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)

Detalles Bibliográficos
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2015
Materias:
Correction
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4517855/
https://www.ncbi.nlm.nih.gov/pubmed/26218833
http://dx.doi.org/10.1371/journal.pone.0134313
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spelling pubmed-45178552015-07-31 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) PLoS One Correction Public Library of Science 2015-07-28 /pmc/articles/PMC4517855/ /pubmed/26218833 http://dx.doi.org/10.1371/journal.pone.0134313 Text en © 2015 The PLOS ONE Staff http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Correction
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)
title 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)
title_full 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)
title_fullStr 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)
title_full_unstemmed 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)
title_short 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)
title_sort 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)
topic Correction
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4517855/
https://www.ncbi.nlm.nih.gov/pubmed/26218833
http://dx.doi.org/10.1371/journal.pone.0134313
work_keys_str_mv AT correctionidentificationofrelevantphytochemicalconstituentsforcharacterizationandauthenticationoftomatoesbygenerallinearmodellinkedtoautomaticinteractiondetectionglmaidandartificialneuralnetworkmodelsanns

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