The electrochemical detection of arsenic(III) was investigated on platinum nanoparticle-modified carbon-based screen-printed electrodes (PtNPs/SPCEs) in 1 M aqueous H 2 SO 4 . PtNPs/SPCEs were prepared by electrochemical deposition of K 2 PtCl 6 . The resulting electrode surfaces were characterized with scanning electron microscopy (SEM). By using the As(III) oxidation peak for the analytical determination, there is no interference from Cu(II) if present in contrast to the other metal surfaces typically used for the detection of arsenic in electrochemistry. Precision of the proposed method was very good and a relative good accuracy determined by analysis of a certificate sample and in a spiked tap water sample. Electroinactive As(V) was reduced to As(III) by sodium thiosulfate prior to determination. The detection limit for As(III) obtained was 5.68 mg L À1. In terms of reproducibility, the precision of the above mentioned method in % RSD was calculated at 2.27%.

Enzymatic amperometric procedures for measuring arsenic, based on the inhibitive action of this metal on acetylcholinesterase enzyme activity, have been developed. Screen-printed carbon electrodes (SPCEs) were used with acetylcholinesterase covalently bonded directly to its surface. The amperometric response of acetylcholinesterase was affected by the presence of arsenic ions, which caused a decrease in the current intensity. The experimental optimum working conditions of pH, substrate concentration and potential applied, were established. Under these conditions, repeatability and reproducibility of biosensors were determined, reaching values below 4% in terms of relative standard deviation. The detection limit obtained for arsenic was 1.1 × 10−8 M for Ach/SPCE biosensor. Analysis of the possible effect of the presence of foreign ions in the solution was performed. The method was applied to determine levels of arsenic in spiked tap water samples.

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A new strategy to approach multiresponse optimization in conjunction to a D-optimal design for simultaneously optimizing a large number of experimental factors is proposed. The procedure is applied to the determination of biogenic amines (histamine, putrescine, cadaverine, tyramine, tryptamine, 2-phenylethylamine, spermine and spermidine) in swordfish by HPLC-FLD after extraction with an acid and subsequent derivatization with dansyl chloride. Firstly, the extraction from a solid matrix and the derivatization of the extract are optimized. Ten experimental factors involved in both stages are studied, seven of them at two levels and the remaining at three levels; the use of a D-optimal design leads to optimize the ten experimental variables, significantly reducing by a factor of 67 the experimental effort needed but guaranteeing the quality of the estimates. A model with 19 coefficients, which includes those corresponding to the main effects and two possible interactions, is fitted to the peak area of each amine. Then, the validated models are used to predict the response (peak area) of the 3456 experiments of the complete factorial design. The variability among peak areas ranges from 13.5 for 2-phenylethylamine to 122.5 for spermine, which shows, to a certain extent, the high and different effect of the pretreatment on the responses. Then the percentiles are calculated from the peak areas of each amine. As the experimental conditions are in conflict, the optimal solution for the multiresponse optimization is chosen from among those which have all the responses greater than a certain percentile for all the amines. The developed procedure reaches decision limits down to 2.5 μg L for cadaverine or 497 μg L for histamine in solvent and 0.07 mg kg and 14.81 mg kg in fish (probability of false positive equal to 0.05), respectively.

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