The feasibility of rapid detection of the process parameters such as moisture content and pH value in solid-state fermentation of Monascus was studied by near infrared technique.In view of the traditional wavelength selection methods based on interval strategy ignoring the disadvantages of the nonlinear factors,this paper adopted a new wavelength selection algorithm based on LS-SVM nonlinear model which was named synergy interval least squares support vector machines(siLS-SVM),and the new algorithm was compared with correlation coefficient method,iPLS algorithm and siPLS algorithm.The results showed that the combination of siLS-SVM and LS-SVM model achieved the best prediction result.The prediction correlation coefficients(Rp) of moisture content and pH value were 0.962 1 and 0.976 1,respectively.The root mean square errors for prediction set(RMSEP) were 0.012 9 and 0.145 2,respectively.The obtained results demonstrated that the fitting and the predictive accuracy were satisfactory,and it was feasible to apply NIRS method to fast determination of moisture contents and pH value in solid state fermentation of Monascus.This study provided a technical foundation for the further online detection of process parameters in solid-state fermentation of Monascus and the optimization of fermentation conditions.