Based on Sentinel-2 remote sensing data of rice at booting stage, heading stage, filling stage and mature stage, this study analyzed the relationship between satellite remote sensing spectral parameters and rice quality indicators in each growth period, and established a prediction model of rice quality indicators based on satellite spectral information in each growth period, carried out pearson correlation between five different quality indexes of rice grains and spectral parameters in four growth stages. The results showed that, the five quality indicators had significant correlation with spectral parameters in different degrees during the four growth stages. Then, the spectral parameters with significant correlation effect were selected to establish the prediction equation of rice quality indicator, the modeling results showed that: (1) Based on the interpretation rate of satellite remote sensing spectral information, the rice quality indicators from large to small are: milled rice rate>length-width ratio>protein content>amylose content>brown rice rate. (2) The best growth period of rice quality indicator inverted by satellite remote sensing spectrum was different. The best growth period of brown rice rate and milled rice rate was heading stage, and the coefficient of determination (R²) was 0.461 and 0.893, respectively. The best growth period of length-width ratio was mature period, and R² was 0.878. The best growth period of amylose content and protein content was filling stage, and R² was 0.646 and 0.647, respectively. (3) The rice quality model based on satellite remote sensing spectral information had a good verification effect, and the interpretation rate was 51%-74%. Therefore, the use of satellite remote sensing technology can realize the quantitative monitoring and evaluation of rice quality indicators in a wide range.