Large-scale evaluation of the effects of adaptation to climate change by shifting transplanting date on rice production and quality in Japan

Abstract

We evaluated the effect of projected increasing temperatures due to climate change on the yield and quality of rice, as well as the effectiveness of shifting the transplanting date as an adaptation measure, throughout Japan. As an indicator of rice quality, we adopted the heat stress index HD_m26, which is related to the decreased percentage of first grade rice due to high temperature, calculated as the cumulative temperature within 20 days after the heading date. We used a process-based rice growth model to assess the effect. We implemented the model for the period 1981 -2100, and shifted the transplanting dates at 7-day intervals from -70 to +70 days from the standard transplanting date. The estimated yield was categorized into three classes with different degrees of quality degradation risk according to values of HD_ m26. Relative to the current transplanting date, nationwide total production was estimated to increase slightly in most climate change scenarios, although the proportion of production with quality degradation risk may increase with the rise in temperature. It may be possible to avoid this increased risk while maintaining total production by selecting an optimum transplanting date in consideration of both yield and quality. However, a large decrease in yield was found in some areas, suggesting that the current rice producing regions in Japan would become separated into suitable and unsuitable areas as temperatures increase.

Rice grain quality degradation and economic loss due to global warming in Japan

“…Therefore, the assumption of constant rice production in the economic assessment would overestimate the economic loss. Furthermore, the effect of global warming on rice production was not considered in the estimation, although global warming will change future rice production [9]. This is one of the limitations of the present study.…”

“…Previous studies have revealed that global warming will have significant impacts not only on crop productivity [1][2][3][4][5] but also on crop quality [6][7][8][9]. In Japan, there have been many studies showing that high temperatures during the growing period drastically degrade rice grain quality [8].…”

“…While there have been a few studies on the impact of global warming on the ratio of first grade grain [6,9], no studies on the occurrence of CRG under predicted global warming conditions. Furthermore, there have been no studies on the economic loss caused by degradation of crop quality due to global warming, although many studies have assessed the economic loss through reduction in crop yields [23][24][25].…”

Estimating first-grade rice production due to high temperature after heading date utilizing the statistical data

“…However, their statistical model does not take the changes in farmers' choice into consideration and hence, they ignore the farmers' adaptation to climate change, such as the substitution of different cultivars and shifting the transplanting day combined with cultivar choice. By contrast, Ishigooka et al 2017 illustrate the effect of climate change on the ratio of production of first-grade quality rice, and propose that the results of conducting crop models across Japan, combined with global circular models GCMs , the production of the highest quality of rice grain as defined by the Ministry of Agriculture, Forestry and Fisheries MAFF of Japan, could be mitigated by the cultivar choice and the shift of the transplanting day. They calculate the Heat-Dose HD index, to demonstrate the geographic distribution of the potential risk of quality reduction as a result of future climate change.…”

“…Nagahata et al 2006 report that the HD with a threshold temperature of 26˚C explained the generation of white immature grain in the growth chamber experiment with a japonica rice cultivar Koshihikari by manipulating the exposure period under high-temperatures 33˚C during day time and 26˚C during night time . Ishigooka et al 2017 utilize this HD index for the simulation of a crop model by fixing the exposure period to 20 days. However, according to Morita 2008 , several other meteorological factors can be contenders for the HD index, such as the daily maximum temperature average during the grain filling period, solar radiation, and so on.…”