Learning to classify organic and conventional wheat - A machine learning driven approach using the MeltDB 2.0 metabolomics analysis platform

Frontiers in Bioengineering and Biotechnology

Volumn 3, Issue MAR, 2015, Pages

  Kessler, Nikolas ^a   Bonte, Anja ^b   Albaum, Stefan P ^a   Mäder, Paul ^c   Messmer, Monika ^c   Goesmann, Alexander ^d   Niehaus, Karsten ^a   Langenkämper, Georg ^b   Nattkemper, Tim W ^a  

^a BIELEFELD UNIVERSITY   (Germany)

^b FEDERAL RESEARCH INSTITUTE OF NUTRITION AND FOOD   (Germany)

^c RESEARCH INSTITUTE OF ORGANIC AGRICULTURE FIBL   (Switzerland)

^d JUSTUS LIEBIG UNIVERSITY   (Germany)

Author keywords

Computational metabolomics; Food authentication; Machine learning; Metabolome informatics; Metabolomics; Organic farming; Statistics

Indexed keywords

ARTIFICIAL INTELLIGENCE; AUTHENTICATION; CLASSIFICATION (OF INFORMATION); CULTIVATION; LEARNING SYSTEMS; STATISTICS;

FARMING SYSTEM; FOOD AUTHENTICATIONS; INFORMATICS; MACHINE LEARNING APPROACHES; METABOLOMICS; ORGANIC AND CONVENTIONAL CULTIVATIONS; ORGANIC FARMING; WHEAT CULTIVARS;

LEARNING ALGORITHMS;

EID: 84947869905     PISSN: None     EISSN: 22964185     Source Type: Journal    
DOI: 10.3389/fbioe.2015.00035     Document Type: Article

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