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Article

Population-Related Variability in Qualitative and Quantitative Secondary Metabolite Profile of Gentianella austriaca (A. & J. Kern.) Holub

by
Zorica Popović
1,*,
Vera Vidaković
1,
Tatjana Mijalković
2 and
Dijana Krstić-Milošević
2
1
Department of Ecology, Institute for Biological Research “Siniša Stanković”—National Institute of the Republic of Serbia, University of Belgrade, Bulevar Despota Stefana 142, 11060 Belgrade, Serbia
2
Department of Plant Physiology, Institute for Biological Research “Siniša Stanković”—National Institute of the Republic of Serbia, University of Belgrade, Bulevar Despota Stefana 142, 11060 Belgrade, Serbia
*
Author to whom correspondence should be addressed.
Plants 2023, 12(13), 2434; https://doi.org/10.3390/plants12132434
Submission received: 18 May 2023 / Revised: 30 May 2023 / Accepted: 20 June 2023 / Published: 23 June 2023
(This article belongs to the Special Issue Qualitative and Quantitative Changes in Plant Metabolite Contents)
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Abstract

:
Phytochemical profiling of six natural populations of Gentianella austriaca was performed by HPLC identification and quantification of a number of secondary metabolites, and evaluation of time series of peak areas by chemometric analysis. Phytochemical analysis of G. austriaca revealed the presence of iridoids, flavone-C-glucosides and xanthones. Twelve secondary metabolites were identified in the aerial parts, roots and seeds, including swertiamarin (SWM), gentiopicrin (GP), sweroside (SWZ), isoorientin (ISOOR), swertisin (SWE), demethylbellidifolin-8-O-glucoside (DMB-8-O-glc), bellidifolin-8-O-glucoside (BDF-8-O-glc), mangiferin (MGF), corymbiferin (CBF), corymbiferin-1-O-glucoside (CBF-1-O-glc), bellidifolin (BDF) and campestroside. Multivariate statistical analyses showed relatively low variability among populations according to secondary metabolite content. However, some pharmacologically important compounds were found in higher amounts in a few populations, which could be useful for conservation and future biotechnological procedures.

