In order to study the influence of the two factors, the signal to noise ratio (SNR) of instrument and number of wavelengths, on the accuracy of quantitative analysis in spectral modeling analysis, the influences of different SNRs, the number of wavelengths participating in partial least square regression, and multi-wavelength modeling in different SNR bands were taken into account. The relationships between these factors and quantitative analysis accuracy were explored by modeling analysis experiments. The results show that the analysis accuracy is directly related to the SNR of instrument. And increasing wavelengths, especial the ones with high SNR, reflects a phenomenon that four times of wavelength number will bring 2 times accuracy increasing, which can compensate for the lack of SNR. The research provides the experimental basis and theoretical guidance to improve the model's quality and reduce the prediction error by the utilization and improvement of the instrument's SNR and the reasonable choice of wavelengths and bands of modeling.