Authors:

Alyson Jones

Date Created:

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About Paper:

We all know that plants absorb nutrients through their roots. However, what we often do not know is the name of the vein in which these nutrients are transported. Xylem is the structure within plants that helps both give them their form and deliver nutrients to the rest of the plant. Here we are developing tools to automate and mathematically quantify mutant patterns within this xylem tissue. We are using image-processing tools within Matlab and topological data analysis libraries within Python in order to characterize the shape of our image data. Topological data analysis is the name of a broader set of tools that we use to determine the shape of data. The main tool that we use in topological data analysis is persistent homology. In computing persistent homology, we start with a set of points and slowly increase their radius. When increasing their radius, these points will eventually touch one another and form connected components (clusters) and possibly holes or loops. These connected components and holes are significant due to persistent homology's roots within topology. Topology is the study of shapes in an abstract way. Within this field of study we focus on how many holes and pieces (connected components) a shape can have. This abstract way of looking at objects is very helpful when giving data, such as a grid of pixels or photo, a shape. Persistent homology allows us to look at images of xylem structure and mathematically determine the impact of mutations on the xylem patterns. Keywords: Topology; Topology Data Analysis; Persistent Homology; Xylem; Image Processing

Source:

Purdue University / 2024

Topics:

No topics listed

Co-authors:

Alyson Jones