摘要：Near-infrared spectroscopy (NIRS) combined with chemometrics analysis was used in this study to qualitatively and quantitatively determine the adulteratedCamelliaoil. A binary model was constructed for determining both the authenticity and the number of adulterated contents. NIRS combined with support vector machine classification was used to establish a full spectral model and a selected spectral model via competitive adaptive heavy-weighted sampling and backward interval partial least squares. Notably, both of them were proved to be suitable for determining the authenticity ofCamelliaoil. NIRS combined with support vector machine regression may be used to predict the amount of adulterated content inCamelliaoil because of the high model correlation coefficient (Rwas higher than 99%, and the maximum mean square error was 0.0605).
