Otrzymano: Czerwiec 21, 2016
Zaakceptowano: Wrzesień 06, 2017
Opublikowano online: 2017-11-27
Biology and microbiology,
Medicine and veterinary
Evaluation of wet digestion methods based on acids in acid mixtures set at different temperatures and ratios is important to assess accurately the content of trace elements in biological samples. This study presents a comparison of three digestion procedures based on nitric acid-hydrogen peroxide (NH), nitric acid-sulfuric acid (NS), and nitric acid-perchloric acid (NP) at different temperatures and ratios of the acid mixture. This study was conducted on blood serum of healthy volunteers (Hospital of Tanta University, Tanta, Egypt) for comparison of different digestion methods. An inductively coupled plasma-mass spectroscopy ICP-MS was calibrated using the certified standard biological samples IAEA-A-13 and then it was used to determine eight elements, Cr, Cu, Fe, Co, Mn, Ni, Se, and Zn in the digested samples. In order to reduce the experimental variables and group the analyzed trace elements into clusters correlated with the preferred digestion procedures, multivariate statistical analysis based on cluster analysis (CA) and principal component analysis (PCA) was used to select the optimal digestion method for each trace element. The results confirmed that none of the used digestion procedures for the certified biological samples, freeze dried animal blood, have given an accurate assessment for all trace elements, however the most acceptable digestion procedure is the one involving nitric acid/perchloric acid, 4:1 and 4:2 v/v, at a temperature of 120 °C. The nitric acid/sulfuric acid procedure, 4:2 v/v, achieved good extraction of trace elements at temperature of 120 °C while the nitric acid/hydrogen peroxide procedure, 4:2 v/v, achieved the highest extraction for cobalt and iron.
Badran M., Morsy R., Soliman H., Elnimr T. 2018. Assessment of wet acid digestion methods for ICP-MS determination of trace elements in biological samples by using Multivariate Statistical Analysis. J. Elem., 23(1): 179 - 189. DOI: 10.5601/jelem.2016.21.3.1232
Cluster analysis; ICP-MS; Multivariate statistical analysis; Principal component analysis; Wet digestion method