Articles
A DECISION SUPPORT SYSTEM FOR TOMATO GROWERS BASED ON PLANT RESPONSES AND ENERGY CONSUMPTION
Article number
1037_62
Pages
501 – 508
Language
English
Abstract
The importance of plant water status for a good production and quality of tomato fruits (Solanum lycopersicum L.) has been emphasized by many authors.
Currently, different new energy-saving technologies and growing strategies are under investigation to cope with the increasing fossil fuel prices.
However, these technologies and growing strategies typically alter the greenhouse climate, thereby affecting the plants response.
Hence, the question arises how to adapt the microclimate to reduce the energy consumption of greenhouse tomato cultivation without compromising fruit yield or quality.
Nowadays, the use of plant-based methods to steer the climate is of high interest and it was demonstrated that monitoring of stem diameter variations and fruit growth provides crucial information on both the plant water and carbon status.
However, interpretation of these data is not straightforward and, hence, mechanistic modelling is necessary for an unambiguous interpretation of the dynamic plant response.
During a 4-year research period, we investigated the response of different plant processes of tomato to dynamic microclimatic greenhouse conditions.
The final aim was to develop a decision support system that helps growers to find an optimal balance between energy consumption, plant response and fruit yield.
To this end, an integrated plant model, including stem, leaves, roots and fruits, was developed in which the various plant processes are mechanistically described.
The plant model was calibrated and extensively validated on datasets collected throughout the different growing seasons in different research facilities in Flanders.
This plant model was finally integrated into an existing greenhouse climate model and validated with data from the greenhouse climate and energy consumption.
After validation, this integrated model was used to run scenarios on growing strategies and their impact on energy consumption, plant photosynthesis and fruit growth.
Currently, different new energy-saving technologies and growing strategies are under investigation to cope with the increasing fossil fuel prices.
However, these technologies and growing strategies typically alter the greenhouse climate, thereby affecting the plants response.
Hence, the question arises how to adapt the microclimate to reduce the energy consumption of greenhouse tomato cultivation without compromising fruit yield or quality.
Nowadays, the use of plant-based methods to steer the climate is of high interest and it was demonstrated that monitoring of stem diameter variations and fruit growth provides crucial information on both the plant water and carbon status.
However, interpretation of these data is not straightforward and, hence, mechanistic modelling is necessary for an unambiguous interpretation of the dynamic plant response.
During a 4-year research period, we investigated the response of different plant processes of tomato to dynamic microclimatic greenhouse conditions.
The final aim was to develop a decision support system that helps growers to find an optimal balance between energy consumption, plant response and fruit yield.
To this end, an integrated plant model, including stem, leaves, roots and fruits, was developed in which the various plant processes are mechanistically described.
The plant model was calibrated and extensively validated on datasets collected throughout the different growing seasons in different research facilities in Flanders.
This plant model was finally integrated into an existing greenhouse climate model and validated with data from the greenhouse climate and energy consumption.
After validation, this integrated model was used to run scenarios on growing strategies and their impact on energy consumption, plant photosynthesis and fruit growth.
Authors
J. Hanssens, T. De Swaef, K. Steppe, D. Pinxteren, H. Marien, L. Wittemans, J. Desmedt
Keywords
Solanum lycopersicum, mechanistic modelling, fruit growth, LVDT, greenhouse climate model, model calibration, model validation, energy
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