Abstract
The fishing industry faces significant challenges in supply chain management and fish quality assurance. Freshness, a crucial quality attribute, decreases over storage time. Traditional freshness control methods like sensory analysis, chromatography, or microbiological analyses, while effective, are slow and costly. Hence, the need for a tool like the electronic nose (E-nose) emerges, capable of predicting fish freshness by evaluating its odor using economical, quick, and portable equipment. This study aimed to classify the river fish Tinca tinca (tench) according to its freshness state and correlate its olfactory pattern with the presence of aerobic mesophilic microorganisms in the samples. The proliferation of aerobic mesophiles accelerates the sensory olfactory degradation of fish and is an indicator of quality. The E-nose used is a prototype developed by the University of Extremadura (UEx) with a matrix of 5 metal oxide semiconductor (MOS) gas sensors. Data were analyzed using Principal Component Analysis (PCA), where the first two components explained 93.4 % of the total variance, and Partial Least Squares Discriminant Analysis (PLSDA) was successful in classifying 95 % of the samples. Lastly, a Partial Least Squares (PLS) model was employed to relate the actual number of aerobic mesophilic bacteria to those predicted by the E-nose, achieving a determination coefficient of R2Pred = 0.990. E-nose technology emerges as a promising alternative for enhancing the precision and efficiency in assessing fresh fish quality.
Keywords: fresh fish, electronic nose, shelf life, quality assessment.
