Comparison of transmission FTIR and ATR spectra for discrimination between beef and chicken meat and quantification of chicken in beef meat mixture using ATR-FTIR combined with chemometrics
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Detecting meat adulteration for quality control and accurate labeling is important and needs convenient analytical methods. This study aimed to investigate and compare the application of the transmission and ATR approaches of FTIR followed by principal component analysis (PCA) to not only discriminate between chicken and beef meat but also quantizing chicken portion of mixtures. Two different approaches are presented; spectra preprocessing with focus on wavenumber region of 1700–1071 cm−1, and no preprocessed where PCA was applied on the whole spectra range of mid-FTIR. The results suggest that applying PCA on specified preprocessed spectra could detect hidden relationships between variables in chicken and beef in both approaches. PCA successfully clustered these kinds of meats when applied on transmission mode spectra without any preprocessing treatment, while applying it on ATR mode’s raw spectra failed to cluster them. Additionally, the preprocessed ATR-FTIR spectrum was used to prepare regression models by Partial Least Square Regression (PLS-R) and artificial neural networks (ANN) for predicting presence and percentage of chicken meat in the beef meat mixture. The results demonstrated the superiority of ANN over PLS-R in this assessment with an R2 of 0.999.
KeywordsTransmission FTIR ATR-FTIR Meat Chemometrics
Authors wish to express their appreciation from the Pharmaceutical Sciences Research Center and SBMU for their support of this work.
Compliance with ethical standards
Conflict of interest
The authors declare that there is no conflict of interest.
- Beasley M, Carmen C (2009) Evaluating diagenetic alterations affecting stable isotopes in bone using C/P and CI values: a comparison of four sample preparation methods for FTIR analysis. Am J Phys Anthropol 138(s48):87Google Scholar
- Goriletsky V, Mitichkin A, Belenko L, Rebrova T (2001) IR spectroscopy of KBr salt and crystals. Semicond Phys Quantum Electron OptoelectronGoogle Scholar
- Grdadolnik J (2002) ATR-FTIR spectroscopy: its advantage and limitations. Acta Chim Slov 49(3):631–642Google Scholar
- He S, Fletcher S, Rimal A (2003) Identifying factors influencing beef, poultry, and seafood consumption. J Food Distrib Res 34(1):50–55Google Scholar
- Lamyaa M (2013) Discrimination of pork content in mixtures with raw minced camel and buffalo meat using FTIR spectroscopic technique. Int Food Res J 20(3):1389Google Scholar
- Mark H, J Workman Jr (2010) Chemometrics in spectroscopy. ElsevierGoogle Scholar
- Obeidat S, Hammoudeh A, Alomary A (2017) Application of FTIR spectroscopy for assessment of green coffee beans according to their origin. Жypнaл пpиклaднoй cпeктpocкoпии 84(6):977–981Google Scholar
- Schrader B (2008) Infrared and Raman spectroscopy: methods and applications. Wiley, HobokenGoogle Scholar
- Vasconcelos H, Saraiva C, de Almeida JM (2014) Evaluation of the spoilage of raw chicken breast fillets using Fourier transform infrared spectroscopy in tandem with chemometrics. Food Bioprocess Technol 7(8):2330–2341Google Scholar
- Walsh MJ, Singh MN, Stringfellow HF, Pollock HM, Hammiche A, Grude O, Fullwood NJ, Pitt MA, Martin-Hirsch PL, Martin FL (2008) FTIR microspectroscopy coupled with two-class discrimination segregates markers responsible for inter-and intra-category variance in exfoliative cervical cytology. Biomarker Insights 3:179CrossRefGoogle Scholar