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. 2019 Feb 8;10:47. doi: 10.3389/fpls.2019.00047

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Copyright © 2019 Paul, Sorrentino, Lucini, Rouphael, Cardarelli, Bonini, Reynaud, Canaguier, Trtílek, Panzarová and Colla.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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Score plot of Orthogonal Projection to Latent Structures Discriminant Analysis (OPLS-DA) supervised modeling carried out on metabolomic profiles following application of selected protein hydrolysates. The variation between groups was separated into predictive and orthogonal components (i.e., that ascribable to technical and biological variation). The OPLS model was cross-validated using CV-ANOVA (p < 0.01) and permutation tested to exclude over fitting. Furthermore, the presence of outliers was investigated according to Hotelling’s T2 method (i.e., the distance from the origin in the model) using 95 and 99% confidence limits for “suspect” and “strong” outliers, respectively. The pattern observed in the score plot was used to identify discriminant compounds based on Variable of Importance in projection (VIP) analysis.