Articles
A MODEL-BASED DECISION SUPPORT SYSTEM FOR TEMPERATURE SET POINT OPTIMISATION FOR GREENHOUSE HEATING UNDER SUBTROPICAL CLIMATE CONDITIONS
Article number
718_41
Pages
359 – 366
Language
English
Abstract
Greenhouse air temperature set points affect not only greenhouse crop growth and development, but also energy consumption for greenhouse climate control.
A greenhouse crop growth model and a greenhouse energy consumption estimation model, were both validated under subtropical climate conditions and were integrated to develop a model-based decision support system for temperature set point optimisation for greenhouse heating.
The system consists of a database and three models.
The database includes information about greenhouse, crop and outside climate data of different regions of subtropical China.
The three models are respectively, a crop growth and development model parameterised for cucumber, tomato and muskmelon, an energy consumption estimation model and a set point optimisation model.
The input of the system includes greenhouse information, crop information, and outside climate data.
The output of the system includes date of crop development stage, crop canopy leaf area index, biomass production, yield, and greenhouse energy consumption at different temperature set point for greenhouse heating.
The temperature set point for greenhouse heating can then be optimised according to the highest ratio of biomass production or yield to energy consumed or highest yield or date of harvesting.
The scenario study results show that the highest biomass production energy use efficiency for greenhouse cucumber crop production in Shanghai can be achieved when daytime and nighttime temperatures for greenhouse heating are set at 21 and 15°C, respectively.
The system developed in this study can be used to make off-line temperature set point optimisation for both automated and non-automated (manually operated) greenhouse heating.
A greenhouse crop growth model and a greenhouse energy consumption estimation model, were both validated under subtropical climate conditions and were integrated to develop a model-based decision support system for temperature set point optimisation for greenhouse heating.
The system consists of a database and three models.
The database includes information about greenhouse, crop and outside climate data of different regions of subtropical China.
The three models are respectively, a crop growth and development model parameterised for cucumber, tomato and muskmelon, an energy consumption estimation model and a set point optimisation model.
The input of the system includes greenhouse information, crop information, and outside climate data.
The output of the system includes date of crop development stage, crop canopy leaf area index, biomass production, yield, and greenhouse energy consumption at different temperature set point for greenhouse heating.
The temperature set point for greenhouse heating can then be optimised according to the highest ratio of biomass production or yield to energy consumed or highest yield or date of harvesting.
The scenario study results show that the highest biomass production energy use efficiency for greenhouse cucumber crop production in Shanghai can be achieved when daytime and nighttime temperatures for greenhouse heating are set at 21 and 15°C, respectively.
The system developed in this study can be used to make off-line temperature set point optimisation for both automated and non-automated (manually operated) greenhouse heating.
Authors
J. Dai, W. Luo
Keywords
microclimate model, crop growth model, energy consumption, biomass production, yield, leaf area index
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