Field based phenotyping of forage crops using close remote sensing … · 2018-09-04 ·...
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Applications Construct a high resolution orthomosaic and digital elevation model based on individual images taken from a drone Field based phenotyping of forage crops using close remote sensing tools Peter Lootens 1 , Irene Borra-Serrano 1,2 , Tom De Swaef 1 , Jonas Aper 1 , Isabel Roldán-Ruiz 1,3 Corresponding author: peter.lootens @ilvo.vlaanderen.be 1 Plant Sciences Unit, ILVO, Caritasstraat 39, 9090 Melle (Belgium); 2 KU Leuven, Division of Forest, Nature and Landscape, Celestijnenlaan 200E, 3001 Leuven (Belgium); 3 Department of Plant Biotechnology and Bioinformatics, Ghent University, Technologiepark 927, 9052 Ghent (Belgium) B A Rising-plate meter (cm) Orthophoto Products DEM Drought tolerance Canopy height/growth Canopy closure/N content Persistency/Sod density (Lootens et al. 2015) (Borra-Serrano et al. 2018, accepted) Canopy height (cm) Orthomosaic Digital Elevation Model Fly field trial Stitch images using Photoscan Description Cultivated perennial grasslands provide forage for livestock farming and are essential elements in European agriculture. To secure biomass production of the required quality, over multiple seasons, farmers need excellent grass and clover varieties. Traditionally, forage crop breeders use visual scores and plot harvesters to evaluate their selections, but they are increasingly implementing technological solutions such as drone based phenotyping tools to keep pace with these high expectations. Furthermore, accurate and reliable phenotyping is essential to allow full exploitation of molecular tools to advance genetic improvement (Lootens et al. 2016). We develop close remote sensing tools to phenotype spaced grass plants and plots in a breeding context. Phenotyping using image analysis under field conditions assures that the genotype (plant/plot) under evaluation develops in an agriculturally relevant environment and allow monitoring of plant traits in a non-destructive manner. The use of drones allows the objective evaluation of numerous selections in parallel. We use images captured using different sensors (RGB, multispectral and thermal), to calculate vegetation indices from orthomosaics at a spatial/planimetric resolution of up to 0.5 cm and digital elevation models, built based on the structure from motion (SfM) technique, with an altimetric resolution up to 1.2 cm. This resolution is more than sufficient to assess and screen individual plants and small plots for traits relevant in breeding. Applications related to the evaluation of sod density, persistency, drought tolerance, growth and biomass accumulation, that are currently being implemented in the ILVO breeding program of perennial ryegrass (Lolium perenne), are presented. Prepare flight plan drone Prepare drone Multiple overlapping images captured
Transcript of Field based phenotyping of forage crops using close remote sensing … · 2018-09-04 ·...
Applications
Construct a high resolution orthomosaic and digital elevation model based on individual images taken from a drone
Field based phenotyping of forage crops using close remote sensing tools
Peter Lootens1, Irene Borra-Serrano1,2, Tom De Swaef1, Jonas Aper1, Isabel Roldán-Ruiz1,3
Corresponding author: [email protected]
1Plant Sciences Unit, ILVO, Caritasstraat 39, 9090 Melle (Belgium); 2KU Leuven, Division of Forest, Nature and Landscape, Celestijnenlaan 200E, 3001 Leuven (Belgium); 3Department of Plant Biotechnology and Bioinformatics, Ghent University, Technologiepark 927, 9052 Ghent (Belgium)
BA
Rising-plate meter (cm)
OrthophotoProducts
DEM
Drought tolerance
Canopy height/growth
Canopy closure/N contentPersistency/Sod density
(Lootens et al. 2015)
(Borra-Serrano et al. 2018, accepted)
Canopy height (cm)
Orthomosaic
Digital Elevation Model
Fly field trial
Stitch images using Photoscan
Description
Cultivated perennial grasslands provide forage for livestock farming and are essential elements in European agriculture. To secure biomass production of therequired quality, over multiple seasons, farmers need excellent grass and clover varieties. Traditionally, forage crop breeders use visual scores and plotharvesters to evaluate their selections, but they are increasingly implementing technological solutions such as drone based phenotyping tools to keep pacewith these high expectations. Furthermore, accurate and reliable phenotyping is essential to allow full exploitation of molecular tools to advance geneticimprovement (Lootens et al. 2016).
We develop close remote sensing tools to phenotype spaced grass plants and plots in a breeding context. Phenotyping using image analysis under fieldconditions assures that the genotype (plant/plot) under evaluation develops in an agriculturally relevant environment and allow monitoring of plant traits in anon-destructive manner. The use of drones allows the objective evaluation of numerous selections in parallel. We use images captured using different sensors(RGB, multispectral and thermal), to calculate vegetation indices from orthomosaics at a spatial/planimetric resolution of up to 0.5 cm and digital elevationmodels, built based on the structure from motion (SfM) technique, with an altimetric resolution up to 1.2 cm. This resolution is more than sufficient to assessand screen individual plants and small plots for traits relevant in breeding. Applications related to the evaluation of sod density, persistency, drought tolerance,growth and biomass accumulation, that are currently being implemented in the ILVO breeding program of perennial ryegrass (Lolium perenne), are presented.
Prepare flight plan drone Prepare drone
Multiple overlapping images captured
