分析与检测

快速感官分析技术在葡萄酒香气感官分析中的应用

  • 田欣 ,
  • 张会宁 ,
  • 祁新春 ,
  • 徐岩 ,
  • 王栋 ,
  • 唐柯
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  • 1 (教育部工业生物技术重点实验室,食品科学与技术国家重点实验室,江南大学 生物工程学院,酿酒微生物与酶技术研究室,江苏 无锡,214122)
    2 (山西戎子酒庄有限公司,山西 临汾,042100)
硕士(王栋教授和唐柯副教授为共同通讯作者,E-mail:dwang@jiangnan.edu.cn;tandy81@163.com)。

收稿日期: 2018-08-26

  网络出版日期: 2019-11-15

基金资助

国家轻工技术与工程一流学科自主课题(LITE2018-12);国家重点研发计划(2016YFD0400504)

The application of rapid sensory profiling technique in wine aromasensory analysis

  • TIAN Xin ,
  • ZHANG Huining ,
  • QI Xinchun ,
  • XU Yan ,
  • WANG Dong ,
  • TANG Ke
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  • 1 (Key Laboratory of Industrial Biotechnology, Ministry of Education, State Key Laboratory of Food Science & Technology, Centre for Brewing Science and Enzyme Biotechnology, School of Biotechnology Jiangnan University, Wuxi 214122, China)
    2 (Chateau Rongzi Company Ltd., Linfen 041000, China)

Received date: 2018-08-26

  Online published: 2019-11-15

摘要

采用快速感官分析技术——Napping®结合Ultra Flash Profiling(UFP) 对来自中国4个产区的12款赤霞珠干红葡萄酒进行香气感官评价,采用普氏多维向量分析(procrusts multiple factor, PMFA)、Indscal模型和聚类分析3种多元统计分析对感官数据进行分析。结果表明,不同产区的葡萄酒具有明显的产区特征性并且具有相似的香气特征,其中3种多元统计分析共同认为,晋西产区和烟台产区的赤霞珠葡萄酒具有明显的产区特征性,晋西产区的葡萄酒都具有黑醋栗、红色水果和山楂的香气,烟台产区的葡萄酒则具有显著的烟熏香气特征。来自宁夏产区和新疆产区的葡萄酒之间的差异性在不同分析方法间略有差别,PMFA和聚类分析显示,二者的差异性较小,而Indscal模型则可以较好区分。此外,宁夏产区的葡萄酒具有青椒和甜香料的香气,而来自新疆产区的葡萄酒则具有更显著的烘烤、李子干和花香的香气。研究结果表明,快速感官分析技术可以准确地对葡萄酒进行感官评价。

本文引用格式

田欣 , 张会宁 , 祁新春 , 徐岩 , 王栋 , 唐柯 . 快速感官分析技术在葡萄酒香气感官分析中的应用[J]. 食品与发酵工业, 2019 , 45(21) : 215 -220 . DOI: 10.13995/j.cnki.11-1802/ts.018601

Abstract

Twelve Cabernet Sauvignon dry red wines in four regions were evaluated by rapid sensory analysis technology-Napping® and Ultra Flash Profiling (UFP). The sensory data was processed by three multi-variate statistical analysis (Procrustes multiple factor analysis, Indscal model and cluster analysis). The results showed that: wines from different regions had obviously regional and similar aroma characteristics. Three kinds of multi-variate statistical analysis revealed that the Cabernet Sauvignon wines from Jinxi and Yantai had obviously regional characteristics. The wines from Jinxi presented black currant, red fruits and hawthorn odors. The wines from Yantai had significant smoky aroma characteristic. The sensory characteristic for wines from Ningxia and Xinjiang regions exhibited slight differences by different analytical methods. Procrustes multiple factor analysis (PMFA) and cluster analysis suggested that the difference between these two was small, while the Indscal model could distinguish better. In addition, the wines from Ningxia presented the odors of green peppers and sweet spices, while the wines from Xinjiang had more prominent baking, prune and floral aroma. The results indicated that the rapid sensory analysis technology can perform well on sensory evaluation of wine samples.

