Evaluation of signal and noise and identification of a suitable target function in the tuning of an ESI ion trap mass spectrometer by multivariate pattern recognition tools.

When mass spectrometry is not combined to separation techniques, the evaluation of signal and noise in a complex mass spectrum is not trivial. The tuning of the spectrometer based only on the increase of the signal of a selected number of m/z values does not ensure the achievement of the best experimental conditions: signal could improve and noise could increase as well. The scope of this work is the development of a function separating signal and noise (for evaluating the S/N) from complex mass spectra for potential use as target function for the automatic tuning of the instrument. Two different methods were applied: the first is based on the separation of a pool of m/z values attributable to the signal from the m/z values due to the noise, while the second is based on the application of principal component analysis to separate the signal (present in the significant components) from the noise (present in the residuals). The comparison of the two methods was carried out by the evaluation of the stability of the signal and the target functions obtained, and the evaluation of the variation of the target functions as a function of concentration.