title: Identification of different varieties of sesame oil using near-infrared hyperspectral imaging and chemometrics algorithms.
abstract: This study investigated the feasibility of using near infrared hyperspectral imaging (NIR-HSI) technique for non-destructive identification of sesame oil. Hyperspectral images of four varieties of sesame oil were obtained in the spectral region of 874-1734 nm. Reflectance values were extracted from each region of interest (ROI) of each sample. Competitive adaptive reweighted sampling (CARS), successive projections algorithm (SPA) and x-loading weights (x-LW) were carried out to identify the most significant wavelengths. Based on the sixty-four, seven and five wavelengths suggested by CARS, SPA and x-LW, respectively, two classified models (least squares-support vector machine, LS-SVM and linear discriminant analysis,LDA) were established. Among the established models, CARS-LS-SVM and CARS-LDA models performed well with the highest classification rate (100%) in both calibration and prediction sets. SPA-LS-SVM and SPA-LDA models obtained better results (95.59% and 98.53% of classification rate in prediction set) with only seven wavelengths (938, 1160, 1214, 1406, 1656, 1659 and 1663 nm). The x-LW-LS-SVM and x-LW-LDA models also obtained satisfactory results (>80% of classification rate in prediction set) with the only five wavelengths (921, 925, 995, 1453 and 1663 nm). The results showed that NIR-HSI technique could be used to identify the varieties of sesame oil rapidly and non-destructively, and CARS, SPA and x-LW were effective wavelengths selection methods.
authors.affiliation: College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou, China.
authors.forename: Chuanqi
authors.initials: C
authors.lastname: Xie
authors.affiliation: College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou, China.
authors.forename: Qiaonan
authors.initials: Q
authors.lastname: Wang
authors.affiliation: College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou, China.
authors.forename: Yong
authors.initials: Y
authors.lastname: He
mesh_terms: D000465:Algorithms; D002138:Calibration; D016002:Discriminant Analysis; D016018:Least-Squares Analysis; D012715:Sesame Oil / Q000737:chemistry*; D019265:Spectroscopy, Near-Infrared / Q000379:methods*; D060388:Support Vector Machine
chemical_list: D012715:Sesame Oil