Optimization of excitation-emission bands for estimating viable bacteria on meat surfaces with fluorescence spectroscopy

Optimization of an excitation-emission system for accurate estimation of viable bacteria on meat surfaces was proposed. Instead of capturing a full excitation-emission data matrix at all wavelengths, samples were excited by a light source filtered at a definite wavelength and the emission was then captured using a visible and near infrared (NIR) spectrometer. A standard calibration model was then developed using partial least square regression (PLSR) on the acquired EEM data. The model was then tested in an independent validation data set and showed higher estimation accuracy compared with the filter pairs suggested in our earlier study. The outcomes of this study reveal great possibility of overall inspection and contamination detection in meat and meat products using the optimized EEM technique.