Changes of Wine Flavor Properties from the Decreased Higher Alcohols Induced by Ultrasound Irradiation
ZHANG QingAn,1,2, XU BoWen1, CHEN BoYu1, ZHANG BaoShan1, CHENG Shuang2责任编辑: 赵伶俐
收稿日期:2020-08-14接受日期:2021-01-25网络出版日期:2021-04-16
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Received:2020-08-14Accepted:2021-01-25Online:2021-04-16
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张清安,Tel:13572932273;E-mail:
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张清安, 徐博文, 陈博宇, 张宝善, 程爽. 超声降低红酒中高级醇含量对酒体风味特性的影响[J]. 中国农业科学, 2021, 54(8): 1772-1786 doi:10.3864/j.issn.0578-1752.2021.08.016
ZHANG QingAn, XU BoWen, CHEN BoYu, ZHANG BaoShan, CHENG Shuang.
开放科学(资源服务)标识码(OSID):
0 引言
【研究意义】近年来,超声技术在酒类酿造和陈熟应用研究中得到了广泛关注,尤其在葡萄酒酿造中,超声波不仅可用于葡萄汁的提取、发酵过程,还可用于杀菌和陈熟等工序。适度超声处理不仅可以提升葡萄酒的产出率、缩短发酵时间[1,2,3],而且还可以改善酒的颜色、口感等品质[4,5]。一般来说,葡萄酒的口感品质除了与酒中单宁、花色苷等物质相关外,还与酒中高级醇(杂醇油)的含量有密切关系。研究显示适度超声处理可以显著降低红葡萄酒中高级醇的含量[6],从而改善酒的口感品质;但其降低高级醇的机制及产物是否会影响葡萄酒的香气风味等尚不明确,这对于该技术能否用于降低酒中高级醇起着至关重要的作用。【前人研究进展】酒中的高级醇含量与酒的感官品质密切相关;白葡萄酒中高级醇的含量在0.2— 1.2 g?L-1,红葡萄酒中为0.4—1.4 g?L-1[7]。一般来说,当酒中高级醇总浓度低于0.3 g?L-1时,高级醇对葡萄酒的芳香形态有积极贡献,可以增加酒体的果香和花香以及香气的复杂度;当高于0.4 g?L-1时,会产生刺激性和使人头疼、恶心、呕吐等不愉快的感受[8]。因此,如果酒中杂醇油含量过高就有必要进行调控,目前常用的方法就是通过调节发酵过程中影响高级醇形成的因素进而降低高级醇的含量[9,10,11,12]。超声波作为一种物理催熟红酒技术,近几年研究报道相对较多,其可能机制是通过超声空化效应所产生的局部瞬时高温、高压,诱发葡萄酒中相关化学成分进行分子裂解而产生自由基,进而引发一系列链式化学反应,加快单宁、花色苷等物质的氧化、缩合反应,最终改善酒的口感、促进酒体呈色和缩短陈酿时间[4-5,13-15]。而对于超声波处理降低酒中高级醇含量的研究报道较少,向英等[16]研究表明,低频超声处理可以降低白酒中高级醇含量,增加酯类含量,缩短酒的陈酿期和加速酒的熟化;笔者课题组前期研究表明,适度超声处理可以将葡萄酒中高级醇的含量降低40.44%[6];闫春明[17]研究了超声波和大孔树脂降低黄酒中高级醇的方法,结果表明超声处理可以将高级醇含量降低22.3%。相比较而言,通过改变发酵条件进行生物调控降低高级醇含量的研究报道较多[18],而且这些研究主要从酵母代谢方面入手调控高级醇的形成[19,20,21,22],其机理也相对清晰。作为一种新型食品物理加工手段,超声波已广泛应用于食品加工的各个领域[23,24]。【本研究切入点】笔者课题组前期研究表明,适度超声处理可以显著降低红葡萄酒中高级醇的含量,但高级醇的最终去向以及其降低对酒体风味带来什么影响,这些问题仍然不清楚。【拟解决的关键问题】采用电子鼻、电子舌与气质联用技术分析超声处理降低高级醇并对红葡萄酒风味品质的影响,通过建立模型酒液体系探究风味变化的具体机制,为应用超声调控高级醇含量并改善红酒感官品质提供理论依据。1 材料与方法
试验于2019年3—10月在陕西师范大学食品工程与营养科学学院进行。1.1 材料与仪器
1.1.1 材料与试剂 干红葡萄酒,购自陕西三贤酒庄(2015年12月产赤霞珠干红葡萄酒),酒精含量12%;正丙醇、异戊醇、正戊醇、异丁醇、无水乙醇均为色谱纯(天津市科密欧化学试剂有限公司);试验所用水为纯净水,购于陕西娃哈哈乳品有限公司。1.1.2 主要仪器设备 槽式超声波多频清洗机(SB- 500DTY),宁波新芝生物科技股份有限公司;电子鼻(Supernose),美国Isenso Group Corporation公司;电子舌(Smartongue),美国Isenso Group Corporation公司;75 μm PDMS萃取头、SPME顶空进样器、HP-INNOWax石英毛细管色谱柱(60 m×0.32 mm×0.25 μm)、气相色谱质谱联用仪(7890B-7000C),安捷伦科技有限公司;色谱柱温箱(ZW230Ⅱ型),大连伊利特分析仪器有限公司;色谱高压恒流泵(P230Ⅱ型),大连伊利特分析仪器有限公司;TC-C18反相液相色谱柱(250 mm×4.6 mm,5 μm),安捷伦科技有限公司。
1.2 方法
1.2.1 样品超声处理过程 试验在槽式超声波多频清洗机(SB-500DTY)中进行,将每组处理样品20 mL分别放置于30 mL螺纹棕色样品瓶中(27.5 mm×72 mm),拧紧瓶盖将样品瓶固定在超声清洗槽内特定位置,控制槽内水面高度相同,每组处理3次重复。超声频率单因素试验:分别以频率为25、40和59 kHz为变量,研究超声温度30℃,功率300 W和超声时间30 min处理条件下酒体风味的变化;超声功率单因素试验:选取功率依次为150、200、300、400和450 W时,研究30℃、40 kHz和30 min处理条件下酒体风味的变化;超声波时间单因素试验:选取超声时间为10、20、30、40和50 min,研究在30℃、40 kHz和300 W处理条件下酒体风味的变化;超声温度单因素试验:选取温度依次为20、25、30、35、40和45℃,研究在300 W、40 kHz和30 min处理条件下酒体风味的变化。这些超声参数处理对酒中高级醇的含量均有一定的降低作用[6]。
采用前期所优化的降低高级醇的超声参数(40 kHz、30 min、150 W和30℃)对酒体进行处理并用GC-MS测定其挥发性成分的变化[6]。
1.2.2 模型酒液的制备 为进一步探究超声降低高级醇时对酒体挥发性物质的影响原因,根据文献[25]制备12%(v/v)的乙醇溶液、4 mol?L-1的氢氧化钠溶液和0.5%(v/v)的硫酸溶液;通过溶解2.502 g七水硫酸亚铁制备500 mL亚铁储备溶液,并用氢氧化钠(4 mol?L-1)或0.5%(v/v)的硫酸溶液调整pH为3.4±0.1。向上述储备液中加入1 mL正丙醇、1 mL异丁醇、1 mL异戊醇和1 mL正戊醇制备成模型酒液体系5 L,即为待测液体系[26]。
