Dr. Danny Fox was inducted into the Animal Science Hall of Fame on April 4, 2019. The event took place during the Celebration of Excellence recognition program hosted by the Department of Animal Sciences. The following is his induction citation.
Dr. Danny Fox is a Professor Emeritus in the Department of Animal Science at Cornell University. He was born and raised in northwest Ohio and received his B.S. in Animal Science in 1962 from The Ohio State University. After operating and managing the family farm in Williams County for 5 years, he returned to OSU Animal Science and received M.S. (1968) and Ph.D. (1970) degrees in Ruminant Nutrition. At Cornell University since 1977, Dr. Fox conducted research and Extension programs in beef and dairy cattle nutrition and taught courses in beef and dairy cattle nutrition and nutrient management. Before joining the Cornell faculty, he held positions as beef cattle Extension feedlot specialist at South Dakota State University and beef cattle feedlot nutrition research and Extension at Michigan State University.
Dr. Fox’s 35 year career in ruminant nutrition research focused on the development of data, methods, mathematical models, and computer software to more accurately predict cattle nutrient requirements and nutrients derived from feeds with wide variations in cattle types, environments, and feeds and the composition of their carbohydrate and protein fractions. At Cornell from 1977 until retiri
ng in 2005, Dr. Fox organized and led a team of faculty, graduate students, and research support staff that developed, evaluated and implemented on farms with microcomputers the Cornell Net Carbohydrate and Protein System (CNCPS) for evaluating and formulating rations for beef and dairy cattle. In 1992 Dr. Fox was asked to serve on the National Research Council (NRC) committee to revise the NRC (1984) nutrient requirement recommendations for beef cattle and to develop a computer model for application of their recommendations, which was based on the CNCPS. Subsequently, many components in the NRC (1996) model were used in the development of the 2016 National Academy of Science, Engineering and Medicine Beef Cattle nutrition model.
Beginning in 1977 and until he retired in 2005, Dr. Fox’s team developed the Cornell Value Discovery Program (CVDS) for sorting and tracking cattle according to days predicted by the CVDS model to reach the target grade, and to allocate pen feed consumed to individuals in the pen to allow mixed ownership. Over 10 million head of feeder steers and heifers have been sorted on arrival in feedlots into pens according to CCS and CVDS predicted days to reach the target quality grade, with an average increase in returns of $10 - $15 per head.
From the early 1990’s until he retired, Dr. Fox’s modeling program became more focused on integrating knowledge about crops, soils, and animals on dairy farms
to improve their sustainability by reducing feed costs and excess nutrients that impact water quality. He organized an inter-disciplinary team of scientists at Cornell (crops, soils, engineering, economics, and water resources) and dairy farmers in the state to develop and implement the Cornell University Nutrient Management Planning System (CUNMPS). In case studies on dairy farms, implementation of precision feeding with the CUNMPS reduced nitrogen and phosphorus excreted an average of 1/3, while increasing milk production 2-4 lb./day and reducing feed costs $50 to $150/lactating dairy cow/year.
Dr. Fox’s research resulted in more than 330 publications, invited presentations at more than 150 conferences, and training of 61 graduate students. His research led to requests to serve on various national committees, including several of the NRC and Council on Agriculture Science and Technology (CAST). He conducted many workshops on describing and using the models described in the United States, Canada, Mexico, Brazil, Argentina, South Korea and Western Europe, and consulted with numerous commercial companies on the application of the CNCPS and CVDS models in their cattle nutrition and management software.