The objectives of this study were to verify changes in potato tuber number and weight under climatic variations in a cool region in Japan. We investigated potato growth over a 3-year period from 2019, establishing plots with different planting times and maturity types. In 2020, early planting encountered dryness during the tuber formation period after sprouting, which significantly reduced tuber numbers. Temperature was identified as the main factor contributing to the annual variation in potato yield, largely due to unusually high temperatures during the study period. In 2021, hot and dry conditions in early summer (mid to late July) corresponded to the tuber bulking period and reduced the yield owing to light tuber weight regardless of the planting time and variety. The present study provided insights into the variability of yield components in potato by focusing on drought effects, weather, and cultivation factors, which vary substantially.
The optimal timing of pest control is forecasted via effective accumulated temperature. We focused on the daily increment of it (Dy,i ; y and i indicate the year and day, respectively). Dy,i is usually estimated using the hourly temperature. The observed hourly temperature data are only available for the time period before the publication date (when the pest control information is released). Normals (historical data from a 30-year period) of hourly temperature have been used for the time period after the publication date, which may lead to errors in estimating Dy,i. We examined the errors caused by the use of normals and developed new methods for estimating Dy,i for the time period after the publication date: the normals of Dy,i. Simulations for the past 30 years showed that pest forecasting using the normals of Dy,i resulted in smaller errors than the existing method because it reflected diurnal temperature variations. We proposed another method for cases where high temperatures are predicted in the time period after the publication date and showed an example in which this method had better accuracy than the existing method.