Bulls are a major contributing factor to the reproductive efficiency and economic viability of beef and dairy businesses

However, current speriograms are incomplete, subjective, unreliable, and without a system for bull buyers to easily access and understand results. Sperm morphology is a critical component of fertility evaluation during a breeding soundness examination and freezing semen. Using machine learning, a form of artificial intelligence, we will develop a chute side semen analysis tool that will compile an objective complete differential spermiogram with consistent accuracy unmatched by humans. This chute side diagnostic tool will remove the subjective nature of semen analysis. Once completed will be an invaluable tool to quickly and accurately assess semen during a bull breeding soundness exam. Accompanying apps will help veterinarians and COW-calf producers understand bull testing results needed tobetter make management decisions for improving herd fertility. Accurate consistent results will be assured through defined processes, careful selection of microscopic equipment, reliable image data, and deep machine learning technologies.veterinarians, artificial insemination centers, researchers, and otherscan use this chute side semen evaluation toolchute sidefor quick accurateresults. COW-calf producers will improveprofits through improvingreproductive efficiency by using bulls and semen with increasedpotential for higher pregnancy rates. The US beef industry can realize up to $1.2 billion from improved production for improved sustainability.