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

  • Zahra Keshavarzi
  • Sahar Barzegari Banadkoki
  • Mehrdad Faizi
  • Yalda Zolghadri
  • Farshad H. ShiraziEmail author
Original Article


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.


Transmission 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.


  1. Alamprese C, Casale M, Sinelli N, Lanteri S, Casiraghi E (2013) Detection of minced beef adulteration with turkey meat by UV–vis, NIR and MIR spectroscopy. LWT Food Sci Technol 53(1):225–232CrossRefGoogle Scholar
  2. Al-Kahtani HA, Ismail EA, Ahmed MA (2017) Pork detection in binary meat mixtures and some commercial food products using conventional and real-time PCR techniques. Food Chem 219:54–60CrossRefGoogle Scholar
  3. Ashtarinezhad A, Panahyab A, Shaterzadeh-Oskouei S, Khoshniat H, Mohamadzadehasl B, Shirazi FH (2016) Teratogenic study of phenobarbital and levamisole on mouse fetus liver tissue using biospectroscopy. J Pharm Biomed Anal 128:174–183CrossRefGoogle Scholar
  4. Baker MJ, Trevisan J, Bassan P, Bhargava R, Butler HJ, Dorling KM, Fielden PR, Fogarty SW, Fullwood NJ, Heys KA (2014) Using Fourier transform IR spectroscopy to analyze biological materials. Nat Protoc 9(8):1771–1791CrossRefGoogle Scholar
  5. Ballin NZ, Vogensen FK, Karlsson AH (2009) Species determination–can we detect and quantify meat adulteration? Meat Sci 83(2):165–174CrossRefGoogle Scholar
  6. Banadkoki SB, Azar FT, Shirazi FH (2018) Estimation and reduction of resonant mie scattering (RMieS) from IR spectra of biological cells by optimization algorithm. J Med Biol Eng 39(3):431–441CrossRefGoogle Scholar
  7. 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
  8. Beasley MM, Bartelink EJ, Taylor L, Miller RM (2014) Comparison of transmission FTIR, ATR, and DRIFT spectra: implications for assessment of bone bioapatite diagenesis. J Archaeol Sci 46:16–22CrossRefGoogle Scholar
  9. Bi Y, Yuan K, Xiao W, Wu J, Shi C, Xia J, Chu G, Zhang G, Zhou G (2016) A local pre-processing method for near-infrared spectra, combined with spectral segmentation and standard normal variate transformation. Analytica chimica acta 909:30–40CrossRefGoogle Scholar
  10. Esslinger S, Riedl J, Fauhl-Hassek C (2014) Potential and limitations of non-targeted fingerprinting for authentication of food in official control. Food Res Int 60:189–204CrossRefGoogle Scholar
  11. Gogna M, Goacher RE (2017) Comparison of three Fourier transform infrared spectroscopy sampling techniques for distinction between lignocellulose samples. BioResources 13(1):846–860CrossRefGoogle Scholar
  12. Goriletsky V, Mitichkin A, Belenko L, Rebrova T (2001) IR spectroscopy of KBr salt and crystals. Semicond Phys Quantum Electron OptoelectronGoogle Scholar
  13. Grdadolnik J (2002) ATR-FTIR spectroscopy: its advantage and limitations. Acta Chim Slov 49(3):631–642Google Scholar
  14. He S, Fletcher S, Rimal A (2003) Identifying factors influencing beef, poultry, and seafood consumption. J Food Distrib Res 34(1):50–55Google Scholar
  15. Jaiswal P, Jha SN, Kaur J, Borah A, Ramya H (2018) Detection of aflatoxin M1 in milk using spectroscopy and multivariate analyses. Food Chem 238:209–214CrossRefGoogle Scholar
  16. Jelle BP, Nilsen T-N, Hovde PJ, Gustavsen A (2012) Accelerated climate aging of building materials and their characterization by Fourier transform infrared radiation analysis. J Build Phys 36(1):99–112CrossRefGoogle Scholar
  17. Kamruzzaman M, Makino Y, Oshita S, Liu S (2015) Assessment of visible near-infrared hyperspectral imaging as a tool for detection of horsemeat adulteration in minced beef. Food Bioprocess Technol 8(5):1054–1062CrossRefGoogle Scholar
