A Strategy for Greenhouse Climate Control, Part I: Model Development

This paper presents an algorithm developed to predict the dynamic ambient greenhouse air conditions which optimize net profits for the production of a greenhouse tomato crop. Profits are equated to the crop yield value less the energy costs for heating and dehumidification and the CO2 injection cost. The climatic conditions considered are CO2 level, temperature, relative humidity and incident radiation. These are varied dynamically for every time interval spanning the harvesting period. The algorithm has two sub-programs. For sets of selected internal climatic parameters, the first calculates crop yield, and the second calculates energy costs (heating and dehumidification) with reference to predicted exterior climatic conditions (solar radiation, temperature, wind velocity and relative humidity). These two algorithms are then used to predict the particular set of climatic parameters, adjusted for each time interval over the harvesting period, that will maximize the crop yield value less the energy costs.