Decision support systems for greenhouse tomato production

摘要: The purpose of greenhouse crop systems is to generate a high quality product at production rates, consistently, economically, efficiently and in sustainable way. To achieve this level productivity, accurate monitoring control some processes the entire biophysical system must be implemented. In addition, proper selection actions strategic, tactical operational management levels implemented.Greenhouse relies largely on human expertise adjust appropriate optimum values for each environmental parameters, most importantly, verify by observation desired responses. subjective nature observing plant responses, directly affects decision-making process (DMP) selecting these `optimums'. Therefore, study several decision support (DSS) were developed enhance DMP managerial levels.A dynamic environment model was implemented Web-based interactive application which allowed design, weather conditions, strategies. produced realistic approximations behavior environments 28-hour simulation periods proved valuable tool strategic evaluating different design configurations strategies.A enhancing remote diagnosis. This DSS automatically gathered presented graphically data crop-oriented parameters from research greenhouses. Furthermore, it real-time visual inspection crop.An intelligent (i-DSS) based records experimental trials commercial operations characterize growth-mode tomato plants with fuzzy modeling. i-DSS discrimination "reproductive", "vegetative" "balanced" growth-modes systems, seasonal variation application.An operation predict weekly fluctuations harvest fruit size developing time neural networks (NN). NN models accurately predicted variable, having correlation coefficients (R) 0.96, 0.87 0.94 respectively, when compared dataset used independent validation.