Robust Authentication of Meat Products Using FTIR Spectroscopy Coupled with Principal Component Analysis

Moh. Nuril Hudha; Yatim Lailun Ni'mah; Kartika Anoraga Madurani; Veni Rori Setiawati; Siti Mardiyah; Fredy Kurniawan

doi:10.22146/ijc.110090

Robust Authentication of Meat Products Using FTIR Spectroscopy Coupled with Principal Component Analysis

https://doi.org/10.22146/ijc.110090

Moh. Nuril Hudha⁽¹⁾, Yatim Lailun Ni'mah⁽²⁾, Kartika Anoraga Madurani⁽³⁾, Veni Rori Setiawati⁽⁴⁾, Siti Mardiyah⁽⁵⁾, Fredy Kurniawan^(6*)

(1) Department of Chemistry, Faculty of Science and Data Analytics, Institut Teknologi Sepuluh Nopember, Jl. Raya ITS, Keputih, Sukolilo, Surabaya 60111, Indonesia; Department of Biology, Faculty of Agriculture, Science, and Technology, University of Abdurachman Saleh Situbondo, Jl. PB Sudirman No. 7, Situbondo 68312, Indonesia
(2) Department of Chemistry, Faculty of Science and Data Analytics, Institut Teknologi Sepuluh Nopember, Jl. Raya ITS, Keputih, Sukolilo, Surabaya 60111, Indonesia
(3) Department of Chemistry, Faculty of Science and Data Analytics, Institut Teknologi Sepuluh Nopember, Jl. Raya ITS, Keputih, Sukolilo, Surabaya 60111, Indonesia
(4) Department of Chemistry, Faculty of Science and Data Analytics, Institut Teknologi Sepuluh Nopember, Jl. Raya ITS, Keputih, Sukolilo, Surabaya 60111, Indonesia
(5) Department of Chemistry, Faculty of Science and Data Analytics, Institut Teknologi Sepuluh Nopember, Jl. Raya ITS, Keputih, Sukolilo, Surabaya 60111, Indonesia
(6) Department of Chemistry, Faculty of Science and Data Analytics, Institut Teknologi Sepuluh Nopember, Jl. Raya ITS, Keputih, Sukolilo, Surabaya 60111, Indonesia
(*) Corresponding Author

Abstract

Pork is often used as a low-cost adulterant in place of beef or chicken, making its identification particularly important in processed meat products such as meatballs. This study investigates the use of Attenuated Total Reflectance-Fourier Transform Infrared Spectroscopy (ATR-FTIR) to detect pork contamination in meatball products. This technique offers a rapid and cost-effective means of analysis. However, the spectral differences among meat types are subtle and not easily discernible by visual inspection alone. To improve differentiation, Principal Component Analysis (PCA) was employed to highlight variations in spectral data. Fresh pork, beef, and chicken samples were sourced from a local supermarket, and meatballs were prepared in a lab. Spectral data were recorded across the 400–4000 cm⁻¹ range. PCA results showed that the first and second principal components clearly separated uncontaminated samples from those adulterated with pork. Complementary PLS-DA analysis (5-fold cross-validation) quantified the spectral separation: beef vs. pork (accuracy = 94.7%, BER = 5.7%), chicken vs. pork (accuracy = 100.0%, BER = 0.0%), beef-meatball vs. pork-meatball (accuracy = 100.0%, BER = 0.0%), and chicken-meatball vs. pork-meatball (accuracy = 100.0%, BER = 0.0%). This approach demonstrates the potential of ATR-FTIR combined with PCA as a robust analytical method for meat authentication, offering a practical solution for quality control and food safety in the meat processing industry.

Keywords

pork; spectroscopy; meatball; analysis

Full Text:

Full Text PDF Full Text PDF-Suppl. Data

References

[1] Aini, A.N., Airin, C.M., and Raharjo, T.J., 2022, Protein markers related to non-halal slaughtering process of rat as mammal animal’s model detected using mass spectrometry proteome analysis, Indones. J. Chem., 22 (3), 867–877.

