DOI: 10.13020/d6bt49
title: Sample 360 video for the analysis of plant movement

description: Violent movement of cereal crop stems can lead to failure under high winds. Known as lodging, this phenomenon is particularly severe in cereal crops such as oat, barley, and wheat, and contributes to yield and economic losses. Quantifying the movement of cereal crops under field wind stress could aid in the breeding and selecting of lodging resistant cereals. We present a method to quantify the wave like movement of cereal crop rows in a high throughput fashion under field wind conditions. By analyzing pre-defined regions of hemispherical 4K resolution video, we obtain a time varying color signal of wind induced stem and canopy movement. Bandpass filtering is applied to the color signals to filter out changes in lighting due to sunlight changes, enabling comparisons across different lighting conditions. Peaks are then identified in the signal, and the distance in frames to the next peak as well as the absolute area under the curve between peaks is recorded. The distributions of distances to adjacent peaks (expressed as frequencies) are recorded and the area within a defined frequency bin is summed to get an approximation of the frequency and amount movement. We applied this method to analyze the wind induced movement of 16 cereal cultivars planted in a randomized complete block design on 5 different windy days. We detected significant differences in the mean frequency and amplitude within 0.2 Hz frequency bins among 16 cereal cultivars, with mean frequencies ranging between 1.24 and 1.53 Hz. This method quantifies the frequency and amplitude of movement in cereal varieties at high throughput in the field, and shows promise for characterizing the physiological basis for differences in cereal movement and lodging resistance.
description: Violent movement of cereal crop stems can lead to failure under high winds. Known as lodging, this phenomenon is particularly severe in cereal crops such as oat, barley, and wheat, and contributes to yield and economic losses. Quantifying the movement of cereal crops under field wind stress could aid in the breeding and selecting of lodging resistant cereals.  We present a method to quantify the wave like movement of cereal crop rows in a high throughput fashion under field wind conditions.  By analyzing pre-defined regions of hemispherical 4K resolution video, we obtain a time varying color signal of wind induced stem and canopy movement.  Bandpass filtering is applied to the color signals to filter out changes in lighting due to sunlight changes, enabling comparisons across different lighting conditions.  Peaks are then identified in the signal, and the distance in frames to the next peak as well as the absolute area under the curve between peaks is recorded.  The distributions of distances to adjacent peaks (expressed as frequencies) are recorded and the area within a defined frequency bin is summed to get an approximation of the frequency and amount movement. We applied this method to analyze the wind induced movement of 16 cereal cultivars planted in a randomized complete block design on 5 different windy days.  We detected significant differences in the mean frequency and amplitude within 0.2 Hz frequency bins among 16 cereal cultivars, with mean frequencies ranging between 1.24 and 1.53 Hz. This method quantifies the frequency and amplitude of movement in cereal varieties at high throughput in the field, and shows promise for characterizing the physiological basis for differences in cereal movement and lodging resistance.
description: Sample video for the analysis of plant movement.  Video was taken using a 360fly 4k hemispherical video camera. The 360 camera contained an 8 Elements Glass Ultra Fisheye Lens with an aperture of F2.5, effective focal length of 0.88mm, and a minimum focus distance of 30cm. The horizontal field of view was 360°, while the vertical field of view was 240°.  Brightness was set to full brightness, while the aperture and contrast settings were set in the middle values for each.  Videos were recorded at 24 frames per second with a per frame image size of 2880 x 2880 pixels.  The 360fly ios app (V 2.0.0) was used to maintain consistent settings and initiate camera recordings while the camera was mounted on the track system, and the 360fly Director (V 0.10.4.0)  software for Microsoft Windows 10 was used to download the videos from the camera and export them into .mp4 format.