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伏安电子舌和近红外光谱法在快速鲜味评估中的应用。

Application of a voltammetric electronic tongue and near infrared spectroscopy for a rapid umami taste assessment.

作者信息

Bagnasco Lucia, Cosulich M Elisabetta, Speranza Giovanna, Medini Luca, Oliveri Paolo, Lanteri Silvia

机构信息

Department of Chemistry and Industrial Chemistry, University of Genoa, Via Dodecaneso 31, I-16146 Genoa, Italy; Department of Pharmacy, University of Genoa, Via Brigata Salerno 13, I-16147 Genoa, Italy.

Department of Chemistry and Industrial Chemistry, University of Genoa, Via Dodecaneso 31, I-16146 Genoa, Italy; Department of Biology and Biotechnology "L. Spallanzani", University of Pavia, Via Ferrata 9, I-27100 Pavia, Italy.

出版信息

Food Chem. 2014 Aug 15;157:421-8. doi: 10.1016/j.foodchem.2014.02.044. Epub 2014 Feb 22.

Abstract

The relationships between sensory attribute and analytical measurements, performed by electronic tongue (ET) and near-infrared spectroscopy (NIRS), were investigated in order to develop a rapid method for the assessment of umami taste. Commercially available umami products and some aminoacids were submitted to sensory analysis. Results were analysed in comparison with the outcomes of analytical measurements. Multivariate exploratory analysis was performed by principal component analysis (PCA). Calibration models for prediction of the umami taste on the basis of ET and NIR signals were obtained using partial least squares (PLS) regression. Different approaches for merging data from the two different analytical instruments were considered. Both of the techniques demonstrated to provide information related with umami taste. In particular, ET signals showed the higher correlation with umami attribute. Data fusion was found to be slightly beneficial - not so significantly as to justify the coupled use of the two analytical techniques.

摘要

为开发一种快速评估鲜味的方法,研究了电子舌(ET)和近红外光谱(NIRS)进行的感官属性与分析测量之间的关系。将市售鲜味产品和一些氨基酸进行感官分析。将结果与分析测量结果进行比较分析。通过主成分分析(PCA)进行多变量探索性分析。使用偏最小二乘法(PLS)回归获得基于ET和近红外信号预测鲜味的校准模型。考虑了合并来自两种不同分析仪器的数据的不同方法。两种技术都证明能提供与鲜味相关的信息。特别是,ET信号与鲜味属性显示出更高的相关性。发现数据融合略有好处,但好处并不显著,不足以证明两种分析技术联合使用的合理性。

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