Characterizing the Moisture Content of Tea with Diffuse Reflectance Spectroscopy Using Wavelet Transform and Multivariate Analysis

Abstract

Effects of the moisture content (MC) of tea on diffuse reflectance spectroscopy were investigated by integrated wavelet transform and multivariate analysis. A total of 738 representative samples, including fresh tea leaves, manufactured tea and partially processed tea were collected for spectral measurement in the 325–1,075 nm range with a field portable spectroradiometer. Then wavelet transform (WT) and multivariate analysis were adopted for quantitative determination of the relationship between MC and spectral data. Three feature extraction methods including WT, principal component analysis (PCA) and kernel principal component analysis (KPCA) were used to explore the internal structure of spectral data. Comparison of those three methods indicated that the variables generated by WT could efficiently discover structural information of spectral data. Calibration involving seeking the relationship between MC and spectral data was executed by using regression analysis, including partial least squares regression, multiple linear regression and least square support vector machine. Results showed that there was a significant correlation between MC and spectral data (r = 0.991, RMSEP = 0.034). Moreover, the effective wavelengths for MC measurement were detected at range of 888–1,007 nm by wavelet transform. The results indicated that the diffuse reflectance spectroscopy of tea is highly correlated with MC.

Chemical composition and antioxidant activity of leaves of mycorrhized sea-buckthorn ( Hippophae rhamnoides L.)

“…Moisture content of fresh leaves used in the experiment was 68 ± 7% of fresh weight (FW). It was lower than the range of 82% to 96% FW in most vegetables (lettuce, green beans, asparagus, green peppers, and spinach) reported by Granado et al (1992), but comparable with that (67% FW) of tea leaf (Li et al, 2012). Morgenstern et al (2014) found the highest DW content in leaves of sea-buckthorn collected at the end of July (32%).…”

Application of Hyperspectral Imaging and Chemometric Calibrations for Variety Discrimination of Maize Seeds

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