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. 2017 May 23;7:2257. doi: 10.1038/s41598-017-02499-1

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© The Author(s) 2017

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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Construction of bioactivity-prediction model to predict the anti-oxidant activity of GTEs based on their composition profiles. (A) Correlation between ORAC and total polyphenol content. ORAC values are presented as Trolox equivalents (TE). Total polyphenol contents are presented as gallic acid equivalents (GAE). Models for predicting (B) ORAC or (C) total polyphenol content were calculated from the MALDI–MS datasets of 21 GTEs, including 13 training (black triangles) and 8 test (blue squares) sets. (D) Bar chart showing the influence of variables used to create the ORAC-prediction model for GTEs (Y-axis is the value of variable-importance-in-projection, VIP). Forty variables with large VIP values (>1) were extracted. Orange bars indicate positive correlations between the intensity of the component and ORAC. Purple bars indicate negative correlations. (E) Correlations between ORAC and the intensity of each of the top-4 components with the largest VIP values (>1). (F) Correlations between ORAC and the summed abundances of multiple components. Left panel: combination of the above-mentioned top-4-VIP components. Middle panel: combination of the 25 positively correlated components with the largest VIP values (>1). Right panel: combination of all 85 positively correlated components from among the 149 total components.