Rapid Quantitative Determination of Adulteration of Camellia Oil Using Portable Raman Spectroscopy and Chemometrics
2025
Boxue Chang | Zhen Li | Kaidi Ji | Yinlan Ruan | Rukuan Liu
Over the past decade, Raman spectroscopy and chemometrics have been extensively utilized in the food industry for the research and development of new products but have failed to establish a strong foothold in quality control and the assessment of food items. To bridge this gap, we introduce a novel application of Raman spectroscopy capable of swiftly identifying free fatty acids (FFAs) in cooking oil and quantifying adulteration. This advanced method was validated using camellia oil, a highly esteemed cooking oil in China and various Asian countries known for its nutritional richness and diverse culinary applications. With its growing popularity among high-end food consumers in Asia, camellia oil has increasingly become a target for adulteration, causing dissatisfaction among both consumers and genuine producers. In this study, we employed Raman spectroscopy to characterize the FFA profiles of cooking oil samples, complemented by principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) for sample categorization and adulteration detection in camellia oil. By segregating camellia oil from other vegetable oils and differentiating genuine from adulterated samples using the partial least squares (PLS) method, we achieved a high determination coefficient (R2) of over 0.98 and a low root mean square error of prediction (RMSEP) of less than 1.45%. These findings offer a robust predictive model for rapid camellia oil adulteration assessment, potentially augmenting traditional qualitative tests and streamlining sampling procedures in the food industry.
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