@article{oai:oacis.repo.nii.ac.jp:00002221,
 author = {Shibata, Mario and Chen, Jizhong and Okada, Kai and Hagiwara, Tomoaki},
 issue = {3},
 journal = {Food Science and Technology Research},
 month = {},
 note = {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., 18K05900},
 pages = {389--397},
 title = {Detection of Food Residues on Stainless Steel Surfaces Using Fluorescence Fingerprint},
 volume = {26},
 year = {2020}
}