Notice of RetractionCombination of ^1H NMR and Chemometrics for Discrimination of Rapeseed Oils

Notice of Retraction

After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.

We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.

The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.

¹H NMR spectroscopy was utilized to distinguish the brands of rapeseed oils. As there are more than four hundreds of NMR variables, uninformative variables should be eliminated to improve model´s discrimination ability and save the calculation time. A hybrid variable selection which is combined with uninformation variable elimination (UVE) and successive projections algorithm (SPA), was used to achieve this objective. 77 effective variables were selected from the full-spectrum variables. They were inputted into least-square support vector machine (LS-SVM) to establish the discrimination model. A good result of 92.5% correct answer rate was obtained. It is improved compared to the result of the full spectrum- SPA-LS-SVM model. It is proved that it is necessary to do UVE before SPA. As a conclusion, the performance of UVE-SPALS-SVM model shows that ¹H NMR spectroscopy is a feasible way to distinguish rapeseed oils fast and accurately.