1. Introduction

The biennial gentian Gentianella austriaca (A. & J. Kern.) Holub is an endemic species that inhabits mountainous semi-dry grasslands, pastures and wet meadows. The species usually forms large populations and metapopulations in the mountains, while its populations in the lowlands are smaller and more isolated [1]. The loss of its natural habitats, particularly oligotrophic meadows, due to land-use changes makes this species highly endangered in Central Europe [2]. It is found in the central mountains of Serbia at altitudes above 2000 m, but also on the plateaus at medium altitudes at 1000 m a.s.l. [3].
Gentianellas, have long been used in traditional medicine of South America as substitutes of related Gentiana species, to treat digestive problems [4]. The aqueous extract of Gentianella nitida whole plant is used in traditional Peruvian medicine as a remedy for hepatitis, as a cholagogue, and in the treatment of obesity [5]. Recently, Leskovac et al. have reported that the aqueous-ethanolic extract of aerial parts of G. austriaca displays radioprotective effect on human lymphocytes in vitro [6]. All gentians were characterized by the presence of three classes of secondary metabolites typical of Gentianaceae family, such as secoiridoids, flavonoids, and xanthones. Earlier phytochemical studies of the genus Gentianella resulted in the isolation of xanthone aglycones and glycosides, C-glucoflavones, iridoids [7,8,9,10], esterterpenoids [11,12,13], ursolic and oleanolic acids [9]. Bitter principles (secoiridoids), which are prevalent constituents of the genera Gentiana, Gentianella, Swertia, and Centaurium, stimulate gastric juice and bile secretion, improving appetite and digestion. Furthermore, they have beneficial pharmacological effects on the central nervous system and smooth muscle relaxation, whereas flavonoids have antidepressant, antiglioma, immunostimulant, antiplatelet aggregation, hypoglycemic, and antihyperlipidemic properties [14]. C-glucoflavones are widely distributed in monocots, but only in a few dicot families, such as Leguminosae, Gentianaceae, and Asteraceae [15]. The most common C-glucoflavones in Gentiana species are isovitexin and isoorientin, both of which are biosynthetically primary compounds. The Swertia genus produces mostly isovitexin and swertisin, whereas Gentianella species contain isoorientin and swertisin [16].
Naturally occurring xanthones with 1,3,5,8-, and less frequently 1,3,7,8-oxidation pattern are typical for gentianellas. These xanthones belong to the bellidifolin type and mostly appear in the form of O-glycosides. Along with them, some Gentianella species contained xanthones with additional oxygenation at C-4. Hence, the chemosystematically oriented study of four Gentianella species from Balkan Peninsula revealed existence of 1,3,4,7,8-oxygenated xanthone for the first time in European gentianellas [17]. This runs contrary to the study previously published by Carbonier et al. (1977) [18] who have reported that this oxygenated pattern, alongside 1,3,4,5,8-, is uniquely found in New Zealand representatives. In the same study, the aerial parts of G. austriaca and G. bulgarica were reported to contain campestroside [17], the compound previously found in G. campestris [19], G. germanica, and G. ramose [7]. Campestroside was the distinguishing compound in the phytochemical profile of the roots of three Gentianella species (detected in G. austriaca and G. bulgarica, but not in G. albanica) [20].
In vitro propagation of G. austraica shoot cultures for the production of xanthones has been successfully developed [21], and in vitro studies have confirmed the pharmacological effects of G. austriaca extracts [22]. Studies suggest that naturally occurring xanthones exhibit a variety of in vitro and in vivo pharmacological activities which include hypoglycemic, antitumor, antioxidant, antihepatotoxic, CNS depressant, or stimulant effects [23]. Evaluation of the structure-activity relationship in a series of structurally related xanthones from G. austriaca and G. kochiana disclosed that dihydroxylation at positions 7, 8 of the xanthone nucleus is the key structural feature responsible for the ability to induce microtubule-associated G2/Mcell block and apoptotic cell death in glioma cells [24]. Two tetraoxidenated xanthones with potent MAO A inhibitory activity were found in G. austriaca [17]. Although G. austraica and its xanthones have been shown to have neuropharmacological in vitro activity, further research on its antidepressant potential based on in vivo studies is needed [22].
