Department of Chemistry, Box 351700, University of Washington, Seattle, WA 98195, USA.
Department of Chemistry, Box 351700, University of Washington, Seattle, WA 98195, USA.
J Chromatogr A. 2024 Aug 16;1730:465093. doi: 10.1016/j.chroma.2024.465093. Epub 2024 Jun 14.
Herein, two "orthogonal" characteristics of moisture damaged cacao beans (temporally dependent molding kinetics versus the time-independent geographical region of origin) are simultaneously analyzed in a comprehensive two-dimensional (2D) gas chromatography time-of-flight mass spectrometry (GC×GC-TOFMS) dataset using tile-based Fisher ratio (F-ratio) analysis. Cacao beans from six geographical regions were analyzed once a day for six days following the initiation of moisture damage to trigger the molding process. Thus, there are two "extremes" to the experimental sample class design: six time points for the molding kinetics versus the six geographical regions of origin, resulting in a 6 × 6 element signal array referred to as a composite chemical fingerprint (CCF) for each analyte. Usually, this study would involve initial generation of two separate hit lists using F-ratio analysis, one hit list from inputting the data with the six time point classes, then another hit list from inputting the dataset from the perspective of geographic region of origin. However, analysis of two separate hit lists with the intent to distill them down to one hit list is extremely time-consuming and fraught with shortcomings due to the challenges associated with attempting to match analytes across two hit lists. To address this challenge, tile-based F-ratio analysis is "orthogonally applied" to each analyte CCF to simultaneously determine two F-ratios at the chromatographic 2D location (F-ratio and F-ratio) for each hit, by ranking a single hit list using the higher of the two F-ratios resulting in the discovery of 591 analytes. Further, using a pseudo-null distribution approach, at the 99.9% threshold over 400 analytes were deemed suitable for PCA classification. Using a more stringent 99.999% threshold, over 100 analytes were explored more deeply using PARAFAC to provide a purified mass spectrum.
本文采用基于图块的 Fisher 比(F-ratio)分析方法,在全面的二维气相色谱飞行时间质谱(GC×GC-TOFMS)数据集中,同时分析了水分损伤可可豆的两个“正交”特性(随时间变化的模塑动力学与不受时间影响的原产地理区域)。从六个地理区域采集的可可豆在水分损伤开始后,每天分析一次,持续六天,以触发模塑过程。因此,实验样本类设计有两个“极端”:模塑动力学的六个时间点与原产地理区域的六个地理区域,从而为每个分析物生成一个称为复合化学指纹(CCF)的 6×6 元素信号数组。通常,这项研究需要使用 F-ratio 分析生成两个单独的命中列表,一个命中列表是从输入具有六个时间点类别的数据生成的,另一个命中列表是从输入数据集的角度生成的原产地理区域。然而,分析两个单独的命中列表并试图将它们归结为一个命中列表是极其耗时的,并且由于试图在两个命中列表中匹配分析物所带来的挑战,存在很多缺点。为了解决这个挑战,基于图块的 F-ratio 分析以“正交方式”应用于每个分析物的 CCF,以在每个命中的色谱 2D 位置(F-ratio 和 F-ratio)同时确定两个 F-ratio,通过使用两个 F-ratio 中的较高者对单个命中列表进行排序,从而发现 591 个分析物。此外,使用伪零分布方法,在 99.9%的阈值下,有 400 多个分析物被认为适合 PCA 分类。使用更严格的 99.999%阈值,通过 PARAFAC 对 100 多个分析物进行了更深入的探索,以提供净化后的质谱。