该研究分别利用电子鼻和气质联用(gas chromatography-mass spectrometry,GC-MS)分析7种不同品牌浓香型白酒的差异。结果表明,电子鼻的S2、S6、S7和S9 4个传感器对不同品牌浓香型白酒具有较好的响应信号,经主成分分析(principal component analysis,PCA)筛选后可以作为浓香型白酒差异的特征指标来衡量。基于传感器信号,比较了PCA和线性判别对不同各品牌浓香型白酒的分类效果,PCA分析能够对不同品牌白酒进行较好区分。GC-MS分析表明,不同品牌浓香型白酒风味物质含量存在明显差异,而PCA分析中关系密切的样品在风味成分层面存在相似性。该研究提供了一种基于电子鼻、GC-MS技术和数理统计分析相结合的浓香型白酒分类方法,为浓香型白酒的快速质量分类方法的开发提供了理论和数据支撑。
Baijiu is a complex system that is constitute of ethanol-water and trace amount of aroma compounds, and its quality is decided by the constitution and ratio of aroma compounds. In this study, electronic nose (e-nose) and gas chromatography-mass spectrometry (GC-MS) were used to analysis the difference in 7 brands of strong-flavor Baijiu (SFB). The results showed that the sensors including S2, S6, S7 and S9 in e-nose presented excellent response signals for different brands of SFB. Based on signals of e-nose, comparison between principal component analysis (PCA) and linear discriminant analysis was conducted. The results suggested that PCA could gave clear classification between different brand of SFB. GC-MS analysis showed that obvious discrimination was determined in different brands of SFB, and samples that clustered together in PCA plot had similar volatile profiles. This study provided a comprehensive method employing e-nose, GC-MS and statistical analysis to classify different SFB, and it also provided theoretical and data reference for the development of fast classification method for SFB.
[1] 沈怡方.白酒生产技术全书[M].北京:中国轻工业出版社, 1998.
[2] 季克良, 郭坤亮, 朱书奎, 等. 全二维气相色谱/飞行时间质谱用于白酒微量成分的分析[J]. 酿酒科技, 2007, 153(3):100-102.
[3] FAN W, QIAN M C. Characterization of aroma compounds of Chinese & quot;Wuliangye & quot; and & quot;Jiannanchun & quot; liquors by aroma extract dilution analysis.[J]. Journal of Agricultural and Food Chemistry, 2006, 54(7):2 695-2 704.
[4] FAN W L, XU Y,QIAN M C. Identification of aroma compounds in Chinese “Moutai” and “Langjiu” liquors by normal phase liquid chromatography fractionation followed by gas chromatography/olfactometry[J]. Flavor Chemistry of Wine and other Alcoholic Beverages,2012:303-338.
[5] 王俊, 胡桂仙, 于勇, 等. 电子鼻与电子舌在食品检测中的应用研究进展[J]. 农业工程学报, 2004, 20(2):292-295.
[6] 徐赛, 陆华忠, 周志艳, 等. 电子鼻对荔枝成熟过程中理化参数的表征[J]. 食品工业科技, 2016, 37(8):100-103;115.
[7] 赵秀洁, 吴海伦, 潘磊庆, 等. 基于电子鼻技术预测草莓采后品质[J]. 食品科学, 2014, 35(18):105-109.
[8] 李宁, 郑福平, 李强, 等. 电子鼻对牛奶、奶油、奶味香精检测参数的研究[J]. 食品科学, 2009, 30(18):335-339.
[9] 陈哲, 赵杰文. 基于电子鼻技术的碧螺春茶叶品质等级检测研究[J]. 农机化研究, 2012, 34(11):133-137.
[10] CYNKAR W, DAMBERGS R, SMITH P, et al. Classification of Tempranillo wines according to geographic origin: Combination of mass spectrometry based electronic nose and chemometrics[J]. Analytica Chimica Acta, 2010, 660(1-2):227-231.
[11] 李静, 宋飞虎, 浦宏杰,等. 基于电子鼻的白酒品质检测[J]. 食品与发酵工业, 2015, 41(4):160-164.
[12] 王立川, 张覃轶, 黄伟. 基于气体传感器阵列的白酒特征分析[J]. 传感技术学报, 2010, 23(12):1 686-1 689.
[13] 李静, 宋飞虎, 浦宏杰, 等. 基于电子鼻的白酒品质检测[J]. 食品与发酵工业, 2015, 41(4):160-164.
[14] ZHANG Q, XIE C, ZHANG S, et al. Identification and pattern recognition analysis of Chinese liquors by doped nano ZnO gas sensor array[J]. Sensors and Actuators B (Chemical), 2005, 110(2):370-376.
[15] 张明霞, 赵旭娜, 杨天佑, 等. 顶空固相微萃取分析白酒香气物质的条件优化[J]. 食品科学, 2011, 32(12):49-53.
[16] 范文来, 徐岩. 白酒风味物质研究方法的回顾与展望[J]. 食品安全质量检测学报, 2014(10):3 073-3 078.
[17] LIU M, HAN X, TU K, et al. Application of electronic nose in Chinese spirits quality control and flavour assessment[J]. Food Control, 2012, 26(2):564-570.
[18] 赵东, 郑佳, 彭志云, 等. 利用顶空固相微萃取、液液萃取和香气分馏技术鉴定糠壳的挥发性成分[J]. 酿酒科技, 2016(12):31-39.
[19] ZHENG J, LIANG R, WU C, et al. Discrimination of different kinds of Luzhou-flavor raw liquors based on their volatile features[J]. Food Research International, 2014, 56:77-84.
[20] MORENO-GARCIA J, RAPOSO R M, MORENO J. Biological aging status characterization of Sherry type wines using statistical and oenological criteria[J]. Food Research International, 2013, 54(1):285-292.
