[Objectives] To determine the aromatic components of Rosa davurica Pall. [Methods] 42 kinds of aromatic components were identified from the flowers of R. davurica by headspace solid phase microextraction( HS-SPME) com...[Objectives] To determine the aromatic components of Rosa davurica Pall. [Methods] 42 kinds of aromatic components were identified from the flowers of R. davurica by headspace solid phase microextraction( HS-SPME) combined with gas chromatography-mass spectrometry( GC-MS). The main compounds were alcohols( 54. 88%) and aldehydes( 19. 55%). [Results] The top five components with the highest relative content were phenylethyl alcohol( 12. 69%),geraniol( 9. 85%),citronellol( 8. 80%),nerol( 7. 84%) and 2-n-pentylfuran( 7. 45%). [Conclusions] Headspace solid phase microextraction( HS-SPME) combined with gas chromatography-mass spectrometry( GC-MS) can provide basis for further development and utilization of R. davurica.展开更多
In this report, gas chromatography-mass spectrometry (GC-MS) based non-targeted metabolomics is used to develop appropriate headspace solid phase microextractions (HS-SPME) to enhance the understanding of volatile com...In this report, gas chromatography-mass spectrometry (GC-MS) based non-targeted metabolomics is used to develop appropriate headspace solid phase microextractions (HS-SPME) to enhance the understanding of volatile complexity of flue-cured tobacco leaves. Non-targeted metabolic profiling of GC-MS shows that the extraction condition of HS-SPME at 100?C for 30 min provides a better metabolite profile than other extraction conditions tested. GC-MS and principal component analyses (PCA) show that among five types of fibers tested, 100 μm polydimethylsiloxane (PMDS), 65 μm polydimethylsiloxane/divinylbenzene (PMDS/DVB) and 75 μm carboxen/polydimethylsiloxane (CAR/ PMS) provide a better reproducible metabolite profile. Based on an appropriate PDMS extraction condition optimized, we use GC-MS analysis and PCA to compare metabolite profiles in flue-cured leaves of tobacco plants grown in North Carolina, India and Brazil, respectively. The resulting data of PCA show that the global metabolic profiles in North Carolina samples are separated from those in Brazil and India samples, two groups of which are characterized by a partially overlapped pattern. Several peaks that were differentially accumulated in samples were annotated to known metabolites by deconvolution analysis, such as norsolanadione, solavetivone and rishtin. Norsolanadione is detected only in Brazil samples. Solavetivone is detected in samples of India and Brazil but not in those of North Carolina. Rishtin is detected in samples of North Carolina and India but not in Brazil samples. These data indicate that not only can a non-targeted metabolic profiling approach enhance the understanding of volatile complexity, but also can identify marker volatile metabolites in tobacco leaves produced in different growth regions.展开更多
