采用电子鼻和GC-MS技术研究慕萨莱思葡萄酒中呈香物质的变化

发布时间：2018-03-10 06:51

  本文选题：慕萨莱思　切入点：香气成分　出处：《塔里木大学》2017年硕士论文　论文类型：学位论文

【摘要】：本研究以新疆阿瓦提刀郎慕萨莱思公司和新疆特色农产品深加工兵团重点实验室生产的的葡萄浓缩汁、原酒以及成品酒为研究对象,采用电子鼻技术(E-nose)和固相微萃取-气相色谱质谱联用(SPME-GC-MS)技术对葡萄浓缩汁及成品酒中的呈香物质进行检测分析。针对葡萄浓缩汁以及葡萄酒中的呈香气物质,采用主成分分析(PCA)和判别因子分析(DFA)区分评价电子鼻传感器对样品的响应值,建立预测模型。结合GC-MS检测慕萨莱思葡萄酒中主要的呈香物质,主要研究结果如下:(1)通过对葡萄酒的总糖、还原糖、酒精度、总酸以及pH值等理化指标的测定发现,葡萄酒的酒精度、总酸、总糖、还原糖、pH值的含量都在正常水平范围内,G1、G2、G3和EF-14的总糖、总酸含量均高于G4、G5、G6、G7这四种成品酒中的含量;此外,对葡萄酒的感官进行了评定,慕萨莱思葡萄酒的整体感官特征表现为:酒体颜色以棕色为主,酸甜突出、略微的苦涩味、具有浓厚的焦糖香和醇香以及宜人的水果香,香气较为丰富、典型性强。(2)对电子鼻检测条件进行了优化,结果表明:慕萨莱思葡萄酒的取样量为50μL、稀释20倍、加热时间30 min、加热温度为45℃,此时的电子鼻传感器对葡萄酒样的响应值最佳。(3)通过电子鼻技术采集实验室的葡萄浓缩汁、不同发酵过程的酒样和工厂提供的葡萄浓缩汁、原酒以及成品酒中的挥发性香气成分,建立主成分分析模型(PCA)和判别因子分析(DFA)预测模型,并采用实验室浓缩后的葡萄汁进行验证。结果表明PCA模型的区分指数DI值在80以上,说明样品能够很好的被区分;监督型DFA模型主要用来预测未知样品,结合使用PCA模型和DFA模型可以有效建立区分辨别不同种类的慕萨莱思葡萄酒以及葡萄浓缩汁;本文中建立基于电子鼻技术对慕萨莱思葡萄酒以及葡萄浓缩汁快速的区分鉴别方法是可行的。(4)对慕萨莱思葡萄酒香气成分的萃取条件进行了优化。结果表明,SPME的最佳萃取条件为:萃取温度为60℃、平衡时间20 min、萃取时间为20 min、萃取头为50/30μm DVB/CAR/PDMS、添加氯化钠的量为1 g。从葡萄原汁到不同浓缩过程共检测出挥发性香气物质160种,主要包括醇类(25种)、酯类(39种)、酸类(22种)、醛类(28种)、萜烯类(7种)、酮类(11种)、酚类(7种)、烯烃类(5种)、胺类(5种)、吡嗪类(2种)以及其他(5种)。葡萄原汁中香气物质的种类最为丰富,葡萄原汁的香气成分种类主要包括醇类(16.696 mg/L)、酚类(6.097 mg/L)、醛类(5.679 mg/L)、酮类(4.245 mg/L)、酸类(3.269 mg/L)、酯类(3.282 mg/L)、萜烯类(0.929 mg/L)等。其中醇类、酚类、醛类含量较高,这些醇类、醛类、酮类、萜烯类是构成慕萨莱思葡萄酒品种香的主要香气物质基础。(5)刀郎公司生产的慕萨莱思原酒以及成品葡萄酒香气成分的分析三个不同发酵罐的慕萨莱思原酒中共检测出138种挥发性香气物质,主要包括醇类(32种)、酯类(42种)、酸类(14种)、酮类(11种)、醛类(9种)、酚类(5种)、烯烃类(9种)、呋喃类(3种)、胺类(3种)、烷烃类(3种)、其它类(7种),其中共有物质26种。四种不同慕萨莱思葡萄酒中共检测到香气物质149种,主要包括酯类(50种)、酸类(21种)、醇类(33种)、酮类(14种)、醛类(9种),其中共有香气物质20种。利用HS-SPME结合GC-MS,并通过PCA分析鉴定出慕萨莱思酒中主要香气物质包括:苯乙醇、1-戊醇、辛酸乙酯、苯乙酸乙酯、乙酸乙酯、硬脂酸乙酯、丁二酸二乙酯、棕榈酸乙酯、辛酸、己酸、癸酸、辛酸、月桂酸、5-甲基呋喃醛、糠醛、大马士酮等。分析结果显示,不同工艺的葡萄浓缩汁及不同种类的慕萨莱思葡萄酒其挥发性成分均具有一定的差异,从而引起慕萨莱思葡萄酒之间香气的差异,该差异能够被电子鼻识别区分。GC-MS与电子鼻数据结果建立的PLS模型决定系数均大于90.0%,具有很好的相关性。采用具有“模糊评价”属性的电子鼻技术结合具有“精准检测特性”的GC-MS分析可以区分不同浓缩过程的葡萄汁、原酒以及成品酒。
[Abstract]:In this study, Xinjiang Dao Lang Awati Msalais company and Xinjiang characteristics of agricultural products deep processing Production Corps Key Laboratory of condensed grape juice, wine and wine as the research object, using electronic nose technology (E-nose) and solid phase microextraction gas chromatography mass spectrometry (SPME-GC-MS) technology on the aroma of grape concentrate juice and wine products in the detection and analysis. According to the aroma of a grape juice concentrate and Wine in, using principal component analysis (PCA) and discriminant factor analysis (DFA) to