What do trees and statistics have in common? Pierre Dutilleul, a statistician and professor in McGills Department of Plant Science (Montreal, Canada), will tell you that many natural systems can be better understood using equations and models, provided appropriate data are collected.
Dutilleul is one of the first scientists who have used a computed tomography (CT) scanner to study how tree branching affects light interception. "We collect CT scan data, which basically measures of density in 3D, to quantify the complexity of plant branching patterns," he explains. "This will lead to a more complete and accurate model providing a better understanding of why some plants perform better in given light environments. This is important because in the long run, it means less fertilizer application and less greenhouse gas in the atmosphere through enhanced photosynthesis".
Dutilleul and his group are using CT scan data to create 3-D images of plant canopies. After scanning a plant, such as a young cedar, a computer converts the CT scan data into a digital 3-D model. As leaves and branches yield different CT scan data, the leaves can be removed from the digital model. The resulting skeletal images give more detailed and accurate information than the traditional methods of plant characterization. This information can then be used to estimate the amount of light intercepted by the plant.
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