Quality Analysis of Olive Oil and Quantification Detection of Adulteration in Olive Oil by Near-Infrared Spectrometry and Chemometrics
Discriminant analysis was used to classify 20 olive oil samples based on their near-infrared (NIR) spectra. The sam-ples were successfully classified into two categories which are consistent with extra virgin olive oil and ordinary olive oil defined in the products. The NIR spectra of olive-oil mixtures containing colza oil, corn oil, peanut oil, camellia oil, sunflower oil, and poppy seed oil were collected, respectively. The volume percent of adulterants ranged from 0 to 100%. The best spectrum bands for analysis were selected before developing partial least-squares (PLS) calibration models. The relative errors of prediction ranged from -5.67% to 5.61%. Results showed that the method combined with chemometrics methods and near-infrared spec-trometry is simple, fast and credible for qualitative and quantitative analyses of olive oil samples.
Near-infrared spectrum (NIRS)Olive oilDiscriminant analysisPartial least square (PLS)
NETL
NSTL
万方数据
维普
