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

Yıl 2025, Cilt: 14 Sayı: 3, 67 - 72, 26.09.2025
https://doi.org/10.46810/tdfd.1706519

Öz

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.

Kaynakça

  • Nakyinsige K, Man YBC, Sazili AQ. Halal authenticity issues in meat and meat products. Meat Sci. 2012;91(3):207-214.
  • Iqbal Z, Afseth NK, Postelmans A, Wold JP, Andersen PV., Kusnadi J, et al. Detection and quantification of pork adulteration in beef meatballs with Raman spectroscopy and near infrared spectroscopy. Spectrochim Acta A Mol Biomol Spectrosc. 2025;337:126069.
  • Anagaw YK, Ayenew W, Limenh LW, Geremew DT, Worku MC, Tessema TA, et al. Food adulteration: Causes, risks, and detection techniques. SAGE Open Med. 2024;12:20503121241250184.
  • Borovikov SN, Mukantayev KN, Bulashev AK, Tursunov K, Syzdykova AS. Meat Product Adulteration: Modern Detection Methods and Food Safety Assurance. Herald of science of S. Seifullin KazATU: Vet sci. 2025;1(009);48-62.
  • Chang L, Fu C, Huang P, Li Y, Liu Y, Lu F. Reliable multiplex real-time PCR method for detecting adulteration in processed beef products. J Food Compos Anal. 2025;143:107595.
  • Adenuga BM, Biltes R, Villa C, Costa J, Spychaj A, Montowska M, et al. Unravelling red deer (Cervus elaphus) meat adulteration in gourmet foods by quantitative real-time PCR. Food Control. 2025;168:110872.
  • Alkhalidi AA, Althwani AN. Detecting adulteration in processed meat products from various sources using a multiplex PCR assay targeting cytochrome B genes from cattle, sheep, goat, and chicken. Heath biotechnol biopharma. 2025;8(3):80-94.
  • Zhao Y, Du X, Liu S, Sun M, Man L, Zhu M, et al. Characterization and Discrimination of Volatile Compounds of Donkey and Horse Meat Based on Gas Chromatography–Ion Mobility Spectrometry. Foods. 2025;14(7):1203.
  • Hoffmann B, Münch S, Schwägele F, Neusüß C, Jira W. A sensitive HPLC-MS/MS screening method for the simultaneous detection of lupine, pea, and soy proteins in meat products. Food Control. 2017;71:200-209.
  • Alexandrakis D, Downey G, Scannell AG. Detection and identification of bacteria in an isolated system with near-infrared spectroscopy and multivariate analysis. J Agric Food Chem. 2008;56(10):3431-3437.
  • Cawthorn DM, Steinman HA, Hoffman LC. A high incidence of species substitution and mislabelling detected in meat products sold in South Africa. Food control. 2013;32(2):440-449.
  • Aït-Kaddour A, Loudiyi M, Ferlay A, Gruffat, D. Performance of fluorescence spectroscopy for beef meat authentication: Effect of excitation mode and discriminant algorithms Meat Sci. 2018;137:58-66.
  • Deniz E, Güneş Altuntaş E, Ayhan B, İğci N, Özel Demiralp D, Candoğan, K. Differentiation of beef mixtures adulterated with chicken or turkey meat using FTIR spectroscopy. J Food Process Preserv. 2018;42(10):e13767.
  • Saleem A, Sahar A, Pasha I, Shahid M. Determination of adulteration of chicken meat into minced beef mixtures using front face fluorescence spectroscopy coupled with chemometric. Food Sci Anim Resour. 2022;42(4):672.
  • Soyuçok A, Kılıç B, Kılıç GB, Yalçın H. In vitro antimicrobial activity of ginseng extract against Staphylococcus aureus, Salmonella Typhimurium and Listeria monocytogenes and its inhibitory effects on these pathogens in cooked ground beef. Meat Sci. 2024;216: 109559.
  • Lawrie RA, Ledward DA. Lawrie’s meat science, 7th ed. Woodhead Publishing: Abington; 2006.
  • Sahar A, Boubellouta T, Dufour É. Synchronous front-face fluorescence spectroscopy as a promising tool for the rapid determination of spoilage bacteria on chicken breast fillet. Food Res. Int. 2011;44(1):471-480.
  • Sidira M, Smaoui S, Varzakas T. Recent proteomics, metabolomics and lipidomics approaches in meat safety, processing and quality analysis. Appl Sci. 2024;14(12):5147.
  • Aprilia P, Ummami R, Airin CM, Aziz F, Astuti P. Comparison of ELISA and PCR assays for detection of pork adulteration in Halal-labelled beef products. J Food Qual Hazards Control. 2022;9:112-117.
  • Alamprese C, Amigo JM, Casiraghi E, Engelsen SB. Identification and quantification of turkey meat adulteration in fresh, frozen-thawed and cooked minced beef by FT-NIR spectroscopy and chemometrics. Meat Sci. 2016;121:175-181.
  • Weng S, Guo B, Tang P, Yin X, Pan F, Zhao J, et al. Rapid detection of adulteration of minced beef using Vis/NIR reflectance spectroscopy with multivariate methods. Spectrochim Acta A Mol Biomol Spectrosc. 2020;230:118005.
  • Prandi B, Varani M, Faccini A, Lambertini F, Suman M, Leporati A, et al. Species specific marker peptides for meat authenticity assessment: A multispecies quantitative approach applied to Bolognese sauce. Food Control. 2019;97:15-24.
  • Zuo X, Li Y, Chen X, Chen L, Liu C. Rapid Detection of Adulteration in Minced Lamb Meat Using Vis-NIR Reflectance Spectroscopy. Processes. 2024;12(10):2307.
  • Chaudhary V, Kajla P, Dewan A, Pandiselvam R, Socol CT, Maerescu CM. Spectroscopic techniques for authentication of animal origin foods. Front Nutr. 2022;9:979205.
  • Kök S, Atalay S. Determination of the fraud of processed meat products by ELISA. Lahaed. 2018;58(2):95-98.
  • T.C. Tarım ve Orman Bakanlığı [Internet]. Veteriner Hizmetleri, Bitki Sağlığı, Gıda ve Yem Kanunu (Kanun No: 5996). Resmî Gazete, 27610. 2010 [cited 2025 May 20]. Available from: https://istanbul.tarimorman.gov.tr/Belgeler/SolMenu/RESMIGAZETE2018/5996SAYILIKANUN.pdf
  • T.C. Tarım ve Orman Bakanlığı [Internet]. Taklit veya tağşiş yapan firmalar listesi. Güvenilir Gıda Bilgi Sistemi. 2025 [cited 2025 May 20]. Available from: https://guvenilirgida.tarimorman.gov.tr/GuvenilirGida/GKD/TaklitVeyaTagsis
  • Yu Y, Chen W, Zhao D, Zhang H, Chen W, Liu R, et al. Meat species authentication using portable hyperspectral imaging. Front nutr. 2025;12:1577642.

