This research was funded by “BisOlive: Use of olive pomace in the feeding of Bísaro swine.
Evaluation of the effect on meat quality” project. NORTE-01-0247-FEDER-072234. Financial support
under the CIMO project (UIDB/00690/2020).
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.