  18. Karoui R, Downey G, Blecker C (2010) Mid-infrared spectroscopy coupled with chemometrics: a tool for the analysis of intact food systems and the exploration of their molecular structure—quality relationships—a review. Chem Rev 110(10):6144–6168CrossRefGoogle Scholar
  19. Kendix EL, Prati S, Joseph E, Sciutto G, Mazzeo R (2009) ATR and transmission analysis of pigments by means of far infrared spectroscopy. Anal Bioanal Chem 394(4):1023–1032CrossRefGoogle Scholar
  20. 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
  21. Lee LC, Liong C-Y, Jemain AA (2017) A contemporary review on Data Preprocessing (DP) practice strategy in ATR-FTIR spectrum. Chemometr Intell Lab Syst 163:64–75CrossRefGoogle Scholar
  22. Magdelaine P, Spiess M, Valceschini E (2008) Poultry meat consumption trends in Europe. World’s Poult Sci J 64(1):53–64CrossRefGoogle Scholar
  23. Mark H, J Workman Jr (2010) Chemometrics in spectroscopy. ElsevierGoogle Scholar
  24. Moreira MJP, Silva A, Saraiva C, Marques Martins de Almeida JM (2018) Prediction of adulteration of game meat using FTIR and chemometrics. Nutr Food Sci 48(2):245–258CrossRefGoogle Scholar
  25. Nunes KM, Andrade MVO, Santos Filho AM, Lasmar MC, Sena MM (2016) Detection and characterisation of frauds in bovine meat in natura by non-meat ingredient additions using data fusion of chemical parameters and ATR-FTIR spectroscopy. Food Chem 205:14–22CrossRefGoogle Scholar
  26. 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
  27. Rahmania H, Rohman A (2015) The employment of FTIR spectroscopy in combination with chemometrics for analysis of rat meat in meatball formulation. Meat Sci 100:301–305CrossRefGoogle Scholar
  28. Rohman A, Erwanto Y, Man YBC (2011) Analysis of pork adulteration in beef meatball using Fourier transform infrared (FTIR) spectroscopy. Meat Sci 88(1):91–95CrossRefGoogle Scholar
  29. Schrader B (2008) Infrared and Raman spectroscopy: methods and applications. Wiley, HobokenGoogle Scholar
  30. Torrecilla JS, Otero L, Sanz P (2004) A neural network approach for thermal/pressure food processing. J Food Eng 62(1):89–95CrossRefGoogle Scholar
  31. 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
  32. 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
  33. Wang W, Peng Y, Sun H, Zheng X, Wei W (2018) Spectral detection techniques for non-destructively monitoring the quality, safety, and classification of fresh red meat. Food Anal Methods 11(10):2707–2730CrossRefGoogle Scholar
  34. Yang H, Irudayaraj J (2001) Characterization of beef and pork using Fourier-transform infrared photoacoustic spectroscopy. LWT Food Sci Technol 34(6):402–409CrossRefGoogle Scholar
  35. Yi S, Lai Z, He Z, Cheung Y-M, Liu Y (2017) Joint sparse principal component analysis. Pattern Recogn 61:524–536CrossRefGoogle Scholar
  36. Zhao M, Downey G, O’Donnell CP (2014) Detection of adulteration in fresh and frozen beefburger products by beef offal using mid-infrared ATR spectroscopy and multivariate data analysis. Meat Sci 96(2):1003–1011CrossRefGoogle Scholar

Copyright information

© Association of Food Scientists & Technologists (India) 2019

Authors and Affiliations

  • Zahra Keshavarzi
    • 1
  • Sahar Barzegari Banadkoki
    • 2
  • Mehrdad Faizi
    • 1
  • Yalda Zolghadri
    • 3
  • Farshad H. Shirazi
    • 1
    • 2
    Email author
  1. 1.Department of Toxicology and Pharmacology, School of PharmacyShahid Beheshti University of Medical ScienceTehranIran
  2. 2.Pharmaceutical Sciences Research CenterShahid Beheshti University of Medical SciencesTehranIran
  3. 3.Division of Pharmacology and Toxicology, Department of Basic Sciences, School of Veterinary MedicineShiraz UniversityShirazIran

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