Abstract:The hyperspectral method was used to characterize various soluble solid contents of Nanguo pear under different freezing and rewarming conditions such as critical temperature，cycle time，holding time，and cooling rate.Hyperspectral reflection images were collected and the soluble solid contents were determined.Using four different pretreatment methods[multiplicative scatter correction （MSC），standard normal variate（SNV），Savitzky-Golay standard normal variate（S-G-SNV），and Savitzky-Golay multiplicative scatter correction （S-G-MSC）]and the characteristic spectra identified by competitive adaptive reweighted sampling（CARS），the soluble solid model of Nanguo pear under different freezing and rewarming conditions was established by partial least squares method（PLS）.The results showed that the hyperspectra reflect the changes in the soluble solid contents of Nanguo pear.The accuracy of S-G-MSC-CARS-PLS model was the highest under different cycles of freezing treatment.Under different cooling rates，the accuracy of MSC-CARS-PLS model was the highest.The accuracy of SNV-CARS-PLS model was the highest at different holding time.The accuracy of S-G-SNV-CARS-PLS model was the highest at different critical temperatures.