http://dx.doi.org/10.4322/sc.2016.015

 

The software importance in analysis by GC×GC: comparative study of software GCImageTM and ChromaTOFTM

Schneider, Jaderson K.; Cunha, Michele E. da; Brasil, Márcia C.; Machado, Maria E.; Jacques, Rosângela A.; Caramão, Elina B.

Palavras-chave ChromaTOFTM, CGImageTM, data processing, software comparison.

Resumo Comprehensive two-dimensional gas chromatography (GC×GC) is a technique that allows the separation and identification of compounds with higher performance than the one-dimensional gas chromatography (GC-1D). The GC×GC generates a considerable amount of data, which need a powerful computational tool for the identification of compounds. In this context, the use of suitable software and highly specialized becomes the heart of the analysis. This study aimed to compare the efficiency of two different software, GCImageTM and ChromaTOFTM in the identification of compounds present in a sample of bio-oil of sugarcane straw analyzed in a GC×GC/TOFMS system. The data processing was performed in ChromaTOFTM using the following conditions, peak width in 1D: 10 s; peak width in 2D: 0.2 s; signal / noise ratio: 3 and mass range: 40-550 Daltons. For the treatment of the same sample GCImageTM, it was only necessary to inform the modulation period, which was 10 s. In both softwares, the library used was NIST MS Search version 2.0. The total amount of compounds tentatively identified applying ChromaTOFTM was 324 while using GCImageTM, only 271 peaks were identified. The difference of 53 compounds can be mainly attributed to spectral deconvolution present in ChromaTOFTM software tool, which is automatically performed in this software and manually, at the option of the operator, in the CGImageTM. The ChromaTOFTM identified a higher number of compounds belonging to the classes of ketones and sugars, in large part, identified by spectral deconvolution. The ChromaTOFTM identified a higher number of compounds belonging to the classes of ketones and sugars, in large part, identified by spectral deconvolution. From the comparative study it can be concluded that the data identification obtained in a GC×GC/TOFMS must be held in ChromaTOFTM software for a more precise result. However, when the research aims a general characterization of the sample, it can employing the GCImageTM with good results.


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