Plant foliage is known to respond rapidly to environmental stressors by adjusting leaf orientation at different timescales. One of the most fascinating mechanisms is paraheliotropism, also known as light avoidance through leaf movement. The leaf orientation (zenith and azimuth angles) is a parameter often overlooked in the plant and remote sensing community due to its challenging measurement procedures under field conditions. In this study, we investigate the synergistic potential of uncrewed aerial vehicle (UAV)-based mutlispectral imaging, terrestrial laser scanning (TLS) and radiative transfer model (RTM) inversion to identify the paraheliotropic response of two distinct soybean varieties: Minngold, a chlorophyll-deficient mutant, and Eiko, a wild variety. We examined their responses to drought stress during the boreal summer drought in 2022 in western Germany by measuring average leaf inclination angle (ALIA) and canopy reflectance. Measurements were taken in the morning and at midday to track leaf movement. Our observations show significant differences between the paraheliotropic response of both varieties. Eiko’s terminal and lateral leaves became vertically erect in the midday (54→61∘), while Minngold’s ALIA remained largely unchanged (52→57∘). Apart from the vertical leaf movement, we also observed leaf inversion (exposing the abaxial side of the leaf) in Eiko under extreme water scarcity. The red edge band at 740 nm showed the strongest correlation with ALIA (r2=0.52−0.76) The ratio of the far red edge to near infrared (RE740/NIR842) vegetation index compensated for varying light levels during morning and afternoon measurements, exhibiting strong correlations with ALIA when considering only sun-lit leaf spectra (r2=0.72). The retrieval of ALIA with PROSAIL varied based on ALIA constraints and the spectra used for retrieval (full spectrum or the combination of bands 742 and 842), resulting in a root mean square error (RMSE) of 7.7-12.9°. PROSAIL faced challenges in simulating the spectra of plots with very low LAI due to the soil background. This study made the first attempt to observe different paraheliotropic responses of two soybean varieties with UAV-based multispectral imaging. Proximal sensing opens up the possibilities to observe early stress indicators such as paraheliotropism, at much higher spatial and temporal resolution than ever before.

中文翻译：

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多光谱成像和地面激光扫描检测干旱诱导的大豆近日向叶片运动


众所周知，植物叶子通过在不同时间尺度调整叶子的方向来快速响应环境压力源。最迷人的机制之一是向日性，也称为通过叶子运动避光。叶片方向（天顶角和方位角）是工厂和遥感界经常被忽视的一个参数，因为它在野外条件下的测量程序具有挑战性。在这项研究中，我们研究了基于无人驾驶飞行器 （UAV） 的多光谱成像、地面激光扫描 （TLS） 和辐射传输模型 （RTM） 反演的协同潜力，以确定两种不同大豆品种的近日向性响应：Minngold，一种叶绿素缺乏的突变体，和 Eiko，一种野生品种。我们通过测量平均叶片倾角 （ALIA） 和冠层反射率，研究了它们在 2022 年德国西部北方夏季干旱期间对干旱胁迫的反应。在早上和中午进行测量以跟踪叶子的运动。我们的观察表明，两种品种的向日性响应之间存在显著差异。Eiko 的顶叶和侧叶在中午垂直直立 （54→61∘），而 Minngold 的 ALIA 基本保持不变 （52→57∘）。除了垂直的叶子运动外，我们还观察到在极度缺水的情况下，Eiko 的叶子倒置（暴露叶子的背面）。740 nm 处的红边带与 ALIA 的相关性最强 （r2=0.52−0.76）远红边与近红外 （RE740/NIR842） 植被指数的比率补偿了上午和下午测量期间不同的光照水平，当仅考虑阳光照射的叶光谱时，与 ALIA 表现出很强的相关性 （r2=0.72）。 使用 PROSAIL 对 ALIA 的反演根据 ALIA 约束和用于反演的光谱（全谱或 742 和 842 波段的组合）而变化，导致均方根误差 （RMSE） 为 7.7-12.9°。由于土壤背景，PROSAIL 在模拟 LAI 非常低的地块的光谱时面临挑战。本研究首次尝试用基于无人机的多光谱成像观察两个大豆品种的不同向日向响应。近端传感为以比以往更高的空间和时间分辨率观察早期应力指标（如向日性）提供了可能性。