Using Concept-Based Computer Simulation Modeling to Study and Develop an Integrated Understanding of Tree Crop Physiology

Studying and developing an integrated understanding fruit tree physiology and growth and development is a difficult endeavor. Plants are very complex organisms that are governed and influenced by a multitude of factors. Traditional experimental approaches to plant function have been largely limited to examining a small number of factors at a time and describing those interactions verbally or with two-or three-dimensional static diagrams. These approaches result in valuable insights into the interactions of a limited number of variables on a similarly limited number of somewhat isolated processes such as organ growth, photosynthesis, or respiration. However it is very difficult to develop and communicate an integrated understanding of natural processes that involve multiple interacting factors. The study and understanding of environmental and endogenous influences on carbon assimilation, partitioning, transport and utilization in plants is a good example of these limitations. The development and testing of hypotheses that explain carbon partitioning and utilization presents complex problems because of the dynamic nature and relationships among carbohydrate partitioning, growth and plant architecture as well as the multitude of factors that can influence each process and organ. One way to dynamically integrate the influence of multiple factors on multiple processes is to use recent advances in computer technology to develop concept-based, computer simulation models of tree crop growth and physiology. For the past two decades research in our laboratories has focused on developing environmental and endogenous influences on carbon assimilation, partitioning, transport and utilization in peach trees. This work has resulted in the PEACH and L-PEACH models. Modeling has allowed us to develop a systematic analysis and integration of hypotheses regarding the factors that control peach fruit growth, crop yield, and tree growth; as well how these processes respond to management practices.