Noninvasive freshness evaluation of bighead carp heads based on fluorescence spectroscopy coupled with long short-term memory network: simulation of cold chains

To swiftly and noninvasively assess the freshness of bighead carp heads within simulated cold chain environments, an excitation-emission matrix fluorescence spectroscopy coupled with a long short-term memory network (EEM-LSTM) model was developed. Through the parallel factor algorithm based on analysis of residuals, diagnosis of core consistency, and split-half evaluation, three key fluorescent components from fish fillets were extracted, with the most significant components linked to tryptophan and NADH, both indicative of fish freshness. The EEM-LSTM model exhibited coherent trends in freshness indicators and demonstrated exceptional predictive capabilities for four freshness indicators simultaneously, achieving R² values exceeding 0.8840 in simulated cold chain situations. Relative errors in the supermarket direct sales cold chain were less than 10%, surpassing those of the long-distance transport cold chain. Hence, the EEM-LSTM model stands validated for predicting fish freshness in simulated cold chains, holding promise for real-world aquatic product freshness forecasting within cold chain scenarios.