Analytical strategies for determination of cadmium in Brazilian vinegar samples using ET AAS

AbstractThis paper proposes two methods for determination of cadmium in vinegar employing electrothermal atomic absorption spectrometry. The optimization step was performed using two-level full factorial and Box–Behnken designs, being that a new multiple response function was established. Under experimental conditions of pyrolysis temperature of 640°C and atomization temperature of 2000°C, the direct method allows the analysis using the external calibration technique, with limit of quantification of 14ngL−1 and characteristic mass of 1.2pg, having aluminium as chemical modifier. This method was applied in six samples of vinegar acquired from Salvador City, Brazil. The cadmium content varied from 20 to 890ngL−1. Other method was also proposed by digestion using nitric acid and hydrogen peroxide in reflux system employing cold finger, being cadmium determined by ETAAS. The results obtained with the complete digestion procedure were in agreement with those found by the direct method proposed herein

The chemical generation of NO for the determination of nitrite by high-resolution continuum source molecular absorption spectrometry

AbstractIn the present work, we propose a method for the determination of nitrite based on the chemical generation of nitric oxide (NO) and its detection by high-resolution continuum source molecular absorption spectrometry. NO is generated by the reduction of nitrite in acidic media with ascorbic acid as the reducing agent and then transferred into a quartz cell by a stream of argon carrier gas. The conditions under which the NO is generated are as follows: 0.4molL−1 hydrochloric acid, 1.5%(w/v) ascorbic acid, an argon gas pressure of 0.03MPa and an injection time of the reducing agent of 4s. All measurements of molecular absorption were performed using the NO line at 215.360nm, and the signal was measured by peak height. Under these conditions, the method described has limits of detection and quantification of 0.045 and 0.150μgmL−1 of nitrite, respectively. The calibration curve is linear for nitrite concentrations in the range 0.15–15μgmL−1. The precision, estimated as the relative standard deviation (RSD), was 3.5% and 4.4% for solutions with nitrite concentrations of 0.5 and 5.0μgmL−1, respectively. This method was applied to the analysis of different water samples (well water, drinking water and river water) collected in Cachoeira City, Bahia State, Brazil. The results were in agreement with those obtained by a spectrophotometric method using the Griess reaction. Addition/recovery tests were also performed to check the validity of the proposed method. Recoveries of 93–106% were achieved

A Multiple Response Function for Optimization of Analytical Strategies Involving Multi-elemental Determination

This paper presents a comparison between a multiple response function (MR) proposed for optimization of analyticalstrategies involving multi-element determinations with the desirability function D, which was proposed by Derringerand Suich in 1980. The MR function is established by the average of the sum of the normalized responses for eachanalyte considering the highest value of these. This comparison was performed during the optimization of an spectrometerfor quantification of six elements using inductively coupled plasma optical emission spectrometry (ICP OES). Four instrumentalfactors were studied (auxiliary gas flow rate, plasma gas flow rate, nebulizer gas flow rate and radio frequencypower). A (24) two-level full factorial design and a Box Behnken matrix were developed to evaluate the performance ofthe two multiple response functions. The results found demonstrated great similarity in the interpretations obtained consideringthe effect values of the factors calculated using the two-level full factorial design employing the two multiple responses.Also a Box Behnken design was performed to compare the applicability of the two multiple response functions inquadratic models. The results achieved demonstrated high correlation (0.9998) between the regression coefficients of thetwo models. Also the response surfaces obtained showed great similarity in terms of formats and experimental conditionsfound for the studied factors. Thus, the multiple response (MR) is presented as a simple tool, easy to manipulate, efficientand very helpful for application in analytical procedures involving multi-response. An overview of applications of thisfunction in several multivariate optimization tools as well as in various analytical techniques is presented.Fil: Novaes, Cleber G.. Universidade Estadual do Sudoeste da Bahia; Brasil. Universidade Federal da Bahia; BrasilFil: Ferreira, Sergio L.C.. Universidade Federal da Bahia; BrasilFil: Neto, João H. S.. Universidade Estadual do Sudoeste da Bahia; BrasilFil: de Santana, Fernanda A.. Universidade Federal da Bahia; BrasilFil: Portugal, Lindomar A.. Universidad de las Islas Baleares; EspañaFil: Goicoechea, Hector Casimiro. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional del Litoral. Facultad de Bioquímica y Ciencias Biológicas; Argentin