Classifying fish freshness according to the relationship between EIS parameters and spoilage stages

A statistical data fitting model is a common and effective analysis method for the classification of fish freshness by electrochemical impedance spectroscopy (EIS). However, it is difficult to extend the exploration of biological EIS to the mechanism level on the basis of statistical results. In this study, the relationship between electrical parameters and fish spoilage stages was observed. First, the peaks in the EIS morphological characteristic curves (PEMC) were used to classify fish freshness. For samples from different origins, PEMC had 78% classification accuracy rate and the corresponding values of the conventional data fitting model were 52% (impedance modulus) and 55% (phase angle). The results showed that PEMC could significantly improve classification quality for samples with different basic electrical properties. Moreover, the proposed classification method was based on a relationship rather than on statistical data fitting, meaning that more insight on microcosmic mechanisms and universal theories of biological EIS could be obtained in follow-up studies.