Rapid identification of adulterated camellia seed oil by e-nose combined with chemometrics

Objective： To establish a rapid qualitative and quantitative method for the adulteration of Camellia seed oil. Methods： The electronic nose technology combined with chemometrics was used to screen the difference variables based on one-way ANOVA. The qualitative model for identification of adulteration types of camellia seed oil was established through principal component analysis (PCA) and discriminant analysis (DA). A quantitative model for identifying the types and degrees of camellia seed oil adulteration was established using orthogonal partial least squares (OPLS). Results： The R2 of the model was over 0.98, the RMSEE was lower than 0.005, and the RMSECV was lower than 0.01, which had the high performance indicators. Through external verification, the qualitative identification rate of DA model for camellia seed oil samples of different adulteration types was as high as 100%, and OPLS model had good accuracy. Conclusion： The electronic nose technology combined with chemometrics could realize the rapid and nondestructive identification of camellia seed oil adulteration.