OpenDroneMap was used to stitch images together and create an orthomosaic of each flight. Parameters were default except for the following arguments: 

min-num-features: 4000, max-concurrency: 6, skip-3dmodel: TRUE, fast-orthophoto: TRUE, crop: 0, texturing-outlier-removal-type: gauss_damping, orthophoto-resolution: 0.125, orthophoto-compression: NONE 

The minimum number of features defines the number of tie points needed to stitch each pair of images. ‘min-num-features’ was lowered from the default 8000 to 4000 to ease processing time and memory load. ‘max-concurrency’ allocates CPU cores to the stitching project. ‘skip-3Dmodel’ and ‘fast-orthophoto’ keep the stitching procedure from creating undesired files like a 3D model and digital elevation model (DEM). ‘crop’ and ‘orthophoto-compression’ maintain the imagery quality, so nothing was cropped or down sampled. ‘texturing-outlier-removal’ defines how moving objects are processed and the option ‘gauss-damping’ was chosen because it is a less aggressive approach that prioritizes images that do not include the moving object. In this image set, there were no moving objects. ‘orthophoto- resolution’ defines the final resolution of the image. A value of 0.125 was selected for this dataset as a conservative estimate of the true resolution collected by the sensor. 

Field Operations: 

The field was planted on April 26th, 2022, with spring barley from the S2MET population. Aggregated by Neyhart et. al. 2019, the S2MET barley population provides a representation of high-performance barley from around the United States, selected to be grown across many environments to study genotype-by-environment interactions. Lines were planted in an augmented block design including 12 blocks and four control varieties planted across all blocks. These control varieties were selected as common high-performing barley lines in the Montana region: Odyssey, Lavina, Merit 57, and Hockett. All other lines were planted once. Planting was conducted with a 6-row planter, planting two 3-row plots simultaneously in a North-South orientation. In total, 23-24 plots were planted per block, for a total of 282 plots. After emergence alleys were cut East-West to distinguish plots more easily.  

Data Processing:  

This dataset was used to develop an analysis workflow using QGIS and R. After stitching, imagery was loaded into QGIS. First, each image was georeferenced to the flight on June 16th using the 6 ground control points laid out over the extent of the field. Further, each band was calibrated relative to the June 16th flight image using the reflectance calibration pad (Micasense, panel serial number RP02-1622081-SC). 

Once georeferenced and calibrated, plants were extracted from each image using the excess greenness index threshold (2 * Green) – Red – Blue). Next, plots were defined through a user-defined line grid overlay that was then translated into a polygon shapefile. This overlay was used to extract digital number statistics in each band, for every plot, on each flight date.  

References:

• Neyhart, J.L., Sweeney, D., Sorrells, M., Kapp, C., Kephart, K.D., Sherman, J., Stockinger, E.J., Fisk, S., Hayes, P., Daba, S., Mohammadi, M., Hughes, N., Lukens, L., Barrios, P.G., Gutiérrez, L. and Smith, K.P. (2019), Registration of the S2MET Barley Mapping Population for Multi-Environment Genomewide Selection. Journal of Plant Registrations, 13: 270-280. https://doi.org/10.3198/jpr2018.06.0037crmp