Toward Classification of Fish Meat Using Fluorescence Excitation–Emission Matrix and Multivariate Statistics

Abstract

Frequent intentional mislabeling of particular fish and fish products, such as the sale of frozen and thawed fish instead of fresh fish, occurs on all continents. Therefore, two studies were conducted to classify fish meat using excitation–emission matrix (EEM) nondestructively. The first study assessed EEM for differentiation between fresh and frozen–thawed spotted mackerel fillets. Fresh fillets were yielded with different post-mortem freshness variations (ice storage for 0–40 h). The right-side fillets were used as fresh fillets, whereas the left-side fillets were frozen and stored at −30 °C for three months, then thawed at 4 °C. Subsequently, EEM acquisition and chemical analyses were performed. Results of principal component analysis (PCA) of EEM spectra showed clear discrimination between fresh and frozen–thawed meat of fish fillet. In the second study, post-mortem freshness variations in four fish species (horse mackerel, spotted mackerel, cod, and flounder) were simulated by ice storage (0–48 h) and subsequent freezing. PCA of the EEM demonstrated a clear distinction among the fish meat categories, which was also revealed from the freshness data of chemical analysis. Results show that this novel method can be used to monitor fishery product authenticity.