Use of an unmanned aerial vehicle with a multi-spectral image camera for high throughput phenotyping in precision agriculture Shara Ahmed, Catherine E. Nicholson, John R Marshall, Justin J. Perry and John R Dean Department of Applied Sciences, Northumbria University, UK. Canopy height data is crucial in precision agriculture (PA) to monitor both the growth rate of crops throughout the growing season as well as provide information on when to apply soil nutrients to achieve the highest yield. Traditional field measurements of canopy height are time consuming, laborious and are limited to retrieve plot-level information. However, recent developments in remote sensing techniques using an unmanned aerial vehicle (UAV) with multi-spectral image (MSI) camera can be used to effectively predict canopy height using mathematical modelling of the sensor data. The application of a UAV with MSI camera can be used to derive canopy height models (CHM) using dense point cloud data derived using the structure from motion method (SfM); this allows extraction of canopy height for each individual field plot. In our latest research we conduct a multi- temporal study to estimate canopy height of winter canola ( Brasica napus L.), otherwise known as rapeseed, using a UAV fitted with a 5 camera-array covering the blue (450 ± 16 nm), green (560 ± 16 nm), red (650 ± 16 nm), red edge (730 ± 16 nm) and near infrared (840 ± 26 nm) spectra with an additional camera that can also provide live images in RGB (visible) mode. Previous studies from our group have used the UAV-MSI for investigations of tree phenotyping in an ancient and semi-natural woodland. 1,2 In this research, the UAV data was collected over a period of 10 months and focused on the growth stages of the crop. Data will be presented on both crop height and its link with PA, and its potential to provide valuable information to farmers / land managers to guide their decision-making in terms of the application of the amount of water, fertilizer, and pesticides so that the potential within the growing crop is maximised for better yield and quality. References 1. Ahmed, S., Nicholson, C.E., Muto, P., Perry, J.J. and Dean, J.R.,The use of an unmanned aerial vehicle for tree phenotyping studies, Separations 2021, 8, 160. https://doi.org/10.3390/separations8090160 2. Ahmed, S., Nicholson, C.E., Muto, P., Perry, J.J. and Dean, J.R., Applied aerial spectroscopy: A case study on remote sensing of an ancient and semi-natural woodland, PLOS ONE 16(11): e0260056. https://doi.org/10.1371/journal. pone.0260056
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