Plant secondary metabolites are well-established as important components in both biochemical and ecological processes, given their role in plant survival and successful reproduction in natural habitats [25]. Considering the exposure to constantly changing biotic and abiotic environments, continuous adjustment of plant morpho-physiological traits, including secondary metabolite profile is required [26,27]. In this regard, the presence and amount of certain phytoconstituents vary widely within species and these variations are related to plant ontogeny, environmental, and genetic factors, and are believed to reflect species’ ability to adapt and evolve rapidly [28]. The chemical diversity of plant populations can be assessed by holistic qualitative and quantitative analysis of all metabolites present within a biological system under specific conditions (metabolomics approach), or by quantitative and qualitative analysis of target compounds (traditional approach), which can provide the insight into variation in chemical phenotypes of species [29].
Intraspecific variability of secondary metabolites has become a hot topic in a new research field called “eco-metabolomics”, which links metabolomics with ecology to understand the biochemical mechanisms governing species interactions with the environment and with other mechanisms [30]. More empirical data on intraspecific variability of secondary metabolites are needed for quality control of active phytochemicals, which is currently one of the main concerns within the area of medicinal plant use [31]. This study is aimed to (a) qualitatively and quantitatively determine the targeted secondary metabolites and (b) evaluate intraspecific variability of secondary metabolites in natural populations of Gentianella austriaca.

2. Results

Chromatographic analysis of the methanol extracts of G. austriaca natural populations indicated that all tested samples have a similar profile of secondary metabolites (Figure 1 and Figure 2).
Three secoiridoids were identified including swertiamarin (1), gentiopicrin (2) and swerodside (3), as well as two C-glucoflavones isoorientin (7) and swertisin (8), whose permanent coexistence is specific for Genianella species. The xanthone composition consists of seven identified compounds. Among them, three xanthones occure in the form of glucosides-bellidifolin-8-O-glucoside (9), demethylbellidifolin-8-O-glucoside (6) and corymbiferin-1-O-glucoside (10). In addition to glucosides, corresponding aglycones bellidifolin (11) and corymbiferin (12) have also been identified. A very specific compound of gentianellas, campestroside (5), which is a partially saturated analogue of the demethylbellidifolin-8-O-glucoside, has been detected in all the samples. This xanthone was tentatively identified based on comparison of UV spectral data with reference data obtained from our previous studies on tetra-substituted xanthones [17]. Mangiferin (4), xanthone C-glucoside, was detected in a smallest quantity among the xanthones.
Chemical structures of the secondary metabolites identified in G. austriaca plants were shown in Figure 3.
Figure 4 visualizes the results of parametric and non-parametric tests performed on the contents of eleven secondary metabolites in aboveground plant parts of six populations. The contents of seven secondary metabolites (SWM, GP, DMB-8-O-glc, SWE, BDF-8-O-glc, CBF, and BDF) differed significantly between populations, whereas the contents of four secondary metabolites (SWZ, ISOOR, CBF-1-O-glc, and MGF) did not. Population IV had the highest levels of SWM, GP, DMB-8-O-glc, CBF, and BF, as well as very high levels of SWM and BDF-8-O-glc. Furthermore, populations III and V had significantly high levels of certain secondary metabolites (Figure 4).
Regarding the plant part, the highest contents of the investigated secondary metabolites were found in the aboveground parts (A), followed by the belowground parts (B), and the lowest contents were present in the seeds (S), except for GP (B > A > S) and SWZ (A > B = S) (Figure 5).
Linear discriminant analysis (LDA) was performed on the set of six groups of individuals belonging to six populations. The first discriminant function explained 50%, the second 29%, and the third 12% of the discrimination (Table 1). The first discriminant function was mainly determined by the contents of BDF and CBF, the second by the contents of CBF and GP, and the third by the contents of DMB-8-O-glc and BDF-8-O-glc (Table 1). The first discriminant function mainly distinguished Population V, the second Population IV, and the third Population III, from the other populations (Table 2 and Figure 6). DA showed clear separation of Populations I, III, IV and V, and the overlap of Populations II and VI (Figure 6a,b).

