Discrimination of durian ripeness level using gas sensors and neural network

In the agriculture industry, determining the ripeness level of fruits is a very important aspect. This is related to maintaining the quality of the production, and during the distribution process. Currently, human sensory tests are still commonly used to evaluate food products with inconsistent results. This study developed a system to discriminate the durian ripeness level using gas sensors and neural network based on the character of the fruit aroma. This system succeeded in distinguishing the ripeness of durian including unripe, ripe and overripe with performance evaluation values above 91%.