Qualitative Analysis of Edible Oils using Low Field 1H NMR Spectroscopy and Multivariate Statistical Methods
IR@CEERI: CSIR-Central Electronics Engineering Research Institute, Pilani
View Archive Info| Field | Value | |
| Title |
Qualitative Analysis of Edible Oils using Low Field 1H NMR Spectroscopy and Multivariate Statistical Methods
|
|
| Creator |
Aswathy, J
Patel, SS Vaddadi, SK Kumar, N Panchariya, PC |
|
| Subject |
Digital Systems
|
|
| Description |
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.
|
|
| Date |
2021
|
|
| Type |
Conference or Workshop Item
PeerReviewed |
|
| Format |
application/pdf
|
|
| Identifier |
http://ceeri.csircentral.net/572/1/242020.pdf
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. |
|
| Relation |
http://ceeri.csircentral.net/572/
|
|