3. Discussion

Medicinal plants from the gentian family (Gentianaceae) are highly valued as sources of pharmacologically important compounds. However, many of them are facing declining populations due to climate change and habitat loss [32]. Considering that the majority of species in this family are endemic and have low germination capacity, uncontrolled collection for traditional use and overexploitation for commercial purposes pose additional threats. The first in situ conservation measure for these species should be the preservation of natural populations and habitats, followed by ex situ measures such as biotechnology based on plant tissue culture methods. Phytochemical profiling of natural populations is an important step in both conservation approaches, especially when using in vitro methods because the content of some natural compounds has been shown to vary with habitat [33].
Studies on chemodiversity among plant populations have been commonly conducted in the context of natural genetic variation and are based on distance-based measurements [34,35,36,37] or pronounced differences in environmental conditions [38,39]. Populations from non-distant sites with similar environmental patterns, however, offer a more promising opportunity for better understanding naturally occurring variability in species phytochemical profiles. Evidence suggests that intraspecific variation of phytochemicals can exist at a few meters’ scale, and even when individuals have the same secondary chemistry composition, the amounts can be significantly different [40]. This can be attributed to resource heterogeneity, genetic differences, and herbivore or pathogen impact [41]. Considering that plant chemical properties can change in damaged tissues, population/individual life histories can also contribute to this variability [42]. Given that chemically mediated plant-plant interactions are mostly based on secondary metabolite amounts, some authors suggest that intraspecies variability in this trait should be taken into account in allelopathic community research [43]. High interpopulation diversity among natural populations indicates functional redundancy and versatility at the species level [44]. Low interpopulation chemodiversity, on the other hand, may be the result of lower genetic variability and genetic inbreeding [45]. Habitat fragmentation and isolation of small populations has a negative impact on population viability due to a lack of genetic variation, which is required for ecological plasticity [46]. Furthermore, small and isolated populations are often faced with pollen limitation [47], and their fitness can be linked to the presence of jointly flowering species that can either attract [48] or compete for pollinators [49]. Pollen limitation, genetic deterioration, population size decline, and clonal spreading pose significant challenges for endemic species, which are typically found in restricted areas [50]. G. austriaca populations on Maljen Mt. had less than 40 reproductive (flowering) individuals spread out in small patches, making it difficult to attract enough pollinators. Multivariate analyses of the G. austriaca dataset revealed inconspicuous separation and partial overlap of individuals, indicating relatively low interpopulation variability based on the secondary metabolites investigated. Interpopulation variability of secondary metabolites was found to be similarly low in small populations of Gentiana pneumonanthe [51] and Gentiana asclepiadea [52].
The greatest differences in secondary metabolite content were found between plant parts. The majority of the compounds tested were found in both below- and aboveground plant parts and seeds. Only GP was found in comparable amounts in both below- and aboveground parts, whereas the amounts of other compounds were much lower in belowground parts. SWZ (not found in belowground parts, or only in traces in two populations) and MFG and ISOOR (not found in seeds, or only in traces) displayed the most prominent differences between the content of secondary metabolites in plant parts. Secondary metabolite biosynthesis and accumulation demonstrate organ and/or tissue specificity, primarily in four plant morphological compartments: roots and stems, leaves, flowers, fruits, and seeds [53]. These processes are influenced by genetic, environmental, and developmental factors, all of which have a synergistic effect on secondary metabolite biosynthesis and accumulation and may show large-scale range depending on overall photosynthetic and energy metabolism [54]. Secondary metabolite accumulation in roots and stems, for example, is primarily influenced by growth periods, growth seasons, and growth years [52,55]; leaves, with their primarily photosynthetic function, can also store secondary metabolites, which vary with leaf age and growth stage [56,57]; variations in secondary metabolites synthesis and accumulation in flowers are strongly influenced by developmental stages and circadian rhythm [58]; seeds also show developmental stage variations, which are related to gene expression, i.e., enzymes responsible for secondary metabolites biosynthesis [59]. Secondary metabolites are important in seed dispersal and fruit defense [60], and there is evidence that reproductive tissues and organs (flowers, fruits, seeds) have distinct secondary metabolite profiles and higher amounts of secondary metabolites [61]. The qualitative-quantitative analysis of G. austrica in late flowering/early fruiting stage reveals a similar set of secondary metabolites in all plant parts.
The findings show that the content of four compounds (SWZ, ISOOR, CBF-1-O-glc, and MGF) was similar among all populations studied. However, the amounts of seven compounds differed significantly between populations, contributing to the separation of populations III, IV and V based on the high contents of BDF, DMB-8-O-glc, BDF-8-O-glc CBF, and GP. This result suggests the importance of using qualitative/quantitative analyses in phytochemical profiling of species. Quantification of compounds of pharamacological interest can provide information about intraspecies chemodiversity, which is the fundamental for bioprospecting, and can lead to multidisciplinary approaches encompassing ecological, biological, chemical, pharmaceutical, and biomedical disciplines [62]. The majority of gentianelas’ xanthones are bellidifolins. They are commonly found as O-glycosides and are considered to be carriers of a variety of pharmaceutical properties. The two dominant chromatogram peaks belong to demethylbellidifolin-8-O-glucoside and bellidifolin-8-O-glucoside, xanthones with 1,3,5,8-oxidation pattern characteristic for Gentianella species. Bellidifolin and demethylbellidifolin are both antioxidants with antimicrobial, anti-diabetic, and cardioprotective properties, with inhibitory effects on acetylcholinesterase and monoamino oxidase [16], and bellidifolin also has hypoglycemic and neuroprotective properties [63,64]. Bellidifollin reduces oxidative stress and shows hepatoprotective capacity [65], and inhibit acetylcholinesterase (AChE) activity [66]. Evidence of a broad range of pharmacological activities encouraged efforts toward in vitro propagation of gentinellas, as well as testing the conditions for optimal xanthone production in shoot cultures [67]. However, due to the scarcity of plant material (rare, endemic species that grow in inaccessible locations), data on the phytochemistry of these species, particularly the variability within natural populations, is limited. More data on this topic can aid in mapping the locations and populations with high concentrations of secondary metabolites of interest, which can be used as a starting point for future biotechnological research.