参考文献[6]中超声参数,对模型酒液体系进行超声处理并测定其挥发性成分的变化。
1.2.3 电子鼻的检测方法 用电子鼻测定不同超声处理红酒样品的相关风味指标值。电子鼻采样前,量取20 mL样品放置于50 mL离心管中并密封,用电子鼻对其顶空气体进行测定。电子鼻采样参数设置如表1所示,每个样品平行测定3次。随后提取电子鼻各传感器特征值,利用设备自带软件对数据进行主成分分析(principal component analysis,PCA)和判别函数分析(discriminant functions analysis,DFA)。电子鼻是由具选择性的14个传感器阵列、信号采集电路和基于模式识别的数据处理方法组成的现代化定性定量分析检测仪器,主要机理是利用各个气敏传感器对复杂成分气体具有不同响应,借助数据处理方法对多种气味进行识别,最终对气味特性进行分析与评定,各传感器的名称和性能描述如表2所示。
Table 1
表1
表1电子鼻试验设定参数
Table 1
分析参数 Parameter | 参考值 Reference value |
---|---|
载气流量 Carrier gas flow rate | 0.6 L?min-1 |
传感器清洗时间 Sensors cleaning time | 60 s |
气体进样流量 Gas flow rate | 0.6 L?min-1 |
获取时间 Acquisition time | 120 s |
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Table 2
表2
表2电子鼻性能描述
Table 2
传感器名称 Sensor name | 性能描述 Performance description |
---|---|
S1 | 氨气、胺类 Ammonia, amines |
S2 | 硫化氢、硫化物 Hydrogen sulfide, sulfide |
S3 | 氢气 Hydrogen |
S4 | 酒精、有机溶剂 Alcohol, organic solvent |
S5 | 醇类、酮类、醛类、芳香族化合物 Alcohols, ketones, aldehydes, aromatic compounds |
S6 | 甲烷、沼气、天然气 Methane, marsh gas, natural gas |
S7 | 可燃性气体 Combustible gas |
S8 | 挥发性有机物 Volatile organic compounds |
S9 | 液化气、天然气、煤气 Liquefied gas, natural gas, gas |
S10 | 液化气、可燃气体 Liquefied gas, combustible gas |
S11 | 烷烃、酒精、天然气、烟雾 Alkane, alcohol, natural gas, smoke |
S12 | 酒精、有机溶剂 Alcohol, organic solvent |
S13 | 烟气、烹调臭味 Smoke, cooking odor |
S14 | 甲烷、燃气 Methane, gas |
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1.2.4 电子舌检测方法 分别将不同超声处理的红酒样品(每个样品20 mL)放置于电子舌仪器专用测量杯内进行分析测定。电子舌采样参数设置为:仪器选取6个传感器,采样时间和传感器自动清洗时间共计4 min,分别提取各传感器的特征值进行分析,每个样品用电子舌平行测定3次。
1.2.5 样品中挥发性成分的GC-MS测定 取5.0 mL待测样品于20 mL样品瓶中并密封,将样品瓶置于70℃加热器中平衡40 min后,将经老化的萃取头(HS-SPME)插入密封的样品瓶中(美国Supelco公司),70℃孵化30 min,顶空萃取40 min,然后在气相色谱进样口230℃解析3 min,采用GC-MS分析其挥发性成分。GC条件:HP-INNOWax石英毛细管色谱柱(60 m×0.32 mm×0.25 μm,安捷伦科技中国有限公司);起始温度40℃,保留时间2.5 min,以5℃?min-1升至240℃,再以10℃?min-1升至250℃并保留7.5 min;不分流进样,载气为He,流速为1 mL?min-1。MS条件:电离方式EI,电子能量70 eV,离子源温度250℃,进样口温度230℃,连接杆温度230℃,质量范围m/z 35—400 amu;化合物经计算机检索同时与NIST2011数据库进行匹配,仅报道匹配数大于500(最大值为1 000)的化合物,采用峰面积归一化法定量计算各挥发性成分的相对含量[27,28]。
1.3 数据处理
使用Origin 2017软件对相关数据绘制图表,SPSS19.0软件进行单因素方差分析及差异显著性分析(邓肯氏多项式比较),P<0.05表示差异显著。2 结果
2.1 不同超声处理对红酒样品风味影响的电子鼻测定结果
采用电子鼻嗅觉评价方法对不同超声条件(频率、功率、时间、温度)处理后红酒样品的挥发性风味进行分析。从图1中可知,第一主成分(PC1)的贡献率为60.94%,第二主成分(PC2)的贡献率为28.32%,PCA主成分的累积贡献量为89.26%,说明其保留了原始数据中大部分的信息量。DFA分析结果显示DI=-21.66,该值为负值说明样品之间具有重叠性,即不同超声条件处理对红酒的挥发性风味品质影响不显著。图1
新窗口打开|下载原图ZIP|生成PPT图1电子鼻测定不同超声处理红酒样品风味变化的PCA(a)及DFA(b)图
Fig. 1Results of PCA (a) and DFA (b) by electronic nose for wine samples treated with different ultrasound conditions
相比于传感器的变化数据,雷达图数据可以更加直观地反映传感器响应值的差异情况。如图2所示,S8传感器对红酒样品的气味响应值最大,其次为S1、S2、S12、S13、S10和S5。响应值的大小可以反映传感器对红酒中相关气味的区别能力,也可作为风味变化的理论依据[29,30]。
图2
新窗口打开|下载原图ZIP|生成PPT图2不同超声处理条件下红酒样品电子鼻测定响应值的雷达图
Fig. 2Radar images of response value by electronic nose for wine samples treated with different ultrasound conditions
从雷达图中可以发现,改变超声条件后传感器响应值的变化均不显著,这与PCA和DFA所得结果基本一致。同时,鉴于这些超声参数在处理红酒时对高级醇含量有明确的降低作用[31],因此从电子鼻对气味物质的判别来说,所用的超声参数在降低红酒中高级醇时,并未影响到酒的其他相关风味。其原因一方面可能与所选择的超声条件有关,另一方面也可能与电子鼻上传感器所能响应的物质类别有关。
