%0 Journal Article %A Waley SAYRAN? %A Bing-Bai LI %A Jia-Hua ZHANG %A Shen-Bin YANG %T Application of a rice simulation model in high temperature sensitivity study %D 2014 %R 10.3724/SP.J.1258.2014.00048 %J Chinese Journal of Plant Ecology %P 515-528 %V 38 %N 5 %X

Aims For adoption and localization of the high precision rice growth model ORYZA2000, the model parameters were calibrated and high-temperature sensitivity analysis was performed based on observed data for five rice varieties at nine experimental stations and daily meteorological data in Jiangsu Province.
Methods The latest version of ORYZA2000 (V2.13) was used in this study. The model parameters were calibrated using the observed data for three rice varieties at five experimental stations, and then the aboveground biomass, leaf area index, and final yield were estimated for two other rice varieties at four experimental stations for model validation; a t-test was performed for quality evaluation. By using the validated model and raising the temperature at different time periods, a simulation of high temperature impact on rice biomass and yield was carried out. The simulation results were compared with the observational data from the greenhouse experiments assessing the high temperature responses of the rice varieties studied.
Important findings The results show that after calibration, the model parameters reliably simulated the dynamics of biomass accumulation and leaf area index development in the rice varieties studied; the simulated values are consistent with the observed values. The total biomass, panicle biomass, and final yield decreased by 12%-25% compared to the control (CK) when the growth temperature was raised to 35 °C for 3, 5 and 7 consecutive days from booting to flowering stages. Those values decreased by 18%-31% when the temperature was raised to 38 °C and by 20%-38% when the temperature was raised to 41 °C over the same periods. In general, the magnitudes of decline in the growth of rice varieties from model simulations were comparable with controlled laboratory observations. ORYZA2000 model could be applied to predict rice response to temperature increase on the basis of crop parameter calibrations.

%U https://www.plant-ecology.com/EN/10.3724/SP.J.1258.2014.00048