Ecophysiological modeling of fruit growth for smart digital horticulture
The goal of this PhD project is to develop a digital fruit – a mathematical model that accurately describes and predicts biochemical and physical changes in fruit as affected by pre- and postharvest conditions. Such a model can be used to study the effect of environmental factors on fruit physiology during growth and postharvest life. The aim is to develop and apply an ecophysiological model of tomato fruit growth and quality. This model will include submodels for water transport, biomass production, photosynthesis, sugar and acid metabolism, respiration, and takes soil and climate parameters into account. The model will be validated based on measurements of phenology and fruit attributes that are provided by different experimental stations and research institutes that participate in this research. The model will be used to investigate the effect on fruit production and quality of variations in climate conditions, measured across different spatial scales. Ultimately, the research will lead to the development of a decision support tool for fruit growing that can be integrated with distributed sensor networks for better control and management but will as well serve as a means to better understand effects of, among others, climate change on fruit growing.