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Authentication of pure camellia oil by using near infrared spectroscopy and pattern recognition techniques.
- Source :
-
Journal of food science [J Food Sci] 2012 Apr; Vol. 77 (4), pp. C374-80. Date of Electronic Publication: 2012 Mar 19. - Publication Year :
- 2012
-
Abstract
- Total of 4 pattern recognition methods for the authentication of pure camellia oil applying near infrared (NIR) spectroscopy were evaluated in this study. Total of 115 samples were collected and their authenticities were confirmed by gas chromatography (GC) in according to China Natl. Standard (GB). A preliminary study of NIR spectral data was analyzed by unsupervised methods including principal component analysis (PCA) and hierarchical cluster analysis (HCA). Total of 2 supervised classification techniques based on discriminant analysis (DA) and radical basis function neural network (RBFNN) were utilized to build calibration model and predict unknown samples. In the wavenumber range of 6000 to 5750 cm⁻¹, correct classification rate of both supervised and unsupervised solutions all can reach 98.3% when smoothing, first derivative, and autoscaling were used. The good performance showed that NIR spectroscopy with multivariate calibration models could be successfully used as a rapid, simple, and nondestructive method to discriminate pure camellia oil.<br /> (© 2012 Institute of Food Technologists®)
- Subjects :
- Calibration
China
Cluster Analysis
Discriminant Analysis
Fatty Acids analysis
Flame Ionization
Models, Chemical
Neural Networks, Computer
Pattern Recognition, Automated
Plant Oils standards
Principal Component Analysis
Spectroscopy, Near-Infrared
Camellia chemistry
Food Inspection methods
Plant Oils chemistry
Seeds chemistry
Subjects
Details
- Language :
- English
- ISSN :
- 1750-3841
- Volume :
- 77
- Issue :
- 4
- Database :
- MEDLINE
- Journal :
- Journal of food science
- Publication Type :
- Academic Journal
- Accession number :
- 22429109
- Full Text :
- https://doi.org/10.1111/j.1750-3841.2012.02622.x