تعیین مزه پرتقال تامسون با استفاده از پردازش تصویر، مبتنی بر دو روش فازی-عصبی و عصبی-ژنتیک

The diversity and abundance of quality characteristics of agricultural products, has been the main reason for the development of non-destructive methods. Machine vision and artificial intelligence are powerful techniques for diagnosing most physical, mechanical and chemical properties of agricultural products. Before export fruits are classified by shape, volume and weight. Ranking fruit through taste (sweet or tart) non-destructively plays an important role in marketing, choice power and its application. In this research, it was detect the taste of Thompson orange while combining artificial intelligence (AI) and visual machine technique. A closed circuit digital installed in special frame, under specific height and light was used to take picture from samples vertically. Also, an algorithm (program) based on AI was developed to diagnose the variety and taste of Thompson orange through apparent characteristics in Matlab software. The results showed that the success rate of taste determination for Thompson orange using ANFIS and ANN-GA (Artificial Neural Network-Genetic Algorithm) was 96.67 and 90.0% respectively.