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Infrared Spectroscopy-Based Chemometric Analysis for Lard Differentiation in Meat Samples

Muhammad Aadil Siddiqui1,*, M. H. Md Khir1, Zaka Ullah2, Muath Al Hasan2, Abdul Saboor3, Saeed Ahmed Magsi1

1 Department of Electrical and Electronic Engineering, Universiti Teknologi Petronas, Seri Iskandar, 32610, Malaysia
2 College of Engineering, Al Ain University, Al Ain, 64141, United Arab Emirates
3 High Performance Cloud Computing Centre (HPC), Universiti Teknologi Petronas, Seri Iskandar, 32610, Malaysia

* Corresponding Author: Muhammad Aadil Siddiqui. Email: email

Computers, Materials & Continua 2023, 75(2), 2859-2871. https://doi.org/10.32604/cmc.2023.034164

Abstract

One of the most pressing concerns for the consumer market is the detection of adulteration in meat products due to their preciousness. The rapid and accurate identification mechanism for lard adulteration in meat products is highly necessary, for developing a mechanism trusted by consumers and that can be used to make a definitive diagnosis. Fourier Transform Infrared Spectroscopy (FTIR) is used in this work to identify lard adulteration in cow, lamb, and chicken samples. A simplified extraction method was implied to obtain the lipids from pure and adulterated meat. Adulterated samples were obtained by mixing lard with chicken, lamb, and beef with different concentrations (10%–50% v/v). Principal component analysis (PCA) and partial least square (PLS) were used to develop a calibration model at 800–3500 cm−1. Three-dimension PCA was successfully used by dividing the spectrum in three regions to classify lard meat adulteration in chicken, lamb, and beef samples. The corresponding FTIR peaks for the lard have been observed at 1159.6, 1743.4, 2853.1, and 2922.5 cm−1, which differentiate chicken, lamb, and beef samples. The wavenumbers offer the highest determination coefficient R2 value of 0.846 and lowest root mean square error of calibration (RMSEC) and root mean square error prediction (RMSEP) with an accuracy of 84.6%. Even the tiniest fat adulteration up to 10% can be reliably discovered using this methodology.

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APA Style
Siddiqui, M.A., Khir, M.H.M., Ullah, Z., Hasan, M.A., Saboor, A. et al. (2023). Infrared spectroscopy-based chemometric analysis for lard differentiation in meat samples. Computers, Materials & Continua, 75(2), 2859-2871. https://doi.org/10.32604/cmc.2023.034164
Vancouver Style
Siddiqui MA, Khir MHM, Ullah Z, Hasan MA, Saboor A, Magsi SA. Infrared spectroscopy-based chemometric analysis for lard differentiation in meat samples. Comput Mater Contin. 2023;75(2):2859-2871 https://doi.org/10.32604/cmc.2023.034164
IEEE Style
M.A. Siddiqui, M.H.M. Khir, Z. Ullah, M.A. Hasan, A. Saboor, and S.A. Magsi "Infrared Spectroscopy-Based Chemometric Analysis for Lard Differentiation in Meat Samples," Comput. Mater. Contin., vol. 75, no. 2, pp. 2859-2871. 2023. https://doi.org/10.32604/cmc.2023.034164



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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