| Project/Area Number |
18K05909
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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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| Review Section |
Basic Section 41040:Agricultural environmental engineering and agricultural information engineering-related
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| Research Institution | Kagoshima University |
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Principal Investigator |
Kanda Eiji 鹿児島大学, 農水産獣医学域農学系, 准教授 (90355272)
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| Co-Investigator(Kenkyū-buntansha) |
芝山 道郎 鹿児島大学, 農水産獣医学域農学系, 教授 (10354060)
下田代 智英 鹿児島大学, 農水産獣医学域農学系, 准教授 (30315402)
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| Project Period (FY) |
2018-04-01 – 2021-03-31
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| Project Status |
Completed (Fiscal Year 2020)
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| Budget Amount *help |
¥3,510,000 (Direct Cost: ¥2,700,000、Indirect Cost: ¥810,000)
Fiscal Year 2020: ¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000)
Fiscal Year 2019: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2018: ¥1,820,000 (Direct Cost: ¥1,400,000、Indirect Cost: ¥420,000)
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| Keywords | 画像解析 / 全天球画像 / ドローン / 天球カメラ / 水稲 / 全天球カメラ / マルチバンド / 植被率 / LAI / SPAD値 / 天空カメラ / マルチバンドカメラ / 高温登熟障害 / 生育診断 / リスク評価 |
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| Outline of Final Research Achievements |
The growth patterns of rice field rice for the risk of high temperature aging by basic fertilizer and late top dressing are clarified. The transmitted quantum rate measured by the PAR quantum light sensor was related to the vegetation density (LAI). There was a relationship between the proportion of vegetation (VF) from aerial images taken with toy drones and the LAI, the weight of dry materials, and the number of tillers. The relationship between the whole sky images under rice canopy and the investigation items such as rice plant height, number of the tillers, LAI, dry weight was clarified. In addition, the transition of the old dead leaf that was closely related to the failure of high temperature ripening stress was measured by the whole sky images.
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| Academic Significance and Societal Importance of the Research Achievements |
開発した360°カメラを用いて、水稲の群落下で全天球撮影する手法は、水稲の草丈、茎数、LAI、乾物重などの生育調査項目が推定できるだけでなく、下葉の枯れ上りの進行時期や速度を計測することで高温登熟障害リスクを推定することが可能である。さらに、この手法は株の開張度の評価とか、害虫またはその吸汁跡の探索にも使用できる可能性がある。
さらに、カメラを地上走行型ドローンに取り付け、圃場内を定期走行させることで、UAVのような制限なしで、水稲の生育状況の評価に使用できる。
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