Área de trabajo: Análisis de alimentos y bebidas.
Título: Determinación de trazas de elementos en productos de arroz por Absorción Atómica.
Título original: Determination of Trace Elements in Rice Products by Flame and Graphite Furnace Atomic Absorption Spectrometry.
Autor: Rebecca Price, Thermo Fisher Scientific, Cambridge, UK.
Summary
The Thermo Scientific iCE 3000 Series Atomic Absorption Spectrometers are the ideal tool for the accurate and rapid determination of multiple trace elements in rice products. Flame atomic absorption can be used as a fast screening tool for the analysis of nutritional elements such as copper, manganese and zinc, while graphite furnace atomic absorption can be used for the accurate determination of toxic elements such as cadmium and lead. Simple sample preparation and easy method optimization provide a rapid and effective solution for accurate and reliable analysis at minor and trace levels.
Introduction
Rice is the second most prevalent cereal crop in the world with an annual global production of approximately 600 million tons. It is the staple food of most Asian countries, with a daily consumption per person of between 200 and 400 g. Trace elemental analysis of this crop and its products is therefore important on an essential, nutritional and toxicological level. The analysis of heavy metals is of particular relevance to human health following numerous incidents such as the mass cadmium poisoning of hundreds of people in the Toyama Prefecture, Japan.
Results and Discussion
Flame: Copper, Manganese and Zinc
Copper, manganese and zinc were analyzed by flame atomic absorption as these elements can be found as natural constituents in soils and water, therefore detection within the low mg/kg (ppm) range was required. The transverse and lateral burner position and the impact bead were manually optimized using a 5 ppm copper standard prior to analysis. Burner height and fuel gas flow were optimized for each element using the Optimize Gas Flow and Burner Height Wizard in the SOLAAR software, as shown in Figure 1. This allowed quick and easy method development with optimized parameters entered automatically into the analytical method.
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