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首页> 外文期刊>Journal of chromatography, A: Including electrophoresis and other separation methods >Correlating sensory attributes to gas chromatography-mass spectrometry profiles and e-nose responses using partial least squares regression analysis
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Correlating sensory attributes to gas chromatography-mass spectrometry profiles and e-nose responses using partial least squares regression analysis

机译：使用偏最小二乘回归分析将感官属性与气相色谱-质谱图和电子鼻响应相关

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摘要

Sensory scores for 15 attributes identified in soy sauce aroma by quantitative descriptive analysis were correlated with purge and trap gas chromatography-mass spectrometry (GC-MS) profiles and electronic nose (e-nose) responses using partial least squares (PLS) regression analysis. Highly predictive PLS models were obtained for every attribute based on whole GC-MS profiles. However, the predictability has been greatly improved in the models calculated from 20 selected peaks that showed higher contribution to each attribute in the first PLS analysis. Contrarily, except for alcoholic and fishy notes, predictability of PLS models calculated from e-nose responses was poor. The correlation between GC-MS profiles and e-nose responses was unsatisfactory due to high similarity in sensor responses. (C) 2004 Elsevier B.V. All rights reserved.
机译：通过定量描述分析确定的酱油香气中15种属性的感官评分与吹扫捕集气相色谱-质谱（GC-MS）数据以及使用偏最小二乘（PLS）回归分析的电子鼻（e-nose）响应相关。基于整个GC-MS配置文件，为每个属性获得了高度预测的PLS模型。但是，在从20个选定峰中计算出的模型中，可预测性已大大提高，这些峰在首次PLS分析中显示出对每个属性的较高贡献。相反，除酒精和鱼腥味外，根据电子鼻响应计算的PLS模型的可预测性较差。由于传感器响应的高度相似性，GC-MS配置文件与电子鼻响应之间的相关性无法令人满意。 （C）2004 Elsevier B.V.保留所有权利。

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