Packaged butter adulteration evaluation based on spatially offset Raman spectroscopy coupled with FastICA

Authors: LIU, ZHENFANG - Jiangnan University; ZHOU, HAO - Jiangnan University; HUANG, MIN - Jiangnan University; ZHU, QIBING - Jiangnan University; Qin, Jianwei - Tony Qin; Kim, Moon

Submitted to: Journal of Food Composition and Analysis
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 1/13/2023
Publication Date: 1/16/2023
Citation: Liu, Z., Zhou, H., Huang, M., Zhu, Q., Qin, J., Kim, M.S. 2023. Packaged butter adulteration evaluation based on spatially offset Raman spectroscopy coupled with FastICA. Journal of Food Composition and Analysis. 117:105149. https://doi.org/10.1016/j.jfca.2023.105149.
DOI: https://doi.org/10.1016/j.jfca.2023.105149

Interpretive Summary: Butter is a dairy product that is prone to be mixed with cheaper vegetable fat (e.g., margarine) in economically motivated adulteration. Traditional optical sensing techniques can be used for adulteration detection for unpackaged butter products. However, authenticating packaged foods is challenging due to complicated interactions between light and packaging materials. This study presented a point laser-based line-scan spatially offset Raman imaging technique to detect adulterated butter in the packaging. Animal butter was mixed with margarine in different ratios. Raman image and spectral data were acquired from the butter-margarine mixtures covered by original packaging sheets and food-grade plastic packaging materials. Analysis models were developed and successfully used to predict the adulteration content of the butter-margarine samples covered with different packaging materials. The detection method is useful for through-package safety and quality inspection of foods and ingredients. The technique would benefit the food industry and regulatory agencies (e.g., FDA and USDA FSIS) in ensuring and enforcing the safety and quality standards for the packaged food products.

Technical Abstract: Optical detection technology has been widely used in unpackaged food adulteration detection. However, due to the interference of packaging materials on the internal food optical signal, including signal occlusion, mixing and overlap precluded the accurate detection of internal food quality. In this study, a method of packaged butter adulteration evaluation based on spatially offset Raman spectroscopy (SORS) combined with fast independent component analysis (FastICA) was proposed. The adulterated butter from 0 to 100% w/w margarine at 10% intervals was covered with packaging sheets as test samples. A line-scan Raman hyperspectral imaging system was used to obtain a scattering spectral image of the packaged butter samples. The region of interest of the scattering image is extracted as the input of FastICA model to separate the internal butter signals. The extracted butter Raman features were input into four quantitative analysis models to assess the content of butter adulteration. The results showed that the ensemble model Extra-tree has the best performance with RMSEp, Rp2, and RPD values of 0.6, 0.93, and 4.73, respectively. Additionally, the applicability of the method was validated with four types of packaging materials. This rapid non-destructive testing method is beneficial to the effective testing method of packaged butter and other products industry.