Green Chemistry Method Based on PARAFAC EEM Data Modeling for Benzo[a]pyrene Quantitation in Distilled Spirit

• Autor(a) principal: Silva,Amanda C.
• Data de Publicação: 2019
• Outros Autores: Pinto,Licarion, Gomes,Adriano A., Araujo,Mario C. U.
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Journal of the Brazilian Chemical Society (Online)
• Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-50532019000200398
• topic: benzo[a]pyrene; cachaça; excitation-emission matrices; parallel factor analysis; polycyclic aromatic hydrocarbons

Benzo[a]pyrene (BaP) is often used as a marker of polycyclic aromatic hydrocarbons (PAHs) in beverages. This marker is often quantified by chromatographic methods, which require sample preparations involving the use of reagents, solvents, extraction, pre-concentration, and/or cleanup steps. In this study, a new method for quantification of BaP in cachaças (liquors) that does not use any sample preparation was developed. Interferents in cachaças were overcome using excitation-emission matrices data modeling with parallel factor analysis (PARAFAC). The recoveries ranged from 93.20 to 101.13%, and the relative error of prediction and limit of detection were, respectively, estimated at 2.66% and 2.88 ng mL-1. The proposed method is inexpensive and less time consuming than other approaches described in the literature, uses no reagents, solvents or extraction, has no pre-concentration or cleanup steps, contributing to green analytical chemistry.