Establishment of a method for determination of arsenic species in seafood by LC-ICP-MS

An analytical method for determination of arsenic species (inorganic arsenic (iAs), methylarsonic acid (MA), dimethylarsinic acid (DMA), arsenobetaine (AB), trimethylarsine oxide (TMAO) and arsenocholine (AC)) in Brazilian and Spanish seafood samples is reported. This study was focused on extraction...

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Detalles Bibliográficos
Autores: Zmozinski, Ariane V., Llorente Mirandes, Antoni, López Sánchez, José Fermín, Da Silva, Márcia M.
Tipo de recurso: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2014
País:España
Institución:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositorio:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:2445/162332
Acceso en línea:https://hdl.handle.net/2445/162332
Access Level:acceso abierto
Palabra clave:Arsènic
Marisc
Cromatografia de líquids
Química dels aliments
Arsenic
Seafood
Liquid chromatography
Food composition
Descripción
Sumario:An analytical method for determination of arsenic species (inorganic arsenic (iAs), methylarsonic acid (MA), dimethylarsinic acid (DMA), arsenobetaine (AB), trimethylarsine oxide (TMAO) and arsenocholine (AC)) in Brazilian and Spanish seafood samples is reported. This study was focused on extraction and quantification of inorganic arsenic (iAs), the most toxic form. Arsenic speciation was carried out via LC with both anionic and cationic exchange with ICP-MS detection (LC-ICP-MS). The detection limits (LODs), quantification limits (LOQs), precision and accuracy for arsenic species were established. The proposed method was evaluated using eight reference materials (RMs). Arsenobetaine was the main species found in all samples. The total and iAs concentration in 22 seafood samples and RMs ranged between 0.27-35.2 and 0.02-0.71 mg As kg-1, respectively. Recoveries ranging from 100% to 106% for iAs, based on spikes, were achieved. The proposed method provides reliable iAs data for future risk assessment analysis.