Electronic nose technique potential monitoring mandarin maturity

Over the past years, electronic nose technology opened the possibility to exploit information on behavior aroma to assess fruit ripening stage. The objective in this study was to evaluate the capacity of electronic nose to monitoring the change in volatile production of mandarin during different picking-date, using a specific electronic nose device (PEN 2). Principal component analysis (PCA) and linear discriminant analysis (LDA) were used in order to investigate whether the electronic nose was able to distinguish among different picking-date (ripeness states). The loadings analysis was used to identify the sensors responsible for discrimination in the current pattern file. The results obtained prove that the electronic nose PEN 2 can discriminate successfully different picking-date on mandarin using LDA analysis. But, electronic nose was not able to detect a clear difference in volatile profile on mandarin using PCA analysis. During external validation using LDA was obtained to classified 92% of the total samples properly. Some sensors have the highest influence in the current pattern file for electronic nose PEN 2. A subset of few sensors can be chosen to explain all the variance. This result could be used in further studies to optimize the number of sensors.