Fuji Apple Storage Time Predictive Method Using Electronic Nose

An electronic nose-based Fuji apple storage time prediction method is investigated in this paper. A home-made electronic nose with eight metal oxide semiconductors gas sensor array was used to measure the apples stored at room temperature. Principal component analysis cannot discriminate all samples. Stochastic resonance signal-to-noise ratio spectrum distinguishes fresh, medium, and aged apples successfully. The prediction model is developed based on signal-to-noise ratio maximums. In validating experiments, results show that the predicting accuracy of this model is 84.62 %. This method takes some advantages including fast detection, easy operation, high accuracy, and good repeatability.