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Analysis of Flavors Using a Mass Spectral-Based Chemical Sensor

机译：使用质谱化化学传感器的口味分析

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A mass spectrometer based chemical sensor was used to model citrus peel oils. Seven samples and one duplicate were analyzed and subsequently modeled with multivariate analyses such as principal component analysis (PCA) and Soft Independent Modeling of Class Analogy (SIMCA). Discrimination between samples was excellent with clear distinctions between the samples and considerable overlap of the duplicate sample. Samples were also analyzed with a gas chromatograph/mass spectrometer (GC/MS) using similar multivariate models. GCMS results were similar to the ones obtained by sampling the static headspace, but with longer analysis times. Statistics obtained using SIMCA analysis allowed for the determination of which samples were most similar to a "target" sample.
机译：基于质谱仪的化学传感器用于模拟柑橘剥离油。分析七个样本和一种重复，随后用多变量分析（如主成分分析（PCA）和类类比软件（SIMCA）的软独立建模而建模。样品之间的歧视具有优异的，在样品之间具有明显的区别，并对重复样品相当重叠。还使用类似的多级模型用气相色谱/质谱仪（GC / MS）分析样品。 GCMS结果类似于通过对静态页面进行采样而获得的结果，但分析时间更长。使用SIMCA分析获得的统计数据允许测定哪些样本与“靶”样品最相似。

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