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The Application of Chemometrics to Volatile Compound Analysis for the Recognition of Specific Markers for Cultivar Differentiation of Greek Virgin Olive Oil Samples

机译:化学计量学施用在希腊初榨橄榄油样品中栽培品种分化的特定标志物挥发性复合分析

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摘要

In the present study, volatile compound analysis of olive oil samples belonging to ten Greek cultivars was carried out. A total of 167 olive oil samples collected from two consecutive harvest years were analyzed by Head Space-Solid Phase Microextraction-Gas Chromatography/Mass Spectrometry (HS-SPME-GC/MS). Volatile compound data were combined with chemometric methods (Multivariate Analysis of Variance (MANOVA) and Linear Discriminant Analysis (LDA)) with the aim not only to differentiate olive oils but also to identify characteristic volatile compounds that would enable differentiation of botanical origin (marker compounds). The application of Stepwise LDA (SLDA) effectively reduced the large number of statistically significant volatile compounds involved in the differentiation process, and thus, led to a set of parameters, the majority of which belong to compounds that are highly dependent on variety. In addition, the use of these marker compounds resulted in an increased correct classification rate (85.6%) using the cross-validation method indicating the validity of the model developed despite the use of a large number of dependent variables (cultivars).
机译:在本研究中,进行了属于10种希腊品种的橄榄油样品的挥发性化合物分析。通过头部空间 - 固相微萃取 - 气相色谱/质谱法(HS-SPME-GC / MS)分析了从两个连续收集年收集的167个橄榄油样品。将挥发性化合物数据与化学计量方法(多变量分析(MANOVA)和线性判别分析(LDA)相结合,其目的不仅可以区分橄榄油,而且还鉴定将能够分化植物来源的特征挥发性化合物(标记化合物)。逐步LDA(SLDA)的施加有效地降低了参与分化过程中涉及的大量统计学上显着的挥发性化合物,因此导致了一组参数,其中大多数属于高度依赖于多样性的化合物。此外,使用这些标志物化合物的使用,使用表明模型的有效性的交叉验证方法产生了增加的正确分类速率(85.6%),尽管使用大量的依赖变量(品种)。

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