将不同超声处理的红酒样品归为一类建立PCA模型,而未超声处理的红酒样品重复进行3次判别分析。由图3软独立建模聚类分析图与表3结果可知,未经超声处理的红酒样品符合用超声处理过的红酒所建立的模型,即红酒样品经不同超声条件处理后,其嗅觉指标(电子鼻传感器响应值)与未处理红酒样品无显著差异,说明在选定的超声波条件下处理红酒,对其挥发性风味品质的影响较小,用电子鼻也难以鉴别出显著差异。
图3
新窗口打开|下载原图ZIP|生成PPT图3电子鼻对未处理红酒样品判别的SIMCA分析图
Fig. 3Electronic nose identification based on SIMCA for red wine without ultrasound irradiation
Table 3
表3
表3电子鼻和电子舌对未处理红酒样品判别的PCA分析表
Table 3
样品名称 Sample name | 电子鼻结果 Result of electronic nose | 电子舌结果 Result of electronic tongue |
---|---|---|
00-1 | 是 Yes | 是 Yes |
00-2 | 是 Yes | 是 Yes |
00-3 | 是 Yes | 否 No |
00-1、00-2和00-3分别为未处理红酒样品的3个平行测定 00-1, 00-2 and 00-3 represent the three replicates |
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2.2 不同超声处理对红酒样品感官影响的电子舌测定结果
图4为采用电子舌方法评价不同超声处理红酒样品的PCA与DFA的分析结果。由图可知,第一主成分(PC1)的贡献率为27.38%,第二主成分(PC2)的贡献率为20.22%,PCA主成分累积贡献量为47.60%,DI=-80.96,其保留信息量较低。DFA分析显示DI=99.99,说明样品之间具有差异性,不同超声条件处理对红酒的口感品质具有一定的影响。这与电子鼻测定结果有所差异,一方面可能是两种仪器设备测定物质的原理和种类不一样,前者偏向于易挥发性物质;另一方面也说明随着高级醇的降低,确实也对酒体的口感带来了一定影响。图4
新窗口打开|下载原图ZIP|生成PPT图4电子舌测定不同超声处理红酒样品的PCA(a)和DFA(b)图
Fig. 4Results of PCA (a) and DFA (b) by electronic tongue for wine samples with different ultrasound conditions
为进一步判别超声处理对红酒感官品质的影响,将超声处理过的红酒样品进行DFA和PCA建模处理,并与未超声处理的样品进行对比。由图5与表3可知,与未经超声处理红酒样品相比,00-3样品不符合所建模型,说明经不同超声条件处理后部分红酒样品的口感品质确实受到了一定程度的影响;但也存在未处理红酒样品落在G1、G3和G7区域内的情况,说明仍有部分红酒样品在超声降低高级醇的同时并未对其口感品质带来显著影响。
图5
新窗口打开|下载原图ZIP|生成PPT图5电子舌对未处理红酒样品判别的DFA分析(a)和SIMCA分析图(b)
Fig. 5Electronic tongue identification by DFA (a) and SIMCA (b) for red wine without ultrasound irradiation
整体而言,从电子鼻和电子舌分析测定结果可以看出,用选定的超声条件降低酒中高级醇时,对酒体口感及挥发性风味有一定影响,但不显著。
2.3 超声处理降低红酒中高级醇时对酒中挥发性成分的影响
由表4和图6可知,在未处理红酒样品中定性鉴定出41种挥发性成分,酸类、酯类物质种类较多,其中酸类有7种、酯类17种、醇类3种、酮类4种、醛类4种、烷类2种、含硫化合物1种、其他物质3种,其所占比重分别30.04%、33.02%、22.37%、1.61%、2.54%、1.05%、8.48%和0.14%,酸类、酯类、醇类物质所占百分含量较大。酸类物质中L-乳酸含量最高,其次是辛酸;酯类物质中2-羟基丙酸乙酯含量最高,其次是丁二酸二乙酯;醇类物质中β-苯乙醇含量最高;醛类物质中苯甲醛含量最高;酮类物质中3-羟基-2-丁酮含量最高;烷类物质中二甲基-2-辛烷-环丁烷含量最高;含硫化合物中主要检测到3-巯基-L-缬氨酸。Table 4
表4
表4超声处理前后红酒中香气物质的变化
Table 4
类别 Variety | 化合物 Compound | 相对百分含量Relative content (%) | |
---|---|---|---|
处理前Before | 处理后After | ||
酸类 Acids | L-乳酸 L-Lactic acid | 26.18 | 18.47 |
胞壁酸 Parietal acid | 0.24 | 0.25 | |
正癸酸 Decanoic acid | 0.76 | 0.82 | |
己酸 Caproic acid | 0.51 | - | |
二十二碳六烯酸 Docosahexaenoic acid | 0.04 | - | |
辛酸 Caprylic acid | 2.10 | - | |
壬酸 Nonylic acid | 0.21 | 0.26 | |
癸醛 Decyl aldehyde | - | 0.28 | |
油酸 Oleic acid | - | 0.19 | |
4-氨基-1,5-戊二酸 4-amino-1,5-glutaric acid | - | 0.22 | |
酯类 Esters | 2-羟基丙酸乙酯 Ethyl 2-hydroxypropionate | 17.57 | 28.25 |
乳酸异戊酯 Isoamyl lactate | 0.48 | 0.17 | |
己酸乙酯 Ethyl hexanoate | 1.76 | 1.23 | |
丁二酸二乙酯 Diethyl succinate | 7.26 | 8.37 | |
辛酸乙酯 Ethyl caprylate | 2.32 | 1.82 | |
异胆酸乙酯 Ethyl isocholate | 0.55 | 1.23 | |
十六烷酸乙酯 Ethyl hexadecane | 1.18 | 1.35 | |
十八酸乙酯 Ethyl octadecanoate | 0.48 | 0.31 | |
7-甲基-Z-四癸烯-1-醇乙酸酯 7-methyl-z-tetradecene-1-ol acetate | 0.25 | 0.61 | |
1,2-苯二甲酸正辛酯 1,2-noctyl-phthalate | 0.11 | 0.23 | |
癸酸乙酯 Ethyl decanoate | 0.21 | 0.25 | |
丁二酸3-甲基丁基酯 Succinic acid 3-methyl butyl ester | 0.37 | 0.37 | |
Z-(13,14-环氧)四聚-11-烯-1-醇乙酸酯 Z-(13,14-epoxy) tetra-11-ene-1-ol acetate | 0.12 | 0.27 | |
2-苯基-戊酸乙酯 Ethyl 2-phenyl-valerate | 0.13 | - | |
