Detection of Food Residues on Stainless Steel Surfaces Using Fluorescence Fingerprint

• Published in: FOOD SCIENCE AND TECHNOLOGY RESEARCH Vol. 26; no. 3; pp. 389 - 397
• Main Authors: Shibata, Mario, Chen, Jizhong, Okada, Kai, Hagiwara, Tomoaki
• Format: Journal Article
• Language: English; Japanese
• Published: Tsukuba Japanese Society for Food Science and Technology 01.01.2020; The Japanese Society for Food Science and Technology; Japan Science and Technology Agency
• Subjects: Adenosine triphosphate; ATP; excitation-emission matrix (EEM); Fingerprints; Fluorescence; Food; food contact surface; food fouling; Food production; Luminescence; NADH; Nicotinamide adenine dinucleotide; partial least squares regression (PLSR); Prediction models; Regression analysis; Residues; Stainless steel; Stainless steels; Steel plates
• ISSN: 1344-6606; 1881-3984
• DOI: 10.3136/fstr.26.389

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.