Abstract: Since the 1950s, the food cultivation system and rice varieties in Shanghai have undergone continuous replacement, and they have developed into the current wheat-rice or canola-rice as the main annual rotation system, in which rice is mainly single-cropping late japonica rice. In order to effectively estimate the growth status of single-cropping late rice, a linear stepwise regression method was used to establish a relationship model for the length of adjacent rice growth stage and meteorological factors. Three process models such as leaf age, tillering dynamic and grain filling were established based on selection of well-established modules and parameter calibration. Observation data from 16 sowing dates field experiment of the hybrid rice "Qiuyou Jinfeng" from 2014 to 2016 were selected to verify the parameters and the validity of the model. The dynamic changes of rice's growing traits were simulated, and error analysis was performed. The results showed that all models performed good in simulating the development stages, tillering dynamics, leaf age and grain filling process, and the correlation coefficient (R) between the simulated values and measured values in development stages and leaf age are both larger than 0.95 (P<0.001), the normalized root mean squared error (RMSEn) are both below 10. The R value between the simulated and measured values of the tillering dynamics and grain filling dynamic model are both larger than 0.85 (P<0.001), and the RMSEn are 19.8 and 31.2, respectively. The simulation error of grain weight mainly occurs in the middle and late stage of grain filling. Overall, each model has good simulation performance for single cropping late rice in Shanghai, and can help for dynamic prediction of growth period, stem length, leaf age, and grouting process estimation.

Key words: Single-cropping late rice, Development stage, Tillering dynamic, Grain filling process, Crop model