| Project/Area Number |
16K07958
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Agricultural environmental engineering/Agricultural information engineering
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| Research Institution | Kochi University |
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Principal Investigator |
Mori Makito 高知大学, 教育研究部自然科学系農学部門, 准教授 (60325496)
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| Co-Investigator(Kenkyū-buntansha) |
安武 大輔 九州大学, 農学研究院, 准教授 (90516113)
西村 安代 高知大学, 教育研究部自然科学系農学部門, 准教授 (20435134)
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| Project Period (FY) |
2016-04-01 – 2019-03-31
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| Project Status |
Completed (Fiscal Year 2018)
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| Budget Amount *help |
¥4,810,000 (Direct Cost: ¥3,700,000、Indirect Cost: ¥1,110,000)
Fiscal Year 2018: ¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000)
Fiscal Year 2017: ¥260,000 (Direct Cost: ¥200,000、Indirect Cost: ¥60,000)
Fiscal Year 2016: ¥3,770,000 (Direct Cost: ¥2,900,000、Indirect Cost: ¥870,000)
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| Keywords | GPS / 耐凍性 / 日最低気温 / 最低気温 / GPS可降水量 / 夜間冷却 / 氷核形成温度 |
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| Outline of Final Research Achievements |
In the present study, a daily-minimum-temperature estimation system was developed using GPS-derived precipitable water vapor. A mechanism of recursive plant cooling was effectively introduced into the system developed. Micro-meteorological observation stations were deployed to clarify the dependency of the temperature on the radiation environment over an island area with vegetation cover. Freezing tolerance of a plant was evaluated through measuring a plant physical/physiological measure of the experimental plant. A recursive plant cooling model was developed for the estimation under the idealized situation. The developed system depicted a distribution map of daily min imum temperature over the Shikoku District based on a concept of the positive cooling of plants.
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| Academic Significance and Societal Importance of the Research Achievements |
農地や森林等における日最低気温は，植物（作物）の生長を規定する重要な環境因子である．特に春季の遅霜による凍霜害対策や晩秋季における健全な低温馴化（翌春の芽吹きに備えた植物生理作用）の観点からも同温度に対する農業分野の関心は低くない．しかしながら，植生地の日最低気温の発現には不明な点が多いこと，また，そもそもその空間分布を得るには既設のアメダスでは十分ではない．本研究課題は，植生地の夜間冷却機構を数学的に定量化し，さらに，アメダスよりも空間配置密度の高いGPS観測網から得られるデータを活用することにより日最低気温の広域的な推定・予測が可能なことを示した．
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