Development of a Rapid Discrimination Tool for <Emphasis Type="Italic">Luzhou-flavor</Emphasis> Pit Mud Classification by the Kohonen Artificial Neural Network Model

Understanding the volatile composition of pit mud (PM) samples and discriminating these samples has become a highly necessary task, owing to the fact that volatile profiling of PM can significantly affect Chinese Luzhou-flavor liquor quality. In this study, the volatile constitutions of 13 Luzhou-flavor liquor PM samples from four typical producing regions were investigated by gas chromatography–mass spectrometry (GC-MS). Owing to their high concentrations, compounds such as ethyl hexanoate, butyric acid, hexanoic acid, ethyl pentadecanoate, ethyl palmitate, ethyl (9E)-9-octadecenoate, ethyl (9E,12E)-9,12-octadecadienoate, and palmitic acid were considered to be predominant volatiles. A promising artificial neural network model, the Kohonen self-organizing map (SOM), was applied to rapidly discriminate the PM samples in terms of differences based on the quantitative information of volatile compounds. After Kohonen SOM training, 13 distinct clusters, corresponding to PM samples, were clearly visualized on a uniform distance matrix (U-matrix). The influence of volatile compounds on the classification of the PM could be displayed using component panels, which can give quantitative insight. GC-MS coupled with the Kohonen SOM model not only presented the volatile constitution of PM but also provided promising information for discrimination between different PM samples, even in other fermented foods.     

Characterisation of volatile compounds in Maotai flavour liquor during fermentation and distillation

Volatile constituents in raw liquor and zaopei during fermentation and distillation were investigated by gas chromatography. Zaopei (steamed grains mixed with Daqu [FG1], stacking fermented grains [FG2], anaerobic fermented grains [FG3] and steamed grains [FG4]) presented changes in physicochemical properties. In all, 72 volatile compounds were identified in zaopei and raw liquor with similarity across 12 zaopei preparations. Principal component analysis and partial least squares discriminant analysis differentiated FG3 from other samples based on content of aroma compounds. FG3 had the highest level of aroma compounds, which increased from the fourth to sixth batches, and was characterised by the presence of 1, 2‐propanediol, acetic acid and linoleic acid, while the others were portrayed by phenylpropionate, ethyl laurate and 4‐ethyl guaiacol. The volatile compounds of raw liquor were dominated by ethyl acetate and ethyl lactate. Correlation analysis illustrated a lack of correlation of volatile compound content between the raw liquors and the zaopei distillation variants. © 2019 The Institute of Brewing & Distilling     

基于多元统计学分析红曲米醋醋酸发酵阶段挥发性风味特征组分

为探究红曲米醋酿造过程中挥发性风味及特性组分变化规律,以红曲米醋醋酸发酵阶段为研究对象,采用电子鼻、气相色谱-质谱（gas chromatography-mass spectrometry,GC-MS）联用和气相色谱-嗅闻（gas chromatography-olfactometry,GC-O）联用技术对挥发性风味物质进行分析,并结合聚类分析、主成分分析和偏最小二乘判别法的多元统计方法进行不同发酵阶段的风味物质差异性分析,最终筛选出特征性组分。电子鼻分析可用于区分不同发酵时期的红曲米醋。通过GC-MS和GC-O识别出发酵过程中共有54 种挥发性风味化合物。经多元统计学方法筛选得到挥发性风味特征组分,醋酸发酵早期为正辛醇、异丁醇和戊酸乙酯;中期为苯甲酸、棕榈酸乙酯、正己醇、2,4-二叔丁基苯酚和乳酸乙酯;中后期为乙酸丙酯、乳酸乙酯和乙酸异丁酯;末期为L(＋)-2,3-丁二醇和庚酸乙酯。本研究结果为红曲米醋香气的调控和风味改善提供重要理论依据。     

