Near infrared spectroscopy and interval partial least-squares (iPLS) were applied to rapid quantitative analysis of thepoly-β-hydroxybutyrate (PHB), polyphosphate (Poly-P), and glycogen (Gly) during denitrifying phosphorus removal. Wavelet denoising was used to pretreat the raw near infrared spectroscopy, and the quantitative analysis models (iPLS models) of PHB, Poly-P, and GLY were established with interval partial least-squares (iPLS). The iPLS was used to select the optimal spectral interval for modeling. The total phosphorus decreased from 7.9 mg/L to 0.67 ma/L during denitrifying phosphorus removal. The region from 4,320 to 4,640 cm^-1 was selected to establish the iPLS model of intracellular PHB. The region from 4,000 to 4,320 cm^-1 was selected to establish the iPLS model of intracellular Poly-P. Finally, the region from 5,103 to 5,379 cm^-1 was chosen to establish the iPLS model of intracellular GLY. Statistical tests of these iPLS models of PHB, Poly-P, and GLY show that the correlation coefficients (r_c) between the correction values and the chemical values are 0.9637, 0.9582, and 0.9437, with the root mean square error of cross validation (RMSECV) being 0.0069, 0.0039, and 0.0025. Test results of iPLS models show that the correlation coefficients (r_p) between the prediction value (by iPLS model) and the chemical value were 0.9430, 0.9389, and 0.9133, with the root mean square error of prediction (RMSEP) being 0.0523, 0.0040, and 0.0058. These research results show that the proposed models may provide a rapid and effective quantitatively analysis of intracellular PHB, Poly-P, and GLY, and that the effect of the denitrifying phosphorus removal process can be quickly judged from the cell metabolism perspective.