11,13-二甲基-12-十四烯-1-醇乙酸酯 11,13-dimethyl-12-tetradecene-1-ol acetate | 0.05 | - | |
1-甲基乙酸盐(酯) 1-methyl acetate (ester) | 0.08 | - | |
1,2-苯二甲酸,双(2-甲基丙基)酯 1,2-phthalic acid, bis (2-methylpropyl) ester | 0.08 | - | |
9-十八烯酸(2-苯基-1,3-二氧戊环-4-基)甲酯 9-octadecaenoic acid (2-phenyl-1,3-dioxopenyl-4-yl) methyl ester | - | 0.03 | |
壬酸乙酯Ethyl nonanoate | - | 0.05 | |
十四烷酸乙酯 Ethyl Myristate | - | 0.12 | |
邻苯二甲酸正丁酯 N-butyl phthalate | - | 0.12 | |
邻苯二甲酸二正辛酯 Di-n-octyl phthalate | - | 0.06 | |
1-丁醇,3-甲基乙酸酯 1-butanol, 3-methylacetate | - | 0.07 | |
醇类 Alcohols | 1-庚三醇 1-heptanol | 0.21 | 0.21 |
β-苯乙醇 β-phenylethanol | 21.81 | 19.73 | |
2,3-丁二醇 2,3- butane diol | 0.36 | - | |
3-甲基-2-己醇 3-methyl-2-hexanol | - | 0.09 | |
类别 Variety | 化合物 Compound | 相对百分含量Relative content (%) | |
处理前Before | 处理后After | ||
酮类 Ketones | 1-(2-羧基-4,4-二甲基环丁烯基)-1-丁烯-3-酮 1-(2-carboxyl-4,4-dimethylcyclobutanenol)-1-butene-3-one | 0.16 | 0.05 |
2,4,5,6,7,7a-六氢-3-(1-甲基乙基)-7a-甲基,1H-2-茚酮 2,4,5,6,7,7a-hexahydro-3-(1-methylethyl)-7a-methyl, 1h-2-indenone | 0.98 | 0.59 | |
4-(5,5-二甲基-1-氧螺环[2.5]辛-4-基)-3-丁烯-2-酮 4-(5,5-dimethyl-1-oxyspiro [2.5] oct-4-yl)-3-butene-2-one | 0.33 | - | |
1-(2,6,6-三甲基-1-环己烯-1-基)-1-戊烯-3-酮 1-(2,6,6-trimethyl-1-cyclohexene-1-yl)-1-pentene-3-one | 0.13 | - | |
1,8-二甲基-8,9-环氧-4-异丙基-螺环[4.5]癸-7-酮 1,8-dimethyl-8,9-epoxy-4-isopropyl-spiro [4.5] decyl-7-one | - | 0.13 | |
醛类 Aldehyde | 苯甲醛 Benzaldehyde | 1.84 | 1.87 |
2,5-二甲基苯甲醛 2,5-dimethylbenzaldehyde | 0.27 | 0.37 | |
3-(2,6,6-三甲基-1-环己烯-1-基)-2-丙烯醛 3-(2,6,6-trimethyl-1-cyclohexene-1-yl)-2-acrolein | 0.36 | 0.32 | |
2-[4-甲基-6-(2,6,6-三甲基环己-1-烯基)六-1,3,5-三烯基]环己-1-烯-1-甲醛 2-[4-methyl-6-(2,6,6-trimethylcyclohex-1-enyl) hexa-1,3,5-trienyl]cyclohex-1-ene-1-formaldehyde | 0.08 | 0.04 | |
烷类 Alkanes | 3-乙基-5-(2-乙基丁基)-十八烷 3-ethyl-5-(2-ethyl butyl)-octadecane | 0.38 | 0.79 |
二甲基-2-辛烷-环丁烷 Dimethyl-2-octane-cyclobutane | 0.67 | 0.40 | |
十七烷 Heptadecane | - | 0.18 | |
二十一烷 Decane | - | 0.19 | |
酚类 Phenols | 3,5-双(1,1-二甲基乙基)-苯酚 3,5-bis (1,1-dimethylethyl)-phenol | - | 0.16 |
含硫化合物 Sulfur compounds | 3-巯基-L-缬氨酸 3-mercapto-l-valine | 8.48 | 8.48 |
叔十六烷硫醇 Tertiary cetane mercaptan | - | 0.04 | |
其他类 Others | 十二烯基丁二酸酐 2-dodecenylsuccinic anhydride | 0.03 | 0.05 |
苄基-N-(1-苄基-2-羟乙基)-N-甲基氨基甲酸酯 Benzyl-n-(1-benzyl-2-hydroxyethyl)-N-methylcarbamate | 0.04 | - | |
2,5,8-三甲基-1,2-二氢萘 2,5,8-trimethyl-1,2-dihydronaphthalene | 0.07 | - | |
2-2-肉豆醇酰基,泛酰巯基乙胺 2-2-crotonoyl, pan acyl Mercaptoethylamine | - | 0.03 | |
1-甲基-3-(1-甲基乙基)-苯 1-methyl-3-(1-methylethyl)-benzene | - | 0.03 | |
4-苄氧基-6-羟基甲基-四氢吡喃-2,3,5-三醇 4-benzyloxy-6-hydroxymethyl-tetrahydropyran-2,3,5-triol | - | 0.05 | |
4-烯丙基-2-甲氧基苯基乙酸盐 4-allyl-2-methoxyphenyl acetate | - | 0.05 | |
1,2-二氢-2,5,8-三甲基萘 1,2-dihydro-2,5,8-trimethylnaphthalene | - | 0.07 | |
2,6-二十六酸,L-(+)-抗坏血酸 2,6-hexanoic acid, L-(+)-ascorbic acid | - | 0.08 | |
(1-羟基-4-氧代-1-苯基对羟基喹啉-3-基)氨基甲酸苄酯 N-Benzyln-(1-hydroxy-4-oxo-1-phenylp-hydroxyquinoline-3-yl) carbamate | - | 0.15 |
新窗口打开|下载CSV
图6
新窗口打开|下载原图ZIP|生成PPT图6超声处理前后红酒样品中挥发性物质的总离子流图
Fig. 6Total ion chromatograms of the volatile components in the wine samples before and after ultrasound irradiation
