STUDY ON THE COMBINATION WEIGHT PLS MODEL FOR DETERMING SSC OF PEACH BASED ON THE OPTIMAL INFORMATION REGIONS OBTAINED FROM iPLS METHODS: STUDY ON THE COMBINATION WEIGHT PLS MODEL FOR DETERMING SSC OF PEACH BASED ON THE OPTIMAL INFORMATION REGIONS OBTAINED FROM iPLS METHODS

Backward interval partial least squares (BiPLS) and synergy interval partial least squares (SiPLS) were proposed to search for an optimized combination of information spectral intervals about soluble solids content (SSC) from Vis/NIR spectra of peach. A linear combination weight PLS model was developed on the basis of the selected information intervals. The spectra were preprocessed by second-order derivative and Savitzky-Golay smoothing. It is found that the selected result is the best when the interval number is 15. The information intervals selected by BiPLS are 742~770nm and 862~920nm, while those selected by SiPLS are 742~770nm, 832~860nm and 892~920nm. For BiPLS and SiPLS models of direct combination intervals, the root mean square error of prediction (RMSEP) are 0.386 and 0.308, respectively. And for the PLS models of linear combination weight, the RMSEP are 0.351 and 0.364, respectively. The results reveal that the proposed method overcomes the difficulties that the different information intervals for the complicated samples have different contribution to PLS models. The metlod is very promising for vibrational spectroscopy and it gives much better prediction than the whole-spectrum PLS modeling.