High-throughput 3D modellingto dissect the genetic controlof leaf elongationin barley.
The difficulties of tasks in computer vision on plant leaf images should be leaf identification < leaf counting < leaf tracking. As so many cross-overs will happen in leaf development. However, it is potentially interesting that individual leaf development may indicate the reflection of plant to external stimulus. This paper developed a 3D based methods to track individual leaf for barley. Through connecting with populations, it reveals associated loci that can not be identified by other traditional methods, which is promising to be applied in other crop studies. However, to develop a much maturer software to work on later-developed plant will be much more chanllenged, more intelligent methods should be proposed to accomplish it.