超声处理后红酒样品中定性鉴定出51种挥发性成分,同样是酸类、酯类物质种类较多,其中酸类有7种、酯类19种、醇类3种、酮类3种、醛类4种、烷类4种、酚类1种、含硫化合物2种、其他物质8种,其所占比重分别为20.49%、44.91%、20.03%、0.77%、2.60%、1.56%、0.16%、8.52%、0.52%;酸类、酯类和醇类物质所占相对百分含量较大。酸类物质中L-乳酸含量最高,其次是辛酸;酯类物质中2-羟基丙酸乙酯含量最高,其次是丁二酸二乙酯;醇类物质中β-苯乙醇含量最高;醛类物质中苯甲醛含量最高;酮类物质中3-羟基-2-丁酮含量最高;烷类物质中3-乙基-5-(2-乙基丁基)-十八烷含量最高;含硫化合物中主要检测到3-巯基-L-缬氨酸。
一般来说,葡萄酒中挥发性物质都有其特有的风味,这些不同风味组合在一起就构成了葡萄酒特有的风味感官品质。如酸类物质中己酸有类似甜味,辛酸有脂肪味、酸干酪味,壬酸有坚果味;酯类中乳酸异戊酯有类似梨、香蕉的果香味,是葡萄酒酿造过程中乳酸发酵的产物;丁二酸二乙酯有微弱的、令人愉快的风味;己酸乙酯有类似菠萝、香蕉的果香;辛酸乙酯有香皂味、蜡烛味;癸酸乙酯和十六烷酸乙酯有油脂味、果香、花香味;脂肪酸乙酯是酵母菌在发酵过程中由脂肪酸合成或降解过程中形成的酰基辅酶A与乙醇分解而成。醇类是由氨基酸、碳水化合物和脂类等物质的降解形成[32,33],其中β-苯乙醇有花香、木香味;杂醇油作为酵母代谢的副产物主要有异丁醇、异戊醇等,这些化合物来源于酵母作用下的葡萄糖合成代谢或氨基酸(缬氨酸、亮氨酸、异亮氨酸和苯丙氨酸)的分解代谢[9-12,19,34];醛类中苯甲醛有杏仁味、樱桃味、开心果风味。这些挥发性成分对红酒的酒体风味形成都有一定影响,因此,有必要探究超声波在降低高级醇的过程中对这些挥发性风味物质的影响。
根据图7可以看出,经超声处理后红酒中酸类、醇类、酮类物质的含量比未处理样品有所降低,其中酸类下降9.55%、醇类下降2.34%、酮类下降0.84%;酯类物质含量增加11.89%。酯类物质是酒的主体香气物质,其含量显著增加,说明超声波处理降低高级醇时还可加快酒的酯化反应,提升酒的香气;醇类与酮类物质的降低也表明超声处理加速了葡萄酒内部醇-醛-酸-酯之间的转化,最终使葡萄酒的香气风味得到改善。虽然用电子鼻和电子舌进行定性鉴定的结果表明,经超声处理后的红酒样品与未处理样品差异不显著,但经气相色谱质谱联用仪测定后却发现酸类、醇类、酮类物质显著下降,而酯类显著升高;这可能与仪器的测定原理和测定物质种类差异有关。总之,虽然经过超声后酒样总体感官风味差异不大,但部分风味物质(尤其酯类物质)含量还是发生了显著变化。
图7
新窗口打开|下载原图ZIP|生成PPT图7超声处理对红酒中挥发性物质的影响
Fig. 7Effects of ultrasound irradiation on the volatile components of red wine
2.4 超声处理降低高级醇时对模型酒中挥发性成分的影响
由表5和图8可知,未处理模型酒样中定性鉴定到34种挥发性成分,酯类、醇类、烷类物质的种类较多,其中酯类物质有14种、醇类8种、烷类6种、醛类2种、苯类2种、其他物质2种;其相对含量占比分别为:酯类物质54.09%、醇类31.22%、烷类8.17%、醛类3.78%、苯类2.08%、其他物质0.89%;酯类、醇类占比较大。酯类物质中2-甲基丁酸戊酯含量较高,其次是丁酸-3-甲基丁酯;醇类物质中3-甲基-苯甲酸-丁醇、3-甲基-甲酸-丁醇含量较高。Table 5
表5
表5超声处理前后模型酒中挥发性物质的变化
Table 5
种类 Type | 化合物 Compound | 相对百分含量Relative content (%) | |
---|---|---|---|
处理前 Before | 处理后After | ||
酯类 Esters | 己酸乙酯 Ethyl hexanoate | 1.26 | 0.83 |
丁酸-3-甲基丁酯 Butyrate-3-methyl-butyl | 4.45 | 3.26 | |
甲酸辛酯 Octyl formate | 1.79 | 0.93 | |
2-甲基丁酸戊酯 Amyl 2-methyl butyrate | 26.06 | 12.66 | |
3-戊酸-甲基丁酯 3-methyl-butyl valerate | 3.17 | 0.83 | |
1-甲基乙酸丁酯 1-Buty-methylacetate | 2.24 | 1.13 | |
3-甲基己基丁酸酯 3-methylhexylbutyrate | 1.32 | 0.99 | |
己酸异戊酯 Isopentyl hexanoate | 7.83 | 4.69 | |
己酸-2-甲基丁酯 2-methyl-butyl hexanoate | 0.93 | 0.60 | |
壬酸乙酯 Ethyl nonanoate | 1.02 | 0.76 | |
庚酸-3-甲基丁酯 3-methyl-butyl heptanate | 1.00 | 0.75 | |
辛酸-3-甲基丁酯 Octanoic acid-3-methyl butyl ester | 1.33 | 1.30 | |
丙二酸二乙酯 Diethyl malonate | 0.92 | 0.38 | |
2-甲基-3-甲基丙酸丁酯 2-methyl-3-methyl-butyl propionate | 0.78 | 0.61 | |
戊酸戊酯 Amyl valerate | - | 1.08 | |
辛酸乙酯 Ethyl caproate | - | 2.57 | |
十五烷酸-3-甲基丁酯 Pentadecanoic acid-3-methyl butyl ester | - | 4.40 | |
月桂酸异戊酯 Isoamyl Laurate | - | 12.57 | |
十六酸乙酯 Ethyl palmitate | - | 1.58 | |
3-甲基丁酸丁酯 3-methyl-butyl butyrate | - | 0.37 | |
辛酸乙酯 Ethyl caproate | - | 1.74 | |
癸酸乙酯 Ethyl decanoate | - | 0.37 | |
己酸-2-乙氧基乙酯 2-ethoxyethyl hexanoate | - | 1.01 | |
壬酸-3-甲基丁酯 3-methyl-n-butyl nonanoate | - | 0.88 | |
甲酸-2-甲基丁酯 Formic acid-2-methyl butyl ester | - | 1.22 | |
醛类 Aldehyde | 3-甲基丁醛 3-Methylbutyraldehyde | 0.70 | 0.83 |
苯甲醛 Benzaldehyde | - | 0.71 | |
2,4-二甲基苯甲醛 2,4-dimethylbenzaldehyde | 3.08 | - | |
醇类 Alcohols | 苯乙醇 Phenylethanol | 0.75 | 1.01 |
1-壬醇 1-Nonanol | 2.87 | 4.30 | |
1-癸醇 1-Decanol | 1.35 | 1.61 | |
