Effects of maltose and lysine treatment on coffee aroma by flash gas chromatography electronic nose and gas chromatography–mass spectrometry

He, Yang; Zhang, Haide; Wen, Nana; Hu, Rongsuo; Wu, Guiping; Zeng, Ying; Li, Xiong; Miao, Xiaowei

doi:10.1002/jsfa.8450

Cited by 7 publications

(8 citation statements)

References 36 publications

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“…They were ethyl butyrate, butyl acetate, ethyl 2-methylbutyrate, pentyl acetate, butyl butanoate, ethyl octanoate, and hexyl 2-butenoate. Nevertheless, similar results were demonstrated in coffee aroma [ 38 ] and dried jujube fruit [ 9 ]. For instance, a total of 8 and 88 volatiles were identified by FGC E-nose and SPME GC-MS in coffee, respectively.…”

Section: Discussionsupporting

confidence: 78%

“…Only one of the eight volatiles was detected by FGC E-nose and SPME-GC-MS. The remaining seven volatiles were unique to FGC E-nose [ 38 ]. In dried jujube fruit, the volatile compositions detected by FGC E-nose were also different from traditional SPME-GC-MS results [ 9 ].…”

Section: Discussionmentioning

confidence: 99%

“…The non-polar (MXT-5) and slightly polar (MXT-1701) columns were equipped in the FGC E-nose, and they were less effective to detect polar compounds than the frequently used DB-WAX column [ 9 ]. Another reason might be that isolated and identified volatile compounds in FGC E-nose contributed to the smell of volatile compounds [ 38 ]. In qualitative analysis, the ability of FGC E-nose was not as satisfactory as SPME-GC-MS.…”

Section: Discussionmentioning

confidence: 99%

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Characterization and Discrimination of Apples by Flash GC E-Nose: Geographical Regions and Botanical Origins Studies in China

Fauconnier

2022

Foods

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Forty-one apple samples from 7 geographical regions and 3 botanical origins in China were investigated. A total of 29 volatile compounds have been identified by flash GC E-nose. They are 17 esters, 5 alcohols, 3 aldehydes, 1 ketone, and 3 others. A principal component analysis was employed to study the relationship between varieties and volatiles. A partial least squares discriminant analysis (PLS-DA), stepwise linear discriminant analysis (SLDA), and decision tree (DT) are used to discriminate apples from 4 geographical regions (34 apple samples) and 3 botanical origins (36 apple samples). The most influential markers identified by PLS-DA are 2-hexadecanone, methyl decanoate, tetradecanal, 1,8-cineole, hexyl 2-butenoate, (Z)-2-octenal, methyl 2-methylbutanoate, ethyl butyrate, dimethyl trisulfide, methyl formate, ethanol, S(-)2-methyl-1-butanol, ethyl acetate, pentyl acetate, butyl butanoate, butyl acetate, and ethyl octanoate. From the present work, SLDA reveals the best discrimination results in geographical regions and botanical origins, which are 88.2% and 88.9%, respectively. Although machine learning DT is attempted to classify apple samples, the results are not satisfactory.

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Section: Discussionsupporting

confidence: 78%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Characterization and Discrimination of Apples by Flash GC E-Nose: Geographical Regions and Botanical Origins Studies in China

Fauconnier

2022

Foods

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“…The mono-or disaccharides were more likely to take part in the MR. Many studies have reported that aspartic acid, glutamate, cysteine, lysine and arginine react with glucose or maltose to generate color and aroma volatile compounds, and their reaction mechanisms are already elucidated [20][21][22][23][24].…”

Section: Trop J Pharm Res February 2018; 17(2): 304mentioning

confidence: 99%

Investigation of Maillard reaction involvement in the steam processing of <i>Panax Notoginseng</i> root

Li¹,

Liu²,

Huang³

et al. 2018

Trop. J. Pharm Res

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Purpose: To explore the possible mechanism of Maillard reaction (MR) involvement in the steam processing of Panax notoginseng (PN) root. Methods: PN root was soaked in water for 24 h and then steamed at 100 °C using an autoclave for 1, 2, 3, 4, 5 and 6 h, respectively. Several indicators associated with MR during steam processing were measured. The pH and absorbance at 420 nm (A420) of samples were measured using a pH meter and an ultraviolet-visible spectrophotometer, respectively. The contents of 5-hydroxy-methyl-furfural (5-HMF) and sugars were determined by high performance liquid chromatography (HPLC) while amino acids were evaluated using an automatic amino acid analyzer. Results: During PN root steam processing (0-6 h), pH value gradually decreased from 6.35 ± 0.02 to 5.88 ± 0.03 while A420 value gradually increased from 0.23 ± 0.01 to 0.44 ± 0.02. The levels of reducing sugars (maltose and glucose) and amino acids (aspartic acid, glutamate, cysteine, lysine and arginine) in PN root decreased after steaming for 6 h. However, the content of 5-HMF in PN root increased with increase in steaming time. Conclusion: The results indicate that MR occurs during steam processing of PN root, and the reaction mechanism might be closely related to the reaction between the reducing sugars and amino acids.

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“…In one study, ultra-performance liquid chromatography–time-of-flight mass spectrometry (UPLC-TOF-MS) revealed a marker substance for a coffee beverage spiked with acetaldehyde [ 5 ]. Flash gas chromatography electronic nose (FGC E-nose) can obtain a more convincing flavor assessment than a single assessment of aroma or volatile profiles [ 6 ].…”

Section: Introductionmentioning

confidence: 99%

Fast and Non-Destructive Profiling of Commercial Coffee Aroma under Three Conditions (Beans, Powder, and Brews) Using GC-IMS

Chen¹,

Chen²,

Cui³

et al. 2022

Molecules

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The flavor of coffee can be affected by the preparation parameters. In this investigation, the flavor profiles of three coffee brands under three conditions (bean, powder, and brew) were analyzed by gas chromatography—ion mobility spectrometry (GC-IMS) and the electronic nose (E-nose). The flavor results were further studied using multiple factor analysis (MFA). A total of 117 peaks were identified in all coffee samples by GC-IMS, and the principal component analysis (PCA) showed these coffee samples could be grouped and separated. A total of 37 volatile organic compounds (VOCs) were selected as biomarkers to distinguish coffee samples, including 5 aldehydes, 10 ketones, 8 alcohols, 2 acids, 4 esters, 5 furans, and 3 other compounds. The comparison between E-nose and GC-IMS data using partial least squares regression (PLSR) and MFA showed GC-IMS could present very close sample spaces. Compared with E-nose, GC–IMS could not only be used to classify coffee samples in a very short time but also provide VOC bio-markers to discriminate coffee samples.

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Effects of maltose and lysine treatment on coffee aroma by flash gas chromatography electronic nose and gas chromatography–mass spectrometry

Abstract: Thus, our results suggest that the combination of reagents changed overall aroma quality through a series of complex thermal reactions, especially the ratio of Lys/maltose over 2:1. © 2017 Society of Chemical Industry.

Cited by 7 publications

References 36 publications

Characterization and Discrimination of Apples by Flash GC E-Nose: Geographical Regions and Botanical Origins Studies in China

Characterization and Discrimination of Apples by Flash GC E-Nose: Geographical Regions and Botanical Origins Studies in China

Investigation of Maillard reaction involvement in the steam processing of <i>Panax Notoginseng</i> root

Fast and Non-Destructive Profiling of Commercial Coffee Aroma under Three Conditions (Beans, Powder, and Brews) Using GC-IMS

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