Bull subfertility is a hidden drain on america's beef industry, with reproductive inefficiencies costing the nation's cattle producers an estimated $2-3 billion annually through reduced calf crops,…

The Department of Agriculture National Institute of Food and Agriculture awarded Emery Animal Health $181,500 under the Small Business Innovation Research (SBIR) Program on September 15, 2025.

The Phase I project develops artificial intelligence-powered computer vision technology that automatically identifies and classifies sperm abnormalities in bull semen. Emery Animal Health is creating comprehensive image databases using over 500 diverse semen samples collected at its veterinary clinic and training machine learning algorithms to recognize morphological defects that affect fertility. The technology combines advanced image processing with continuously improving machine learning models to achieve accuracy validated against expert veterinary analysis. This Phase I work aims to demonstrate technical feasibility for Sperm Incyte, a portable diagnostic instrument intended to make advanced fertility assessment accessible to rural veterinary practices and livestock producers, ultimately addressing an estimated $2–3 billion in annual economic losses from bull subfertility across the U.S. beef industry.

Performance occurs in Castle Dale, Utah, with a completion date of May 14, 2027. The SBIR program supports small businesses in creating innovative technologies with commercial potential and societal benefit, with Phase I awards intended to demonstrate technical feasibility and lay groundwork for potential Phase II commercialization support.

Bull subfertility is a hidden drain on america's beef industry, with reproductive inefficiencies costing the nation's cattle producers an estimated $2-3 billion annually through reduced calf crops, extended calving intervals, and increased replacement costs. Current breeding soundness examinations rely heavily on manual microscopic evaluation of sperm, which is time-consuming, subjective, and often misses subtle abnormalities that significantly impact fertility. With 20% of bulls in herds potentially having fertility issues affecting over 30 million beef cows nationwide, cattle producers need more accurate, consistent, and accessible tools to evaluate their breeding stock and make informed decisions that strengthen both individual operations and america's beef supply chain. This phase i project develops artificial intelligence-powered computer vision technology that automatically identifies and classifies sperm abnormalities with unprecedented accuracy and consistency. Working with over 500 diverse semen samples at our veterinary clinic, we are creating comprehensive image databases and training sophisticated computer models to recognize and categorize the subtle morphological defects that affect fertility. Our approach combines advanced image processing techniques with machine learning algorithms that continuously improve through use, similar to how smartphone cameras have evolved to automatically detect and focus on faces. By achieving our target accuracy levels and validating results against expert veterinary analysis, this technology will form the foundation for sperm incyte, a portable diagnostic instrument that will make advanced fertility assessment accessible to rural veterinary practices and livestock producers. The successful completion of this project will lead to improved breeding efficiency across the industry, helping reduce the billions in economic losses from poor fertility, supporting more sustainable beef production, and ultimately contributing to a more secure and affordable food supply for consumers.