Development of an Artificial Neural Network as a Tool for Predicting the Targeted Phenolic Profile of Grapevine (Vitis vinifera) Foliar Wastes

High performance liquid chromatography data related to the concentrations of 12 phenolic compounds in vegetative parts, measured at four sampling times were processed for developing prediction models, based on the cultivar, grapevine organ, growth stage, total flavonoid content (TFC), total reducing...

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Detalles Bibliográficos
Autores principales: Eftekhari, Maliheh, Yadollahi, Abbas, Ahmadi, Hamed, Shojaeiyan, Abdolali, Ayyari, Mahdi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2018
Materias:
Plant Science
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6018394/
https://www.ncbi.nlm.nih.gov/pubmed/29971086
http://dx.doi.org/10.3389/fpls.2018.00837

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6018394/
https://www.ncbi.nlm.nih.gov/pubmed/29971086
http://dx.doi.org/10.3389/fpls.2018.00837

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