Exploring Volatile Organic Compounds in Rhizomes and Leaves of Kaempferia parviflora Wall. Ex Baker Using HS-SPME and GC–TOF/MS Combined with Multivariate Analysis

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Abstract

Volatile organic compounds (VOCs) play an important role in the biological activities of the medicinal Zingiberaceae species. In commercial preparations of VOCs from Kaempferia parviflora rhizomes, its leaves are wasted as by-products. The foliage could be an alternative source to rhizome, but its VOCs composition has not been explored previously. In this study, the VOCs in the leaves and rhizomes of K. parviflora plants grown in a growth room and in the field were analyzed using the headspace solid-phase microextraction (HS-SPME) method coupled with gas chromatography and time-of-flight mass spectrometry (GC-TOF-MS). The results showed a total of 75 and 78 VOCs identified from the leaves and rhizomes, respectively, of plants grown in the growth room. In the field samples, 96 VOCs were detected from the leaves and 98 from the rhizomes. These numbers are higher compared to the previous reports, which can be attributed to the analytical techniques used. It was also observed that monoterpenes were dominant in leaves, whereas sesquiterpenes were more abundant in rhizomes. Principal component analysis (PCA) revealed significantly higher abundance and diversity of VOCs in plants grown in the field than in the growth room. A high level of similarity of identified VOCs between the two tissues was also observed, as they shared 68 and 94 VOCs in the growth room and field samples, respectively. The difference lies in the relative abundance of VOCs, as most of them are abundant in rhizomes. Overall, the current study showed that the leaves of K. parviflora, grown in any growth conditions, can be further utilized as an alternative source of VOCs for rhizomes.

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Thawtar, M. S., Kusano, M., Yingtao, L., Wunna, Thein, M. S., Tanaka, K., … Watanabe, K. N. (2023). Exploring Volatile Organic Compounds in Rhizomes and Leaves of Kaempferia parviflora Wall. Ex Baker Using HS-SPME and GC–TOF/MS Combined with Multivariate Analysis. Metabolites, 13(5). https://doi.org/10.3390/metabo13050651

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