Comparison of PhenoCams and drones for lean phenotyping of phenology and senescence of wheat genotypes in variety testing

Abstract In variety testing and breeding of wheat ( Triticum aestivum L.), it is crucial to know the timing of phenological stages and the senescence behavior of genotypes to select for locally adapted varieties. Sound knowledge of the timing of phenological stages also allows for a more meaningful interpretation of measurements such as yield, quality, or disease ratings. In the presence of stresses, only a combined characterization of phenology and environmental conditions can allow for insights into unraveling stress resistance and stress avoidance. Capturing these traits visually in the field is very time‐consuming. Here, a semimobile PhenoCam setup was used to track phenology and senescence from ear emergence to full maturity. PhenoCams mounted on field masts took images of wheat plot trials on a daily basis. In a partial least squares regression analysis, the temporal features of multiple vegetation indices were combined in one model to track phenology and senescence. The method was compared with visual reference methods and repeated drone flights with a multispectral camera. The Pearson's correlation between visual reference methods and PhenoCam predictions was stronger than 0.8, often above 0.9, for most stages. An economic analysis showed that PhenoCams are economically interesting, especially for observing remote experimental sites. Thus, PhenoCams offer a cost‐effective replacement for visual ratings of phenology and senescence, particularly in the context of multienvironment trials.