We synthetically applied computer vision, genetic algorithm and artificial neural network technology to automatically identify the tomatoes that had physiological diseases. Firstly, the tomatoes' images were captured through a computer vision system. Then to identify cavernous tomatoes, we analyzed the roundness and detected deformed tomatoes by applying the variation of fruit's diameter. Secondly, we used a Genetic Algorithm (GA) trained artificial neural network. Experiments show that the

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... e methods can accurately identify tomatoes' shapes and meet requests of classification; the accuracy rate for the identification for tomatoes with physiological diseases was up to 100%. [Nature and Science. 2005;3(2):52-58].