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Precision, quantitative measurement of sunflower capitulum inclination: A trigonometry‐based approach

Agronomy Journal · 12 Oct 2024 · 10.1002/agj2.21708

Abstract

Abstract Sunflower (Helianthus annuus) is a widely cultivated crop that exhibits a trait known as capitulum (or head) inclination at maturity. This trait is influenced by various structural factors, including head weight, stem traits, and plant height. A sunflower head should be at an angle at which the head faces the ground to avoid damage from the sun and birds. While this desired inclination range is known, current methods, including visual estimation and a model of measuring inclined length of the stem, fail to provide precise measurements of angle. This study introduces novel approaches to mathematically measure the head inclination angle. The research, which was conducted over the 2022 and 2023 growing seasons, involved an aluminum rod equipped with a ruler and a digital protractor to measure various height and angle components. Using the data collected, three methods were applied for measuring inclination: a previously published model as a control, a trigonometry‐based approach using angle and height measurements, and other model‐based approaches. A linear model resulted in a formula to calculate the head angle of any plant based solely on two height measurements, the highest point of the plant at both bloom (R5) and maturity (R9). Calculations of heritability and correlation suggest this method has created a precise alternative to existing estimation methods. The resulting formula has the potential to be paired with measurements from high‐throughput phenotyping methods, such as those facilitated with drones and ground robots, to fully automate the process of collecting head inclination data.

Plant phenotyping relevance

ヒマワリ頭花傾斜角という植物形質を対象に、既存法との比較を含む数学的測定法と計算式を開発・評価しており、表現型取得法が研究の中心である。

abstractThis study introduces novel approaches to mathematically measure the head inclination angle.
abstractCalculations of heritability and correlation suggest this method has created a precise alternative to existing estimation methods.

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