Detection of Food Residues on Stainless Steel Surfaces Using Fluorescence Fingerprint

Abstract

This study aimed to develop a method for the detection of food residues on the surface of stainless steel plates using fluorescence fingerprint (FF). Extracts of 20 food products were dropped on stainless steel plates as a model of food residues. Fluorescence fingerprint measurement of the food residues was carried out; the food residue samples were subsequently collected by swabbing the surface to determine adenosine triphosphate (ATP) luminescence. Partial least squares regression (PLSR) models were constructed to predict ATP luminescence (R² = 0.60; RMSE = 1.57×10⁵ RLU) and solid content (R² = 0.46; RMSE = 0.89×10⁻⁴ g) on stainless steel surfaces from the FF data. From the coefficients of the prediction model, NADH and NADPH showed the greatest contribution to the prediction of solid content.