The artificial intelligence-based chemometrical characterisation of genotype/chemotype of Lupinus albus and Lupinus angustifolius permits their identification and potentially their traceability

Food Chemistry

Volumn 129, Issue 4, 2011, Pages 1806-1812

  Coïsson, Jean Daniel ^a   Arlorio, Marco ^a   Locatelli, Monica ^a   Garino, Cristiano ^a   Resta, Donatella ^b   Sirtori, Elena ^b   Arnoldi, Anna ^b   Boschin, Giovanna ^b  

^a UNIVERSITY OF EASTERN PIEDMONT   (Italy)

^b UNIVERSITY OF MILAN   (Italy)

Author keywords

Artificial Neural Networks; Chemotyping; Genotyping; Lupin; Lupinus albus; Lupinus angustifolius; Multivariate analysis; Principal Component Analysis

Indexed keywords

CHEMOTYPING; GENOTYPING; LUPIN; LUPINUS ALBUS; LUPINUS ANGUSTIFOLIUS; MULTI VARIATE ANALYSIS; PRINCIPAL COMPONENTS;

CHEMICAL ANALYSIS; MULTIVARIANT ANALYSIS; NEURAL NETWORKS; PLANTS (BOTANY);

PRINCIPAL COMPONENT ANALYSIS;

13ALPHA ANGELOYLOXYLUPANINE; 13ALPHA HYDROXYLUPANINE; 13ALPHA TIGLOYLOXYLUPANINE; ALPHA ISOLUPANINE; ALPHA TOCOPHEROL; DELTA TOCOPHEROL; DNA; GAMMA TOCOPHEROL; LIPID; LUPANINE; NITROGEN; UNCLASSIFIED DRUG;

ARTICLE; ARTIFICIAL INTELLIGENCE; CHEMOMETRIC ANALYSIS; CULTIVAR; DNA FINGERPRINTING; GENOTYPE; LUPIN; LUPINUS ALBUS; LUPINUS ANGUSTIFOLIUS; NONHUMAN; NUTRITION; PRINCIPAL COMPONENT ANALYSIS; RANDOM AMPLIFIED POLYMORPHIC DNA;

LUPINUS; LUPINUS ALBUS; LUPINUS ANGUSTIFOLIUS;

EID: 80051794020     PISSN: 03088146     EISSN: 18737072     Source Type: Journal    
DOI: 10.1016/j.foodchem.2011.05.107     Document Type: Article

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