Non-destructive Approach for the Prediction of pH in Frozen Fish Meat Using Fluorescence Fingerprints in Tandem with Chemometrics

Abstract

The pH of fish muscle is an important index for quality assessment, but the traditional methods using a pH meter and probe/electrode are destructive, time-consuming, and laborious, making them unsuitable for on-line meat-quality monitoring. Hence, an approach of using fluorescence fingerprints (FFs) for the non-destructive prediction of pH in frozen fish fillets was trialled. Sixty-three live horse mackerel (Trachurus japonicus) and spotted mackerel (Scomber australasicus) were freshly harvested, sacrificed instantly, then preserved in ice, filleted, vacuum-packed, and frozen. Subsequently, the FFs of all frozen fillets were recorded using a fibreoptic-equipped fluorescence spectrometer, and the corresponding pH values of the samples were measured. After pre-processing, the masked FFs were modelled using partial least squares regression (PLSR) for the prediction of pH values. The results revealed that the developed method was accurate enough for predicting the pH changes in frozen horse mackerel and spotted mackerel fillets with R2 = 0.71 and R2 = 0.90, respectively. The proposed technique could be utilized as a rapid and non-contact alternative to traditional pH electrodes for the quality monitoring of fish products.