Literature DB >> 26218833

Correction: Identification of Relevant Phytochemical Constituents for Characterization and Authentication of Tomatoes by General Linear Model Linked to Automatic Interaction Detection (GLM-AID) and Artificial Neural Network Models (ANNs).

Abstract

Entities: Disease

Year: 2015 PMID： 26218833 PMCID： PMC4517855 DOI： 10.1371/journal.pone.0134313

Source DB: PubMed Journal: PLoS One ISSN： 1932-6203 Impact factor: 3.240

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Notice of Republication

This article was republished on July 9, 2015, to replace incorrect figures. The publisher apologizes for the error. Please download this article again to view the correct version.

1 in total

1. Identification of Relevant Phytochemical Constituents for Characterization and Authentication of Tomatoes by General Linear Model Linked to Automatic Interaction Detection (GLM-AID) and Artificial Neural Network Models (ANNs).

Authors: Marcos Hernández Suárez; Gonzalo Astray Dopazo; Dina Larios López; Francisco Espinosa
Journal: PLoS One Date: 2015-06-15 Impact factor: 3.240

1 in total