Modeling leaf photosythetic capacity by combining optimization theories for leaf senescence and environmental acclimation

2023 Fiscal Year Final Research Report

• Project/Area Number: 21K14950
• Research Category: Grant-in-Aid for Early-Career Scientists
• Allocation Type: Multi-year Fund
• Review Section: Basic Section 41040:Agricultural environmental engineering and agricultural information engineering-related
• Research Institution: National Agriculture and Food Research Organization
• Principal Investigator: Kimura Kensuke 国立研究開発法人農業・食品産業技術総合研究機構, 農業環境研究部門, 研究員 (10885502)
• Project Period (FY): 2021-04-01 – 2024-03-31
• Keywords: 光合成 / 環境馴化 / 老化 / モデル / 高速評価 / ハイスループットフェノタイピング

Outline of Final Research Achievements

The photosynthetic capacity of plant leaves fluctuates significantly over time due to acclimation to environments and leaf senescence. The aim of this study was to construct a new model of photosynthetic capacity by integrating a model of photosynthetic capacity considering leaf lifespan and a model considering environmental acclimation of the leaves. Since evaluating photosynthetic capacity requires measurements that take more than 30 minutes per leaf, it was considered that sufficient data for modeling could not be obtained using existing methods. Therefore, I developed a new method that can quickly evaluate photosynthetic rate, making possible to obtain a large amount of data on photosynthetic capacity. Finally, I tried to model photosynthetic capacity using this method.

Free Research Field

農業気象学

Academic Significance and Societal Importance of the Research Achievements

本研究で開発した光合成速度の高速評価法を用いることで，葉の光合成能力を簡易に推定できるだけでなく，光合成の情報に基づく育種・栽培研究の高速化が期待でき，農業分野での利用も見込まれる．また、食物連鎖の出発点となる植物の光合成は，人間を含む地球上すべての動物の生活に深く関わっているため，本手法は，生態学や生物多様性の研究においても活用されることが期待される．さらに，本手法で構築している光合成能力のモデルが完成すれば，作物の生育や収量の予測だけでなく，全球規模での植物の炭素同化シミュレーションにも応用可能と考えられる．