Model prediction of plant morphology, water flows and xylem water potential in a growing tomato plant under heterogeneous growing conditions

We present a comprehensive mathematical model to calculate stem water potential in tomato plants cultivated under greenhouse conditions. Stem water potential is one of the variables that determines the growth of fruit as water potential gradients between the fruit and the stem are the driving forces for import of water and solutes into the fruit. Notably, the model integrates growth dynamics, environmental conditions, and plant management strategies to improve the accuracy of water potential estimation throughout the canopy. Environmental factors (i.e., temperature, relative humidity, light irradiance) were implemented at plant compartment levels, allowing for precise microclimate representation. Plant structure was used to calculate water flows and, ultimately, stem water potential by utilizing a hydraulic resistance model. The model was calibrated and validated using data collected from five growing seasons (2020 – 2024). The precision of water potential estimates across different growth stages was improved by including plant morphology dynamics. This, together with discretisation into compartments, allowed for unique realistic predictions for the whole season. Accurate predictions required accounting for growth dependency in root and xylem resistance. Temperature was the main predictor of plant growth for the investigated conditions of tomato production in Belgium. The greenhouse environment and plant management significantly influenced water fluxes and subsequent water potential estimations and should always be considered, especially for whole-season scenarios. Two hypothetical scenarios were analyzed based on 2019 environmental data, exploring the impact of greenhouse management and climate change. Simulations revealed that an increase in the greenhouse minimum temperature set points (+2 °C) had a greater positive effect on yield than a hypothetical climate change scenario with a larger temperature increase (+4 °C). The latter resulted in a higher prevalence of suboptimal growth conditions, presenting a real challenge for efficient future greenhouse management. Additionally, controlling the vapour pressure deficit instead of relative humidity was shown to significantly reduce water demand due to decreased transpiration rates. This water potential model for tomato growth can be used conjointly with fruit growth models for better crop prediction and optimisation of growing conditions. The presented model is modular and extendable, allowing integration not just with fruit growth models, but also potential inclusion of additional plant organs.