[2] Kurniawati, D.R., Sismindari, S., Rumiyati, R., Wibowo, F.S., Pebriyanti, N.W., Irnawati, I., and Rohman, A., 2024, Specific real-time PCR assay targeting D-loop gene and short amplicon sequencing for identification of monkey meat in beef meatballs, Indones. J. Chem., 24 (2), 315–324.

[3] Aghwan, Z.A., and Regenstein, J.M., 2019, Slaughter practices of different faiths in different countries, J. Anim. Sci. Technol., 61 (3), 111–121.

[4] Sarwar, M., Ashfaq, M., and Raza, A., 2023, Animal rights in Islam and Judaism (an analytical study), Al-Mahdi Res. J., 5 (1), 266–290.

[5] Khoiriah, U.L., Baydillah, P., Darmawan, R., Nasori, N., Taufany, F., and Gunawan, S., 2025, Lysis buffers for detecting pork content in food products, Indones. J. Chem., 25 (4), 1051–1063.

[6] Fuseini, A., Hadley, P., and Knowles, T., 2020, Halal food marketing: An evaluation of UK halal standards, J. Islam. Mark., 12 (5), 977–991.

[7] Ng, P.C., Ahmad Ruslan, N.A.S., Chin, L.X., Ahmad, M., Abu Hanifah, S., Abdullah, Z., and Khor, S.M., 2022, Recent advances in halal food authentication: Challenges and strategies, J. Food Sci., 87 (1), 8–35.

[8] Salamah, N., Erwanto, Y., Martono, S., and Rohman, A., 2021, The employment of real-time polymerase chain reaction using species-specific primer targeting on D-loop mitochondria for identification of porcine gelatin in soft candy, Indones. J. Chem., 21 (4), 852–859.

[9] Fuseini, A., Wotton, S.B., Knowles, T.G., and Hadley, P.J., 2017, Halal meat fraud and safety issues in the UK: A review in the context of the European Union, Food Ethics, 1 (2), 127–142.

[10] Hudha, M.N., Ni’mah, Y.L., Madurani, K.A., Andrayani, M.E., and Kurniawan, F., 2022, Preliminary study of beef and pork FTIR spectra: PCA analysis, IOP Conf. Ser.: Earth Environ. Sci., 1083 (1), 012065.

[11] Candoğan, K., Deni̇z, E., Güneş Altuntaş, E., İğci̇, N., and Özel Demiralp, D., 2020, Detection of pork, horse or donkey meat adulteration in beef-based formulations by Fourier transform infrared spectroscopy, Gıda, 45 (2), 369–379.

[12] Azmi, N., Abidin, S.A.S.Z., Zakaria, N.A., Shukor, M.S.A., Karsani, S.A., Fatt, L.K., and Yuswan, M.H., 2025, Evaluation of extraction buffers for protein identification in fish paste with chicken blood plasma (CBP) spikes: A preliminary mass spectrometry study, Indones. J. Chem., 25 (2), 497–510.

[13] Jo, K., Lee, S., Jeong, S.K.C., Lee, D.H., Jeon, H., and Jung, S., 2024, Hyperspectral imaging–based assessment of fresh meat quality: Progress and applications, Microchem. J., 197, 109785.

[14] Islam, M.M., 2022, "Strategic Perspectives of Islamic Entrepreneurship and Marketing" in Strategic Islamic Marketing: A Roadmap for Engaging Muslim Consumers, Eds. Alserhan, B.A., Ramadani, V., Zeqiri, J., and Dana, L.P., Springer International Publishing, Cham, Switzerland, 183–202.

[15] Masruroh, N., and Faiz, M.F., 2025, “Economic Necessity, Fatwa Authorities, and Halal Awareness: How Mandatory Certification Shapes Producer Practices” in Implementing Halal Principles and Regulations in Business Governance, IGI Global Scientific Publishing, Hershey, PA, US, 1–30.

[16] Misbah, M., Rivai, M., and Kurniawan, F., 2023, Diabetes detection using carbon nanomaterial coated QCM gas sensors and a convolutional neural network through urine sample, Int. J. Intell. Eng. Syst., 16 (5), 417–427.

