Mineral profile exploratory analysis for rice grains traceability

•Total, organic and inorganic arsenic content in rice grains.•The soil, rice grains and husk mineral profile assessed by principal component analysis.•3D models were proposed to geographically discriminate the rice.•Cities and producers discrimination is presented by elemental content. Rice geograph...

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Bibliographic Details
Published in:Food chemistry 2019-12, Vol.300, p.125145-125145, Article 125145
Main Authors: Lange, Camila Neves, Monteiro, Lucilena Rebelo, Freire, Bruna Moreira, Franco, Daniel Fernandez, de Souza, Rogerio Oliveira, dos Reis Ferreira, Cecilia Sacramento, da Silva, Julio José Centeno, Batista, Bruno Lemos
Format: Article
Language:English
Subjects:
Arsenic species
Brazilian rice
Geographical discrimination
Principal component analysis
Rice traceability
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Summary:•Total, organic and inorganic arsenic content in rice grains.•The soil, rice grains and husk mineral profile assessed by principal component analysis.•3D models were proposed to geographically discriminate the rice.•Cities and producers discrimination is presented by elemental content. Rice geographical traceability requires analytical procedures and data evaluation capable of linking its composition to the producing area. In this work, major and trace elements in soil and rice grains and husk from 9 cities and 17 producers were evaluated. Arsenic species were measured solely in rice grains. The rice mineral profile evaluated by principal component analysis allowed the identification of controlling variables and origin fingerprints. Vectors controlling data variability were linked to the geographical area, to crop management, producers and in a lower extent to soil composition. Elemental discrimination through 3D models was proposed. Arsenic species in the grains and elemental husk composition were decisive to achieve the required discrimination. Rice discrimination was obtained by cities, producers and varieties. The present work model was compared with others from similar studies.
ISSN:0308-8146
1873-7072
DOI:10.1016/j.foodchem.2019.125145