In determination of soluble solids content (SSC) in pear by FT-NIR spectroscopy technique, in order to improve precision and robustness, interval partial least square coupled with genetic algorithm (iPLS-GA) was used to select the efficient spectral regions and variables in calibrating model. Selections of spectral regions and variables were implemented by the cross-validation. The performance of the final model was evaluated according to the root mean square error of prediction (RMSEP) and correlation coefficient (Rp) in prediction sets. The results of final model were achieved as follow: the optimal iPLS-GA model was obtained with 10 PLS factors, when 5 spectral regions and 50 variables were selected, respectively. Rp and RMSEP of optimal model was 0.9398 and 0.3250 respectively by a prediction set. This work demonstrated that NIR spectroscopy with iPLS-GA could be applied successfully to determine the SSC in pear as a precise and nondestructive method. 