【Objective】Soil fertility quality assessment and constraint factors analysis of soil quality have vital theoretical and practical significances in regional soil improvement and utilization and guidance agricultural production. Paddy soil is an important component of the soil resources in China. Researchers have been using a set index system to evaluate soil fertility quality with results not so accurate. It is, therefore, essential to explore for a more accurate scientific method for the evaluation.【Method】 Jinxian County of Jiangxi Province was cited as a case for the study. A total of 103 soil samples were collected from the topsoil (0~20 cm) and subsoil (20~40 cm) layers of the paddy fields in the region proportional to their respective areas and types and 51 rice sampling sites set aside as a dataset for verification of the yield prediction based on remote sensing interpretation. A fairly more comprehensive dataset of soil properties was determined in the lab. Correlation analysis and principal component analysis (PCA) of the dataset with predicted yields were performed to determine minimum data set (MDS) and weight and membership read function models of the evaluation index system. Soil fertility was characterized in level with the comprehensive index method and main constraint factors of fertility quality in areas low in soil fertility quality. 【Result】To evaluate accuracy of remote sensing interpretation, a fitting equation was established between measured and estimated yields. In the light of the determination coefficient (R ²) and root of mean square error (RMSE) of the fitting equation, the normalized difference vegetation index (NDVI) can reflect more accurately crop yield. According to the yield prediction based on remote sensing interpretation, yield of the rice crop in the region varied in the range from 2.085 to 11.430 t hm^-2, and averaged 7.215 t hm^-2. Through principal component analysis MDS indices, including organic matter, cation exchange capacity (CEC), total potassium (TK), exchangeable calcium (Ex. Ca), bulk density (BD) and clay/silt, were acquired. CEC and TK were common ones in both topsoil and subsoil and the others standard ones . The correlation between soil quality comprehensive index (SQI) and rice yield was analyzed and calculated to be 0.73 (p<0.01) in coefficient, showing that SQI may be used to indicate fertility level of the soil accurately. Based on the average yield, 7.215 t hm^-2, of the region, threshold value of SQI for the region was determined to be 0.65. Areas with SQI value below the threshold value are subject to the risk of low yield. Further analysis of the indices via principal component analysis shows that the main constraint factors of soil fertility in the area are low organic matter content and heavy soil texture indicating low mellowness of the soil, deficiency of meso-nutrients indicating acidification, and low potassium content and high silt/clay ratio indicating poor soil physical structure. According to restraint-factor-based zoning, the county could be divided into three regions. In the hilly area, southeast of the county, soil acidification and poor soil structure are the main constraint factors; in the low mount and plain area, central and west of the county, soil acidification is; and in the lake area, north of the county, low soil mellowness is. Consequently, proper measures should be taken in correspondence to the areas facing different constraint factors so as to improve soil fertility of the paddy fields.【Conclusion】Yield-based soil fertility quality assessment is good for prediction of soil fertility accurately, and the models based on PCA, MDS, SQI and RS technologies can be used not only in paddy soil regions, but also in other types of region for evaluation of soil quality. Findings of the study show that over 30% of the paddy soil in the county are below the average level, but it is still not very clear what causes the low soil fertility. In order to reveal the reasons PCA will be performed to further reduce dimension of the evaluation indices, and zoning carried out on the town/township scale. Zoning on such a scale will sure be of great practical significance to the government in decision making and guiding agricultural production.