Mallarino, Antonio

Antonio is Professor Emeritus (retired) and was Professor of Agronomy, Nutrient Management Research and Extension Specialist, until December 31, 2023, at Iowa State University (ISU). He continues activities, however, by finishing research reports and articles, helping finish his graduate students, and contributing to ISU Extension for areas within his expertise. He has focused on phosphorus, potassium, lime, micronutrients, manure nutrients management, soil testing and plant analysis, use of precision agriculture technologies, and management impacts on phosphorus loss from fields. He has been co-responsible for ISU Extension nutrient management guidelines, contributed to the development of the Iowa Phosphorus Index and the Iowa Nutrient Reduction Strategy. He has represented ISU at the USDA/NIFA North Central Region Committee for Soil Testing and Plant Analysis and the committee Minimizing P Losses from Agriculture. He served at the North American Proficiency Testing Program oversight committee and served 6 years as Associate Editor of both Agronomy Journal and Soil Science Society of America Journal. He co-developed the ISU Extension Soil Fertility website and continues helping maintain it.

Licht, Mark

Mark Licht is an Associate Professor and Extension Cropping Systems Specialist in the Department of Agronomy at Iowa State University. His extension, research and teaching program is focused on how to holistically manage Iowa cropping systems to achieve productivity, profitability and environmental goals. Research is centered around varied aspects of soybean, corn and cover crop management.

Archontoulis, Sotirios

Sotirios Archontoulis is a professor of integrated cropping systems at the Department of Agronomy. His research aims to predict impacts (e.g. climate change), explain causes (e.g. high/low yields) and design future strategies to improve crop productivity and environmental sustainability across spatial and temporal scales. His approach combines field experimentation and use of agricultural systems process-based models to explain Genotype x Environment x Management interactions and enable prediction and design at scale.