洋河系列绵柔型白酒香气成分研究

利用液液萃取法提取洋河系列绵柔型白酒中的香气化合物,通过气相色谱-闻香法(GC-O)及气相色谱-质谱(GC-MS)技术对其进行鉴定。在具有典型绵柔型特征的海之蓝、天之蓝和梦之蓝三种酒中分别检测出55、57和59种呈香化合物。研究发现洋河系列绵柔型白酒的主要风味物质为己酸乙酯,对其风味有较大贡献的还有己酸、丁酸乙酯、二甲基三硫、三甲基吡嗪、γ-壬内酯。此外,在海之蓝中苯乙醛、3-甲基丁醇、庚酸乙酯、己酸-3-甲基丁酯、丁酸、乙酸对其风味贡献较大;天之蓝中1-辛烯-3-酮、辛酸乙酯、2-乙酰基-5-甲基呋喃、丁酸香气强度较大;梦之蓝中1-辛烯-3-酮、己酸-3-甲基丁酯、2-羟基-3-甲基丁酸乙酯、辛酸乙酯、4-甲基苯酚、庚酸乙酯香气强度较大。     

Characterisation of odour-active compounds in aged rum

The volatiles of rum matured in oak casks were carefully isolated by solvent extraction followed by solvent-assisted flavour evaporation. Among the 116 volatile compounds identified by GC-MS, seven of them were found for the first time in rum. Application of the aroma extract dilution analysis (AEDA) on the volatile fraction revealed 18 odour-active areas in the flavour dilution factor range of 32-1024. On the basis of the quantitative data and odour thresholds in 35% ethanol (v/v), the odour activity values (OAV; ratio of concentration to odour threshold) were calculated. Nineteen aroma compounds showed OAVs >1, among which ethanol, (E)-β-damascenone, ethyl butanoate, ethyl hexanoate, vanillin, (Z)-oak lactone, ethyl 2-methylpropanoate, 1,1-diethoxyethane, ethyl 2-methylbutanoate, 3-methylbutyl acetate, ethyl octanoate, ethyl decanoate, 2-phenylethyl acetate, 2-phenylethanol, 2-methoxyphenol, 4-ethyl-2-methoxyphenol, 4-propyl-2-methoxyphenol, γ-nonalactone, and eugenol showed the highest values and should be considered as the most odour-active compounds.     

Establishment of Monstera deliciosa fruit volatile metabolomic profile at different ripening stages using solid-phase microextraction combined with gas chromatography–mass spectrometry

The volatile metabolomic profile of Monstera deliciosa fruits (M. deliciosa, ceriman) at three ripening stages, ripe, half-ripe and unripe, was established using headspace solid-phase microextraction (HS-SPME) combined with gas chromatography–quadrupole mass spectrometry detection (GC–qMS). To obtain the optimal HS-SPME conditions, the main experimental parameters that influence the extraction efficiency and experimental response were analyzed. The highest extraction efficiency was achieved with 1 g of ceriman sample, using a polydimethylsiloxane/divinylbenzene (PDMS/DVB) fiber for 60 min at 40 °C with 15% NaCl (w/w). After optimization, all ceriman samples were analyzed with the best extraction conditions that allowed to identify 80 volatile metabolites (VOMs), belonging to different chemical groups namely ethyl esters (88.61–77.94%), terpenoids (18.08–9.83%), carbonyl compounds (3.41–1.05%), higher alcohols (1.41–0.51%) and lactones (0.14–0.03%). Thirty-eight of the identified volatile metabolites (47.50%) have not been reported in M. deliciosa, so far, providing a more complete characterization of its volatile composition. The predominant VOMs identified in M. deliciosa fruits were ethyl butanoate, linalool, ethyl hexanoate, ethyl 2-methyl butanoate, butanoic acid, ethyl benzoate and propyl butanoate. Remarkable differences were found in both the quantitative and qualitative composition of M. deliciosa fruits at different ripening stages.Principal component analysis (PCA) provided a suitable tool to differentiate the volatile profile of target fruits among three ripening stages.     

