A Model for the Combine Description of the Temperature and Relative Humidity Regime in the Greenhouse

The critical environmental parameters affecting plant growth in the greenhouse are temperature, relative humidity, carbon dioxide, nutrition, availability of water, and the growing media. From these factors, temperature is of primary importance to most growers because it is responsible for determining the reaction rates of various metabolic processes involved in plant growth, and also regulating temperature has a direct influence on relative humidity and carbon dioxide levels. Tomato crop have the optimal day average temperatures between 20 and 25°C. For night, optimum average temperatures are between 15 to 20 ^oC. In addition, optimal relative humidity is between 50-60%. In trying to keep the environmental variables in the optimal levels greenhouse crop technology have been increased dramatically with the consequently increase in energy consumption. Therefore, it is important to have a precise control for heating, cooling and humidification inside the greenhouse in order to save energy and money. Enthalpy is a variable for a combined description for temperature and relative humidity and it changes under the influence of thermal energy (global radiation, heating systems) and water vapour (evapotranspiration, fog systems) entered into the system, and of the mixing of air (ventilation). In this work we developed a Neural Network model for predictions of the enthalpy based on the environmental factors inside and outside of the greenhouse, also a sensitivity analysis is applied to know the most important variables affecting enthalpy in the system. Enthalpy prediction 5 and 10 min ahead of the sensor signal will allow us to have an strategy for simultaneous control of air temperature and relative humidity. Also a normalized index β, was calculated for evaluating of the ventilation system.