Department of Biology, Tufts University, Medford, MA 02155, USA.
Department of Chemistry, Tufts University, Medford, MA 02155, USA.
Molecules. 2022 Aug 21;27(16):5328. doi: 10.3390/molecules27165328.
Gas chromatography/mass spectrometry (GC/MS) is a long-standing technique for the analysis of volatile organic compounds (VOCs). When coupled with the Ion Analytics software, GC/MS provides unmatched selectivity in the analysis of complex mixtures and it reduces the reliance on high-resolution chromatography to obtain clean mass spectra. Here, we present an application of spectral deconvolution, with mass spectral subtraction, to identify a wide array of VOCs in green and roasted coffees. Automated sequential, two-dimensional GC-GC/MS of a roasted coffee sample produced the retention index and spectrum of 750 compounds. These initial analytes served as targets for subsequent coffee analysis by GC/MS. The workflow resulted in the quantitation of 511 compounds detected in two different green and roasted coffees. Of these, over 100 compounds serve as candidate differentiators of coffee quality, AAA vs. AA, as designated by the Coopedota cooperative in Costa Rica. Of these, 72 compounds survive the roasting process and can be used to discriminate green coffee quality after roasting.
气相色谱/质谱联用技术(GC/MS)是一种用于分析挥发性有机化合物(VOCs)的长期技术。当与 Ion Analytics 软件结合使用时,GC/MS 在分析复杂混合物时具有无与伦比的选择性,并且减少了对获得干净质谱所需的高分辨率色谱的依赖。在这里,我们提出了一种光谱解卷积的应用,通过质谱减法来鉴定绿色和烘焙咖啡中的各种 VOCs。对烘焙咖啡样品进行自动顺序二维 GC-GC/MS 分析,得到了 750 种化合物的保留指数和光谱。这些初始分析物成为随后通过 GC/MS 进行咖啡分析的目标。该工作流程实现了对两种不同绿色和烘焙咖啡中检测到的 511 种化合物的定量。其中,超过 100 种化合物可作为咖啡质量区分的候选物,如哥斯达黎加 Coopedota 合作社指定的 AAA 与 AA。其中,72 种化合物在烘焙过程中幸存下来,可用于区分烘焙后的绿色咖啡质量。