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ARS Home » Northeast Area » Wyndmoor, Pennsylvania » Eastern Regional Research Center » Sustainable Biofuels and Co-products Research » Research » Publications at this Location » Publication #284563
Title: Reliable peak selection for multisample analysis with comprehensive two-dimensional chromatography

Author
item REICHENBACH, STEPHEN - University Of Nebraska
item TIAN, XUE - University Of Nebraska
item Boateng, Akwasi
item Mullen, Charles
item CORDERO, CHIARA - Universita Di Torino
item TAO, QINGPING - Gc Image, Llc

Submitted to: Analytical Chemistry
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 4/22/2013
Publication Date: 4/21/2013
Citation: Reichenbach, S.E., Tian, X., Boateng, A.A., Mullen, C.A., Cordero, C., Tao, Q. 2013. Reliable peak selection for multisample analysis with comprehensive two-dimensional chromatography. Analytical Chemistry. 85:4974-4981.

Interpretive Summary: To meet the renewable fuels standards set by the US government, 21 billion gallons of advanced bio-fuels will need to be produced by 2022. One promising process is to use fast pyrolysis to convert biomass to produce bio-oil which can be refined to “green” gasoline and diesel fuels that are indistinguishable from those produced from petroleum. It can also be used as produced as a boiler fuel or used as a feedstock for production of chemicals. For any of these uses knowledge on the chemical compounds that make up pyrolysis oil is needed. One of the most common methods for identifying and quantifying individual chemicals in pyrolysis oil is gas chromatography coupled with mass spectroscopy (GCMS). However, because bio-oil has hundreds of different compounds within it, peaks for different compounds can overlap. Therefore, we use a technique called two dimensional GC (GCxGC-MS) to perform a second separation to further separate any overlaping peaks. We applied GCxGC-MS to a set of samples consisting of bio-oil undergoing treatments with five different catalysts with each experiment repeated three times. Matching chromatographic features across a large sample set such as this one is difficult. This paper describes a new, automated method for selecting chromatographic peaks that reliably correspond across many chromatograms. This mathematical pattern recognition technique here is called the Consistent Cliques Method (CCM). Experimental results with samples of complex bio-oils analyzed by comprehensive two-dimensional gas chromatography (GCxGC) with mass spectrometry (GCxGC-MS) indicate that CCM provides a good foundation for comparative analysis of complex chemical mixtures. This information will be important to potential users of complex organic mixtures such as biomass pyrolysis oils including boiler operators, refiners and chemical producers.

Technical Abstract: Comprehensive two-dimensional chromatography is a powerful technology for analyzing the patterns of constituent compounds in complex samples, but matching chromatographic features across large sample sets is difficult. This paper describes a new, automated method for selecting chromatographic peaks that reliably correspond across many chromatograms. Reliably corresponding peaks can be used both for directly comparing relative compositions and for aligning chromatographic data for comprehensive comparative analyses of large numbers of samples. The Consistent Cliques Method (CCM) for selecting reliable features for a set of patterns represents all pairwise matches between patterns in a graph, finds the maximal cliques, and then combines cliques with shared vertices to extract reliable features. For two-dimensional chromatography, the pattern matching establishes correspondences between the detected peaks in pairs of chromatograms and the reliable features are those peaks that match across many chromatograms. The size of a clique or a combined clique indicates the number of patterns matched for the feature - here, the number of chromatograms in which the peak is matched - and so is a measure of that feature's reliability. The parameters of CCM are the minimum size of the maximal cliques and the number of desired reliable features. A particular threshold for the maximal clique size ensures that the combined cliques are conflict-free. Experimental results with samples of complex bio-oils analyzed by comprehensive two-dimensional gas chromatography (GCxGC) with mass spectrometry (GCxGC-MS) indicate that CCM provides a good foundation for comparative analysis of complex chemical mixtures.