[17] Kurniawan, F., Nugroho, A., Baskara, R.A., Candle, L., Pradini, D., Madurani, K.A., Sugiarso, R.D., and Juwono, H., 2022, Rapid analysis to distinguish porcine and bovine gelatin using PANI/NiO nanoparticles modified quartz crystal microbalance (QCM) sensor, Heliyon, 8 (5), e09401.

[18] Muharramah, A., Permata, L.M., Juwono, H., Sugiarso, R.D., and Kurniawan, F., 2020, Detection of gelatin in ice cream using QCM sensor, IOP Conf. Ser.: Earth Environ. Sci., 493 (1), 012028.

[19] Suryawan, G.Y., Suardana, I.W., and Wandia, I.N., 2020, Sensitivity of polymerase chain reaction in the detection of rat meat adulteration of beef meatballs in Indonesia, Vet. World, 13 (5), 905–908.

[20] Kim, G.D., Jeong, T.C., Cho, K.M., and Jeong, J.Y., 2017, Identification and quantification of myosin heavy chain isoforms in bovine and porcine longissimus muscles by LC-MS/MS analysis, Meat Sci., 125, 143–151.

[21] Juniawan, A., Suprapto, S., Efendi, M.H., Retnowati, R., and Kurniawan, F., 2020, Study on fluorescence spectra: Characteristics of broiler and pig blood, IOP Conf. Ser.: Earth Environ. Sci., 493 (1), 012029.

[22] Puspita, I., Kurniawan, F., Hatta, A.M., and Koentjoro, S., 2021, Absorption spectra of edible oils on UV-visible-near infrared region, Proc. SPIE, 11789, 117890D.

[23] Cozzolino, D., 2022, Advantages, opportunities, and challenges of vibrational spectroscopy as tool to monitor sustainable food systems, Food Anal. Methods, 15 (5), 1390–1396.

[24] Bureau, S., Cozzolino, D., and Clark, C.J., 2019, Contributions of Fourier-transform mid infrared (FT-MIR) spectroscopy to the study of fruit and vegetables: A review, Postharvest Biol. Technol., 148, 1–14.

[25] Fahelelbom, K.M., Saleh, A., Al-Tabakha, M.M.A., and Ashames, A.A., 2022, Recent applications of quantitative analytical FTIR spectroscopy in pharmaceutical, biomedical, and clinical fields: A brief review, Rev. Anal. Chem., 41 (1), 21–33.

[26] Liu, C., Zuo, Z., Xu, F., and Wang, Y., 2023, Authentication of herbal medicines based on modern analytical technology combined with chemometrics approach: A review, Crit. Rev. Anal. Chem., 53 (7), 1393–1418.

[27] Rohman, A., and Putri, A.R., 2019, The chemometrics techniques in combination with instrumental analytical methods applied in halal authentication analysis, Indones. J. Chem., 19 (1), 262–272.

[28] Rohman, A., Himawati, A., Triyana, K., Sismindari, S., and Fatimah, S., 2017, Identification of pork in beef meatballs using Fourier transform infrared spectrophotometry and real-time polymerase chain reaction, Int. J. Food Prop., 20 (3), 654–661.

[29] Dashti, A., Weesepoel, Y., Müller-Maatsch, J., Parastar, H., Kobarfard, F., Daraei, B., and Yazdanpanah, H., 2022, Assessment of meat authenticity using portable Fourier transform infrared spectroscopy combined with multivariate classification techniques, Microchem. J., 181, 107735.

[30] Kurniawati, E., Rohman, A., and Triyana, K., 2014, Analysis of lard in meatball broth using Fourier transform infrared spectroscopy and chemometrics, Meat Sci., 96 (1), 94–98.

[31] Rahmania, H., Sudjadi, S., and Rohman, A., 2015, The employment of FTIR spectroscopy in combination with chemometrics for analysis of rat meat in meatball formulation, Meat Sci., 100, 301–305.

[32] Dimitriou, L., Koureas, M., Kapageridou, S., Pappas, C.S., Manouras, A., and Malissiova, E., 2025, Meat authenticity predictive classification by implementing Fourier transform infrared spectroscopy (FTIR) combined with chemometrics, J. Food Compos. Anal., 145, 107862.

DOI: https://doi.org/10.22146/ijc.110090