Seasonal color shifts and genetic diversity in Scots pine: a generalizable RGB imaging and CNN-based framework for conifer seedlings
Key message
Leveraging affordable red-green-blue (RGB) imaging and neural network algorithms, this study delivers a high-throughput method to quantify seasonal color shifts and genetic variation in Scots pine seedlings. Hue-saturation-brightness (HSB) color analysis, and RGB values can be used for population and seasonal differentiation and hold potential for advancing breeding programs in forestry under changing climatic conditions.
Keywords
Scots pine seedlings; Phenology; Autumn reddening; Heritability; Forest nursery; Affordable phenotyping; RGB imaging; HSB color; Deep learning; Convolutional neural network
Publication
Chuchlík, J., Čepl, J., Neuwirthová, E. et al. Seasonal color shifts and genetic diversity in Scots pine: a generalizable RGB imaging and CNN-based framework for conifer seedlings. Annals of Forest Science 82, 38 (2025). https://doi.org/10.1186/s13595-025-01308-4
Data availability
The datasets generated during and analyzed during the current study are available in the Figshare repository, https://doi.org/10.6084/m9.figshare.28239326.v2 and referenced as Cuchlik (2025) The custom code generated during the current study are available in the Figshare repository, https://doi.org/10.6084/m9.figshare.28805840.v2.
Handling editor
Erwin Dreyer