Development of Decision Support Application based on the Prediction Model of Tomato Yields in Intelligent Greenhouse

In intelligent greenhouse, balance of yield with heating cost is one of important point for manager. In this study, we constructed growing model of tomato based on accumulated temperature in greenhouse, predictive model of air temperature inside greenhouse based on weather forecast, and heating load model in greenhouse. Then using these models, we developed the application to support manager's decision by predicting yield of tomato, and flower differentiation date, flowering date, harvest start date and harvest end date of each stage, and furl cost of heating.