基于电子鼻技术的豨莶草炮制前后气味比较

Odor Comparison of Unprocessed and Processed Herba Siegesbeckiae by Electronic Nose Technique

目的:揭示豨莶草炮制前后气味的变化规律。方法:通过电子鼻检测豨莶草炮制前后气味在传感器上的响应值,采用判别因子分析(DFA)及单类成分判别分析(SIMCA)对特征数据进行分析。结果:建立了豨莶草生品与炮制品的电子鼻检测方法,载气为合成干燥空气,空气发生器供给,流速150 mL·min-1,顶空产生温度60℃,时间30 min,搅动速度250 r·min-1,注射体积2 mL,获取时间2 min,延滞时间6 min。豨莶草炮制前后的气味在传感器LY2/gCT的响应值差异率-82%;DFA判别模型可将豨莶草炮制前后的气味进行较好的分类,将豨莶草生品与炮制品分成2个区域,左侧区域为生品,右侧区域为炮制品;SIMCA模型为有效模型,经交叉有效性验证的得分92。结论:豨莶草炮制前后气味存在显著性差异,且差异可根据电子鼻测得的气味特征参数以数值的形式表述。

Objective： To reveal variation regular patterns in odor of unprocessed and processed Herba Siegesbeckiae. Method： Evaporability composition of unprocessed and processed Herba Siegesbeckiae was sampled from headspace of emanating and then response values were obtained. Discriminant factor analysis （DFA） and soft independent modeling of class analogy （SIMCA） were used to analyze characteristic parameters. Result： Electronic nose detection methods of unprocessed and processed Herba Siegesbeckiae were established, synthesis dry air supplied by air generators as carrier gas, flow rate 150 mL-min-1, headspace temperature 60 ~C ,time 30 rain, agitation speed 250 r ＂min-1 , injection volume 2 mL, acquisition time 2 min, lag time 6 min. Discrepancy rate of response values from sensor LY2/gCT in odor of unprocessed and processed Herba Siegesbeckiae was - 82% ; Odor of unprocessed and processed Herba Siegesbeckiae could be divided into two areas by DFA discriminant model, the left area was unprocessed products, the right area was processed products; SIMCA was effective model, score was 92 by cross-validation. Conclusion： Odor of unprocessed and processed Herba Siegesbeckiae had a significant difference, and the difference could be digitalized according to odor characteristic parameters tested with electronic nose.