distinguish the response evaluation of electronic nose sensor values of the sample, the prediction model is established. Combined with the aroma substances of major GC-MS detection Msalais Wine. The main results are as follows: (1) the total sugar, reducing sugar of Wine, alcohol, determination of total acid and pH value of the physicochemical index, Wine alcohol, total acid, total sugar, reducing sugar, pH value The content is in a normal range, G1, G2, G3 and EF-14 of the total sugar, total acid content was higher than that of G4, G5, G6, G7 content of the four in the finished wine; in addition, the Wine sensory evaluation is carried out, the overall sensory characteristics of Msalais Wine for wine color to brown, and prominent, slightly bitter taste, strong Caramel smell and mellow and pleasant fruit aroma, rich aroma, strong typicality. (2) to examine the condition of electronic nose were optimized. The results show that the sampling volume Msalais Wine is 50 L, diluted 20 times. The heating time is 30 min, the heating temperature is 45 DEG C, response of electronic nose sensor at this time of Wine kind of best value. (3) the grape juice concentrate acquisition Laboratory of electronic nose technology, grape juice concentrate with different fermentation and wine samples provided by the factory, volatile aroma components in wine and wine, The establishment of the model of principal component analysis (PCA) and discriminant factor analysis (DFA) prediction model, and using the laboratory after concentration Grape Juice was verified. The results show that the index DI value of PCA model in more than 80 samples that can well be distinguished; the supervision model of DFA is mainly used to predict unknown samples, combined with the use of PCA model and DFA model can be used to establish the identification of different types of Wine and Msalais grape juice concentrate; this paper is based on the electronic nose technology is feasible for Msalais Wine and distinguish method of grape juice concentrate rapidly. (4) Wine extraction conditions on Aroma Components of Sa mu were optimized. LyThe the results showed that the optimum extraction conditions for SPME extraction temperature is 60 DEG C, the equilibrium time of 20 min, extraction time 20 min, extraction for 50/30 m DVB/CAR/PDMS head, adding amount of sodium chloride is 1 g. from grape 鍘熸眮鍒颁笉鍚屾祿缂╄繃绋嬪叡妫，

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