• Title/Summary/Keyword: SPME/GC-MS

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Flavor Components of Mideoduck (Styela clava) (미더덕의 향기 성분)

  • Choi, Byeong-Dae;Oh, Bong-Se;Kang, Seok-Joong
    • Journal of Life Science
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    • v.20 no.11
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    • pp.1648-1655
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    • 2010
  • The flavor extracts of Mideoduck muscle and its juices were concentrated by simultaneous distillation and extraction (SDE) and solid-phase microextraction (SPME) methods. Each component present in the extracts was identified with GC and GC-MS by the n-paraffin hydrocarbon retention index and standard MS library data system. By SDE, $371.3\;{\mu}g/g$ of hexanal, $80.1\;{\mu}g/g$ of 1-tridecanol, $72.1\;{\mu}g/g$ of (Z)-4,5-dimethylhex-2-en-4-ol with other alcohols, aldehydes and acids were present in the flavor extracts, with the alcohols having the highest composition and being the most important factor in Mideoduck muscle flavor. By SPME, 9 alcohols, 1 acid, 1 aldehyde, 1 hydrocarbon, 1 ester, 1 amine and 2 ketones were detected in the extracts, with alcohol such as 1-nonanol, 1-decanol and 1-tridecanol as the major components. In SPME, the muscle sample, consisting of $31.6\;{\mu}g/g$ of 1-nonanol, $20.3\;{\mu}g/g$ of (E)-2-butenedioic acid dibutylester, and $26.7\;{\mu}g/g$ of heptadecanoic acid made up the 62.1% of total flavor extracts of Mideoduck muscle. The results of the SPME methods were similar to the composition of the raw material flavor of the sample even at a low concentration.

Analysis of Volatile Flavor Compounds in Jeju Apple Mango by Using Different Extraction Methods (추출방법에 따른 제주산 애플망고의 휘발성 향기성분 분석)

  • An, Mi-Ran;Keum, Young-Soo;Lee, Si-Kyung
    • Journal of the Korean Society of Food Science and Nutrition
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    • v.44 no.5
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    • pp.775-783
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    • 2015
  • This study was carried out to investigate the physicochemical properties and volatile ingredients of Jeju Apple mango subjected to different extraction methods and GC/MS. The crude protein, fat, and ash contents were $0.22{\pm}0.01$, $0.09{\pm}0.00$, and $0.27{\pm}0.02%$, respectively, and contents of free sugar increased in the order of sucrose, fructose, and glucose, whereas maltose, lactose, and galactose were not detected. The numbers of volatile flavor compounds obtained by the SE (solvent extraction), SDE (simultaneous steam distillation extraction), and SPME (solid-phase micro-extraction) methods were 51, 59, and 71, respectively. The percentages of extracted volatile flavor compounds in mango were 11.44, 15.68, and 73.54% by the SE, SDE, and SPME methods, respectively. The most abundant compounds found in Jeju Apple mango were terpenes and their derivatives, which accounted for 44.49~94.57% of total volatiles obtained. SPME method was considered to be the most effective extraction method in terms of the numbers of detected compounds and their amounts. ${\delta}$-3-Carene was identified as the dominant compound in mango, whereas ${\alpha}$-phellandrene, ${\gamma}$-terpinene, trans-${\beta}$-ocimene, ${\alpha}$-terpinolene, limonene, ${\alpha}$-pinene, and furaneol were the next important compounds.

Volatile Compounds of Elsholtzia splendens (꽃향유의 휘발성 향기성분)

  • Lee, So-Young;Chung, Mi-Sook;Kim, Mi-Kyung;Baek, Hyung-Hee;Lee, Mi-Soon
    • Korean Journal of Food Science and Technology
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    • v.37 no.3
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    • pp.339-344
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    • 2005
  • Volatile compounds, isolated from Elsholtzia splendens using simultaneous steam distillation extraction (SDE) and headspace solid phase microextraction (HS-SPME), were analyzed by gas chromatography/mass spectrometry(GC-MS). Twenty-nine compounds, comprising 3 aldehydes, 7 alcohols, 11 hydrocarbons, 5 ketones, and 3 miscellaneous ones, were tentatively identified from volatile compounds of Elsholtzia splendens flowers. From leaves, 30 compounds, comprising 3 aldehydes, 6 alcohols, 11 hydrocarbons, 6 ketones, and 11 miscellaneous ones, were tentatively identified. Volatile compounds extracted by HS-SPME in E. splendens flowers were 3 alcohols, 18 hydrocarbons, 3 ketones, and 2 miscellaneous ones. In leaves, 31 compounds, comprising 7 alcohols, 15 hydrocarbons, 7 ketones, and 2 miscellaneous ones, were tentatively identified. Major volatile compounds identified by SDE and HS-SPME were naginataketone and elsholtziaketone, which were identified as aroma-active compounds, representing characteristic aroma of E. splendens.

The Global Volatile Signature of Veal via Solid-phase Microextraction and Gas Chromatography-mass Spectrometry

  • Wei, Jinmei;Wan, Kun;Luo, Yuzhu;Zhang, Li
    • Food Science of Animal Resources
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    • v.34 no.5
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    • pp.700-708
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    • 2014
  • The volatile composition of veal has yet to be reported and is one of the important factors determining meat character and quality. To identify the most important aroma compounds in veal from Holstein bull calves fed one of three diets, samples were subjected to solid-phase microextraction (SPME) combined with gas chromatography-quadrupole mass spectrometry (GC-MS). Most of the important odorants were aldehydes and alcohols. For group A (veal calves fed entirely on milk for 90 d before slaughter), the most abundant compound class was the aldehydes (52.231%), while that was alcohols (26.260%) in group C (veal calves fed starter diet for at least 60 d before slaughter). In both classes the absolute percentages of the volatile compounds in veal were different indicating that the veal diet significantly (p<0.05) affected headspace volatile composition in veal as determined by principal component analysis (PCA). Twenty three volatile compounds showed significance by using a partial least-squared discriminate analysis (PLS-DA) (VIP>1). The establishment of the global volatile signature of veal may be a useful tool to define the beef diet that improves the organoleptic characteristics of the meat and consequently impacts both its taste and economic value.

