Phenological assessment of the wild blueberry field using an unmanned aerial vehicle

Several studies have demonstrated the use of remote sensing to monitor phenological developments in various crops. However, the technology is currently underutilized in wild blueberry production. Therefore, the objective of this study was to assess the potential of using a multispectral sensor to monitor plant phenology in a wild blueberry field. The DJI Matrice 600 Pro unmanned aerial vehicle (UAV) was equipped with a 5-band (blue, green, red, red edge, and near-IR bands) multispectral MicaSense camera and flown at 30 m. The site used in the study was a commercial field located at Kemptown (Nova Scotia). A randomized complete block experimental design with six replications, four treatments, and a plot size of 6×8 m, with a 2-m buffer between plots was used. Aerial images and field-level data were collected from each plot (high plant variability) simultaneously, with flights conducted at regular intervals. Data were sampled until fruit set, with ortho-mosaic and digital elevation model (DEM) maps generated using an algorithm software (Precision Analytics). Correlation and regression analyses were conducted using the different vegetative indices (VIs); NDVI, ENDVI, and NDRE. Correlation results for all VI's indicated that similar trends were observed in all three VIs at the different phenological stages. VIs at the bud break stage were generally low with R² values ranging between 0.13 to 0.71. Plant height and vegetative number proved to be consistent with the near-infrared band (NIR) vegetation indices (NDVI, NDRE, and ENDVI). Anthesis stage II (F4/F5) and flowering stage (F6/F7) showed significantly high correlation values among all growth stages. Results from this study imply that F4/F5 and F6/F7 stages are good phenological stages for making phenological predictions and estimations about plants using the UAV system.