A remarkable declining trend in rice quality has already been observed in western Japan and the future global warming associated with climate change is likely to exacerbate such risk. In this study, a simple statistical model was constructed to estimate the rice quality, which is defined as the proportion of white immature grains on a prefectural scale, in terms of two major climate variables during the grain-filling stage: the cumulative weighted effective temperature δ and the cumulative solar radiation SR. In order to account for the uncertainties included in the processes involved, Bayesian inference was used to estimate the model parameters. The modeled time changes in rice quality correlated well to those observed. Specifically, the reproducibility of rice quality since 2000 was particularly high. These results suggested that a combination of the two climate factors was responsible for the recent variability in rice quality on a prefectural scale. Subsequently, the elasticity of rice quality relative to δ and SR was examined based on the model. The elasticity represents the relative change in rice quality in response to a change in δ or SR, with a positive (negative) sign indicating increased (decreased) quality. Consequently, the mean elasticity of the rice quality relative to SR was larger than that to δ in Kyushu. Moreover, the time changes of rice quality in Kyushu synchronized with that of SR under high temperature conditions, suggesting that rice plants become more sensitive to conditions of insufficient radiation if exposed to high temperatures. Consequently, it was concluded that the contribution of the radiation condition to the variation in rice quality become relatively larger along with the recent increase in temperature.
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