基于化学计量学分析堆青时间对白茶香气的影响

堆青是一种有利于茶叶香气转化的手段，本文研究了堆青时间对白茶香气的影响，并分析了感官香气与化合物变化间的联系。感官审评结果表明，堆青使白茶甜香增强而鲜度下降。通过顶空固相微萃取和气相色谱-串联质谱联仪从样品中表征出55种化合物，它们的组成受堆青影响甚微，但含量变化显著。基于化学计量学方法筛选并分析37种差异化合物；主成分分析和层次聚类分析均可区分不同堆青处理的样品，其中堆青前后样品间差异明显。苯乙醇、苯甲醛和苯乙醛等随堆青的总体上升，以及β-环柠檬醛、反-2-辛烯醛和α-紫罗兰酮在堆青后含量的普遍增加，可能是引起甜香增强的原因。而正己醇、反,反-2,4-己二烯醛和辛醛在堆青后含量的普遍减少，则可能与鲜度下降相关。32 h的堆青较有利于白茶香气的发展。化学计量学方法的引入使得样品间差异信息的获取更有效率。
Pile-up is a tea manufacture process,which is beneficial to the transformation of tea aroma.. In this study, the effect of pile-up processing duration on the white tea aroma was investigated, and the relationship between sensory aroma and the changes of volatile organic compounds (VOCs) along different durations was analyzed. The sensory evaluation results indicated that pile-up treatment could improve sweetness of white tea, but decreased freshness. A total of 55 VOCs were characterized through headspace-solid phase micro-extraction (HS-SPME) coupled with gas chromatography-triple quadrupole mass spectrometry (GC/MS/MS). The VOCs profiles showed that pile-up had little effect on the composition changes, but the content changed significantly. Chemometric approaches were applied to select and analyze the 37 differential VOCs patternsin white tea. The results showed that all samples of different pile-up treatments were distinguished based on the principle component analysis and hierarchical cluster analysis, of which the difference between samples was obvious before and after pile-up processing. The content of 2-phenylethanol, benzaldehyde, phenylacetaldehyde increased after pile-up treatment, as well as the content of β-cyclocitral, (E)-2-octenal and α-ionone widely increased in post-pile-up samples, which might be the cause of stronger sweetness flavor. However, the content of 1-hexanol, (E,E)-2,4-hexadienal and octanal in post-pile-up samples decreased widely, which might be related to the reduction of freshness. The 32h pile-up was considered as the optimum duration for processing white tea. The introduction of chemometric approaches in VOCs analysis facilitated in revealing the variations and exploring the biochemical patterns among samples.