气相色谱-质谱法分析比较牛栏山牌清香型二锅头酒和浓香型白酒中的香味成分

采用液液萃取的方法分别提取清香型牛栏山二锅头酒和浓香型牛栏山白酒中的香味成分,结合气相色谱-质谱联用仪进行分析检测。结果表明两种香型白酒共检测出65种香味成分,其中：清香型牛栏山二锅头酒中共检测出34种香味成分,主要呈香化合物有酯类化合物、烷烃类化合物和醇类化合物,主要香味成分有3-甲基-1-丁醇、2-羟基-丙酸乙酯、棕榈酸乙酯、油酸乙酯和亚油酸乙酯;浓香型牛栏山白酒共检测出43种香味成分,其主要呈香化合物有酯类化合物、醇类化合物和酸类化合物,主要香味成分有己酸乙酯、1,1-二乙氧基乙烷、3-甲基-1-丁醇、己酸和2-羟基丙酸乙酯。表明酿酒原料和工艺不同导致的香味成分的差异,是赋予两种白酒不同口感和风格的关键。     

采用电子鼻和GC-MS技术研究慕萨莱思中挥发性成分

以阿瓦提慕萨莱思为研究对象,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)技术对不同酒精度原酒(G1、G2、G3)及慕萨莱思成品酒(G4、G5、G6、G7)中的挥发性成分进行检测,研究分析其挥发性成分的变化,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;利用GC-MS共检测出挥发性物质164种,其中G1为67种、G2为47种、G3为55种、G4为45种、G5为54种、G6为57种、G7为51种。通过主成分分析(PCA)可知,慕萨莱思中醇类、酯类以及酸类物质是最主要的挥发性组成成分。其中贡献较大的为苯乙醇、1-戊醇、己酸、辛酸、月桂酸、癸酸、乙酸乙酯、苯乙酸乙酯、辛酸乙酯、棕榈酸乙酯等。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。     

Addition of yogurt to wort for the production of spirits: Evaluation of the spirit aroma over a two-year period

Triggered by the development of lactic acid bacteria (LAB) during the production of Scotch whisky, this study examined the influence of yeast and LAB inoculation on whisky flavor. Four new spirits were produced using the same process. LAB were added as a form of a Greek yogurt's live culture. In each category (barley and rye), one sample was fermented with Greek yogurt while the other was fermented without it. The spirits were matured and analyzed at five different points. Results from gas chromatography-mass spectrometry (GC-MS) analysis showed basic volatile compounds, along with some important extra compounds with yogurt culture. The most obvious differences were observed in the concentration of butanoic acid, a characteristic acid in spirits undergoing lactic acid fermentation: to identify esters such as ethyl butanoate, ethyl isobutanoate, isoamyl butanoate, and 2-phenylethyl butanoate, they are not typical compounds in whisky.     

基于气相色谱-质谱技术与多元统计分析对不同栗香特征绿茶判别分析

采用气相色谱-质谱联用技术结合多元统计分析主成分分析（principal component analysis,PCA）、偏最小二乘法-判别分析（partial least squares-discriminant analysis,PLS-DA）和系统聚类分析（hierarchical cluster analysis,HCA）对18?个不同栗香特征的绿茶开展研究。结果表明,PCA、PLS-DA和HCA均可直观地对3?种不同栗香特征的绿茶进行有效区分;PLS-DA中,18?个栗香茶样基于其香气特征实现良好分离,其中R2Y＝0.843、Q2＝0.694,说明该模型对3?种栗香特征绿茶具有良好的稳定性和较好的预测能力;HCA中,3种栗香绿茶在聚类距离12处被清晰地分成3?类,其中板栗香型和嫩栗香型距离更接近,聚类效果和感官辨识基本一致。此外,基于变量投影重要性大于1,筛选出了38?种区分不同栗香特征的重要挥发性组分。     

应用HS-SPME技术测定固态发酵浓香型酒醅微量成分

HS-SPME的方法是检测酒醅中微量风味物质的一种好的方法。该法简单、方便、快速。样品不需要进行预处理。检测成分完全可以用于浓香型固态发酵酒醅的发酵过程分析。从浓香型固态发酵酒醅中共检测出106种挥发性化合物,其中醇类9种,醛类6种,酮类2种,酸类10种,酯类47种,芳香族化合物12种,硫化物3种,呋喃类化合物4种,酚类化合物8种,以及其它化合物5种。重要的挥发性化合物是己酸乙酯、己酸、辛酸乙酯、丁酸、乙酸乙酯、乳酸乙酯和丁酸乙酯。     

