Berna Amalia Z, Trowell Stephen, Clifford David, Cynkar Wies, Cozzolino Daniel
CSIRO Entomology & Food Futures Flagship, Canberra, ACT 2601, Australia.
Anal Chim Acta. 2009 Aug 26;648(2):146-52. doi: 10.1016/j.aca.2009.06.056. Epub 2009 Jun 30.
Analysis of 34 Sauvignon Blanc wine samples from three different countries and six regions was performed by gas chromatography-mass spectrometry (GC-MS). Linear discriminant analysis (LDA) showed that there were three distinct clusters or classes of wines with different aroma profiles. Wines from the Loire region in France and Australian wines from Tasmania and Western Australia were found to have similar aroma patterns. New Zealand wines from the Marlborough region as well as the Australian ones from Victoria were grouped together based on the volatile composition. Wines from South Australia region formed one discrete class. Seven analytes, most of them esters, were found to be the relevant chemical compounds that characterized the classes. The grouping information obtained by GC-MS, was used to train metal oxide based electronic (MOS-Enose) and mass spectrometry based electronic (MS-Enose) noses. The combined use of solid phase microextraction (SPME) and ethanol removal prior to MOS-Enose analysis, allowed an average error of prediction of the regional origins of Sauvignon Blanc wines of 6.5% compared to 24% when static headspace (SHS) was employed. For MS-Enose, the misclassification rate was higher probably due to the requirement to delimit the m/z range considered.
采用气相色谱-质谱联用仪（GC-MS）对来自三个不同国家和六个地区的34个长相思葡萄酒样品进行了分析。线性判别分析（LDA）表明，存在三种具有不同香气特征的明显聚类或类别葡萄酒。法国卢瓦尔河谷地区的葡萄酒以及来自塔斯马尼亚和西澳大利亚的澳大利亚葡萄酒具有相似的香气模式。基于挥发性成分，来自马尔堡地区的新西兰葡萄酒以及来自维多利亚州的澳大利亚葡萄酒被归为一类。来自南澳大利亚地区的葡萄酒形成一个独立的类别。发现七种分析物（其中大多数是酯类）是表征这些类别的相关化合物。通过GC-MS获得的分组信息用于训练基于金属氧化物的电子鼻（MOS-Enose）和基于质谱的电子鼻（MS-Enose）。在MOS-Enose分析之前，将固相微萃取（SPME）与乙醇去除相结合使用，长相思葡萄酒产地预测的平均误差为6.5%，而采用静态顶空（SHS）时为24%。对于MS-Enose，误分类率可能更高，这可能是由于需要限定所考虑的m/z范围。
