Abstract
Near-infrared spectroscopy (NIRS) combined with chemometrics analysis was used in this study to qualitatively and quantitatively determine the adulterated Camellia oil. 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 of Camellia oil. NIRS combined with support vector machine regression may be used to predict the amount of adulterated content in Camellia oil because of the high model correlation coefficient (R was higher than 99%, and the maximum mean square error was 0.0605).
Highlights
Camellia oil is a natural high-grade woody oil with an extremely high nutritional value[1]
multi-scatter correction (MSC) and standard normal variate (SNV) transformation plus de-trending technique (DT) were used for the preprocessing of near-infrared spectroscopy (NIRS)
The preprocessed spectral data and the spectral data optimized by CARS and backward interval partial least squares (BiPLS) characteristic variables were separately used as the input data of the support vector machine classification (SVC) model with optimal SVC modeling parameters (C and g) selected by CV
Summary
Camellia oil is a natural high-grade woody oil with an extremely high nutritional value[1] It is one of the edible vegetable oils recommended by the “Outline of China's Food Structure Reform and Development Plan.”. The identification of adulterated plant edible oil is based mainly on compositional analysis with chromatography, mass spectrometry, spectroscopy, and nuclear magnetic resonance[3]. These techniques have several common problems: they are usually expensive, time-consuming, and difficult to operate. The near-infrared spectroscopy (NIRS) technique has rapidly developed in China in recent years It has been successfully employed for other rapid detection applications[5,6,7]. A rapid detection method suitable for determining adulterated Camellia oil was established based on the aforementioned technique
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