Aswathy, J and Patel, SS and Vaddadi, SK and Kumar, N and Panchariya, PC
(2021)
Qualitative Analysis of Edible Oils using Low Field 1H NMR Spectroscopy and Multivariate Statistical Methods.
In: 4th International Conference on Intelligent Sustainable Systems (ICISS-2021), February 26-27, 2021, SCAD College of Engineering and Technology, Tirunelveli, India.
Abstract
Low field Nuclear Magnetic Resonance (LF NMR) Spectroscopy is an efficient tool to capture a research sample's content and purity. LF NMR is employed for the qualitative analysis of Edible oils. Edible oils used for the study include Coconut, Groundnut, Olive, Mustard, Rice bran and Soyabean oil. Principal Component Analysis(PCA) is used to build a model initially that could classify the oils based on their chemical composition. This model built using PCA could capture 96% of total variance in data. Linear Discriminant Analysis (LDA) was used to build a model that could classify with 100% accuracy. The results provide successful proof for detecting adulteration and further classification of edible oils using Low field 1H NMR Spectroscopy in conjunction with Multivariate Statistical methods such as PCA and LDA.
| Item Type: |
Conference or Workshop Item
(Paper)
|
| Uncontrolled Keywords: |
Low field 1H NMR spectroscopy, Multivariate statistical methods, Principal component analysis (PCA), Linear discriminant analysis (LDA), Adulteration detection, Classification, Edible oils.
|
| Subjects: |
Electronic Systems > Digital Systems |
| Divisions: |
Electronic Systems |
| Depositing User: |
Mr. Jitendra Nath Bajpai
|
| Date Deposited: |
14 Sep 2021 07:14 |
| Last Modified: |
14 Sep 2021 07:14 |
| URI: |
http://ceeri.csircentral.net/id/eprint/572 |
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