnología de los alimentos
K1 Consumers
K1 Meat products
K1 Bísaro breed
K1 Food quality assessment
K1 NIR analysis
K1 Non-linear SVR models
K1 3309 Tecnología de Los Alimentos
AB [EN] This study involved a comprehensive examination of sensory attributes in dry-cured Bísaro loins, including odor, androsterone, scatol, lean color, fat color, hardness, juiciness, chewiness, flavor intensity and flavor persistence. An 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 unveiled distinct peaks associated with significant components, such as proteins, lipids 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 the radial base kernel (non-linear SVR model). This process involved partitioning the data into calibration (67%) and prediction (33%) subsets using the SPXY algorithm. The model parameters were optimized via a hybrid algorithm based on particle swarm optimization (PSO) to effectively minimize the root-mean-square error (RMSECV) derived from five-fold cross-validation and ensure the attainment of optimal model performance and predictive accuracy. 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 meat 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. Such advancements have the potential to benefit both the research community and the meat industry by closely aligning their practices with consumer preferences and expectations.
PB MDPI
LK https://hdl.handle.net/10612/19956
UL https://hdl.handle.net/10612/19956
NO Vasconcelos, L., Dias, L. G., Leite, A., Ferreira, I., Pereira, E., Bona, E., Mateo, J., Rodrigues, S., & Teixeira, A. (2023). Can Near-Infrared Spectroscopy Replace a Panel of Tasters in Sensory Analysis of Dry-Cured Bísaro Loin? Foods, 12(23), Article e4335. https://doi.org/10.3390/FOODS12234335
NO Copyright: © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).
DS BULERIA. Repositorio Institucional de la Universidad de León
RD 30-jun-2024