Thank you to the Targeting Excellence sponsors, board, and committees. Your time and efforts in organizing this award and associated events are invaluable. The networking events and financial support you provide greatly assists developing young professionals within the food animal industry.
I first became interested in food animal agriculture on my family farm in southern Iowa where we raised pigs, cattle, sheep and goats in addition to row crops. While I enjoyed all aspects of agriculture, my main passion was for pigs. As a youth, I was the sole owner of a small herd of pigs and cattle. I showed the animals I raised at the county and state levels as a member of both 4-H and FFA. However, outside of the fair period I would sell my livestock to local consumers. My experiences growing up on the farm and participating in youth organizations led me to pursue higher education at Iowa State University where I graduated in 2018 with a bachelor’s degree in animal science with a minor in agricultural business. While an undergrad, I was an active member in Block & Bridle as well as Meat Science Club. Also, I was a member of the 2016 Iowa State University Intercollegiate Meat Judging team and the 2018 Iowa State University Intercollegiate Meat Animal Evaluation team. These judging teams along with my internships with Iowa Select Farms and Tyson Foods further sparked my interest in animal agriculture and especially the swine industry. This led me to pursue graduate education at North Carolina State University (NCSU) under the advisement of Dr. Mark Knauer.
As a master’s student my research consisted of several different projects concerning applied swine production and quantitative breeding and genetics. Following completion of my degree during the summer of 2020, I decided to continue my education by pursuing a doctoral degree in animal science. My research involves the utilization of artificial intelligence and machine learning in the analysis of images within swine production. The first stage of the project was to develop a model to automate the estimation of intramuscular fat percentage, backfat and loin depth from ultrasound images of live hogs. The second stage involves utilizing these techniques of image analysis and apply them to other swine production traits such as feeding behavior and feet and leg conformation. The goal is to apply this technology to analyze images used in the evaluation and selection of market and breeding animals. After graduation, I plan to obtain a position with a swine genetics or technology company and further develop tools to advance swine production. From my experience, there tends to be a gap at times between the technology being developed and its real-life application within the swine industry. Using my experience within swine production and computer science, I hope to be able to do my part in bridging that gap. I expect to use the knowledge and experience I have gained within the pork and swine production industries to continue to improve production practices and the pigs we produce through genetic selection and technological advancements. Wherever my path leads me in the future, I know for certain it will be a part of the food animal industry. Thank you for your consideration of my application.