In the work discussed in this paper we investigated the feasibility of determination of the pH of a fermented substrate in solid-state fermentation (SSF) of wheat straw. Fourier-transform near-infrared (FT-NIR) spectroscopy was combined with an appropriate multivariate method of analysis. A genetic algorithm and synergy interval partial least-squares (GA-siPLS) were used to select the efficient spectral subintervals and wavelengths by k-fold cross-validation during development of the model. The performance of the final model was evaluated by use of the root mean square error of cross-validation (RMSECV) and correlation coefficient (R (c)) for the calibration set, and verified by use of the root mean square error of prediction (RMSEP) and correlation coefficient (R (p)) for the validation set. The experimental results showed that the optimum GA-siPLS model was achieved by use of seven PLS factors, when four spectral subintervals were selected by siPLS and then 45 wavelength variables were chosen by use of the GA. The predicted precision of the best model obtained was: RMSECV = 0.0583, R (c) = 0.9878, RMSEP = 0.0779, and R (p) = 0.9779. Finally, the superior performance of the GA-siPLS model was demonstrated by comparison with four other PLS models. The overall results indicated that FT-NIR spectroscopy can be successfully used for measurement of pH in solid-state fermentation, and use of the GA-siPLS algorithm is the best means of calibration of the model.