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. 2022 Mar 15;10(6):1888–1898. doi: 10.1002/fsn3.2805

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© 2022 The Authors. Food Science & Nutrition published by Wiley Periodicals LLC.

This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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Multivariate statistical analysis of phenolic compounds from various samples. (a) Score plot of the principal component analysis (PCA). (b) Variable importance on projection (VIP) plot of partial least squares regression discriminant analysis (PLS‐DA). (c) Correlation heatmap analysis. (d) Circosplot shows an intuitive result of the correlation coefficients between the samples and various phenolic compounds. (A: 20‐mesh; B: 40‐mesh; C: 60‐mesh; D: 3‐CQA; E:4‐CQA; F: 5‐CQA; G: 3,4‐CQA; H: 3,5‐CQA; I: 4,5‐CQA; J: luteolin‐7‐O‐glucoside; K: apigenin‐7‐O‐glucoside; L: linarin; M: luteolin; N: apigenin; O: acacetin)