4. Materials and Methods

4.1. Study Site

Field research was conducted at Divčibare (44°06′13″ N, 19°59′19″ E), which is located in the central part of Mt. Maljen in northwest Serbia. The six G. austriaca populations studied were spread over a 5 km × 5 km area (Figure 7), distributed in small patches in meadow communities, and accounted for approximately 30–40 mature individuals (generative adults with flowering stalks). Table 3 shows the coordinates and altitudes of the studied populations.

4.2. Plant Material and Sample Preparation

The field research was carried out in August 2022. Seven individuals from each population were harvested immediately following flowering (late flowering/early fruiting phase). The collected plants were determined by Dr. Z. Popović at the Institute for Biological Research, Department of Ecology, using standard keys for the determination of the plant species [3,68]. Plants were and air-dried in the laboratory. Each plant was divided into two parts: belowground and aboveground. The flowers and fruits were separated from the stem and seeds that fell out of the dried fruits were collected. Further analyses were performed on the vegetative aboveground parts (A) (7 individuals × 6 populations, n = 42). Belowground parts (B) and seeds (S) were analyzed as a mixed sample per population due to the small amount of material (thin roots and small amount of seeds).

4.3. Analytical Procedure

Samples including belowground and aboveground plant parts, and seeds, were ground to fine powder using a mortar and a pestle. Fifty milligrams of powdered samples were extracted with 1 mL of methanol (HPLC grade, J.T. Baker, Deventer, The Netherlands) in an ultrasonic bath at room temperature for 20 min. After sonication extracts were centrifuged at 10,000 rpm for 10 min. The supernatants were filtered through 0.45 μm nylon syringe filters (Captiva Econo Filters, 13 mm, Agilent Technologies, Waldbronn, Germany) before injection into the HPLC system for analysis.
Identification and quantification of secondary metabolites in tested extracts were carried out on an Agilent Series 1100 HPLC system equipped with diode array detector (DAD). A reverse phase ZorbaxSB-C18 (Agilent) analytical column (150 × 4.6 mm, 5 μm) was used for the component separation. The mobile phase consisted of solvent A (1%, v/v solution of orthophosphoric acid in water) and solvent B (acetonitrile, HPLC grade, J.T. Baker, Deventer, The Netherlands) using a gradient elution of 98–90% A 0–3 min, 90% A 3–6 min, 90–85% A 6–8 min, 85% A 8–13 min, 85–70% A 13–18 min, 70–30% A 18–25 min, and 30–0% A 25–30 min. Column elution was monitored at 260 and 320 nm, with a flow rate of 1 mL min−1.
Standards of xanthone glucosides demethylbellidifolin-8-O-glucoside, bellidifolin-8-O-glucoside and corymbiferin-1-O-glucoside, aglycones corymbiferin and bellidifolin, as well as C-glucoflavones swertisin and isoorientin were isolated previously in our laboratory from the aerial parts of Gentianella albanica [17]. Camprestroside was isolated from aerial parts of G. austriaca [17]. Mangiferin was purchased from Sigma-Aldrich Inc., Germany/USA. Secoiridoids swertiamarin, gentiopicrin and sweroside were bought from Cfm Oscar Tropitzsch (Bayern, Germany).
Stock solutions of standards were prepared by dissolving compounds in methanol.
The quantification of secondary metabolites was done using the external standard method by preparing calibration standards and recording the calibration curves at 260 nm for secoiridoids, C-glucoflavones and xanthones, and at 320 nm for xanthones mangiferin and bellidifolin. The results are presented as mg/g of dry weight (dw).

4.4. Statistical Analysis

Six populations of G. austriaca were compared on the basis of the contents of eleven secondary metabolites (secoiridoids, flavonoids and xanthones). The assumption of normality was tested with the Shapiro-Wilk test (p > 0.05 indicated normal distribution). ANOVA was applied for comparing the populations when the variables appeared to follow normal distribution, whereas a non-parametric Kruskal-Wallis rank sum test was used when the variables did not appear to follow a normal distribution. The False Discovery Rate (FDR) p-adjustment method was used to control the type I error rate in hypothesis testing. Linear discriminant analysis (LDA) was carried out on log-transformed data (y′ = log10(y + 1), y = original data value) in order to visualize the data structure. Statistical analyses were performed using R statistical software, version 4.2.2 [69].

5. Conclusions

The findings suggest that G. austriaca is a rich source of pharmacologically important compounds. The overall intraspecies variability in the total dataset was relatively low, which is characteristic of small and isolated populations. However, the amounts of some compounds (DMB-8-O-glc, BDF-8-O-glc) with high pharmacological potential (inhibitors of monoamine oxidases A, cardiovascular protective and antitumor effect) were significantly higher in a few populations, which could be useful for conservation and future biotechnological procedures. These findings highlight the significance of qualitative/quantitative analyses of natural populations and evaluating their quality-related characteristics.

Author Contributions

Conceptualization, Z.P. and D.K.-M.; methodology, Z.P. and D.K.-M.; data collection Z.P. and V.V.; laboratory analyses D.K.-M. and T.M.; statistical analyses V.V.; visualization and contribution to the writing, D.K.-M. and V.V.; writing—original draft preparation, Z.P.; writing—review and editing, Z.P. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Ministry of Science, Technological Development and Innovation of the Republic of Serbia under contract 451-03-47/2023-01/200007.

Data Availability Statement

The data presented in this study are available from the authors.