Makine Öğrenmesi Destekli Floresans Spektroskopisi ile Pişmiş Kıyma Sığır Etinde Hindi Eti Tağşişinin Belirlenmesi

Yıl 2025, Cilt: 14 Sayı: 3, 67 - 72, 26.09.2025
https://doi.org/10.46810/tdfd.1706519

Öz

Sığır etine hindi eti karıştırılması genellikle finansal nedenlerle gerçekleştirilmektedir. Hindi eti, sığır etine kıyasla daha ucuz olduğundan, maliyetleri düşürmek ve kâr oranlarını artırmak isteyen üreticiler, belirli oranlarda hindi etini sığır eti ürünlerine karıştırmaktadır. Bu çalışma, et hilelerinin tespiti için hızlı, tahribatsız ve kapsamlı bir yöntem olarak floresans spektroskopisinin çok değişkenli analizlerle birlikte kullanımını araştırmayı amaçlamıştır. Çiğ hindi kıyması, %0–100 (a/a) aralığında ve %10’luk artışlarla çiğ sığır kıyması ile karıştırılmış, ardından pişirme işlemi uygulanmıştır. Pişmiş örneklerin floresans ölçümleri (Ex: 200–500 nm, Em: 525 nm) alınmıştır. Elde edilen spektral veriler, temel bileşen analizi (PCA) ve kısmi en küçük kareler regresyonu (PLSR) gibi kemometrik araçlar kullanılarak analiz edilmiş, hata metrikleri hesaplanmıştır. Eğitim, doğrulama ve test veri kümeleri için sırasıyla 0.941, 0.922 ve 0.916 R² değerleri ve 8.124, 10.856 ve 8.456 RMSE değerleri elde edilmiştir. Bu araştırma, floresans spektroskopisi ve çok değişkenli analizlerin, et ürünlerinde %20 oranındaki hindi eti taklitçiliğini tespit etmek için hızlı, tahribatsız ve etkili yöntemler olarak kullanılabileceğini ortaya koymuştur.

