To investigate the effect of surface temperature (T_c) differences and to clarify the plant physiological differences between F₁s (F₁：First filial generation) and their parents, we analyzed the differences of the stomatal conductance (g_s), transpiration rate (E) and net photosynthesis rate (A) among six sugar beet genotypes.
　Three of the genotypes: “NK195BR”, “NK235BR” and “NK388” were tested as parents, while the other three “NK235BR×NK195BR”, “NK195BR×NK388” and “NK235BR×NK388” were tested as F₁s. From the comparison of the mean T_c value of six genotypes measured at 6 hours (from 10:00 to 16:00), the results, in descending order of their value, showed “NK235BR” > “NK388” > “NK195BR” > “NK195BR×NK388” > “NK235BR×NK195BR” > “NK235BR×NK388”.
　To analyze the relationship between T_c and plant physiology, g_s, E and A were measured at six times during mid-growing season. As a result, g_s and E had a significant varietal difference among the six genotypes every measurement. Both the g_s and E values of F₁s had a trend higher than those of their parents. A comparison between g_s and the differences between T_c and air temperature (ΔT), revealed that the two had a negative liner correlation such that the higher the g_s was, the lower the ΔT. On the other hand, A had a significant varietal difference depending on the day. However, there was no clear relationships to indicate that F₁s had a trend higher than those of their parents.
　In relation to yield component and plant physiological properties, root weight and sugar yield were significantly correlated with both of g_s and E and had no significant correlation with the sugar content. On the other hand, A had no significant correlation with root weight, sugar content or sugar yield.

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　We developed the cloudiness ratio (CR), a climate index calculated using Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data considered to be related to sunshine duration and precipitation, and then applied CR in Tottori prefecture during 2000-2019. The CR correlated well with sunshine duration, the percentage of possible sunshine, and precipitation, and displayed both seasonality and regionality. We used these relationships to produce high-resolution (650 m) maps of the spatial distributions of sunshine duration and precipitation.

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　The Winter-sweetened Technique (WST) was developed at the Tohoku National Agricultural Experiment Station in the early 1990s. In the WST, cold winter air is let into greenhouses in northern Japan to make Nappa taste better and richer in nutrients. Nappa is a generic name of Japanese leaf vegetables such as headless Brassica, spinach or chrysanthemum with a length approximately 25 cm, and mainly eaten boiled. The WST operation is quite easy for farmers, opening doors and side films of greenhouses when Nappa has been grown to the marketable size. However, unexpected problems had come out after the extension started. As a member of its developers, I recorded the inside stories in this paper to consider the relationship between technical developments and extensions.
　In the WST, low temperature exposure for one to two weeks enriches sugar and functional components in Nappa, and changes the shape of its leaves to rosettes. Traders disliked the shape, however consumers prefer it due to the excellent taste. Convinced by consumers’ acceptance, we made efforts to inform them that the rosette shape is the proof of WST. Gradually, farmers started to produce WST Nappa, and distribute it in small local markets. The WST was featured in programs on TV and articles in newspapers.
　In 1999, a seed company introduced to farmers and traders a cultivar of the rosette shape produced even in higher temperatures. Production of the so called WST Nappa increased rapidly, and it was supplied to markets in Tokyo. However, these farmers with less understanding of WST could not continue to open their greenhouses through the days for enough time. The Nappa lost the WST qualities. The situation has continued until now. In other areas, high quality WST Nappa has been produced using normal cultivars by farmers with their good understandings of the WST.

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　A large ensemble historical and future climate simulation dataset (d4PDF; database for Policy Decision making for Future climate change) was spatially interpolated into a grid-spacing of approximately 1-km to cover Hokkaido, Japan using a statistical downscaling method. This dataset offers daily mean 2-m air temperatures and daily total precipitations under historical and future climate with 2 K and 4 K temperature rises. 900-year meteorological variables were available for historical and future climate, allowing probabilistic assessment of effects of meteorology on agricultural productivity. Biases in the downscaled data were corrected by a method based on cumulative density function of the variables and present-day climate dataset called the Agro-Meteorological Grid Square Data developed by National Agricultural and Food Research Organization (NARO) as the reference dataset. We here present the procedure of statistical downscaling and a typical use case of this dataset focusing on probabilistic assessment of wine grape production in Hokkaido. Several points to be noted are mentioned for potential users of this dataset.

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