Acknowledgments

The authors acknowledge their gratitude to the Ministry of Science, Technological Development and Innovation of the Republic of Serbia for financial support of this research. We thank Aleksandra Petrović, Petnica Science Center, for the help in collecting the plant material.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Greimler, J.; Dobeš, C. High Genetic Diversity and Differentiation in Relict Lowland Populations of Gentianella austriaca (A. and J. Kern.) Holub (Gentianaceae). Plant Biol. 2000, 2, 628–637. [Google Scholar] [CrossRef]
  2. Reich, D.; Wrbka, T.; Plutzar, C.; Greimler, J. The Effect of Land-Use Change on the Distribution of Gentianella austriaca and G. Praecox in Austria. Preslia 2020, 92, 213–234. [Google Scholar] [CrossRef]
  3. Jovanović-Dunjić, R. Rod Gentianella Moench. In Flora SR Srbije; Josifović, M., Ed.; SANU: Beograd, Serbia, 1973; Volume 5, pp. 426–433. [Google Scholar]
  4. Nadinic, E.; Gorzalczany, S.; Rojo, A.; Van Baren, C.; Debenedetti, S.; Acevedo, C. Topical Anti-Inflammatory Activity of Gentianella achalensis. Fitoterapia 1999, 70, 166–171. [Google Scholar] [CrossRef]
  5. Lacaille-Dubois, M.A.; Galle, K.; Wagner, H. Secoiridoids and Xanthones from Gentianella nitida. Planta Med. 1996, 62, 365–367. [Google Scholar] [CrossRef]
  6. Leskovac, A.; Joksic, G.; Jankovic, T.; Savikin, K.; Menkovic, N. Radioprotective Properties of the Phytochemically Characterized Extracts of Crataegus monogyna, Cornus mas and Gentianella austriaca on Human Lymphocytes In Vitro. Planta Med. 2007, 73, 1169–1175. [Google Scholar] [CrossRef]
  7. Hostettmann-Kaldas, M.; Jacot-Guillarmod, A. Xanthones et C-Glucosides Flavoniques Du Genre Gentiana (Sous-Genre Gentianella). Phytochemistry 1978, 17, 2083–2086. [Google Scholar] [CrossRef]
  8. Lacaille-Dubois, M.A.; Wagner, H. A Review of the Biological and Pharmacological Activities of Saponins. Phytomedicine 1996, 2, 363–386. [Google Scholar] [CrossRef]
  9. Nadinic, E.L.; Saavedra, C.L.; Di Leo Lira, P.; Bandoni, A.L.; Debenedetti, S.L. Tetraoxygenated Xanthones from Gentianella florida. Pharm. Biol. 1997, 35, 379–381. [Google Scholar] [CrossRef]
  10. Kawahara, N.; Masuda, K.; Sekita, S.; Satake, M. A New Secoiridoid Glucoside, Amaronitidin, from the Peruvian Folk Medicine “Hercampuri” (Gentianella nitida). Chem. Pharm. Bull. 2001, 49, 771–772. [Google Scholar] [CrossRef] [Green Version]
  11. Kawahara, N.; Nozawa, M.; Flores, D.; Bonilla, P.; Sekita, S.; Satake, M.; Kawai, K. Nitidasin, a Novel Sesterterpenoid, from the Peruvian Folk Medicine “Hercampuri” (Gentianella nitida). Chem. Pharm. Bull. 1997, 45, 1717–1719. [Google Scholar] [CrossRef] [Green Version]
  12. Kawahara, N.; Nozawa, M.; Atsuyo, K.; Hakamatsuka, T.; Sekita, S.; Satake, M. A Novel Sesterterpenoid, Nitiol, as a Potent Enhancer of IL-2 Gene Expression in a Human T Cell Line, from the Peruvian Folk Medicine “Hercumpuri” (Gentianella nitida). Chem. Pharm. Bull. 1999, 47, 1344–1345. [Google Scholar] [CrossRef] [Green Version]
  13. Kawahara, N.; Nozawa, M.; Flores, D.; Bonilla, P.; Sekita, S.; Satake, M. Sesterterpenoid from Gentianella alborosea. Phytochemistry 2000, 53, 881–884. [Google Scholar] [CrossRef] [PubMed]
  14. Yang, J.L.; Liu, L.L.; Shi, Y.P. Phytochemicals and Biological Activities of Gentiana Species. Nat. Prod. Commun. 2010, 5, 649–664. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  15. Jensen, S.R.; Schripsema, J. Chemotaxonomy and Pharmacology of Gentianaceae. In Gentianaceae—Systematics and Natural History; Cambridge University Press: Cambridge, UK, 2002; pp. 573–632. [Google Scholar]
