The importance of spectral correction of UAV-based phenotyping with RGB cameras

•Orthomosaics from different RGB cameras without spectral corrections, was very precise to assess early vigor in wheat.•Spectral correction allowed the estimation of nExG based on reflectance, which improved the accuracy of measurements.•Spectral correction did not remove statistical interaction between camera and genotype.•Using repeated flights as benchmarks, showed that improvements in accuracy through spectral correction were marginal.•Camera-effects leading to statistical interaction between camera and genotype were considered irrelevant in plant-breeding. Spectral correction of colour (RGB) cameras mounted on unmanned aerial vehicles (UAV) is considered important to produce accurate data for quantitative studies in agricultural field research and breeding nurseries. This study investigated the extent to which a simplified spectral correction improves the precision and accuracy of early vigour assessments in winter wheat and winter barley genotypes based on the excess green vegetation Index (nExG) from a pairwise comparison of colour-corrected orthomosaics produced with two different RGB cameras. Two methods of spectral correction were compared, the empirical line method (ELM) and the spectral correction performed in a commercial photogrammetry software package (Pix4D Mapper). Both methods improved the accuracy, with the ELM spectral correction performing better than the Pix4D Mapper spectral correction. Despite high precision and improved accuracy after spectral correction, there were still statistically significant camera effects on vigour assessments because of the minute differences in nExG between genotypes. However, camera effects were evaluated as marginal and with little practical and agronomical relevance under field conditions and in breeding nurseries, as the minute differences between genotypes is overall difficult to reproduce in outdoor field experiments.