Leaf Size

Leaf size, a crucial plant trait influencing growth and yield, is a focus of ongoing research employing computer vision and machine learning techniques. Current studies utilize various deep learning architectures, including Mask R-CNN, vision transformers, and convolutional neural networks (CNNs), to automate leaf size estimation and analysis from images, often incorporating image segmentation and 3D modeling for improved accuracy. These advancements enable high-throughput phenotyping, facilitating efficient plant breeding and precision agriculture by providing rapid, non-destructive measurements of leaf morphology and its correlation with other plant characteristics. The resulting data contributes to a deeper understanding of plant growth and development, ultimately improving crop yields and resource management.