关键词: 山苍子, 精油, 抑菌活性, 精油成分鉴定, 相关性分析

Abstract: May Chang tree contains several species,including Litsea cubeba (Lour.) Pers.,Litsea mollis Hemsl. and Litsea cubeba var. formosana,in Lauraceae.As important aromatic tree species,they have wide application value in traditional Chinese medicine,natural spices and commodity products.In order to explore the inhibitory effects of different species of May Chang trees,five families of L. cubeba,L. mollis and L. cubebavar. formosana, respectively,were selected as biological replicates for analysis.The inhibition rate of essential oil against Fusarium oxysporum f. sp. fordii 1 was determined by growth rate method,and the antibacterial activities of essential oils against Escherichia coliand Listeria monocytogenes was valued using the agar disc diffusion method.Meanwhile,the gas chromatographymass spectrometer (GCMS) was used to detect the chemical components of essential oils.Moreover,the significant difference analysis among the chemical components and its correlation with inhibition rate were conducted by data processing system (DPS).The results showed that the average content of essential oil in L. cubeba was 6.13%,which was significantly higher than those of L. mollis and L. cubeba var. formosana.The average EC₅₀ value of L. cubeba essential oil (74.176 μL/L) was significantly lower than that in L. cubeba var. formosana and the MIC value (459.315 μL/L) was significantly lower than that in  L. mollis.In addition,a significant positive correlation between the citral content and the essential oil content was found;the content of citral and linalool were shown a significant positive correlation with the inhibition rate,respectively.In summary,the relative content of citral in essential oil can be used as a reliable index for screening highquality antimicrobial essential oil of May Chang trees.The data here provided a basis information for the development of botanical antimicrobial substances of May Chang trees.

Key words: May Chang tree, essential oil, antimicrobial activity, chemical component, correlation analysis