Crop phenotyping research: Self-supervised deep learning enhances green fraction estimation in rice and wheat

The accurate measurement of the green fraction (GF), a critical photosynthetic trait in crops, typically relies on RGB image analysis employing segmentation algorithms to identify green pixels within the crop. Traditional methods have limitations in accuracy due to environmental variances, while advanced deep learning techniques, like the SegVeg model, show improvement but don't fully leverage the latest vision transformer models.