Theodore Dejong

Theodore Dejong is a distinguished professor in the Department of Plant Sciences at the University of California, Davis, College of Agricultural and Environmental Sciences. With a research career spanning nearly five decades, his work has significantly advanced our understanding of fruit tree physiology, particularly in peach and plum cultivation. His extensive publication record demonstrates expertise in plant-water relations, photosynthesis mechanisms, and computational modeling of tree growth.

Dr. Dejong's research focuses on the physiological mechanisms governing fruit tree growth and productivity. His work examines how water status affects vegetative growth and leaf gas exchange in peach trees, the photosynthetic contribution of developing fruits to their carbohydrate requirements, and the autonomy of branches in resource partitioning. He has pioneered modeling approaches to simulate fruit tree growth, structure, and physiology, with his PEACH model representing a significant contribution to the field. His research also addresses practical orchard management issues, including irrigation strategies, orchard system configurations, and responses to environmental stressors like ozone and salinity.

Analysis of Dr. Dejong's publication history reveals a progression from fundamental physiological studies to sophisticated modeling approaches. His early work established critical relationships between water status and tree physiology, while his more recent research integrates biological principles with computational modeling. This evolution reflects broader trends in plant science toward systems-level understanding, with his work bridging laboratory findings with field applications for commercial orchard management.

Dr. Dejong has made substantial contributions to understanding how environmental factors affect fruit tree performance. His research on ozone impacts on plum production, salinity effects on photosynthesis, and the role of branch autonomy in fruit development has provided growers with science-based management strategies. His work on spring phenology modeling represents an important step toward predicting bloom timing under changing climate conditions, with implications for agricultural planning and adaptation.