We have investigated the use of flash evaporation, headspace solid-phase microextraction (HS-SPME) and steam distillation (SD) as sample concentration and preparation techniques for the analysis of volatile constituen...We have investigated the use of flash evaporation, headspace solid-phase microextraction (HS-SPME) and steam distillation (SD) as sample concentration and preparation techniques for the analysis of volatile constituents present in Houttuynia cordata Thunb. The samples were analyzed by gas chromatography (GC) and identified by mass spectrometry (MS). Comparison studies were performed. It was found that the results obtained between Headspace solid-phase microextraction HS-SPME and SD techniques were in good agreement. Seventy-nine compounds in Houttuynia cordata Thunb were identified by MS. In flash evaporation, thirty-nine compounds were identified. Discrimination in the response for many constituents studied was not observed, which can be clearly observed in SD and HS-SPME techniques. As a conclusion, HS-SPME is a powerful tool for determining the volatile constitutes present in the Houttuynia cordata.展开更多
为探究油炸对牦牛肉风味物质及品质的影响,对不同油炸温度和时间下的牦牛肉进行感官评分、水分含量、色差值、质构指标的测定;采用顶空固相微萃取-气相色谱-质谱联用技术(headspace solid phase microextraction combined with gas chro...为探究油炸对牦牛肉风味物质及品质的影响,对不同油炸温度和时间下的牦牛肉进行感官评分、水分含量、色差值、质构指标的测定;采用顶空固相微萃取-气相色谱-质谱联用技术(headspace solid phase microextraction combined with gas chromatography-mass spectrometry,HS-SPME-GC-MS)分析油炸前后牦牛肉风味物质的种类和含量变化。结果表明:E_2组(160℃、80 s)牦牛肉感官评分、色差值、质构品质指标均最优。HS-SPME-GC-MS共鉴定出41种挥发性风味物质,包括醛类20种、醇类5种、酯类2种、酮类1种、呋喃类1种、烃类7种、有机酸类1种、其它类4种化合物;A组(参照组)检测出27种化合物,E_2组检测出38种化合物,两组牦牛肉中挥发性成分种类及相对含量有较大差异。根据香气特征雷达图得出,E_2组的香气种类更丰富。利用相对气味活度值对牦牛肉关键风味成分分析得出,A组关键挥发性风味物质有10种,E_2组关键挥发性风味物质有17种,其中反式-2-癸烯醛、壬醛、1-辛烯-3-醇相对气味活度值最大,分别为47.35、35.14、17.63,赋予油炸牦牛肉烤肉味、果香味、蘑菇香味。通过韦恩图得出,A组特有的挥发性风味物质有3种,E_2组特有的挥发性风味物质有14种,A组特有关键香气成分2种,E_2组特有关键香气成分9种。综合风味指标、质构指标和感官评价指标得出,油炸工艺对牦牛肉的风味及品质有明显提升。展开更多
采用顶空固相微萃取结合全二维气相色谱-质谱(Headspace solid-phase microextraction-comprehensive two dimensional gas chromatography/mass spectrometry HS-SPME-GC×GC-MS)技术,对4种保健黄酒(黄精酒、黄米酒、藜麦酒和苦荞...采用顶空固相微萃取结合全二维气相色谱-质谱(Headspace solid-phase microextraction-comprehensive two dimensional gas chromatography/mass spectrometry HS-SPME-GC×GC-MS)技术,对4种保健黄酒(黄精酒、黄米酒、藜麦酒和苦荞酒)中挥发性物质的种类、含量分进行分析,并且通过主成分分析法很好地区分不同原料的保健黄酒,找出重要的组分差异特征,探究其风味成分。结果表明,GC×GC-MS检测到4种保健黄酒中挥发性组分156种,选取匹配度大于800的挥发性组分,4种保健黄酒中共鉴定出140种挥发性组分,其中包括酯类、醇类、醛酮类、酸类、烃类、含氮化合物、苯系芳烃及其它化合物等。该方法可以通过鉴定黄酒挥发性组分,寻找挥发性组分与黄酒品质之间的关系,为保健黄酒的生产优化提供一定的理论依据。展开更多
基金Supported by Key Science and Technology Project of Gansu Province(1302NKDA028)Science and Technology Planning Project of Lanzhou(2010-1-239+2 种基金 2016-3-4)Talent Project of Lanzhou Science and Technology Bureau(2015-RC-87)Project of Science and Technology Cooperation between Gansu Academy of Agricultural Sciences and Local Areas(2017GAAS63)
文摘[Objectives] To determine the aromatic components of Rosa davurica Pall. [Methods] 42 kinds of aromatic components were identified from the flowers of R. davurica by headspace solid phase microextraction( HS-SPME) combined with gas chromatography-mass spectrometry( GC-MS). The main compounds were alcohols( 54. 88%) and aldehydes( 19. 55%). [Results] The top five components with the highest relative content were phenylethyl alcohol( 12. 69%),geraniol( 9. 85%),citronellol( 8. 80%),nerol( 7. 84%) and 2-n-pentylfuran( 7. 45%). [Conclusions] Headspace solid phase microextraction( HS-SPME) combined with gas chromatography-mass spectrometry( GC-MS) can provide basis for further development and utilization of R. davurica.
