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Two-Dimensional Retention Indices Improve Component Identification in Comprehensive Two-Dimensional Gas Chromatography of Saffron

化学 科瓦茨保留指数 色谱法 二维气体 气相色谱法 分析化学(期刊) 气相色谱-质谱法 保留时间 二维色谱法 质谱法
作者
Ming Jiang,Chadin Kulsing,Yada Nolvachai,Philip J. Marriott
出处
期刊:Analytical Chemistry [American Chemical Society]
卷期号:87 (11): 5753-5761 被引量:82
标识
DOI:10.1021/acs.analchem.5b00953
摘要

Comprehensive two-dimensional gas chromatography hyphenated with accurate mass time-of-flight mass spectrometry (GC × GC-accTOFMS) was applied for improved analytical accuracy of saffron analysis, by using retention indices in the two-dimensional separation. This constitutes 3 dimensions of identification. In addition to accTOFMS specificity, and first dimension retention indices (1I), a simple method involving direct multiple injections with stepwise isothermal temperature programming is described for construction of isovolatility curves for reference alkane series in GC × GC. This gives access to calculated second dimension retention indices (2I). Reliability of the calculated 2I was evaluated by using a Grob test mixture, and saturated alkanes, revealing good correlation between previously reported I values from the literature, with R2 correlation being 0.9997. This essentially recognizes the retention property of peaks in the GC × GC 2D space as being reducible to a retention index in each dimension, which should be a valuable tool supporting identification. The benefit of 2I data, in supplementing 1I and MS library matching, was clearly demonstrated by the progressive reduction of the number of possible compound matches for peaks observed in saffron. 114 analytes were assessed according to 1I and 2I values within ±20 index unit of reference values, and by MS spectrum matching above a match statistic of 750 (including mass accuracy of the molecular ion <20 ppm) and their possible identities derived. The described method provides a new avenue to utilize the full capability of the two-dimensional separation (GC × GC), in combination with MS library matching in complex sample analysis, to provide improved component identification.

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