首页|基于电子鼻和HS-SPME-GC-MS的不同叮咬程度的紫金蝉茶鲜叶品质分析及判别

基于电子鼻和HS-SPME-GC-MS的不同叮咬程度的紫金蝉茶鲜叶品质分析及判别

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紫金蝉茶鲜叶的叮咬程度的判别是其加工过程中关键的一道工序,目前主要由人工对鲜叶的蜜香浓郁程度进行判别,但该方法存在生产效率低下的问题.采集新鲜的不同叮咬程度的紫金蝉茶鲜叶进行理化指标的测定,同时采用电子鼻和气相色谱技术对紫金蝉茶的挥发性成分进行检测.理化检测结果表明:随着叮咬程度的增加,茶多酚、儿茶素和可溶性糖含量呈现先增加后减少的趋势,并且在叮咬程度适中的时候达到最大值;氨基酸含量呈现正相关,最大增加量为0.27%,而咖啡碱含量呈现负相关,最大减小量为0.90%.这些变化主要是茶树抵抗茶小绿叶蝉叮咬的性能体现,并且对茶叶口感有一定的提升作用.顶空固相微萃取色谱-质谱分析的气味特征表明,不同叮咬程度的茶叶香气特征存在显著差异,出现了来自于3-苯丙酸乙酯以及环戊乙酸甲酯的蜂蜜气味.此外,基于偏最小二乘回归(PLSR)揭示了电子鼻传感器响应与HS-SPME-GC-MS检测到的香气物质之间的内在关系.通过支持向量机对降维后的电子鼻数据建模能够最大程度地辨别不同叮咬程度的茶叶.研究结果实现了紫金蝉茶特征香气的定性分析,为紫金蝉茶叮咬程度的鉴别提供了一种新方法.
Quality analysis and identification of Zijin Cicada tea fresh leaves with different biting degrees based on E-nose and HS-SPME-GC-MS
The identification of biting degree of Zijin Cicada tea fresh leaves is a key step in the production,which relies on manual assessment of the honey fragrance intensity in fresh leaves currently.However,this method suffers from the drawback of low production efficiency.In this study,fresh leaves with different biting degrees were collected to determine the physicochemical parameters,and the volatile components were detected by E-nose and high-performance headspace gas chromatography-mass spectrometry(HS-SPME-GC-MS).The results showed that:the tea polyphenols,catechins and soluble sugars increased initially and then decreased with the increase of biting de-gree,and the concentrations reached peak values at moderate biting degree;the amino acid content exhibited a posi-tive correlation with the biting degree,showing the maximum increase of 0.27%,while the caffeine content had a neg-ative correlation,with the maximum reduction of 0.90%.These changes mainly reflected the tea's response to insect infestation,consequently impacting the overall taste of the tea.HS-SPME-GC-MS results indicated significant differences in the aroma compounds of tea with different biting degrees,including ethyl 3-Phenylpropionate and Methyl cyclopentylacetate,which contributed to honey aromas.The partial least squares regression(PLSR)analysis revealed the intrinsic relationship between the electronic nose sensor response and the aroma substances detected by HS-SPME-GC-MS.The model of E-nose data after dimensionality reduction by support vector machine identified tea with different biting degrees.The results of the study enable the qualitative analysis of characteristic tea aromas and provide a novel approach for identifying the biting degree of Zijin Cicada tea.

Zijin Cicada teabiting degreeE-noseclassificationGC-MS

刘志禹、杨树恩、厉彦超、周巧仪、李露青、宋春芳、Li Zhenfeng、凌彩金

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江南大学机械工程学院/江苏省食品先进制造装备技术重点实验室,无锡 214122

山东碧海包装材料有限公司,临沂 276600

广东省农业科学院茶叶研究所/广东省茶树资源创新利用重点实验室,广州 510640

安徽农业大学茶业学院,合肥 230036

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紫金蝉茶 叮咬程度 电子鼻 判别 GC-MS

2024

安徽农业大学学报
安徽农业大学

安徽农业大学学报

CSTPCD
影响因子:0.412
ISSN:1672-352X
年,卷(期):2024.51(6)