Leaf area index soft sensor for tomato crops in greenhouses
Francisco García-Mañas, Francisco Rodríguez, Manuel Berenguel
Abstract
In this work, a soft sensor for tomato crop has been developed using dynamic models to reproduce physical and biological phenomena inside a greenhouse. External weather forecasts were utilised to predict crop growth for a short-term horizon. In addition, data assimilation was performed from observable information of the process, such as measurements captured by sensors, in order to correct uncertainty errors of simulated variables by dynamic models. From the automatic control perspective, the proposed mechanism might allow to implement optimal resource management strategies. Furthermore, crop prediction systems could offer relevant information to farmers as a support tool for decision making.