Detection of fabricated eggs using Fourier Transform Infrared (FT- IR) spectroscopy coupled with multivariate classification techniques

Authors: JOSHI, RITU - Chungnam National University; BAEK, INSUCK - Orise Fellow; JOSHI, RAUL - Chungnam National University; Kim, Moon; CHO, BYOUNG-KWAN - Chungnam National University

Submitted to: Food Analytical Methods
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 3/30/2022
Publication Date: 4/1/2022
Citation: Joshi, R., Baek, I., Joshi, R., Kim, M.S., Cho, B. 2022. Detection of fabricated eggs using Fourier Transform Infrared (FT- IR) spectroscopy coupled with multivariate classification techniques. Food Analytical Methods. https://doi.org/10.1016/j.infrared.2022.104163.
DOI: https://doi.org/10.1016/j.infrared.2022.104163

Interpretive Summary: Eggs are an inexpensive, high protein food and also have additional nutritional and health benefits for consumers. In recent years, fake eggs have appeared in some marketplaces, creating problems for consumers and distributors because these fakes are relatively easy to make and not easily discernible to the naked eye. Furthermore, fake eggs pose health concerns due to the presence of harmful chemicals in their composition. Thus, nondestructive methods are needed to help assess compositions and authenticity of eggs for food safety screening. In this study, a Fourier-transform infrared (FT-IR) spectroscopy technique in conjunction with multivariate analysis methods was investigated for the classification of fake and authentic eggs, with fake egg samples created empirically in the lab similar to fake eggs found recently in the marketplace. The results showed that the technique could classify fake eggshells and albumen compared to the real eggs samples with over 99% accuracy. This study demonstrates the application of FT-IR spectroscopy as a nondestructive analytical tool to differentiate and detect real and fake eggs, for potential use by the egg industry to ensure safe, high-quality egg products.

Technical Abstract: Fabricated eggs can lead to many severe human health problems due to the consumption of the harmful chemicals used to make them. Therefore, developing technology for detecting fabricated eggs is of high priority in terms of food safety. Fourier transform infrared (FT-IR) spectroscopy is widely used for non-destructive detection applications for its capacity to rapidly assess targets via optical properties. In this study, one-way analysis of variance (ANOVA) and principal component analysis (PCA) were performed to interpret FT-IR spectral data related to the chemical composition of fabricated eggs. As a result, particular wavenumbers 20 were observed that were highly sensitive to the external (eggshell) and internal (albumen and yolk) constituents of fabricated and real chicken eggs. Based on the spectral interpretation, multivariate models using partial least-squares discriminant analysis (PLS-DA), partial least-squares regression (PLSR), support vector machine (SVM), and support vector regression (SVR) were built to detect the constituents of fabricated eggs. The PLS-DA and SVM models classified fabricated eggshells and fabricated albumen with 100% accuracy. Moreover, the PLSR and SVR predictive values exhibited coefficients of determination (Rp2) of 0.99. Hence, this study demonstrates that FT-IR spectroscopy combined with multivariate models can be potentially used as an efficient method to detect both surface and internal constituents of fabricated eggs.