Analysis and Differentiation of the Volatile Compounds in Red and White Wines Using Desiccated Headspace Gas Chromatography-Mass Spectrometry Coupled with Chemometrics

A well-tailored method for the fingerprinting analysis of volatile compounds in wines has been developed. Based on the complete hydrate formation between sample solvent and anhydrous salt, an in situ desiccated sampling of volatile compounds into GC-MS was achieved, which can be directly applied to the aqueous wine sample without any pretreatment. By this means, the volatile compounds in 17 wine samples have been successfully detected. To explore the common features underlying the fingerprinting differences in volatile compounds between red and white wines, PCA and PLS-DA were successively performed on 18 peaks and 10 peaks of volatile compounds in the wine samples, and good clustering was obtained for the classification of the two kinds of wines. The results showed that five characteristic components, i.e., 2-hydroxy-propanoic acid ethyl ester, butanedioic acid monomethyl ester, 4-oxo-pentanoic acid ethyl ester, 1-dodecene, and 1,2,3-trimethoxy-5-methyl-benzene, were found to be quite different in their contents between red and white wines among the other volatiles, which, to some extent, may take responsibility for the differences in their volatile aroma. This work will provide a useful tool and valuable guidance for elucidating the chemical fingerprinting differences in organoleptic quality among different wines.     

Changes in Volatile Compounds of Chinese Luzhou‐Flavor Liquor during the Fermentation and Distillation Process

The aim of this study was to investigate the dynamic of volatile compounds in the Zaopei during the fermentation and distillation process by headspace solid‐phase microextraction‐gas chromatography mass spectrometry (HS‐SPME‐GCMS). Physicochemical properties analysis of Zaopei (fermented grains [FG], fermented grains mixed with sorghum [FGS], streamed grains [SG], and streamed grains mixed with Daqu [SGD]) showed distinct changes. A total number of 66 volatile compounds in the Zaopei were identified, in which butanoic acid, hexanoic acid, ethyl hexanoate, ethyl lactate, ethyl octanoate, hexyl hexanoate, ethyl hydrocinnamate, ethyl oleate, ethyl hexadecanoate, and ethyl linoleate were considered to be the dominant compounds due to their high concentrations. FG had the highest volatile compounds (112.43 mg/kg), which significantly decreased by 17.05% in the FGS, 67.12% in the SG, and 73.75% in the SGD. Furthermore, about 61.49% of volatile compounds of FGS were evaporated into raw liquor, whereas head, heart, and tail liquor accounted for 29.84%, 39.49%, and 30.67%, respectively. Each volatile class generally presented a decreasing trend, except for furans. Especially, the percentage of esters was 55.51% to 67.41% in the Zaopei, and reached 92.60% to 97.67% in the raw liquor. Principal component analysis based ordination of volatile compounds data segregated FGS and SGD samples. In addition, radar diagrams of the odor activity values suggested that intense flavor of fruit was weakened most from FG to SGD.     

固相微萃取-气相色谱-质谱联用法测定传统酸肉发酵过程中特征挥发性成分

通过固相微萃取-气相色谱-质谱联用仪对鲜肉及发酵10、30、50 d酸肉的挥发性物质进行鉴定,探究传统发酵酸肉中挥发性成分种类及含量变化。结果表明：4 个时期的肉样中共检出106 种挥发性物质,其中酯类32 种、酸类2 种、醇类11 种、醛类16 种、酮类3 种、碳氢化合物29 种及其他类化合物13 种;采用主成分分析、偏最小二乘判别分析酸肉发酵过程中挥发性风味物质的动态变化,发现不同发酵阶段酸肉挥发性物质组成差异显著;基于气味活度值从106 种挥发性成分中筛选出49 种对酸肉整体风味具有重要贡献的物质,除碳氢类化合物主要促进鲜肉风味形成外,癸酸乙酯、丁酸乙酯、辛酸乙酯等酯类物质,庚醇、1-壬醇等醇类,(E)-2-庚烯醛、壬醛等醛类物质均为传统发酵酸肉的主体风味物质。     

