An evaluation of extraction techniques for arsenic in staple diets (fish and rice) utilising both classical and enzymatic extraction methods.

نویسندگان

  • Bashdar A Sadee
  • Mike E Foulkes
  • Steve J Hill
چکیده

Enzymatic extraction methods were evaluated with classical extraction approaches for the determination of arsenic in food. The extraction efficiency for total arsenic was determined by analysing CRM materials DORM-3 fish protein, NIES 106 rice flour and GBW10015 spinach. These were compared with total arsenic concentration determined using microwave-assisted acid digestion and ICP-MS. The total arsenic concentrations in the CRM materials were in good agreement with the certified values. Enzymatic hydrolysis using trypsin has been successfully employed to extract arsenic species in DORM-3 and fish samples. Whilst this method of hydrolysing the proteins worked well for the fish samples, an alternative approach was required to facilitate the digestion of cellulose in plant materials. However, enzymatic extraction using cellulase was found to give unsatisfactory results for both the NIES and GBW10015 CRM materials. Dilute nitric acid (1% HNO3) was found to give a more efficient extraction for arsenic species in the same CRM materials and rice samples. The study was extended to evaluate a range of real samples. Total arsenic concentrations in 13 different types of fish tissue were determined following microwave-assisted acid digestion using nitric acid/hydrogen peroxide, followed by measurement using HPLC-ICP-MS for speciation analysis. The results obtained for fish were in the range of 3.53-98.80 µg g(-1) As (dry weight). Similarly, the results of 17 rice samples were in the range of 0.054-0.823 µg g(-1). This study demonstrates the importance of selecting an appropriate extraction technique for the quantitative measurement of arsenic species in food.

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عنوان ژورنال:
  • Food additives & contaminants. Part A, Chemistry, analysis, control, exposure & risk assessment

دوره 33 3  شماره 

صفحات  -

تاریخ انتشار 2016