Kaynakça

  • Nakyinsige K, Man YBC, Sazili AQ. Halal authenticity issues in meat and meat products. Meat Sci. 2012;91(3):207-214.
  • Iqbal Z, Afseth NK, Postelmans A, Wold JP, Andersen PV., Kusnadi J, et al. Detection and quantification of pork adulteration in beef meatballs with Raman spectroscopy and near infrared spectroscopy. Spectrochim Acta A Mol Biomol Spectrosc. 2025;337:126069.
  • Anagaw YK, Ayenew W, Limenh LW, Geremew DT, Worku MC, Tessema TA, et al. Food adulteration: Causes, risks, and detection techniques. SAGE Open Med. 2024;12:20503121241250184.
  • Borovikov SN, Mukantayev KN, Bulashev AK, Tursunov K, Syzdykova AS. Meat Product Adulteration: Modern Detection Methods and Food Safety Assurance. Herald of science of S. Seifullin KazATU: Vet sci. 2025;1(009);48-62.
  • Chang L, Fu C, Huang P, Li Y, Liu Y, Lu F. Reliable multiplex real-time PCR method for detecting adulteration in processed beef products. J Food Compos Anal. 2025;143:107595.
  • Adenuga BM, Biltes R, Villa C, Costa J, Spychaj A, Montowska M, et al. Unravelling red deer (Cervus elaphus) meat adulteration in gourmet foods by quantitative real-time PCR. Food Control. 2025;168:110872.
  • Alkhalidi AA, Althwani AN. Detecting adulteration in processed meat products from various sources using a multiplex PCR assay targeting cytochrome B genes from cattle, sheep, goat, and chicken. Heath biotechnol biopharma. 2025;8(3):80-94.
  • Zhao Y, Du X, Liu S, Sun M, Man L, Zhu M, et al. Characterization and Discrimination of Volatile Compounds of Donkey and Horse Meat Based on Gas Chromatography–Ion Mobility Spectrometry. Foods. 2025;14(7):1203.
  • Hoffmann B, Münch S, Schwägele F, Neusüß C, Jira W. A sensitive HPLC-MS/MS screening method for the simultaneous detection of lupine, pea, and soy proteins in meat products. Food Control. 2017;71:200-209.
  • Alexandrakis D, Downey G, Scannell AG. Detection and identification of bacteria in an isolated system with near-infrared spectroscopy and multivariate analysis. J Agric Food Chem. 2008;56(10):3431-3437.
  • Cawthorn DM, Steinman HA, Hoffman LC. A high incidence of species substitution and mislabelling detected in meat products sold in South Africa. Food control. 2013;32(2):440-449.
  • Aït-Kaddour A, Loudiyi M, Ferlay A, Gruffat, D. Performance of fluorescence spectroscopy for beef meat authentication: Effect of excitation mode and discriminant algorithms Meat Sci. 2018;137:58-66.
  • Deniz E, Güneş Altuntaş E, Ayhan B, İğci N, Özel Demiralp D, Candoğan, K. Differentiation of beef mixtures adulterated with chicken or turkey meat using FTIR spectroscopy. J Food Process Preserv. 2018;42(10):e13767.
  • Saleem A, Sahar A, Pasha I, Shahid M. Determination of adulteration of chicken meat into minced beef mixtures using front face fluorescence spectroscopy coupled with chemometric. Food Sci Anim Resour. 2022;42(4):672.
  • Soyuçok A, Kılıç B, Kılıç GB, Yalçın H. In vitro antimicrobial activity of ginseng extract against Staphylococcus aureus, Salmonella Typhimurium and Listeria monocytogenes and its inhibitory effects on these pathogens in cooked ground beef. Meat Sci. 2024;216: 109559.
  • Lawrie RA, Ledward DA. Lawrie’s meat science, 7th ed. Woodhead Publishing: Abington; 2006.
  • Sahar A, Boubellouta T, Dufour É. Synchronous front-face fluorescence spectroscopy as a promising tool for the rapid determination of spoilage bacteria on chicken breast fillet. Food Res. Int. 2011;44(1):471-480.
  • Sidira M, Smaoui S, Varzakas T. Recent proteomics, metabolomics and lipidomics approaches in meat safety, processing and quality analysis. Appl Sci. 2024;14(12):5147.
  • Aprilia P, Ummami R, Airin CM, Aziz F, Astuti P. Comparison of ELISA and PCR assays for detection of pork adulteration in Halal-labelled beef products. J Food Qual Hazards Control. 2022;9:112-117.
  • Alamprese C, Amigo JM, Casiraghi E, Engelsen SB. Identification and quantification of turkey meat adulteration in fresh, frozen-thawed and cooked minced beef by FT-NIR spectroscopy and chemometrics. Meat Sci. 2016;121:175-181.
  • Weng S, Guo B, Tang P, Yin X, Pan F, Zhao J, et al. Rapid detection of adulteration of minced beef using Vis/NIR reflectance spectroscopy with multivariate methods. Spectrochim Acta A Mol Biomol Spectrosc. 2020;230:118005.
  • Prandi B, Varani M, Faccini A, Lambertini F, Suman M, Leporati A, et al. Species specific marker peptides for meat authenticity assessment: A multispecies quantitative approach applied to Bolognese sauce. Food Control. 2019;97:15-24.
  • Zuo X, Li Y, Chen X, Chen L, Liu C. Rapid Detection of Adulteration in Minced Lamb Meat Using Vis-NIR Reflectance Spectroscopy. Processes. 2024;12(10):2307.
  • Chaudhary V, Kajla P, Dewan A, Pandiselvam R, Socol CT, Maerescu CM. Spectroscopic techniques for authentication of animal origin foods. Front Nutr. 2022;9:979205.
  • Kök S, Atalay S. Determination of the fraud of processed meat products by ELISA. Lahaed. 2018;58(2):95-98.
  • T.C. Tarım ve Orman Bakanlığı [Internet]. Veteriner Hizmetleri, Bitki Sağlığı, Gıda ve Yem Kanunu (Kanun No: 5996). Resmî Gazete, 27610. 2010 [cited 2025 May 20]. Available from: https://istanbul.tarimorman.gov.tr/Belgeler/SolMenu/RESMIGAZETE2018/5996SAYILIKANUN.pdf
  • T.C. Tarım ve Orman Bakanlığı [Internet]. Taklit veya tağşiş yapan firmalar listesi. Güvenilir Gıda Bilgi Sistemi. 2025 [cited 2025 May 20]. Available from: https://guvenilirgida.tarimorman.gov.tr/GuvenilirGida/GKD/TaklitVeyaTagsis
  • Yu Y, Chen W, Zhao D, Zhang H, Chen W, Liu R, et al. Meat species authentication using portable hyperspectral imaging. Front nutr. 2025;12:1577642.
Toplam 28 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Veteriner Bilimleri (Diğer)
Bölüm Makaleler
Yazarlar