固相微萃取与GC-MS法分析发酵型臭豆腐中挥发性成分

采用固相微萃取技术结合气质联用分析了北京产发酵型臭豆腐中挥发性香成分,共鉴定出31种成分,其中酯类9种、含硫类化合物6种、醛酮类5种、醇类4种、酸类2种、舍氮化合物1种、酚类1种、其他3种,检测到的含量较高的化合物有二甲基三硫、吲哚、二甲基二硫、苯酚、乙酸丁酯、正丁醇、丁酸乙酯、二甲基四硫、丁酸、正己醛、丁酸丙酯.     

Classification of Brazilian vinegars according to their H NMR spectra by pattern recognition analysis

This work describes using ¹H NMR data and pattern recognition analysis to classify vinegars. Vinegar authenticity is linked to raw ingredient source and manufacturing conditions. Application of PCA and HCA methods resulted in the natural clustering of the samples according to the raw material used. Wine vinegars were characterized by a high concentration of ethyl acetate, glycerol, methanol and tartaric acid, while glycerol and ethyl acetate signals were not visible in alcohol/agrin vinegars. Apple vinegars showed to be richer in alanine. The KNN, SIMCA and PLS-DA methods were used to build predictive models for classification of vinegar type wine, apple and alcohol/agrin (27 samples - 22 as training set). The models were tested using an independent set (5 samples), no samples were wrongly classified. Validated models were used to predict the class of 21 commercial samples, which, as expected, were correctly classified. Eight commercial vinegars (honey, orange, pineapple and rice) were discriminated from these samples using PCA method. Honey vinegars did not present ethanol signals and pineapple vinegars presented the largest amount of tartaric acid. Rice and orange vinegars are richer in lactic acid and did not present the methanol signal. Alanine signals were not visible in orange vinegars.     

Volatile Metabolites of Goat Cheeses Determined by Ion Mobility Spectrometry. Potential Applications in Quality Control

Headspace sampling coupled with multi-capillary column-ion mobility spectrometry (HS-MCC-IMS) has been used for extraction and identification of some volatile metabolites from different types of goat cheese samples. The only manual operation carried out in this method was the introduction of samples into vials; the following steps (headspace generation, injection of the volatiles compounds into MCC and IMS detection) were fully automated. The analysis by MCC-IMS allowed rapid and simple differentiation of goat cheeses made with raw and pasteurized milk. MCC-IMS produced multidimensional ion mobility spectra with different retention times and intensity information different for some individual metabolites. A total of six metabolites were identified in goat cheeses including 1 alcohol (1-hexanol), 1 ketone (2-nonanone), 2 aldehydes (octanal, trans-2-heptanal) and 2 esters (ethyl butanoate and propyl butanoate). Furthermore, the evolution of one targeted metabolite (ethyl butanoate) was monitored through different ripening times (60, 150, 180, 210, 240, 270 days). These preliminary results showed that this volatile compound increased during cheese ageing according to biochemical and microbial dynamic of the matrix, and therefore ethyl butanoate could be a potential marker of ripening time in these kinds of cheese samples. Therefore, the method could be used for quality control purposes in goat cheese producers.     

Effects of time of grape pomace fermentation and distillation cuts on the chemical composition of grape marcs

