Speaker
Prof Charlie Messina
Thursday 13 November, 2025
Dr Charlie Messina is a professor of predictive breeding in the Department of Horticultural Sciences at the University of Florida. Prior to joining the university, Professor Messina had a long and distinguished career in industry. While at Corteva, he made critical contributions to the development of drought tolerant maize hybrids, now grown commercially in North and South America, the design of nitrogen management decision support systems used by the industry in North America and led the initiative on circular agriculture.
Dr Messina works with breeders to improve the nutritional value of Florida produce and to reimagine agriculture as a solution to climate change. He also specialises in developing AI for plant breeding, which he believes will enable society to harmonize crop improvement efforts for regenerative agricultural systems that improve human health, nutrient security, and adaptation to climate change. He is also invested in training the leaders of tomorrow. His program at the University of Florida focuses on developing prediction methods for agriculture and horticulture, with a strong emphasis on genome to phenome modelling for prediction of properties of complex traits, the improvement of crop adaptation to current and future climates and the enablement of circularity in horticulture.
Plenary presentation
Predictive Breeding: Unlocking Genetic Potential for Sustainable Growth
Thursday 13 November, 2025
KEY SPEAKER ABSTRACT
Predictive Breeding: Unlocking Genetic Potential for Sustainable Growth
A global nutritional and health crisis is unfolding, marked not only by rising rates of obesity, cardiovascular disease, and diabetes but also by widespread micronutrient deficiencies such as iron, zinc, and vitamin A.
These challenges are most acute in tropical and subtropical regions, where access to nutrient-dense foods remains limited. While the issue requires cross-disciplinary solutions, a key bottleneck lies in the insufficient local production of fruits and vegetables rich in essential vitamins and minerals.
High-value crops such as broccoli, spinach, strawberries, and blueberries remain largely adapted to temperate climates, restricting their availability to wealthier nations with access to improved varieties or the resources to import them.
Building on our previous work in broccoli, we present a predictive framework that extends AI-driven breeding to a broader range of nutrient-rich crops.
By integrating advances in molecular biology, dynamical modeling, and genetics, we demonstrate the capacity to identify target populations of environments, uncover valuable genetic diversity, and accelerate genetic gain.
This framework illustrates how unlocking the latent genetic potential of high nutritional value crops can enable adaptation in the regions that need them most, fostering sustainable agricultural growth and equitable access to nutritious food in a more resilient global system.
Messina C & Cabrera M
