Mathematical modeling for 3D plant morphology as fundamental technologies of plant phenotyping

2023 Fiscal Year Final Research Report

• Project/Area Number: 21K14947
• 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: Kyushu University
• Principal Investigator: Noshita Koji 九州大学, 理学研究院, 助教 (10758494)
• Project Period (FY): 2021-04-01 – 2024-03-31
• Keywords: 形態測定学 / 植物フェノタイピング / 画像解析 / 機械学習 / 数理生物学

Outline of Final Research Achievements

To accumulate phenome data, especially 3D morphological properties of plants, I attempt to improve the throughput of phenotyping individual components and develop mathematical models to integrate these components into hierarchical structures.
In this study, we developed a method for estimating the shape of leaf outlines in 3D space by integrating 2D and 3D information and quantification and morphospace analysis of the network structure of leaf veins as network features.
Through these efforts, I have provided phenotyping methods and data acquisition platforms for appropriately quantifying 3D plant morphology, and have developed the theory and technology that enables highly efficient phenome analysis of 3D plant morphology.

Free Research Field

形態測定学

Academic Significance and Societal Importance of the Research Achievements

開発した植物フェノタイピング手法は，従来定量的に評価することが難しい形質についての定量化を実現した．本研究では，植物３次元形態を個別に定量化可能な要素の表現型値の個別のモデル化とその多変量確率分布モデルにより階層的な集合を表現可能にするというアプローチにより実現した．植物３次元形態の過不足のない定量化はもちろん，野外圃場などの計測が不安定な状況でもノイズに頑健なフェノタイピングが可能になることが期待される．