Quality Discriminant of Xinyang Maojian Tea based on Near Infrared Spectroscopy
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Abstract:
Near-infrared spectroscopy technology was widely used in many fields as a kind of fast nondestructive testing method, especially, which was more extensively used in the field of food science. As one of top ten Chinese green teas, Maojian tea is also well known abroad with high quality. In this study, near-infrared spectral data from 800 to 2500 nm for three different grades of Maojian tea were collected and analyzed. One-way analysis of variance of near-infrared spectral data was acquired from the three different grades of Maojian tea, in order to choose the most suitable wavelength range of near-infrared spectral data for further analysis. The original spectral signals were pretreated by wavelet transform for denoising. Orthogonal partial least-squares discriminant analysis (OPLS-DA) and partial least squares (PLS) were employed to distinguish the quality grades of Maojian tea. Results showed that the near infrared spectral data obtained in the wavelength range from 800 nm to 1800 nm can be used to predict the quality grades of Maojian tea. The three different grades of Maojian tea can be distinguished effectively by OPLS-DA analysis. PLS forecast model was established, the theoretical values and predicted values showed good correlation, while the correlation coefficient is 0.994, prediction accuracy is 100%, Root mean square error of cross validation is 0.090, which showed the accuracy and reliability of the models. NIRS combined with PLS analysis can be used for fast nondestructive testing of the quality grades of Maojian tea.