  16. Tovilovic-Kovacevic, G.; Zogovic, N.; Krstic-Milosevic, D. Secondary Metabolites from Endangered Gentiana, Gentianella, Centaurium, and Swertia Species (Gentianaceae): Promising Natural Biotherapeutics. In Biodiversity and Biomedicine: Our Future; Academic Press: London, UK, 2020; pp. 335–384. ISBN 9780128195413. [Google Scholar]
  17. Janković, T.; Krstić, D.; Aljančić, I.; Šavikin-Fodulović, K.; Menković, N.; Vajs, V.; Milosavljević, S. Xanthones and C-Glucosides from the Aerial Parts of Four Species of Gentianella from Serbia and Montenegro. Biochem. Syst. Ecol. 2005, 33, 729–735. [Google Scholar] [CrossRef]
  18. Carbonier, J.; Massias, M.; Molho, D. Taxonomic importance of the substitution scheme of xanthones in Gentiana L. Bull. Mus. Natl. Hist. Sci. Phys.-Chim. 1997, 13, 23–40. [Google Scholar]
  19. Kaldas, M.; Miura, I.; Hostettmann, K. Campestroside, a New Tetrahydroxanthone from Gentiana campestris. Phytochemistry 1978, 17, 295–297. [Google Scholar] [CrossRef]
  20. Menković, N.; Tadić, V. Comprehensive Combined Chemical and Pharmacognostic Approach in the Investigation of Montenegrin Flora, with Emphasis on Endemic Species: Past Performance and Future Potential. Nat. Med. Mater. 2021, 41, 106–125. [Google Scholar] [CrossRef]
  21. Vinterhalter, B.; Janković, T.; Šavikin, K.; Nikolić, R.; Vinterhalter, D. Propagation and Xanthone Content of Gentianella austriaca Shoot Cultures. Plant Cell. Tissue Organ Cult. 2008, 94, 329–335. [Google Scholar] [CrossRef]
  22. Tovilović, G.; Tomić, M.; Janković, T.; Krstić, D. Neurochemical In Vitro Activity of Xanthones from Gentianella austriaca. Iugosl. Physiol. Pharmacol. Acta 2005, 41, 83–86. [Google Scholar]
  23. Peres, V.; Nagem, T.J.; de Oliveira, F.F. Tetraoxygenated Naturally Occurring Xanthones. Phytochemistry 2000, 55, 683–710. [Google Scholar] [CrossRef] [Green Version]
  24. Isakovic, A.; Jankovic, T.; Harhaji, L.; Kostic-Rajacic, S.; Nikolic, Z.; Vajs, V.; Trajkovic, V. Antiglioma Action of Xanthones from Gentiana kochiana: Mechanistic and Structure-Activity Requirements. Bioorg. Med. Chem. 2008, 16, 5683–5694. [Google Scholar] [CrossRef]
  25. Müller, C.; Bräutigam, A.; Eilers, E.; Junker, R.; Schnitzler, J.-P.; Steppuhn, A.; Unsicker, S.; van Dam, N.; Weisser, W.; Wittmann, M. Ecology and Evolution of Intraspecific Chemodiversity of Plants. Res. Ideas Outcomes 2020, 6, e49810. [Google Scholar] [CrossRef]
  26. Kessler, A.; Kalske, A. Plant Secondary Metabolite Diversity and Species Interactions. Annu. Rev. Ecol. Evol. Syst. 2018, 49, 115–138. [Google Scholar] [CrossRef]
  27. Isah, T. Stress and Defense Responses in Plant Secondary Metabolites Production. Biol. Res. 2019, 52, 39–64. [Google Scholar] [CrossRef] [Green Version]
  28. Tugizimana, F.; Piater, L.; Dubery, I. Plant Metabolomics: A New Frontier in Phytochemical Analysis. S. Afr. J. Sci. 2013, 109, 18–20. [Google Scholar] [CrossRef] [Green Version]
  29. Fiehn, O. Metabolomics—The Link between Genotypes and Phenotypes. Plant Mol. Biol. 2002, 48, 155–171. [Google Scholar] [CrossRef] [PubMed]
  30. Moore, B.D.; Andrew, R.L.; Külheim, C.; Foley, W.J. Explaining Intraspecfic Diversity in Plant Secondary Metabolites in an Ecological Context. New Phytol. 2014, 201, 733–750. [Google Scholar] [CrossRef] [PubMed]
  31. Rai, A.; Saito, K.; Yamazaki, M. Integrated Omics Analysis of Specialized Metabolism in Medicinal Plants. Plant J. 2017, 90, 764–787. [Google Scholar] [CrossRef]
  32. Ibrahim, M.A.; Na, M.; Oh, J.; Schinazi, R.F.; McBrayer, T.R.; Whitaker, T.; Doerksen, R.J.; Newman, D.J.; Zachos, L.G.; Hamann, M.T. Significance of Endangered and Threatened Plant Natural Products in the Control of Human Disease. Proc. Natl. Acad. Sci. USA 2013, 110, 16832–16837. [Google Scholar] [CrossRef] [Green Version]
  33. Yang, H.; Ding, C.; Duan, Y.; Liu, J. Variation of Active Constituents of an Important Tibet Folk Medicine Swertia mussotii Franch. (Gentianaceae) between Artificially Cultivated and Naturally Distributed. J. Ethnopharmacol. 2005, 98, 31–35. [Google Scholar] [CrossRef]
