Automated Recognition of Corn Embryos for Selective Breeding
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The Symposium provides undergraduates from all academic disciplines with an opportunity to share their research with the university community and other guests through conference-style oral presentations. The Symposium represents part of a larger effort of Iowa State University to enhance, support, and celebrate undergraduate research activity.
Though coordinated by the University Honors Program, all undergraduate students are eligible and encouraged to participate in the Symposium. Undergraduates conducting research but not yet ready to present their work are encouraged to attend the Symposium to learn about the presentation process and students not currently involved in research are encouraged to attend the Symposium to learn about the broad range of undergraduate research activities that are taking place at ISU.
The first Symposium was held in April 2007. The 39 students who presented research and their mentors collectively represented all of ISU's Colleges: Agriculture and Life Sciences, Business, Design, Engineering, Human Sciences, Liberal Arts and Sciences, Veterinary Medicine, and the Graduate College. The event has grown to regularly include more than 100 students presenting on topics that span the broad range of disciplines studied at ISU.
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An analysis of a kernel of corn is essential to determining its worth for selective breeding. The embryo found in a kernel of corn is what is used to produce oils, and therefore maximizing its size would make a farmer's yield more efficient. The current method of recording the area of the corn's embryo, however, is to take measurements by hand. This project seeks to provide a solution by developing a program that can recognize and mark the embryo on a picture of a kernel of corn without needing guidance. The program will be taught to recognize patterns in thousands of images which have already been marked, until it can successfully apply those patterns to mark the embryo on an unlabeled kernel. A user interface will then be developed to allow researchers a simpler method of employing the program, simply uploading images to it and running the application. When complete, this project will expedite the kernel marking process significantly, allowing researchers more time to do more extensive and in-depth analysis on the data collected. This could likely result in faster improvements to embryo size as well as more impressive end results.