Objectives: The objective of this study is to determine and compare antibacterial efficacy of aqueous extracts of black, green, and lemon tea of a commercially available brand. Overall results sufficiently demonstrate that hyperspectral imaging technology can be used to perform classification of green tea.Ĭomparative assessment of antibacterial efficacy of aqueous extract of commercially available black, green, and lemon tea: an in vitro studyĪrun, S. The receiver operating characteristic curve (ROC) assessment methods were used to evaluate the LS-SVM classification algorithm.

Experimental results showed that discriminating rate was 100% in the prediction set. Finally, integration of the 12 texture features and three PCA spectral characteristics for each green tea sample were extracted as the input of LS-SVM. e., mean, covariance, homogeneity, energy, contrast, correlation, entropy, inverse gap, contrast, difference from the second-order and autocorrelation) based on the statistical moment were extracted from each characteristic band image. Then, 12 gray level co-occurrence matrix (GLCM) features (i.

First 512 spectral images of six brands of famous green tea in the 380 approximately 1 023 nm wavelength range were collected and principal component analysis (PCA) was performed with the goal of selecting two characteristic bands (545 and 611 nm) that could potentially be used for classification system. Hyperspectral imaging technology was developed to identify different brand famous green tea based on PCA information and image information fusion. Zhang, Hai-Liang Liu, Xiao-Li Zhu, Feng-Le He, Yong

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