3-甲基-苯甲酸-丁醇 3-Methyl-benzoic acid-butanol | 15.92 | 17.25 | |
5-甲基-2-(1-甲基乙基)-1-己醇 5-methyl-2-(1-methylethyl)-1-hexanol | - | 1.07 | |
3-甲基-甲酸-丁醇 3-methyl-formic acid-butanol | 6.28 | - | |
3-乙酸-甲基-1-丁醇 3-Acetic acid-methyl-1-butanol | 1.82 | - | |
2-丁基-辛醇 2-butyl-octanol | 0.65 | - | |
2,2,4,4-四甲基-3-(四氢呋喃基) 3-戊醇 2,2,4,4-tetramethyl-3-(tetrahydrofuran group) 3-pentanol | 1.58 | - | |
烷类 Alkanes | 戊烷 Pentane | 2.54 | 4.20 |
十二甲基-环己烷 Dodecyl cyclohexane | 1.06 | 2.12 | |
十四甲基-环庚烷 Tetramethyl cycloheptane | 2.15 | 3.21 | |
十四烷 Tetradecane | 1.04 | - | |
十六烷 Cetane | 0.84 | - | |
十七烷 Heptadecane | 0.54 | - | |
苯类 Benzene | 1,2,4-三甲基-苯 1,2,4-trimethyl-benzene | 1.69 | 2.49 |
1,2,3,5-四甲基-苯 1,2,3,5-tetramethyl-benzene | 0.39 | - | |
酚类 Phenols | 2,4-二(1,1-二甲基乙基)-苯酚 2,4-bis (1,1-dimethylethyl)-phenol | - | 3.46 |
其他类 Others | 萘 Naphthalene | 0.42 | - |
2-丁基-萘 2-butyl-naphthalene | 0.47 | - |
新窗口打开|下载CSV
图8
新窗口打开|下载原图ZIP|生成PPT图8超声处理前后模型酒样挥发性成分的总离子流图
Fig. 8Total ion chromatograms of the volatile components in the model wine before and after ultrasound irradiation
超声处理后模型酒中定性鉴定到37种挥发性成分,同样酯类、醇类物质种类较多,其中酯类有25种、醇类5种、醛类2种、烷类3种、酚类1种、苯类物质1种;占比分别为:酯类57.50%、醇类25.24%、醛类1.54%、烷类9.53%、酚类3.46%、苯类2.49%,酯类、醇类物质占比较大。与未超声模型酒液相比,经超声处理后酒液体系中无论酯类物质种类还是含量都有所增加,这与红酒中的相关变化基本一致。
由图9可知,模型酒中主要的挥发成分为酯类、醇类、醛类和烷类,这与红酒样中主要挥发性物质基本吻合。醛类、醇类含量经超声处理后含量有所降低,其中醇类物质下降19.15%、醛类下降59.40%,而酯类物质含量增加3.41%。说明超声处理对模型酒中挥发性成分有一定影响,尤其对醇类、醛类和酯类物质。超声处理后模型酒中酯类物质如戊酸戊酯、辛酸乙酯、月桂酸异戊酯、癸酸乙酯等增加,而3-甲基-甲酸-丁醇、2-丁基-辛醇和2,4-二甲基苯甲醛下降,这可能与超声导致酒体内发生了酯化反应有关[16]。3-甲基-甲酸-丁醇具有强烈的香蕉、李子等水果香味,是异戊醇的酯化产物;辛酸乙酯具有白兰地酒香味,月桂酸异戊酯具有微弱的油脂香气和奶油香,癸酸乙酯具有椰子香型香气,超声处理后这些酯类物质含量的增加有利于红酒香气风味的改善,但其具体机制仍有待进一步研究。
图9
新窗口打开|下载原图ZIP|生成PPT图9超声处理对模型酒中挥发性物质的影响
Fig. 9Effects of ultrasound irradiation on the volatile components of model wine
3 讨论
前期研究表明,适度超声处理可有效降低红酒中高级醇的含量,其可能原因是超声空化效应可一定程度提高分子间的有效碰撞,加速葡萄酒的氧化、缩合和酯化等反应,致使高级醇含量降低[6,31];但在降低高级醇的同时是否会影响葡萄酒的感官品质仍不确定。电子鼻作为一种新兴智能感官分析仪器,通过模拟人类嗅觉系统来实现对待测对象的品质评价,利用气味指纹信息对气体或挥发性成分进行识别[35,36,37]。电子舌是基于生物仿生学原理通过模仿人类唾液及味觉感知机理而制成的一种新型仿生分析仪器,它通过味觉传感器阵列获取待测液信息,采用多元统计分析方法对传感器输出信号进行处理,最终建立一个反映待测样品某种特定感官的评价模型,从而形成反映样本整体信息的“指纹”数据;电子舌已在茶叶饮料、酒类、咖啡等液体滋味的分类与评价方面有所应用[38,39]。无论电子鼻还是电子舌,都具有操作简单、能反映样品整体信息、速度快和灵敏度高等优点,可实现对待测样品的相对客观分析,减少因感官评价员主观反应不同而导致的评定误差,如果再结合气质联用技术可实现对挥发性成分的定性与定量融合分析。考虑到葡萄酒中的挥发性成分决定着酒体香气的协调程度,对酒的风味有决定性作用。鉴于此,本研究中将具有“模糊评价”属性的电子鼻和电子舌技术结合具有“精准检测特性”的GC-MS分析技术来探讨超声处理对红酒风味特性的影响。
电子鼻定性判定结果表明,经不同超声条件处理后红酒样品嗅觉指标与未处理红酒样品无显著性差异,说明在选定的超声波条件下处理红酒对其挥发性风味品质特性影响较小。而电子舌测定结果表明,与未经超声处理红酒样品相比,经不同超声条件处理后部分红酒样品的口感品质确实受到了一定程度的影响。这可能与两种仪器测定物质的种类和方法不同有关。
气相色谱质谱联用分析结果表明,在挥发性物质的种类方面,超声处理后比未处理酒样多10种;但主体挥发性物质如酸、酯和醇类等主要类别基本没变化;但超声处理后酯类含量显著提高,而酸类和醇类含量降低,提示超声波可能是通过加速醇和酸的酯化反应从而提升酯类物质含量和酒体的香气风味特性[4,14,23,40]。为进一步探究在超声降低高级醇时对酒中风味物质的影响机制,本研究采用构建模型酒液并添加高级醇标准品的方式以简化酒中非目标物质的干扰,增加研究的针对性。结果表明,在模型酒液体系中,酯类、醇类等物质的变化趋势与红酒基本一致;经超声处理后模型酒液体系中醇类、醛类含量有所降低,而酯类含量增加;与红酒样品不同的是并未检测到酸类物质,原因有待进一步探究。酯类物质是酒的主体香气物质,其含量增加说明超声波处理除了降低高级醇外,还可以加快酒的酯化反应、提升酒的香气,但这种香气未必能与所用的电子鼻、电子舌传感器有良好响应,这也是电子鼻、电子舌判定结果不显著的原因之一;醇类与酮类物质的降低表明超声处理可能加速了葡萄酒内部醇-醛-酸-酯物质间的转化。另外,葡萄酒的感官特征是由香气物质的种类、数量、单个物质的嗅觉阈值及香气物质之间的相互作用决定的[41]。刘迪等[42]研究表明,储藏期间葡萄酒的香气感官品质与香味物质(E)-2-辛稀-1-醇、香叶基丙酮等呈正相关性,而与香味物质5-甲基呋喃醛、香茅醇等呈负相关性。李博斌等[43]研究表明,黄酒中挥发性成分与香气评分值间的相关性不高,被认为对黄酒香气有极大作用的乙酸乙酯和香气评分之间的相关性却较低,甚至呈负相关。这说明酒体系中的香气物质与感官品质的相关性较为复杂,不能仅以香味物质的含量推断整体的感官品质,两者的具体相关性仍需后续深入研究。这也从一定程度上解释了电子鼻、电子舌测定结果与气质联用分析结果之间有一定差异或不完全一致的原因。
