TY  - JOUR
A1  - Aadil Siddiqui, M.
A1  - Khir, M.H.Md.
A1  - Ullah, Z.
A1  - Al Hasan, M.
A1  - Saboor, A.
A1  - Magsi, S.A.
JF  - Computers, Materials and Continua
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85156232013&doi=10.32604%2fcmc.2023.034164&partnerID=40&md5=d4737ce1cbc52c816773933bb8eda683
EP  - 2871
VL  - 75
Y1  - 2023///
N2  - 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 (10â??50 v/v). Principal component analysis (PCA) and partial least square (PLS) were used to develop a calibration model at 800â??3500 cmâ??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 cmâ??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. © 2023 Tech Science Press. All rights reserved.
IS  - 2
N1  - cited By 1
SP  - 2859
ID  - scholars19305
TI  - Infrared Spectroscopy-Based Chemometric Analysis for Lard Differentiation in Meat Samples
KW  - Animals; Beef; Extraction; Mean square error; Principal component analysis; Spectrum analysis
KW  -  Error prediction; Halal; Infrared: spectroscopy; Lard; Meat products; Partial least-squares; Principal-component analysis; Root mean square error of calibrations; Root mean square error prediction; Root mean square errors
KW  -  Fourier transform infrared spectroscopy
AV  - none
ER  -