RESUMEN
Mass spectra are widely used in order to identify the peaks resulting from a chromatographic separation. The most common approach to solve the problem for unknowns on whom very little other structural information is available is the use of a retrieval algorithm and a reference mass spectra database. The wide variety of mass spectra recorded with different instruments under various experimental conditions can lead to erroneous results. In order to improve the accuracy of the results, we proposed earlier an identification algorithm, which combines the information obtained from both GC and MS fingerprints. This paper presents a new algorithm based on the comparison of the unknown mass spectra with several libraries (including Wiley and NIST) by using reverse and direct search algorithms respectively. The results of the comparisons were quantified with respect to the match quality and the interference compounds. A global match index for the comparison using all the above information was computed and the results were presented as the match probability. This index expresses more accurately the matches between unknown and all the available libraries mass spectra. In order to verify our algorithm, we tried to identify the compounds separated by GC-MSD from different species of Acorus calamus L. (Araceae) essential oils. The probability of the matches increases compared with the quality of matches resulting from Wiley and NIST libraries.