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食品研究与开发:2020,41(13):93-100
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顶空固相微萃取茶油挥发性成分的响应面优化
(1.广东省森林培育与保护利用重点实验室,广东广州510520;2.广东省林业科学研究院,广东广州510520)
Optimization of Headspace Solid Phase Micro-extraction of Volatile Components from Camellia Oleifera Seeds Oil by Response Surface Methodology
(1.Key Laboratory of Forest Cultivation and Protection and Utilization,Guangzhou 510520,Guangdong,China;2.Guangdong Academy of Forestry,Guangzhou 510520,Guangdong,China)
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投稿时间:2019-07-29    
中文摘要: 挥发性成分组成及含量是油茶籽油特色风味形成的重要影响因素,结合顶空固相微萃取技术(headspace solid phase micro-extraction,HS-SPME)和气相色谱-质谱法(gas chromatography-mass spectrometry,GC/MS),探讨茶油挥发性成分的最佳萃取条件。在单因素试验基础上,选用50/30 μm DVB/CAR/PDMS萃取头,进行响应面优化分析HS-SPME萃取条件。结果表明,HS-SPME-GC/MS法分析茶油挥发性成分的最佳条件为萃取温度70℃、萃取时间31 min,解析时间3min。此条件下检测出70种茶油挥发性物质,与预测值偏差2.66%,总峰面积2.16×107,其中醛类、酮类、酯类、烷烃类、醇类、酸类和萜烯类分别含有16、12、12、12、7、6和5种挥发性化合物,其相对含量分别为39.95%、7.42%、3.07%、6.87%、6.50%、33.70%和2.47%。
Abstract:Composition and content of volatile components are important factors affecting the formation of characteristic flavor of Camellia oleifera seeds oil that were analyzed by headspace solid phase micro-extraction(HS-SPME)and gas chromatography-mass spectrometry (GC/MS),and the optimum extraction conditions were discussed in this study.On the basis of single factor experiment,50/30 μm DVB/CAR/PDMS extraction fiber head was selected to optimize the HS-SPME extraction conditions by response surface analysis.The results showed that the optimum conditions for the volatile components analysis of C.oleifera oil by HS-SPME-GC/MS were 70℃ of extraction temperature,31 min of extraction time and 3 min of resolution time.Under these conditions,70 kinds of volatile components in C.oleifera oil were detected,with a deviation of 2.66%from the predicted value.The total peak area was 2.16×107.The kinds of volatile components of aldehydes,ketones,alcohols,alkanes,acids,esters and alkenes were 16,12,12,12,7,6 and 6,respectively,the relative contents of which were 39.95%,7.42%,3.07%,6.87%,6.50%,33.70%and 2.47%,respectively.
文章编号:202013015     中图分类号:    文献标志码:
基金项目:广东省林业科技创新项目(2018KJCX036)
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