因此,虽然经过超声后酒样总体感官风味差异不大,但部分滋味物质(尤其酯类物质)含量还是发生了显著变化,说明超声在降低高级醇的同时还可以提升酒的滋味特性;而且这些酯类物质可能与超声波降解高级醇有关,但其具体变化机制仍有待进一步研究。
4 结论
不同超声处理不会显著影响红酒的口感风味品质,但可以显著降低红酒中酸类和醇类等挥发性物质并提升酯类物质的含量。模型酒液体系研究结果也证实,超声波在有效降低模型酒液中高级醇含量的同时,增加了酒中挥发性物质的种类,并促进了酯类物质的生成。用优化的超声参数处理红酒,不仅可以有效降低高级醇的含量,而且还可促进酒中挥发性酯类物质的生成,一定程度的改善红酒的风味品质。参考文献 原文顺序
文献年度倒序
文中引用次数倒序
被引期刊影响因子
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As a potential novel technique in the wine-making industry, ultrasound has received considerable attention. In this paper, a model wine system was constructed to investigate the effect of ultrasonic irradiation on the formation of xanthylium cation pigment derived from the (+)-catechin and the glyoxylic acid, an oxidation product of tartaric acid, so as to explore the changing mechanism of the wine color mediated by ultrasound. The results indicate that the long-term ultrasonic treatment can enhance the formation of the xanthylium cation pigment in the model wine, which is attributed to free radicals triggered by ultrasound, meanwhile, iron ions and oxygen can influence the ultrasonic effect. All these results suggest that ultrasound is promising to be employed in regulating the formation of the yellow pigment during wine aging thus modifying the wine organoleptic characteristic.
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To evaluate the partition coefficients of volatiles between the liquid and gas phases, an analytical method was developed and optimized using static headspace analysis and low-pressure injection gas chromatography coupled to mass spectrometry (SHS-LP-GC/MS). Two different types of analytical columns were coupled for low-pressure chromatography injection: a narrow restriction microbore column on the inlet side and a mega-bore column on the mass spectrometer side. Coupling these two columns and static headspace analysis to gas chromatography and mass spectrometry resulted in a simple, fast, sensitive, and accurate approach. Several points have been optimized: time to reach the thermodynamic equilibrium in the gas phase, syringe filling rate, gas injection rate, and volume ratio between the gas and liquid phases. This new method was used to determine partition coefficients between the liquid and gas phases and study multicomponent mixtures for which particular perceptive interactions had previously been highlighted. The partition coefficients of 9 esters and 5 higher alcohols were determined in dilute alcohol solution (12% v/v) and dearomatized red wine. These partition coefficients revealed modifications in ester headspace release in the presence of higher alcohols for the first time in this type of matrix. The correlation of these results with sensory data highlighted the role of physicochemical, presensory effects on sensory modifications for the first time, suggesting that this type of interaction may partly modulate qualitative and quantitative fruity perception.
