Variation of Secondary Metabolite Profile of Zataria multiflora Boiss. Populations Linked to Geographic, Climatic, and Edaphic Factors - PubMed (original) (raw)

Variation of Secondary Metabolite Profile of Zataria multiflora Boiss. Populations Linked to Geographic, Climatic, and Edaphic Factors

Ali Karimi et al. Front Plant Sci. 2020.

Abstract

Geographic location and connected environmental and edaphic factors like temperature, rainfall, soil type, and composition influence the presence and the total content of specific plant compounds as well as the presence of a certain chemotype. This study evaluated whether geographic, edaphic, and climatic information can be utilized to predict the presence of specific compounds from medicinal or aromatic plants. Furthermore, we tested rapid analytical methods based on near infrared spectroscopy (NIR) coupled with gas chromatography/flame ionization (GC/FID) and gas chromatography/mass spectrometry (GC/MS) analytical methods for characterization and classification metabolite profiling of Zataria multiflora Boiss. populations. Z. multiflora is an aromatic, perennial plant with interesting pharmacological and biological properties. It is widely dispersed in Iran as well as in Pakistan and Afghanistan. Here, we studied the effect of environmental factors on essential oil (EO) content and the composition and distribution of chemotypes. Our results indicate that this species grows predominantly in areas rich in calcium, iron, potassium, and aluminum, with mean rainfall of 40.46 to 302.72 mm·year-1 and mean annual temperature of 14.90°C to 28.80°C. EO content ranged from 2.75% to 5.89%. Carvacrol (10.56-73.31%), thymol (3.51-48.12%), linalool (0.90-55.38%), and _p_-cymene (1.66-13.96%) were the major constituents, which classified 14 populations into three chemotypes. Corresponding to the phytochemical cluster analysis, the hierarchical cluster analysis (HCA) based on NIR data also recognized the carvacrol, thymol, and linalool chemotypes. Hence, NIR has the potential to be applied as a useful tool to determine rapidly the chemotypes of Z. multiflora and similar herbs. EO and EO constituent content correlated with different geographic location, climate, and edaphic factors. The structural equation models (SEMs) approach revealed direct effects of soil factors (texture, phosphor, pH) and mostly indirect effects of latitude and altitude directly affecting, e.g., soil factors. Our approach of identifying environmental predictors for EO content, chemotype or presence of high amounts of specific compounds can help to select regions for sampling plant material with the desired chemical profile for direct use or for breeding.

Keywords: Zataria multiflora Boiss; carvacrol; chemical diversity; environmental factors; essential oil; linalool; near-infrared spectroscopy; soil chemistry.

Copyright © 2020 Karimi, Krähmer, Herwig, Schulz, Hadian and Meiners.

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Figures

Figure 1

Figure 1

Collection sites (A) and overview on geographic, climatic, and edaphic factors (B) affecting Zataria multiflora populations from Iran.

Figure 2

Figure 2

Essential oil content of Zataria multiflora populations.

Figure 3

Figure 3

Hierarchical cluster analysis of Zataria multiflora populations based on phytochemical composition.

Figure 4

Figure 4

Hypothetical structural equation models (SEMs) to describe the relationships between geographical and edaphic factors and (A) EO, (B) thymol, (C) carvacrol, and (D) linalool content of Zataria multiflora. The climatic factors, temperature, and rainfall were included in the full model but did not explain EO or EO constituent content. R²: coefficient of determination indicating the variability explained for each variable. ß- values indicate the path coefficients, P: significance level for relationship.

Figure 5

Figure 5

Hierarchical cluster analysis of the studied populations of Zataria multiflora based on the NIR spectra.

Figure 6

Figure 6

Results of 10-fold cross-validation of NIR and GC data for the (A) EO content, (B) carvacrol, (C) thymol, (D) linalool by correlation of averaged spectra for each population.

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References

    1. Abkenar S. D., Yamini Y., Shemirani F., Assadi Y. (2008). Headspace solid phase microextraction using a porous-layer activated charcoal coating fused silica fiber for identification of volatile organic compounds emitted by Zataria multiflora Boiss. Chem. Anal-Warsaw 53, 277–287.
    1. Aboukhalid K., Al Faiz C., Douaik A., Bakha M., Kursa K., Agacka-Mołdoch M., et al. (2017). Influence of environmental factors on essential oil variability in Origanum compactum Bent. Chem. Biodivers. 14, e1700158. 10.1002/cbdv.201700158 - DOI - PubMed
    1. Adams R. P. (2014). Identification of essential oil components by gas chromatography/mass spectrometry Vol. 456 (Carol Stream, IL: Allured publishing corporation; ).
    1. Basti A. A., Misaghi A., Khaschabi D. (2007). Growth response and modelling of the effects of Zataria multiflora Boiss. essential oil, pH and temperature on Salmonella typhimurium and Staphylococcus aureus . LWT Food Sci. Technol. 40, 973–981. 10.1016/j.lwt.2006.07.007 - DOI
    1. Boira H., Blanquer A. (1998). Environmental factors affecting chemical variability of essential oils in Thymus piperella L. Biochem. Syst. Ecol. 26, 811–822. PII S0305-1978(98)00047-7. 10.1016/S0305-1978(98)00047-7 - DOI

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