A computational study on the effect of random noise on the precision and accuracy of the integration of chromatographic peaks

Abstract

This paper describes the results of a computational study on the effect of random noise on the precision and accuracy of the integration of chromatographic peaks. The focus of the study is to provide guidance for practical integration of peaks in the presence of random noises. The effect of noise is examined for the following integration parameters: noise levels, number of data points, integration range, digitally filtering (bunching), and peak asymmetry. The baseline is determined from the first and last points of the peaks. We conclude that the major contribution to peak area integration imprecision is the effect of noise on the determination of peak baseline. For all the parameters examined, the signal-to-noise ( S/ N) ratio has the most significant effect on the precision. The number of data points within a peak should be about 30 to provide the best integration precision and peak representation. The absolute integration range should be as small as possible, however, for peaks with different asymmetry and width, the precision is determined by the relative integration range if other integration parameters are kept about the same. Moreover, the increase in peak asymmetry results in the decrease in S/ N ratio, and then an increase in the imprecision. Finally, bunching is always preferred to improve the precision. The results of the study should be applicable to situations where random noises are dominant such as in capillary electrophoresis.