Development of Electronic Nose for classification of fruits on the basis of their ripeness

A comprehensive methodology has been developed to estimate the ripeness level of climacteric fruit in a non-contact manner. This study investigates the use of an artificial olfactory system as a non-destructive tool to assess the ripeness stage of fruit. The selected cultivar for this research is Guava fruit. The system comprises a metal oxide semiconductor gas sensor, specifically the MQ135 from Parallax Corporation, Inc., along with a data acquisition card and custom-developed data acquisition and analysis software utilizing the LabVIEW platform. The responses of Guava fruits at various ripeness levels categorized as green, ripe, overripe, and spoiled are recorded using the MQ3 sensor, which is connected in a half-bridge circuit. Each ripeness stage of the guava fruit leaves a distinct odorprint on the sensors and software. A custom-developed interface software using LabVIEW is employed to acquire, train, define, and display distinct classes of ripeness according to the fruit's state. The system demonstrates an accuracy of approximately 90% in detecting the ripeness of the fruit.