Multispectral imaging and terrestrial laser scanning for the detection of drought-induced paraheliotropic leaf movement in soybean

Abstract

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.

Keywords

• Leaf inclination angle
• PROSAIL
• UAV
• TLS
• Paraheliotropism