参考文献

[1] 中国食品发酵工业研究院, 烟台张裕葡萄酿酒股份有限公司,中法合营王朝葡萄酿酒有限公司, 等. GB/T 15037—2006, 葡萄酒[S].中华人民共和国国家质量监督检验检疫总局;中国国家标准化管理委员会, 2006.
[2] LAWLESS H T, HEYMANN H. Sensory Evaluation of Food Principles and Practices [J]. Food Engineering & Ingredients, 2010, 98(7-8): A09.
[3] 李华, 张莉,王华, 等. 西拉干红葡萄酒香气感官特性描述语分析[J]. 食品科学, 2010,31(17): 22-24.
[4] 糜川清. “媚丽”桃红葡萄酒的特征香气成分和感官特性描述符研究[D]. 杨凌:西北农林科技大学, 2012.
[5] 唐柯, 马玥,席艳茹, 等. 黄土高原赤霞珠桃红葡萄酒感官描述符筛选研究[J]. 酿酒科技, 2017(12): 17-20;26.
[6] STONE H, SIDEL J L. Sensory Evaluation Practices[J]. Sensory Evaluation Practices, 1992: 296-304.
[7] CADOT Y, CAILLE S, SAMSON A, et al. Sensory dimension of wine typicality related to a terroir by quantitative descriptive analysis, just about right analysis and typicality assessment[J]. Anal Chim Acta, 2010, 660(1-2): 53-62.
[8] 席艳茹, 唐柯,徐岩, 等. 应用定量描述分析和气相色谱-闻香/质谱法研究黄土高原赤霞珠干红葡萄酒香气特征[J]. 食品与发酵工业, 2016, 42(5): 192-197.
[9] HUANG L, MA Y, TIAN X, et al. Chemosensory characteristics of regional Vidal icewines from China and Canada[J]. Food Chemistry, 2018.
[10] 苏晓霞, 黄序,黄一珍, 等. 快速描述性分析方法在食品感官评定中应用进展[J]. 食品科技, 2013, 34(7): 298-303.
[11] DEHLHOLM C, BROCKHOFF P B, MEINERT L, et al. Rapid descriptive sensory methods-comparison of free multiple sorting, partial napping, napping, flash profiling and conventional profiling[J]. Food Quality and Preference, 2012, 26(2): 267-277.
[12] SANTOS B A, POLLONIO M A R, CRUZ A G, et al. Ultra-flash profile and projective mapping for describing sensory attributes of prebiotic mortadellas[J]. Food Research International, 2013, 54(2): 1 705-1 711.
[13] PAGES J. Direct collection of sensory distances: application to the evaluation of ten white wines of the Loire Valley[J]. Scinces Des Aliments, 2003, 23(5-6):679-688.
[14] PERRIN L, SYMONEAUX R, MAITRE I, et al. Comparison of three sensory methods for use with the Napping® procedure: Case of ten wines from Loire valley[J]. Food Quality and Preference, 2008, 19(1): 1-11.
[15] LOUW L, MALHERBE S, NAES T, et al. Validation of two Napping® techniques as rapid sensory screening tools for high alcohol products[J]. Food Quality and Preference, 2013, 30(2): 192-201.
[16] MORAND E, PAGES J. Procrustes multiple factor analysis to analyse the overall perception of food products[J]. Food Quality & Preference, 2006, 17(1): 36-42.
[17] ABDI H, VALENTIN D. Some new and easy ways to describe, compare, and evaluate products and assessors[C]. SPISE 2007 New Trends in Sensory Evaluation of Food and Nonfood Products, 2007: 321-345.
[18] DEHLHOLM C, BROCKHOFF P B, BREDIE W L P. Confidence ellipses: A variation based on parametric bootstrapping applicable on Multiple Factor Analysis results for rapid graphical evaluation[J]. Food Quality and Preference, 2012, 26(2): 278-280.
[19] HUSSON F, LÊ S, PAGES J. Confidence ellipse for the sensory profiles obtained by principal component analysis[J]. Food Quality & Preference, 2005, 16(3): 245-250.
[20] CARROLL J D, CHANG J J. Analysis of individual differences in multidimensional scaling via an n-way generalization of "Eckart-Young" decomposition[J]. Psychometrika, 1970, 35(3): 283-319.
[21] HUSSON F. INDSCAL model: geometrical interpretation and methodology[M]. Elsevier Science Publishers B V, 2006: 358-378.
[22] NAS T, BERGET I, LILAND K H, et al. Estimating and interpreting more than two consensus components in projective mapping: INDSCAL vs. multiple factor analysis (MFA)[J]. Food Quality & Preference, 2017, 58: 45-60.
[23] RYBOWSKA A, BABICZ- ZIELINSKA E. Cluster analysis in dietary behaviour assessment of students[J]. Food Quality and Preference, 2007, 18(1): 130-132.
[24] MULLER H, HAMM U. Stability of market segmentation with cluster analysis-A methodological approach[J]. Food Quality and Preference, 2014, 34: 70-78.
[25] CARIOU V, QANNARI E M. Statistical treatment of free sorting data by means of correspondence and cluster analyses[J]. Food Quality and Preference, 2018, 68: 1-11.
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