Ali Soyuçok 0000-0003-2626-5827

Samet Uçak 0000-0002-3461-2481

Yayımlanma Tarihi 26 Eylül 2025
Gönderilme Tarihi 26 Mayıs 2025
Kabul Tarihi 14 Temmuz 2025
Yayımlandığı Sayı Yıl 2025 Cilt: 14 Sayı: 3

Kaynak Göster

APA Soyuçok, A., & Uçak, S. (2025). Determination of Turkey Meat Adulteration in Cooked Ground Beef Using Fluorescence Spectroscopy with Machine Learning. Türk Doğa ve Fen Dergisi, 14(3), 67-72. https://doi.org/10.46810/tdfd.1706519
AMA Soyuçok A, Uçak S. Determination of Turkey Meat Adulteration in Cooked Ground Beef Using Fluorescence Spectroscopy with Machine Learning. TDFD. Eylül 2025;14(3):67-72. doi:10.46810/tdfd.1706519
Chicago Soyuçok, Ali, ve Samet Uçak. “Determination of Turkey Meat Adulteration in Cooked Ground Beef Using Fluorescence Spectroscopy with Machine Learning”. Türk Doğa ve Fen Dergisi 14, sy. 3 (Eylül 2025): 67-72. https://doi.org/10.46810/tdfd.1706519.
EndNote Soyuçok A, Uçak S (01 Eylül 2025) Determination of Turkey Meat Adulteration in Cooked Ground Beef Using Fluorescence Spectroscopy with Machine Learning. Türk Doğa ve Fen Dergisi 14 3 67–72.
IEEE A. Soyuçok ve S. Uçak, “Determination of Turkey Meat Adulteration in Cooked Ground Beef Using Fluorescence Spectroscopy with Machine Learning”, TDFD, c. 14, sy. 3, ss. 67–72, 2025, doi: 10.46810/tdfd.1706519.
ISNAD Soyuçok, Ali - Uçak, Samet. “Determination of Turkey Meat Adulteration in Cooked Ground Beef Using Fluorescence Spectroscopy with Machine Learning”. Türk Doğa ve Fen Dergisi 14/3 (Eylül2025), 67-72. https://doi.org/10.46810/tdfd.1706519.
JAMA Soyuçok A, Uçak S. Determination of Turkey Meat Adulteration in Cooked Ground Beef Using Fluorescence Spectroscopy with Machine Learning. TDFD. 2025;14:67–72.
MLA Soyuçok, Ali ve Samet Uçak. “Determination of Turkey Meat Adulteration in Cooked Ground Beef Using Fluorescence Spectroscopy with Machine Learning”. Türk Doğa ve Fen Dergisi, c. 14, sy. 3, 2025, ss. 67-72, doi:10.46810/tdfd.1706519.
Vancouver Soyuçok A, Uçak S. Determination of Turkey Meat Adulteration in Cooked Ground Beef Using Fluorescence Spectroscopy with Machine Learning. TDFD. 2025;14(3):67-72.