Estimated parameters of the model of growth rate.

Predictions from process-based crop models have suggested that shorter growing seasons due to increases in temperature will lead to reductions in crop yields. However, a study to assess this relationship using statistical data would not be sufficient. In this study, a statistical analysis was carried out using historical crop calendar data and yield data for common buckwheat (Fagopyrum esculentum) to investigate how increased temperature affects crop yields through changes in the growing season. First, the parameters of the model representing the relationship between weather and growth rate were estimated using crop calendar data in Japan. Second, the relationship between climate factors and yield was estimated using the generalized additive model. We then examined how rising temperatures under future weather conditions would affect yield through changes in buckwheat growth rate. The results suggested that integrated solar radiation before flowering had a negative effect on buckwheat yield, while integrated solar radiation after flowering had a positive effect on yield. It was suggested that the growth rate of buckwheat was faster at higher temperatures and slower at longer day lengths. Under future climate conditions, higher temperatures and shorter pre-flowering periods were predicted to result in longer post-flowering day lengths and more integrated post-flowering solar radiation due to a longer post-flowering growing season. As a result, the increase in growth rate due to increased temperatures had a positive effect on yield outweighed the slight negative effect of the temperature increase after flowering. Based on historical statistical data, this study analyzed the complex effects of phenology changes due to increased temperature on crop yields, and similar analyses are expected to be conducted for other crops in the future.