Monitoring alkyl pyrazines in roasted hazelnuts by SHS-GC-IMS: IMS response assessment and standardization

Mazzucotelli, Maria; Khomenko, Iuliia; Betta, Emanuela; Cetto, Irene; Farneti, Brian; Gabetti, Elena; Cavallero, Andrea; Aprea, Eugenio; Biasioli, Franco

doi:10.1016/j.talanta.2023.124568

Cited by 7 publications

(5 citation statements)

References 17 publications

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“…In addition, there are also certain separation results among other varieties. Among them, ZL1 and ZL2 are in one group, and ZM1 and ZM2 are in one group, which shows that this classification analysis can help trace the origin of seeds [41]. Subsequently, through PLS-DA model construction, cross-validation and confidence testing were conducted on the volatile compounds that caused the sample differences [42], and it was concluded that 20 substances had a significant contribution to the differences between samples (Figure 7).…”

Section: Discussionmentioning

confidence: 91%

Analysis and Identification of Differences in Volatile Components of Various Alfalfa Seeds Based on GC-IMS

Zhao,

Zhu,

Yang

et al. 2024

Agronomy

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Volatile components are one key factor in sample identification, differential analysis, quality control and origin traceability. In order to identify and analyze the differences in volatile substances in different alfalfa seeds, this study used gas chromatography–ion mobility spectrometry (GC-IMS), combined with the Gallery Plot plug-in, and PCA, PLS-DA and other analysis methods. In this way, a comprehensive analysis of volatile components in 10 alfalfa seeds, including aerospace varieties, was conducted. A comparative analysis of the characteristics of different sample compounds using topographic maps and fingerprints led to isolation of 48 kinds of 54 volatile compounds. Among them, esters (9 types), olefins (8 types), ketones (8 types), alcohols (6 types) and aldehydes (6 types) were found to be the most abundant volatile compounds in alfalfa seeds. At the same time, PCA and PLS-DA analysis models showed that esters, ketones and alcohols were the main volatiles causing the differences among alfalfa seeds. Among them, the content of various substances in the ZT2 and ZT3 aerospace varieties were higher than that of other varieties, while the types and contents of volatiles in ZT1, ZM2 and GN3 were relatively low. Therefore, in combination with the differences in maturity of each sample, the 10 varieties of alfalfa were finally divided into three categories, and the varieties of the same series were basically classified into one category. This provides a basis and convenience for future seed screening, identification, traceability and forage breeding.

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Section: Discussionmentioning

confidence: 91%

Analysis and Identification of Differences in Volatile Components of Various Alfalfa Seeds Based on GC-IMS

Zhao,

Zhu,

Yang

et al. 2024

Agronomy

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“…44 Pyrazines impart a baked-like flavor to dairy products. 45 These volatile flavor compounds jointly combine to produce the characteristic flavor of KYS-164 fermented milk.…”

Section: Resultsmentioning

confidence: 99%

“…44 Pyrazines impart a baked-like flavor to dairy products. 45 These volatile flavor compounds jointly combine to produce the characteristic flavor of KYS-164 fermented milk. Fingerprints of volatile substances in the samples showed that 2-methylisoborneol, isobutyl 3-methylbutanoate, 2-butanone, 2-heptanone, methoxybenzene and (E,E)-2,4-hexadiena were dominant aroma components originally present in milk (Fig.…”

Section: Papermentioning

confidence: 99%

The composition of Tibetan kefir grain TKG-Y and the antibacterial potential and milk fermentation ability of S. warneri KYS-164 screened from TKG-Y

Guo,

He,

Cheng

et al. 2024

Food Funct.

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“…Var ID (Primary) analysis is used to screen the main volatile diference components between GGEC and its diferent processed products through the value of VIP >1 [15]. SP and QC were analyzed by OPLS-DA, and the three key evaluation indicators of OPLS-DA model quality, R 2 Xcum � 0.974, R 2 Ycum � 0.992, and Q 2 cum � 0.971, showed that the samples were well clustered and signifcantly separated [9]. Components with a VIP value greater than 1 can signifcantly afect the classifcation of SP and QC.…”

Section: Principal Component Analysis (Pca) Pca Analysis Ofmentioning

confidence: 99%

“…Gas chromatography-ion mobility spectrometry (GC-IMS) is a volatile substance detection method that uses different ions with different mobilities under the same conditions to make different ions have different drift time through the electric field, thus achieving sample separation [ 8 ]. GC-IMS provides a nonselective response to several common chemical functional groups (alcohols, amines, ketones, and aldehydes) in the positive ion mode, so that most aroma compounds can be detected by it [ 9 ]. GC-IMS is a widely used technique in various fields such as food, agriculture, and pharmaceuticals.…”

Section: Introductionmentioning

confidence: 99%

Gas Chromatographic-Ion Mobility Spectrometry Combined with Chemometrics to Study the Changes in Characteristic Odor Components of Galli gigerii Endothelium Corneum in Different Processing Methods

Zhao

Zhang

et al. 2023

Journal of Analytical Methods in Chemistry

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Galli gigerii endothelium corneum (GGEC) is a traditional Chinese medicine commonly used in clinical practice to treat various conditions such as indigestion, vomiting, spermatorrhea, and enuresis. In this study, the volatile components of different concoctions of GGEC were examined by gas chromatography-ion mobility spectrometry (GC-IMS), and the changes of the components were compared by fingerprinting, combined with principal component analysis (PCA) and orthogonal partial least squares-discriminant analysis (OPLS-DA) to analyze the main volatile components and find out the different markers that can distinguish the different concoctions of GGEC. In the result, the GC-IMS fingerprints of GGEC and its different concoctions showed differences in their volatile components, of which 49 volatiles were clearly characterized, with some components including monomers and dimers. The characteristic volatile components of raw GGEC (SP) were n-nonanal, (E)-2-octenal, beta-ocimene, 2-ethyl-1-hexanol, etc. The characteristic volatile components of stir-fried GGEC (QC) are heptanal, 2-octanol, (E)-2-heptenal, etc. The characteristic volatile components of sand ironing GGEC (ST) are isoamyl acetate, decanal, cyclohexanone, 2-ethyl pyrazine, etc. The characteristic volatile components of stir-fried GGEC with vinegar (CZ) are thiazole, linalool, 2,3,5-trimethylpyrazine, etc. The characteristic volatile components of stir-fried GGEC with milk (FH) are 2-methylbutanoic acid, ethyl acetate, ethyl 2-hydroxypropanoate, butyl acetate, etc. By chemometric analysis, components such as n-nonanal, (E)-2-octenal, 2-pentyl-furan, butanal, 1,4-dioxane, and 2-methylpropanoic acid could be used as difference markers to distinguish different concoction products of GGEC. Furthermore, by analyzing different volatile compounds, we can examine the changes in volatile components during processing of GGEC, which can provide experimental data for the identification and establishment of quality standards.

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Monitoring alkyl pyrazines in roasted hazelnuts by SHS-GC-IMS: IMS response assessment and standardization

Cited by 7 publications

References 17 publications

Analysis and Identification of Differences in Volatile Components of Various Alfalfa Seeds Based on GC-IMS

Analysis and Identification of Differences in Volatile Components of Various Alfalfa Seeds Based on GC-IMS

The composition of Tibetan kefir grain TKG-Y and the antibacterial potential and milk fermentation ability of S. warneri KYS-164 screened from TKG-Y

Gas Chromatographic-Ion Mobility Spectrometry Combined with Chemometrics to Study the Changes in Characteristic Odor Components of Galli gigerii Endothelium Corneum in Different Processing Methods

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