Maize Authentication: Quality Control Methods and Multivariate Analysis (Chemometrics)

Arvanitoyannis, Ioannis; Vlachos, Antonios

Maize Authentication: Quality Control Methods and Multivariate Analysis (Chemometrics)

2009

Arvanitoyannis, Ioannis | Vlachos, Antonios

Maize is one of the most important cereals because of its numerous applications in processed foods where it is the major or minor component. Apart from maize authenticity issues related to cultivar and geographical origin (national and/or international level), there is another important issue related to genetically modified maize. Various objective parameters such as fatty acids, phenolic compounds, pigments, heavy metals were determined in conjunction with subjective (sensory analysis) in order to identify the maize authenticity. However, the implementation of multivariate analysis (principal component analysis, cluster analysis, discriminant analysis, canonical analysis) is of great importance toward reaching valid conclusions on authenticity issues. This review summarized the most important finding of both objective and subjective evaluations of maize in five comprehensive tables in conjunction with the discussion.

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Mots clés AGROVOC

analysis antioxidants corn flour discriminant analysis fatty acids food food composition food contamination food quality genetic markers heavy metals humans lipid content literature reviews multivariate analysis multivariate analysis phenolic compounds plants principal component analysis protein content quality control quantitative analysis seeds sensory properties standards transgenic plants zea mays

Informations bibliographiques

Publié dans

Critical reviews in food science and nutrition

Volume 49 Numéro 6 Pagination 501 - 537 ISSN 1040-8398

Editeur

Elsevier B.V.

D'autres materias

Prevention & control; Genetically modified; Corn; Canonical analysis; Food composition and quality - field crop products; Plant physiology and biochemistry; Center of origin; Germplasm authentication; Center of diversity; Plant breeding and genetics; Cultivar identification; Mathematics and statistics; Plant pigments; Cluster analysis

Langue

anglais

Type

Journal Article; Text

Sur AGRIS depuis: 2024-02-28

Format: MODS

Fournisseur de données

Cette notice bibliographique a été fournie par National Agricultural Library

Découvrez la collection de ce fournisseur de données dans AGRIS

Liens

DOI DOI http://dx.doi.org/10.1080/10408390802068140

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