Quality control of Lonicera japonica stored for different months by electronic nose.

The objective of this study was to investigate the potential of the electronic nose (E-nose) technique for monitoring the storage time and quality of L. japonica. An E-nose was used to detect odors of L. japonica samples during a storage period of 16 months. Linear discriminant analysis (LDA) and radial basis function (RBF) neural network were performed to differentiate L. japonica samples stored for different months. The content of chlorogenic acid of L. japonica was determined to confirm the quality changes and investigate its correlation with the odor response values. Results showed that L. japonica samples of different storage months could be classified correctly by LDA and RBF neural network. The change trends of the odor response and the content of chlorogenic acid had both declined along with the storage time. Also, there was a significant correlation (p=0.000) between the odor index and the content of chlorogenic acid. In conclusion, the odor intensity could reflect the quality of L. japonica to a certain degree. The E-nose technique could be used as a rapid, simple, sensitive and effective method for the quality control of L. japonica.