2020
DOI: 10.1016/j.lwt.2020.109688
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Differentiating grades of Xihu Longjing teas according to the contents of ten major components based on HPLC-DAD in combination with chemometrics

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Cited by 30 publications
(9 citation statements)
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“…Principal Component Analysis (PCA) was performed on vitamin and carotenoids content data for all fruits (Figure 4). The first and second PCA components represented 83.02% and 8.05% of the total variation, respectively, which meets the general requirement of cumulative percent variation (CPV) > 70%-85% for PCA analysis (Liu, 2007;Gu et al, 2020).…”
Section: Principal Component Analysismentioning
confidence: 72%
“…Principal Component Analysis (PCA) was performed on vitamin and carotenoids content data for all fruits (Figure 4). The first and second PCA components represented 83.02% and 8.05% of the total variation, respectively, which meets the general requirement of cumulative percent variation (CPV) > 70%-85% for PCA analysis (Liu, 2007;Gu et al, 2020).…”
Section: Principal Component Analysismentioning
confidence: 72%
“…Longjing tea quality grades are mainly determined by plucking standard according to National Standard of China GB/T 18650‐2008 (Product of geographical indication— Longjing tea). High‐grade tea is produced by the youngest tea shoots, which has prominent of “tender” and “umami” induced by rich aroma and taste constituents (Gu et al, 2020; Zhou et al, 2021), that's why they have relatively high prices. In contrast, woody flavor in teas always increased with tea shoot maturity, which may be caused by the increase of woody‐volatiles such as 1‐Heptanol, nerolidol, α‐farnesene, etc.…”
Section: Resultsmentioning
confidence: 99%
“…Obviously, most of Longjing teas with higher hedonic values "tender" and "umami" induced by rich aroma and taste constituents (Gu et al, 2020;Zhou et al, 2021), that's why they have relatively high prices. In contrast, woody flavor in teas always increased with tea shoot maturity, which may be caused by the increase of woodyvolatiles such as 1-Heptanol, nerolidol, α-farnesene, etc.…”
Section: Penalty Analysis Based On St-catamentioning
confidence: 99%
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“…An effective way of extracting characteristic information is to develop useful chemometrics or properly employ the proposed methods. In the past years, a variety of chemometric methods have been used to analyze EEMs, such as parallel factor analysis (PARAFAC) [ 8 ], alternating trilinear decomposition (ATLD) [ 9 , 10 ] and its variants, N-way partial least squares (N-PLS) [ 11 ], multivariate curve resolution-alternating least squares (MCR-ALS) [ 12 ], and unfolded partial leasts quares/residual bilinearization (U-PLS/RBL) [ 13 ]. The attractive merit of the “second-order advantage” of these methods makes sure that multiple target compounds can be accurately quantified even in the presence of unknown interferences [ 14 , 15 ].…”
Section: Introductionmentioning
confidence: 99%