Volatile Metabolic Markers for Monitoring Pectobacterium carotovorum subsp. carotovorum Using Headspace Solid-Phase Microextraction Coupled with Gas Chromatography-Mass Spectrometry

  • Yang, Ji-Su;Lee, Hae-Won;Song, Hyeyeon;Ha, Ji-Hyoung
    • Journal of Microbiology and Biotechnology
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    • v.31 no.1
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    • pp.70-78
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    • 2021
  • Identifying the extracellular metabolites of microorganisms in fresh vegetables is industrially useful for assessing the quality of processed foods. Pectobacterium carotovorum subsp. carotovorum (PCC) is a plant pathogenic bacterium that causes soft rot disease in cabbages. This microbial species in plant tissues can emit specific volatile molecules with odors that are characteristic of the host cell tissues and PCC species. In this study, we used headspace solid-phase microextraction followed by gas chromatography coupled with mass spectrometry (HS-SPME-GC-MS) to identify volatile compounds (VCs) in PCC-inoculated cabbage at different storage temperatures. HS-SPME-GC-MS allowed for recognition of extracellular metabolites in PCC-infected cabbages by identifying specific volatile metabolic markers. We identified 4-ethyl-5-methylthiazole and 3-butenyl isothiocyanate as markers of fresh cabbages, whereas 2,3-butanediol and ethyl acetate were identified as markers of soft rot in PCC-infected cabbages. These analytical results demonstrate a suitable approach for establishing non-destructive plant pathogen-diagnosis techniques as alternatives to standard methods, within the framework of developing rapid and efficient analytical techniques for monitoring plant-borne bacterial pathogens. Moreover, our techniques could have promising applications in managing the freshness and quality control of cabbages.

Volatile Compounds for Discrimination between Beef, Pork, and Their Admixture Using Solid-Phase-Microextraction-Gas Chromatography-Mass Spectrometry (SPME-GC-MS) and Chemometrics Analysis

  • Zubayed Ahamed;Jin-Kyu Seo;Jeong-Uk Eom;Han-Sul Yang
    • Food Science of Animal Resources
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    • v.44 no.4
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    • pp.934-950
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    • 2024
  • This study addresses the prevalent issue of meat species authentication and adulteration through a chemometrics-based approach, crucial for upholding public health and ensuring a fair marketplace. Volatile compounds were extracted and analyzed using headspace-solid-phase-microextraction-gas chromatography-mass spectrometry. Adulterated meat samples were effectively identified through principal component analysis (PCA) and partial least square-discriminant analysis (PLS-DA). Through variable importance in projection scores and a Random Forest test, 11 key compounds, including nonanal, octanal, hexadecanal, benzaldehyde, 1-octanol, hexanoic acid, heptanoic acid, octanoic acid, and 2-acetylpyrrole for beef, and hexanal and 1-octen-3-ol for pork, were robustly identified as biomarkers. These compounds exhibited a discernible trend in adulterated samples based on adulteration ratios, evident in a heatmap. Notably, lipid degradation compounds strongly influenced meat discrimination. PCA and PLS-DA yielded significant sample separation, with the first two components capturing 80% and 72.1% of total variance, respectively. This technique could be a reliable method for detecting meat adulteration in cooked meat.

Discriminating Eggs from Two Local Breeds Based on Fatty Acid Profile and Flavor Characteristics Combined with Classification Algorithms

  • Dong, Xiao-Guang;Gao, Li-Bing;Zhang, Hai-Jun;Wang, Jing;Qiu, Kai;Qi, Guang-Hai;Wu, Shu-Geng
    • Food Science of Animal Resources
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    • v.41 no.6
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    • pp.936-949
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    • 2021
  • This study discriminated fatty acid profile and flavor characteristics of Beijing You Chicken (BYC) as a precious local breed and Dwarf Beijing You Chicken (DBYC) eggs. Fatty acid profile and flavor characteristics were analyzed to identify differences between BYC and DBYC eggs. Four classification algorithms were used to build classification models. Arachidic acid, oleic acid (OA), eicosatrienoic acid, docosapentaenoic acid (DPA), hexadecenoic acid, monounsaturated fatty acids (MUFA), polyunsaturated fatty acids (PUFA), unsaturated fatty acids (UFA) and 35 volatile compounds had significant differences in fatty acids and volatile compounds by gas chromatography-mass spectrometry (GC-MS) (p<0.05). For fatty acid data, k-nearest neighbor (KNN) and support vector machine (SVM) got 91.7% classification accuracy. SPME-GC-MS data failed in classification models. For electronic nose data, classification accuracy of KNN, linear discriminant analysis (LDA), SVM and decision tree was all 100%. The overall results indicated that BYC and DBYC eggs could be discriminated based on electronic nose with suitable classification algorithms. This research compared the differentiation of the fatty acid profile and volatile compounds of various egg yolks. The results could be applied to evaluate egg nutrition and distinguish avian eggs.