2.5. Determination of total phenolic contentTPC in each sample was determined by using the Folin-Ciocalteucolorimetric method that was previously described (Cai et al., 2004)with a slight modification. In brief, aliquots (0.1 mL) of appropriately diluted sample or standard solutions were mixed with 0.5 mL of 0.5 N Folin–Ciocalteu’s phenol reagent, and the reaction was neutralized with 1.0 mL of saturated sodium carbonate (75.0 g/L). The absorbance of the resulting blue color was measured at 760 nm with a UV–vis spectrophotometer after incubation for 2 h at room temperature (∼23 ◦C). A calibration curve was prepared using gallicacid solution (5–100 g/mL). TPCs were expressed as grams of gallic acid equivalent (g GAE) per 100 g of dry weight. The determination was performed in triplicate.2.6. Color parameters of samplesThe color of tea samples (infusions) was measured with a ColorQuest XE color measurement spectrophotometer (HunterAssociates Laboratory, Inc. Virginia, USA). Color measurements were expressed as tristimulus parameters, L∗, a∗, and b∗. L∗ indicates lightness, a∗ indicates redness–greenness, and b∗ indicates yellowness–blueness. Negative a∗ indicates green, and higher positive a∗ indicates red color. Higher positive b∗ indicates more yellow color. Moreover, the chroma (C∗) value indicates the color intensity or saturation, which is calculated as C∗ = (a∗2 + b∗2)1/2. Hue angle (H◦) indicates sample color, which is calculated as H◦ = tan−1 (b∗/a*) when a∗ > 0, b∗ > 0 and H◦ = tan−1 (b*/a*) + 180◦ when a∗<0,b∗>0, where 0◦ or 360◦ = red–purple, 90◦ = yellow, 180◦ = green, and 270◦ = blue (Bao et al., 2005). All determinations were performed in triplicate.2.7. Statistical analysisAll results are expressed as mean ± standard deviation (n = 3). Analysis of variance (ANOVA), correlation analysis, principal component analysis and hierarchical cluster analysis ofthe results were performed in Data Processing System (DPS v7.05 for Windows). Euclidian distance as distance measurement and Ward’s as aggregation method were used in hierarchical cluster analysis (Deetae et al., 2012).
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