Chromatographic methods

Bagur-González, M. Gracia; Jiménez-Carvelo, Ana M.; Ortega-Gavilán, Fidel; González‐Casado, Antonio

doi:10.1016/b978-0-12-821104-5.00012-x

Cited by 1 publication

(1 citation statement)

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“…Analytical methods are mostly based on separation by gas chromatography or liquid chromatography and analysis by mass spectrometry, or on inductively coupled plasma-mass spectrometry (ICP-MS) [32]. These methods were successfully employed to identify the geographic origin of different types of rice [33][34][35] and they proved particularly useful for the detection of contaminants and adulterants [36][37][38].…”

Section: Brief Overview Of Non-dna Based Methods For Rice Certificationmentioning

confidence: 99%

DNA-Based Tools to Certify Authenticity of Rice Varieties—An Overview

Vieira

Faustino

Lourenço

et al. 2022

Foods

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Rice (Oryza sativa L.) is one of the most cultivated and consumed crops worldwide. It is mainly produced in Asia but, due to its large genetic pool, it has expanded to several ecosystems, latitudes and climatic conditions. Europe is a rice producing region, especially in the Mediterranean countries, that grow mostly typical japonica varieties. The European consumer interest in rice has increased over the last decades towards more exotic types, often more expensive (e.g., aromatic rice) and Europe is a net importer of this commodity. This has increased food fraud opportunities in the rice supply chain, which may deliver mixtures with lower quality rice, a problem that is now global. The development of tools to clearly identify undesirable mixtures thus became urgent. Among the various tools available, DNA-based markers are considered particularly reliable and stable for discrimination of rice varieties. This review covers aspects ranging from rice diversity and fraud issues to the DNA-based methods used to distinguish varieties and detect unwanted mixtures. Although not exhaustive, the review covers the diversity of strategies and ongoing improvements already tested, highlighting important advantages and disadvantages in terms of costs, reliability, labor-effort and potential scalability for routine fraud detection.

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