AREI Crop Research Department has started the implementation of NOBALwheat research in the following project activities
WP1: Identification of high plasticity wheat genotypes by phenotyping.
Task 1.1 To establish a joint spring wheat collection and to implement field experiments in four project partner countries
Task 1.2 To phenotype core germplasm collection for the most important agronomic traits
At Stende research centre the field trials including 300 spring wheat genotypes originated from Baltic States and Norway were established. Phenotyping of important agronomic traits is started and will be carried out throughout growing season.
WP2: Implementing low-cost high throughput plant phenotyping in Baltic wheat breeding.
Task 1.1 to establish a core germplasm collection of spring wheat and to implement field experiments at four project partner countries
Task 1.2 to phenotype core germplasm collection for the most important agronomic traits: disease resistance, nitrogen and water use efficiency, yield potential.
Yield trials established in WP1 will be phenotyped using UAVs fitted with RGB and multispectral cameras at weekly intervals during the growing season, from emergence to crop maturity in order to monitor crop growth and development and derive breeding-relevant traits. Images will be processed in Pix4D or similar software to obtain image mosaics for calculations of vegetation indices and 3D point clouds for monitoring plant height throughout the season, which will be done in QGIS or similar software with geo-referencing in order to extract data on field trial plot basis. Estimates obtained from UAV imaging will be compared to ground truth measurements in order to assess the accuracy of the high throughput phenotyping data.
Proximal imaging vehicle have been constructed equipped with NDVI (modified RGB) and RGB cameras. It will be employed to phenotype plots for each spring wheat cultivar at three time points during the season starting from growth stage 13 (GS13) till ripening (GS91). Various Vegetation Indices and traits will be calculated: Canopy cover, Visible Atmospherically Resistant Index (VARI), Triangular Greenness Index (TGI), Senescence will be evaluated using RGB images. The normalized difference vegetation index (NDVI) will be recorded from NDVI camera for retrieval of vegetation canopy biophysical properties.
Estimates obtained from both high throughput plant phenotyping platforms will be compared to ground truth measurements in order to assess the accuracy of the high throughput phenotyping data.