Literature DB >> 31330371

Mineral profile exploratory analysis for rice grains traceability.

Camila Neves Lange1, Lucilena Rebelo Monteiro2, Bruna Moreira Freire3, Daniel Fernandez Franco4, Rogerio Oliveira de Souza5, Cecilia Sacramento Dos Reis Ferreira6, Julio José Centeno da Silva7, Bruno Lemos Batista8.   

Abstract

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.
Copyright © 2019 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Arsenic species; Brazilian rice; Geographical discrimination; Principal component analysis; Rice traceability

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Year:  2019        PMID: 31330371     DOI: 10.1016/j.foodchem.2019.125145

Source DB:  PubMed          Journal:  Food Chem        ISSN: 0308-8146            Impact factor:   7.514


  2 in total

1.  Are the elemental fingerprints of organic and conventional food different? ED-XRF as screening technique.

Authors:  Yiannis Fiamegos; Sergej Papoci; Catalina Dumitrascu; Michele Ghidotti; Tereza Zdiniakova; Franz Ulberth; María Beatriz de la Calle Guntiñas
Journal:  J Food Compost Anal       Date:  2021-06       Impact factor: 4.556

2.  Development of an Ozone-Assisted Sample Preparation Method for the Determination of Cu and Zn in Rice Samples.

Authors:  Mariela Pistón; Ignacio Machado; Esteban Rodríguez-Arce; Isabel Dol
Journal:  J Anal Methods Chem       Date:  2021-07-19       Impact factor: 2.193

  2 in total

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