(100-20) Measuring leaf elevation angles during shade avoidance response in Arabidopsis thaliana using Raspberry Pi microcomputers and computer vision technique
Assistant Professor University of North Alabama Florence, Alabama
Body of Abstract: Light quality is one of the most important regulators of plant development. In a densely populated area such as a crop field, the red spectrum (R: λ = 660 nm) in the sunlight is selectively consumed by actively photosynthesizing plants while far-red spectrum (FR: λ = 730 nm) is not consumed. As a result, a lower ratio between the red light and the far-red light (R:FR) is created in the surrounding area, which serves as a signal for impending competition with neighboring plants. The low R:FR conditions sensed by the plant trigger a series of developmental processes called shade avoidance response (elongational growth, higher leaf elevation angles, etc.) to better receive the sunlight. Traditionally, hypocotyl length has been measured to quantify this response in Arabidopsis. However, such conventional methods have often been invasive, in which the measurement can be done just once during the plants’ lifetime. In addition, such a method has limitations in measuring leaf elevation angles. Therefore, I adopted a noninvasive high throughput image analysis technique to measure the dynamics of leaf elevation angles during the shade avoidance response in Arabidopsis. Time-laps images were taken from the top and the side of a plant using Raspberry Pi microcomputers under shade avoidance conditions. The leaf elevation index for each plant is determined from the plant dimensions measured by an image analysis software package PlantCV. This cost-effective method was used to monitor the dynamics of changing leaf elevation angles in wild-type plants and in shade avoidance mutants such as phyB and pif mutant plants.