文摘In this report, gas chromatography-mass spectrometry (GC-MS) based non-targeted metabolomics is used to develop appropriate headspace solid phase microextractions (HS-SPME) to enhance the understanding of volatile complexity of flue-cured tobacco leaves. Non-targeted metabolic profiling of GC-MS shows that the extraction condition of HS-SPME at 100?C for 30 min provides a better metabolite profile than other extraction conditions tested. GC-MS and principal component analyses (PCA) show that among five types of fibers tested, 100 μm polydimethylsiloxane (PMDS), 65 μm polydimethylsiloxane/divinylbenzene (PMDS/DVB) and 75 μm carboxen/polydimethylsiloxane (CAR/ PMS) provide a better reproducible metabolite profile. Based on an appropriate PDMS extraction condition optimized, we use GC-MS analysis and PCA to compare metabolite profiles in flue-cured leaves of tobacco plants grown in North Carolina, India and Brazil, respectively. The resulting data of PCA show that the global metabolic profiles in North Carolina samples are separated from those in Brazil and India samples, two groups of which are characterized by a partially overlapped pattern. Several peaks that were differentially accumulated in samples were annotated to known metabolites by deconvolution analysis, such as norsolanadione, solavetivone and rishtin. Norsolanadione is detected only in Brazil samples. Solavetivone is detected in samples of India and Brazil but not in those of North Carolina. Rishtin is detected in samples of North Carolina and India but not in Brazil samples. These data indicate that not only can a non-targeted metabolic profiling approach enhance the understanding of volatile complexity, but also can identify marker volatile metabolites in tobacco leaves produced in different growth regions.
文摘We have investigated the use of flash evaporation, headspace solid-phase microextraction (HS-SPME) and steam distillation (SD) as sample concentration and preparation techniques for the analysis of volatile constituents present in Houttuynia cordata Thunb. The samples were analyzed by gas chromatography (GC) and identified by mass spectrometry (MS). Comparison studies were performed. It was found that the results obtained between Headspace solid-phase microextraction HS-SPME and SD techniques were in good agreement. Seventy-nine compounds in Houttuynia cordata Thunb were identified by MS. In flash evaporation, thirty-nine compounds were identified. Discrimination in the response for many constituents studied was not observed, which can be clearly observed in SD and HS-SPME techniques. As a conclusion, HS-SPME is a powerful tool for determining the volatile constitutes present in the Houttuynia cordata.
文摘为探究油炸对牦牛肉风味物质及品质的影响,对不同油炸温度和时间下的牦牛肉进行感官评分、水分含量、色差值、质构指标的测定;采用顶空固相微萃取-气相色谱-质谱联用技术(headspace solid phase microextraction combined with gas chromatography-mass spectrometry,HS-SPME-GC-MS)分析油炸前后牦牛肉风味物质的种类和含量变化。结果表明:E_2组(160℃、80 s)牦牛肉感官评分、色差值、质构品质指标均最优。HS-SPME-GC-MS共鉴定出41种挥发性风味物质,包括醛类20种、醇类5种、酯类2种、酮类1种、呋喃类1种、烃类7种、有机酸类1种、其它类4种化合物;A组(参照组)检测出27种化合物,E_2组检测出38种化合物,两组牦牛肉中挥发性成分种类及相对含量有较大差异。根据香气特征雷达图得出,E_2组的香气种类更丰富。利用相对气味活度值对牦牛肉关键风味成分分析得出,A组关键挥发性风味物质有10种,E_2组关键挥发性风味物质有17种,其中反式-2-癸烯醛、壬醛、1-辛烯-3-醇相对气味活度值最大,分别为47.35、35.14、17.63,赋予油炸牦牛肉烤肉味、果香味、蘑菇香味。通过韦恩图得出,A组特有的挥发性风味物质有3种,E_2组特有的挥发性风味物质有14种,A组特有关键香气成分2种,E_2组特有关键香气成分9种。综合风味指标、质构指标和感官评价指标得出,油炸工艺对牦牛肉的风味及品质有明显提升。
文摘采用顶空固相微萃取结合全二维气相色谱-质谱(Headspace solid-phase microextraction-comprehensive two dimensional gas chromatography/mass spectrometry HS-SPME-GC×GC-MS)技术,对4种保健黄酒(黄精酒、黄米酒、藜麦酒和苦荞酒)中挥发性物质的种类、含量分进行分析,并且通过主成分分析法很好地区分不同原料的保健黄酒,找出重要的组分差异特征,探究其风味成分。结果表明,GC×GC-MS检测到4种保健黄酒中挥发性组分156种,选取匹配度大于800的挥发性组分,4种保健黄酒中共鉴定出140种挥发性组分,其中包括酯类、醇类、醛酮类、酸类、烃类、含氮化合物、苯系芳烃及其它化合物等。该方法可以通过鉴定黄酒挥发性组分,寻找挥发性组分与黄酒品质之间的关系,为保健黄酒的生产优化提供一定的理论依据。
