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

Abstract

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.

Plant phenotyping relevance

UAV-RGB画像のスペクトル補正法を比較・評価し、コムギとオオムギの初期生育形質（nExG）推定精度への影響を検証しており、植物表現型取得法が中心である。

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