Comparison of Different PLS Algorithms for Simultaneous Determination of Cd(II), Cu(II), Pb(II), and Zn(II) by Anodic Stripping Voltammetry at Bismuth Film Electrode

In this work we evaluated the use of different variable selection techniques combined with partial least‐squares regression (PLS) – genetic algorithm PLS (GA‐PLS), interval PLS (iPLS), and synergy interval PLS (siPLS) – in the simultaneous determination of Cd(II), Cu(II), Pb(II) and Zn(II) by anodic stripping voltammetry at a bismuth film. Generally, variable selection provided an improvement in prediction results when compared to full‐voltammogram PLS. The use of interval selection based algorithms have shown to be most adequate than the selection of discrete variables by GA. Excellent analytical performances were obtained despite the inherent complexity of the simultaneous determination.