In this work, a correlation model of tilapia fillets quality evaluation was established by principal component analysis (PCA) based on fractal dimension change. The tilapia fillets were stored at 3 and −2°C, respectively, and the pH, color, electrical conductivity (EC), total volatile base nitrogen (TVB‐N), texture, and fractal dimension were periodically measured. A major component was extracted and it explained 82.726% of the total variance. Then the comprehensive quality score was calculated during the storage of the fillets. Three function correlation models including linear function, logarithmic function, and quadratic function were obtained by establishing the relationship between the comprehensive quality score of fillets and the fractal dimension. The determination coefficient R2 of quadratic function correlation model reached 0.841 and 0.962 under 3 and −2°C, respectively. This result indicated that the quality evaluation was accurate under low‐temperature storage conditions by quadratic function correlation model based on the change of fractal dimension.
Practical applications
The conventional quality evaluation methods of tilapia fillets are time‐consuming and cumbersome. This work used PCA to integrate many tilapia fillets quality indicators into a comprehensive quality indicator. Then a correlation function model was established between comprehensive quality indicator and fractal dimension. The quality of tilapia fillets would be evaluated by the change of fractal dimension in profile. The result showed that this method was simple and fast, and laid a foundation for the application of fractal dimension in tilapia processing and transportation.