本文以花椒油得率为指标，通过响应面法优化超临界CO2法萃取花椒挥发油工艺，并利用GC-MS分析挥发油的成分，同时以水蒸气蒸馏法作对比。结果表明，当温度42 ℃，压力30 MPa，提取180 min时，超临界CO2法的得率高达12.70%，是水蒸气蒸馏法得率的2.27倍。GC-MS分析发现两种提取方法所得挥发油的组成相似，含量差异较大，主要成分有花椒油素（32.99%/10.56%）、芳樟醇（4.68%/4.84%）、桉叶油醇（3.92%/5.84%）、α-松油醇（4.55%/7.04%）、4-萜烯醇（2.95%/10.42%）、乙酸松油酯（5.19%/7.24%）、薄荷酮（5.40%/4.41%）、茴香脑（2.91%/3.73%）等，其中超临界CO2法所得挥发油中的花椒油素含量最高，达到32.99%。这说明与传统的水蒸气蒸馏法相比，超临界CO2萃取法的提取效率更高，而且所得挥发油含有高含量的花椒油素，这为花椒油素的提纯，花椒挥发油的开发利用提供了参考。

As compared with steam distillation, the volatile oil from Zanthoxylum bungeanum Maxim. was extracted by supercritical CO2 extraction (SCE) and identified by GC-MS. Taking the yield of volatile oil as the evaluation index, the extraction process was optimized by response surface method. The experimental results showed that the essential oil yield was as high as 12.70% when the sample was extracted by the supercritical CO2 extraction method for 180 min at 42 ℃ and 30 MPa, which was 2.27 times as that obtained by steam distillation (SD). The chemical composition in the essential oils obtained by SCE and SD were similar but with very different contents analyzed by GC-MS. The main constituents were xanthoxylin (32.99%/10.56%), linalool (4.68%/4.84%), eucalyptol (3.92%/5.84%), α.-terpineol (4.55%/7.04%), terpinen-4-ol (2.95%/10.42%), terpinyl acetate (5.19%/7.24%), piperitone (5.40%/4.41%) and anethole(2.91%/3.73%). The relative contents of the components in the essential oils were determined with area normalization method. Among them, the relative content of xanthoxylin in the volatile oil obtained by SCE was the highest (32.99%). It showed that the extraction yield of the essential oil extracted by SCE was much higher, compared with traditional steam distillation. Moreover, the content of xanthoxylin, which is the characteristic chemical constituent of volatile oil from Zanthoxylum bungeanum Maxim., was very high. This is beneficial for the purification and manufacture of xanthoxylin. Our results provide a foundation for the development and utilization of volatile oil from Zanthoxylum bungeanum Maxim.

湖南省自然科学基金项目（2017JJ3342）；长沙市科技计划项目（kc1809036）；长沙学院2019年度大学生创新创业训练计划项目