 The effects of fermentation time and distillation cuts on the composition of distillates in terms of ethanal, 1,1-diethoxyethane, methanol, 1-butanol, 2-butanol, 1-propanol, 2-methyl-1-propanol, 2-methyl-1-butanol, 3-methyl-1-butanol, ethyl acetate, ethyl 2-hydroxypropanoate, 3-methylbutyl acetate, hexyl acetate, 2-phenylethyl acetate, hexanol, trans-2-hexenol, trans-3-hexenol, cis-3-hexenol, 2-phenylethanol, ethyl butyrate, ethyl hexanoate, ethyl octanoate, ethyl decanoate, ethyl dodecanoate, 2-methylpropanoic acid, 3-methylbutanoic acid, hexanoic acid, octanoic acid, decanoic acid, and dodecanoic acid were assessed through data generated according to a factorial design using analysis of variance and principal component analysis. Four times of storage of pomace obtained following winemaking of two grape varieties of white Verde wine (Alvarinho and Loureiro) and three distillation cuts were considered; volatile compounds in the 24 samples generated were analyzed directly, and indirectly after extraction and concentration, by capillary gas chromatography. The results generated have suggested clear differences (P<0.05) between distillate cuts obtained throughout fermentation times for each grape variety. The major differences between the different distillate fractions analyzed were accounted for by the contents of diethyl butanoate, ethyl 2-hydroxypropanoate, and the sum of 3-methylbutanoic and 2-methylpropanoic acids for Loureiro, whereas the main differences were accounted for by the contents of diethyl butanoate and the sum of the carboxylic acids for Alvarinho.     

Effects of time of grape pomace fermentation and distillation cuts on the chemical composition of grape marcs

 The effects of fermentation time and distillation cuts on the composition of distillates in terms of ethanal, 1,1-diethoxyethane, methanol, 1-butanol, 2-butanol, 1-propanol, 2-methyl-1-propanol, 2-methyl-1-butanol, 3-methyl-1-butanol, ethyl acetate, ethyl 2-hydroxypropanoate, 3-methylbutyl acetate, hexyl acetate, 2-phenylethyl acetate, hexanol, trans-2-hexenol, trans-3-hexenol, cis-3-hexenol, 2-phenylethanol, ethyl butyrate, ethyl hexanoate, ethyl octanoate, ethyl decanoate, ethyl dodecanoate, 2-methylpropanoic acid, 3-methylbutanoic acid, hexanoic acid, octanoic acid, decanoic acid, and dodecanoic acid were assessed through data generated according to a factorial design using analysis of variance and principal component analysis. Four times of storage of pomace obtained following winemaking of two grape varieties of white Verde wine (Alvarinho and Loureiro) and three distillation cuts were considered; volatile compounds in the 24 samples generated were analyzed directly, and indirectly after extraction and concentration, by capillary gas chromatography. The results generated have suggested clear differences (P<0.05) between distillate cuts obtained throughout fermentation times for each grape variety. The major differences between the different distillate fractions analyzed were accounted for by the contents of diethyl butanoate, ethyl 2-hydroxypropanoate, and the sum of 3-methylbutanoic and 2-methylpropanoic acids for Loureiro, whereas the main differences were accounted for by the contents of diethyl butanoate and the sum of the carboxylic acids for Alvarinho. Received: 23 January 1998 / Revised version: 5 June 1998     

Evolution of aroma compounds of murtilla fruits (Ugni molinae Turcz) during storage

BACKGROUND: ‘Murtilla’, ‘mutilla’ or ‘murta’ (Ugni molinae Turcz) is a native Chilean species that produces a small berry fruit with a special aroma, whose volatile compounds have not yet been identified. The fruit may be consumed raw and also as jams, juice, canned products, confections and liquor. RESULTS: At the beginning and end of the storage, 24 volatile compounds were identified in murtilla fruit aroma and the concentration of these compounds in murtilla fruit ranged from 1.2 to 250.5 µg kg^?1 fresh weight. Methyl 2‐methyl butanoate, ethyl butanoate, ethyl 2‐methyl butanoate, methyl hexanoate, ethyl hexanoate, methyl benzoate and ethyl benzoate were the major components, all of which have been reported as potent odors in other aromatic fruits. Based on estimated odor activity value, the most potent compound in the murtilla fruit aroma were ethyl hexanoate and 4‐methoxy‐2,5‐dimethyl‐furan‐3‐one. The statistical analysis showed that the storage produced a distinct effect on the same volatile compounds released from the murtilla ecotypes. CONCLUSION: The volatile compounds identified in murtilla fruit aroma, which may be described as fruity, sweet and floral, have been found in other aromatic fruits. Concerning the aroma, the murtilla fruit from ecotype 19‐1 was shown to be the best in cooled storage. Copyright © 2007 Society of Chemical Industry