Characterization and Classification of Mangifera Indica Ripeness with Electronic Nose using Fuzzy Logic Algorithm

In the Philippines, agriculture plays a vital role. Mangoes are exported to 48 nations throughout the world. The Philippines ranks 7th in the world in mango output. An electronic nose that can distinguish between ripe and unripe Mangifera Indica is the primary goal of this research. The gases generated by the mango will be used to determine the ripeness of the mango utilizing MQ sensors. The Fuzzy Logic Algorithm can tell the difference between ripe and unripe mangoes. Future researchers that employ and improve the use of Electronic Nose in other applications will benefit from this research. This system can be used to determine whether a mango is unripe or ripe. The focus of the characterization will be on the results of our research's testing component. Because the electronic nose and fuzzy logic algorithm will be used for characterization and categorization. The MQ sensors were used to detect chemicals released by the Mangifera Indica, according to the researchers. Unripe mangoes were identified with an accuracy of 93.33 percent, whereas ripe mangoes were identified with an 86.67 percent accuracy. The system's total accuracy is 90 percent.