Notice of RetractionGrowing area determination of Tremella fuciformis using visible and near-infrared spectroscopy

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.

Visible and near infrared (NIR) spectroscopy was utilized to determine the growing areas of Tremella fuciformis. Principal component analysis (PCA) obtained the cluster plot which shows the difficulty to determine the growing area by the first three principal components. Least-square support vector machine (LS-SVM) was used to establish the calibration model. Successive projections algorithm (SPA) was applied to select the effective variables from the full-spectrum (FS) which have 675 spectra variables. Finally eleven variables were selected. Effective variables based LS-SVM model obtain 100% determination correct rate. It was proved that SPA was an effective algorithm for spectra variable selection. As a conclusion, Vis-NIR spectroscopy could be used to determine the growing areas of Tremella fuciformis fast and accurately.