Machine learning methods for efficient and automated in situ monitoring of peach flowering phenology

•Image colors vary dramatically at different BBCH flowering phenological stages.•A random forest model classifies BBCH stages by image color ranges accurately.•Growing degree days and biological growth time improve the model accuracy.•In situ flowering phenology monitoring is applicable for peach br...

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