@article{article_1706519, title={Determination of Turkey Meat Adulteration in Cooked Ground Beef Using Fluorescence Spectroscopy with Machine Learning}, journal={Türk Doğa ve Fen Dergisi}, volume={14}, pages={67–72}, year={2025}, DOI={10.46810/tdfd.1706519}, author={Soyuçok, Ali and Uçak, Samet}, keywords={Sığır eti, floresans spektroskopisi, makine öğrenmesi, et tağşişi, hindi eti}, abstract={Beef adulteration with turkey meat is typically driven by financial motives. Since turkey meat is less expensive than beef, producers aiming to cut costs and boost profits blend turkey meat into beef products in certain ratios. This study aimed to investigate the use of fluorescence spectroscopy as a fast, non-destructive, and comprehensive method, combined with multivariate analysis, to predict meat adulteration. Raw turkey ground was combined with raw beef ground in concentrations from 0-100% (w/w) in 10% increments and then cooked. Fluorescence measurements of the cooked samples were taken (Ex 200-500 nm, Em 525 nm). The resulting spectral data were analyzed using chemometric tools, such as principal component analysis and partial least squares regression, and error metrics were calculated. For the training, validation, and test datasets, R² values of 0.941, 0.922, and 0.916, and RMSE values of 8.124, 10.856, and 8.456 were identified, respectively. This research demonstrated that fluorescence spectroscopy and multivariate analyses can serve as rapid, non-destructive, and effective methods for detecting a 20% turkey meat adulteration in meat products.}, number={3}, publisher={Bingöl Üniversitesi}