Development of Novel Electronic Nose Applied for Strawberry Freshness Detection during Storage

Abstract

Abstract A newly self-developed electronic nose (E-nose) system for the detection of “Hongyan” strawberry freshness at different storage periods was studied. The system consisted of six metal oxide semiconductor sensors connected to a data acquisition system and a computer with pattern recognition software. The aroma emitted by “Hongyan” strawberry samples was detected during post-harvesting storage, and stable E-nose response values were used to develop cluster analysis and classification models. The successive projections algorithm was employed to optimize the sensors array, and the results obtained by gas chromatography–mass spectrometry analysis proved that the optimized sensor array was feasible to differentiate decayed strawberries from fresh ones. Partial least squares discriminant analysis and support vector machine (SVM) models were built. Accuracy of 94.9 % on the testing set was obtained based on the optimized sensor array, and this result was satisfactory compared to that of commercial PEN3 E-nose.