Measurement of Soluble Solids Content in Pear by NIR Spectroscopy Based on Synergy Interval Partial Least-Squares

In order to improve the precision and stability of determination of soluble solids content(SSC) in pear by FT-NIR spectroscopy,the collected original spectra of was pretreated by standard normalization(SNV),and prediction medel of SSC was established by synergy interval partial least-squares(SiPLS).The number of SiPLS components was confirmed by the cross-validation,the predict results of SiPLS model were analyzed with correlation coefficient(Rp) and the root mean square error of prediction(RMSEP) as evaluation index,compared with the classical PLS model and interval PLS(iPLS) model.Results showed that the optimal prediction model by SiPLS contained 21spectral interval combined with 4 subinterval and principal component factor was 15,and Rp and RMSEP of prediction were 0.9633 and 0.203,respectively.It is concluded that NIR spectroscopy combining with SiPLS can be applied to accurate and lossless determination of the SSC in pear.