主成分分析
葡萄酒
质谱法
色谱法
化学
气相色谱-质谱法
层次聚类
气相色谱法
挥发性有机化合物
固相微萃取
萘
分辨率(逻辑)
作文(语言)
二维气体
聚类分析
数学
食品科学
统计
计算机科学
有机化学
人工智能
语言学
哲学
作者
Nemanja Koljančić,A. A. Gomes,Ivan Špánik
标识
DOI:10.1002/jssc.202300249
摘要
One of the most effective methods for gaining insight into the composition of trace-level volatile organic characteristics of wine products is through the use of a comprehensive two-dimensional gas chromatography-high resolution mass spectrometry (GC × GC-HRMS) technique. The vast amount of data generated by this method, however, can often be overwhelming requiring exhaustive and time-consuming analysis to identify significant statistical characteristics. The use of advanced chemometric software can achieve the same or even higher efficiency. This study aimed to identify differences based on geographical locations by analyzing the volatile organic compounds in the composition of botrytized wines from Slovakia, Hungary, France, and Austria. The volatile organic compounds were extracted by solid-phase microextraction and analyzed using GC × GC-HRMS. The data obtained from the analysis underwent Fisher-ratio (F-ratio) tile-based analysis to identify statistically significant differences. Principal component analysis demonstrated a significant distinction between wine samples based on geographical location, using only 10 statistically significant features with the highest F-ratio. In the samples, the following compounds were analyzed: methyl-octadecanoate, 2-cyanophenyl-β-phenylpropionate, α-ionone, n-octanoic acid, 1,2-dihydro-1,1,6-trimethyl-naphthalene, methyl-hexadecanoate, ethyl-pentadecanoate, ethyl-decanoate, and γ-nonalactone. These, all play an important role in cluster pattern observed on principal component analysis results. Additionally, hierarchical cluster analysis confirmed this.
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