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In red wine, the contents of higher alcohols and ethyl carbamate (EC) are two significant health concerns. To reduce the production of higher alcohols by wine yeast YZ22 with low production of EC, one BAT2 was replaced by a BAT1 expression cassette first and then another BAT2 was deleted to obtain the mutant SYBB3. Real-time quantitative PCR showed that the relative expression level of BAT1 in SYBB3 improved 28 times compared with that in YZ22. The yields of isobutanol and 3-methyl-1-butanol produced by mutant SYBB3 reduced by 39.41% and 37.18% compared to those by the original strain YZ22, and the total production of higher alcohols decreased from 463.82 mg/L to 292.83 mg/L in must fermentation of Cabernet Sauvignon. Meanwhile, there were no obvious differences on fermentation characteristics of the mutant and parental strain. This research has suggested an effective strategy for decreasing production of higher alcohols in Saccharomyces cerevisiae.
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Undesirable flavor caused by excessive higher alcohols restrains the development of the wheat beer industry. To clarify the regulation mechanism of the metabolism of higher alcohols in wheat beer brewing by the top-fermenting yeast Saccharomyces cerevisiae S17, the effect of temperature on the fermentation performance and transcriptional levels of relevant genes was investigated. The strain S17 produced 297.85 mg/L of higher alcohols at 20 degrees C, and the production did not increase at 25 degrees C, reaching about 297.43 mg/L. Metabolite analysis and transcriptome sequencing showed that the metabolic pathways of branched-chain amino acids, pyruvate, phenylalanine, and proline were the decisive factors that affected the formation of higher alcohols. Fourteen most promising genes were selected to evaluate the effects of single-gene deletions on the synthesis of higher alcohols. The total production of higher alcohols by the mutants Deltatir1 and Deltagap1 was reduced by 23.5 and 19.66% compared with the parent strain S17, respectively. The results confirmed that TIR1 and GAP1 are crucial regulatory genes in the metabolism of higher alcohols in the top-fermenting yeast. This study provides valuable knowledge on the metabolic pathways of higher alcohols and new strategies for reducing the amounts of higher alcohols in wheat beer.
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Direct evidence for the formation of 1-hydroxylethyl radicals by ultrasound in red wine and air-saturated model wine is presented in this paper. Free radicals are thought to be the key intermediates in the ultrasound processing of wine, but their nature has not been established yet. Electron paramagnetic resonance (EPR) spin trapping with 5,5-dimethyl-l-pyrrolin N-oxide (DMPO) was used for the detection of hydroxyl free radicals and 1-hydroxylethyl free radicals. Spin adducts of hydroxyl free radicals were detected in DMPO aqueous solution after sonication while 1-hydroxylethyl free radical adducts were observed in ultrasound-processed red wine and model wine. The latter radical arose from ethanol oxidation via the hydroxyl radical generated by ultrasound in water, thus providing the first direct evidence of the formation of 1-hydroxylethyl free radical in red wine exposed to ultrasound. Finally, the effects of ultrasound frequency, ultrasound power, temperature and ultrasound exposure time were assessed on the intensity of 1-hydroxylethyl radical spin adducts in model wine.
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Low-alcohol Huangjiu (LAH), which contains reduced contents of ethanol and higher alcohols, is prepared by diluting original Huangjiu that has a high ethanol content, which leads to a weakened flavor (i.e., acidity). To increase acidity and reduce higher alcohols level in LAH, the gene ALD6 encoding aldehyde dehydrogenase was expressed in yeast HJ-1 under the control of the pPGK1 promoter and terminators with varying activities (tGIC1, tPGK1 and tCPS1) by scarless replacement at BAT2 locus, yielding the engineered strains HJDeltaB-AG, HJDeltaB-AP, and HJDeltaB-AC. The acetate concentration produced by HJDeltaB-AG, HJDeltaB-AP, and HJDeltaB-AC was 1.26-, 1.84-, and 2.51-fold of that of HJ-1, respectively. Furthermore, the concentration of higher alcohols produced by HJDeltaB-AG, HJDeltaB-AP, and HJDeltaB-AC decreased by 39.91%, 45.55%, and 52.80%, respectively. This study resulted in the creation of promising recombinant yeast strains and introduced a method that can be used for the high-quality production of LAH by acid-producing Saccharomyces cerevisiae.
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Replacement of conventional transportation fuels with biofuels will require production of compounds that can cover the complete fuel spectrum, ranging from gasoline to kerosene. Advanced biofuels are expected to play an important role in replacing fossil fuels because they have improved properties compared with ethanol and some of these may have the energy density required for use in heavy duty vehicles, ships, and aviation. Moreover, advanced biofuels can be used as drop-in fuels in existing internal combustion engines. The yeast cell factory Saccharomyces cerevisiae can be turned into a producer of higher alcohols (1-butanol and isobutanol), sesquiterpenes (farnesene and bisabolene), and fatty acid ethyl esters (biodiesel), and here we discusses progress in metabolic engineering of S. cerevisiae for production of these advanced biofuels.
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In order to elucidate the aroma components of wine produced in the Loess Plateau region of China, volatile compounds of young wines from Cabernet Sauvignon, Cabernet Gernischet and Chardonnay varieties grown in the new ecological region were investigated for the first time in this research. Among the volatile compounds analyzed by HS-SPME with GC-MS, a total of 45, 44 and 42 volatile compounds were identified and quantified in Cabernet Sauvignon, Cabernet Gernischet and Chardonnay wines, respectively. In the volatiles detected, alcohols formed the most abundant group in the aroma compounds of the three wines, followed by esters and fatty acids. According to their odor active values (OAVs), 18 volatile compounds were always present in the three wines at concentrations higher than their threshold values, but ethyl octanoate, ethyl hexanoate, and isoamyl acetate were found to jointly contribute to 92.9%, 93.3%, and 98.7%, of the global aroma of Cabernet Sauvignon, Cabernet Gernischet and Chardonnay wines, respectively. These odorants are associated with
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An electronic nose (e-nose) based on thin film semiconductor sensors has been developed in order to compare the performance in threshold detection and concentration quantification with a trained human sensory panel in order to demonstrate the use of an e-nose to assess the enologists in an early detection of some chemical compounds in order to prevent wine defects. The panel had 25 members and was trained to detect concentration thresholds of some compounds of interest present in wine. Typical red wine compounds such as whiskeylactone and white wine compounds such as 3-methyl butanol were measured at different concentrations starting from the detection threshold found in literature (in the nanograms to milligrams per liter range). Pattern recognition methods (principal component analysis (PCA) and neural networks) were used to process the data. The results showed that the performance of the e-nose for threshold detection was much better than the human panel. The compounds were detected by the e-nose at concentrations up to 10 times lower than the panel. Moreover the e-nose was able to identify correctly each concentration level therefore quantitative applications are devised for this system.
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