Determination of Turkey Meat Adulteration in Cooked Ground Beef Using Fluorescence Spectroscopy with Machine Learning

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.

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Publication Details

Journal
Türk doğa ve fen dergisi :/Türk doğa ve fen dergisi
Published
2025-09-26
DOI
https://doi.org/10.46810/tdfd.1706519
Primary Topic
Identification and Quantification in Food
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article
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article

Determination of Turkey Meat Adulteration in Cooked Ground Beef Using Fluorescence Spectroscopy with Machine Learning

Ali Soyuçok, Samet Uçak
Türk doğa ve fen dergisi :/Türk doğa ve fen dergisi
Identification and Quantification in Food
article

Determination of Turkey Meat Adulteration in Cooked Ground Beef Using Fluorescence Spectroscopy with Machine Learning

Ali Soyuçok, Samet Uçak
article en

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.

Türk doğa ve fen dergisi :/Türk doğa ve fen dergisiVol. 14(3)
Istanbul Aydın University (TR), Burdur Mehmet Akif Ersoy Üniversitesi (TR)
Openalex Percentile: Top 77%
Identification and Quantification in Food
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