A FUZZY PHOTOSYNTHESIS MODEL FOR TOMATO

This study arises from the question whether fuzzy logic is feasible fo r modeling crop growth processes. The article focuses on developing a fuzzy model to predict total photosynthesis (TotPHT) of tomato crop ca nopy. The fuzzy model uses qualitative relationships to describe the e ffects of temperature, carbon dioxide concentration, and light intensi ty in three canopy layers to determine TotPHT. The fuzzy model was tun ed for Israel (fuzzy model I) and Gainesville, Florida, (fuzzy model 2 ) conditions. The predictions of TotPHT by the fuzzy models compared w ell with computations from a tomato crop growth model (TOMGRO)for 16 d ays crop growth intervals with r(2) values of 0.970 and 0.963 for mode ls I and 2. Additionally, the predictions of the fuzzy model 2 when co mpared to experimental data from a controlled chamber study in Gainesv ille gave an r(2) value of 0.947. These results indicate that fuzzy lo gic may provide another possibility to model crop processes. Fuzzy mod els can incorporate intuitive knowledge and cart be developed in a rel atively short time.