Abstract:

This study established a method for evaluating the yield loss due to chilling injury during the flowering stage of rice to improve the ability to assess the chilling injury. Key parameters for rice growth by the ORYZA.v3 model were determined using the experimental observation data from Tonghua agricultural meteorological experimental station in Jilin from 1993 to 2000. The sensitivity of the model to simulate the chilling injury of rice was analyzed based on the calibrated model and meteorological data from 1961 to 2021. The method for evaluating chilling injury during the flowering stage of rice was established by combining the 0.125°×0.125° European Centre for Medium-range Weather Forecasts (ECMWF) grid data with real-time weather data. The method was used to quantitatively assess the loss of rice yield due to chilling injury from 2022 to 2023. The results showed that: (1) the ORYZA.v3 model could effectively reproduce the rice development and growth, for the reason that the MAE values were 1.2d, 2.6d and 345.7kg·ha⁻¹ with the rice flowering stage, maturing stage and yield. (2) There was a significant correlation between the intensity of chilling injury (chilling daily mean temperature, duration) and the yield reduction of rice. When the chilling injury occurred during the flowering stage of rice, the yield reduction increased by 2.13% along with the daily mean temperature decreasing 1℃. In addition, the reduction in yield increased by 2.66% with the duration of 1d chilling injury. The simulation error of the model was less than 10.0% when compared to the historical disaster data, indicating high simulation accuracy. Thus, the ORYZA.v3 model was able to quantitatively simulate the effect of sterile−type chilling injury on rice yield loss. (3) The yield reduction of rice under the light, moderate, and serious chilling injury were estimated to be 3.0%, 3.7% and 5.1%, respectively, the TS scores were 0.76, 0.50, and 0.63 from 2022 to 2023. The distribution of chilling injury was in good agreement with the measured values, while the comprehensive TS score was 0.63, which indicated a good estimation.

Key words: Rice, Chilling injury assessment, Grid weather forecast, ORYZA.v3 model, Jilin province