This study arises from the question whether fuzzy logic is feasible for modeling crop growth processes. Thearticle focuses on developing a fuzzy model to predict total photosynthesis (TotPHT) of tomato crop canopy. The fuzzymodel uses qualitative relationships to describe the effects of temperature, carbon dioxide concentration, and lightintensity in three canopy layers to determine TotPHT. The fuzzy model was tuned for Israel (fuzzy model 1) andGainesville, Florida, (fuzzy model 2) conditions. The predictions of TotPHT by the fuzzy models compared well withcomputations from a tomato crop growth model (TOMGRO) for 16 days crop growth intervals with r2 values of 0.970 and0.963 for models 1 and 2. Additionally, the predictions of the fuzzy model 2 when compared to experimental data from acontrolled chamber study in Gainesville gave an r2 value of 0.947. These results indicate that fuzzy logic may provideanother possibility to model crop processes. Fuzzy models can incorporate intuitive knowledge and can be developed in arelatively short time.
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A 1997 study studied this question.