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.

人们认为，安装在无人机（UAV）上的彩色（RGB）摄像机的光谱校正对于为农业领域研究和育种苗圃中的定量研究提供准确的数据非常重要。这项研究调查了基于过量绿色植被指数（nExG）的简化光谱校正在何种程度上提高了冬小麦和冬大麦基因型早期活力评估的准确性和准确性，这是通过两种不同颜色校正的正镶嵌材料成对比较得出的RGB相机。比较了两种光谱校正方法：经验线法（ELM）和在商业摄影测量软件包（Pix4D Mapper）中执行的光谱校正。两种方法都提高了准确性，ELM光谱校正的性能优于Pix4D Mapper光谱校正。尽管光谱校正后具有较高的精度和更高的准确性，但由于基因型之间nExG的微小差异，照相机在活力评估上仍具有统计学意义上的显着效果。但是，在田间条件下和育种苗圃中，相机效果被评估为微不足道，几乎没有实用和农艺方面的相关性，因为基因型之间的微小差异总体上很难在户外田间实验中再现。