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http://dx.doi.org/10.3839/jabc.2021.019

Variation in essential oil composition and antimicrobial activity among different genotypes of Perilla frutescens var. crispa  

Ju, Hyun Ju (Department of Industrial Plant Science and Technology, College of Agricultural, Life and Environmental Sciences, Chungbuk National University)
Bang, Jun-Hyoung (Department of Industrial Plant Science and Technology, College of Agricultural, Life and Environmental Sciences, Chungbuk National University)
Chung, Jong-Wook (Department of Industrial Plant Science and Technology, College of Agricultural, Life and Environmental Sciences, Chungbuk National University)
Hyun, Tae Kyung (Department of Industrial Plant Science and Technology, College of Agricultural, Life and Environmental Sciences, Chungbuk National University)
Publication Information
Journal of Applied Biological Chemistry / v.64, no.2, 2021 , pp. 127-131 More about this Journal
Abstract
Perilla frutescens var. crispa (Pfc), a herb belonging to the mint family (Lamiaceae), has been used for medicinal and aromatic purposes. In the present study, we analyzed the variation in the chemical composition of essential oils (EOs) obtained from five different genotypes of Pfc collected from different regions. Based on principal component analysis (PCA) and hierarchical cluster analysis (HCA), we identified three groups: PA type containing perillaldehyde, PP type containing dillapiole, and 2-acetylfuran type. To assess the correlation between EO components and antimicrobial activities, we compared classification results generated by PCA and HCA based on antimicrobial activity values. The findings suggested that the major compounds obtained from EOs of Pfc are responsible for their antimicrobial activities. Chemotypes of Pfc plants are essentially qualitative traits that are important for breeders. The present findings provide potential information for breeding Pfc as an antimicrobial agent.
Keywords
Antimicrobial activity; Chemotype; Essential oil; Perilla frutescens var. crispa; Principal component analysis;
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