Learning to Classify Organic and Conventional Wheat – A Machine Learning Driven Approach Using the MeltDB 2.0 Metabolomics Analysis Platform

We present results of our machine learning approach to the problem of classifying GC-MS data originating from wheat grains of different farming systems. The aim is to investigate the potential of learning algorithms to classify GC-MS data to be either from conventionally grown or from organically gr...

Descripción completa

Detalles Bibliográficos
Autores principales: Kessler, Nikolas, Bonte, Anja, Albaum, Stefan P., Mäder, Paul, Messmer, Monika, Goesmann, Alexander, Niehaus, Karsten, Langenkämper, Georg, Nattkemper, Tim W.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2015
Materias:
Bioengineering and Biotechnology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4371749/
https://www.ncbi.nlm.nih.gov/pubmed/25853128
http://dx.doi.org/10.3389/fbioe.2015.00035

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4371749/
https://www.ncbi.nlm.nih.gov/pubmed/25853128
http://dx.doi.org/10.3389/fbioe.2015.00035

Ejemplares similares