Non-destructive detection of cocoon shell weight based on variable selection by visible and near infrared spectroscopy

Visible and near-infrared reflectance spectroscopy (Vis-NIRS) was applied to measure cocoon shell weight. Least square-support vector machine (LS-SVM) was used to establish the Vis-NIR model. Uninformative variable elimination and successive projections algorithm were combined to select wavelength from Vis-NIR spectroscopy. Eight wavelength variables, namely 673, 937, 963, 982, 989, 992, 995 and 1 008 nm, were selected. The UVE-SPA-LS-SVM model was established based on these eight wavelength variables. The results showed that the determination coefficient for prediction set (Rp2) was 0.5354, and the root mean square error for prediction (RMSEP) was 0.0373. It is concluded that Vis-NIRS can be used in the cocoon shell weight measurement, and UVE-SPA is a feasible and efficient algorithm for the spectral variable selection.