  34. Berkov, S.; Sidjimova, B.; Evstatieva, L.; Popov, S. Intraspecific Variability in the Alkaloid Metabolism of Galanthus elwesii. Phytochemistry 2004, 65, 579–586. [Google Scholar] [CrossRef]
  35. Vidaković, V.; Stefanović, M.; Novaković, M.; Jadranin, M.; Popović, Z.; Matić, R.; Tešević, V.; Bojović, S. Inter- and Intraspecific Variability of Selected Diarylheptanoid Compounds and Leaf Morphometric Traits in Alnus glutinosa and Alnus incana. Holzforschung 2018, 72, 1031–1041. [Google Scholar] [CrossRef] [Green Version]
  36. Labarrere, B.; Prinzing, A.; Dorey, T.; Chesneau, E.; Hennion, F. Variations of Secondary Metabolites among Natural Populations of Sub-Antarctic Ranunculus Species Suggest Functional Redundancy and Versatility. Plants 2019, 8, 234. [Google Scholar] [CrossRef] [Green Version]
  37. Karimi, A.; Krähmer, A.; Herwig, N.; Schulz, H.; Hadian, J.; Meiners, T. Variation of Secondary Metabolite Profile of Zataria multiflora Boiss. Populations Linked to Geographic, Climatic, and Edaphic Factors. Front. Plant Sci. 2020, 11, 969–984. [Google Scholar] [CrossRef] [PubMed]
  38. Meijõn, M.; Feito, I.; Oravec, M.; Delatorre, C.; Weckwerth, W.; Majada, J.; Valledor, L. Exploring Natural Variation of Pinus pinaster Aiton Using Metabolomics: Is It Possible to Identify the Region of Origin of a Pine from Its Metabolites? Mol. Ecol. 2016, 25, 959–976. [Google Scholar] [CrossRef]
  39. Chograni, H.; Riahi, L.; Messaoud, C. Variability of Qualitative and Quantitative Secondary Metabolites Traits among Wild Genetic Resources of Lavandula stoechas L. Biochem. Syst. Ecol. 2021, 98, 104327. [Google Scholar] [CrossRef]
  40. Valares Masa, C.; Alías Gallego, J.C.; Chaves Lobón, N.; Sosa Díaz, T. Intra-Population Variation of Secondary Metabolites in Cistus ladanifer L. Molecules 2016, 21, 945. [Google Scholar] [CrossRef] [Green Version]
  41. Vourc’h, G.; Vila, B.; Gillon, D.; Escarré, J.; Guibal, F.; Fritz, H.; Clausen, T.P.; Martin, J.L. Disentangling the Causes of Damage Variation by Deer Browsing on Young Thuja plicata. Oikos 2002, 98, 271–283. [Google Scholar] [CrossRef] [Green Version]
  42. van Geem, M.; Gols, R.; Raaijmakers, C.E.; Harvey, J.A. Effects of Population-Related Variation in Plant Primary and Secondary Metabolites on Aboveground and Belowground Multitrophic Interactions. Chemoecology 2016, 26, 219–233. [Google Scholar] [CrossRef] [Green Version]
  43. Jandová, K.; Dostál, P.; Cajthaml, T.; Kameník, Z. Intraspecific Variability in Allelopathy of Heracleum mantegazzianum Is Linked to the Metabolic Profile of Root Exudates. Ann. Bot. 2015, 115, 821–831. [Google Scholar] [CrossRef] [Green Version]
  44. Wink, M. Evolution of Secondary Metabolites from an Ecological and Molecular Phylogenetic Perspective. Phytochemistry 2003, 64, 3–19. [Google Scholar] [CrossRef]
  45. Raijmann, L.E.L.; Van Leeuwen, N.C.; Kersten, R.; Oostermeijer, J.G.B.; Den Nijs, H.C.M.; Menken, S.B.J. Genetic Variation and Outcrossing Rate in Relation to Population Size in Gentiana pneumonanthe L. Conserv. Biol. 1994, 8, 1014–1026. [Google Scholar] [CrossRef]
  46. Didham, R.K. The Ecological Consequences of Habitat Fragmentation. In Encyclopedia of Life Sciences; John Wiley & Sons, Ltd.: Chichester, UK, 2010. [Google Scholar]
  47. Pierce, S.; Spada, A.; Caporali, E.; Puglisi, F.; Panzeri, A.; Luzzaro, A.; Cislaghi, S.; Mantegazza, L.; Cardarelli, E.; Labra, M.; et al. Identifying Population Thresholds for Flowering Plant Reproductive Success: The Marsh Gentian (Gentiana pneumonanthe) as a Flagship Species of Humid Meadows and Heathland. Biodivers. Conserv. 2018, 27, 891–905. [Google Scholar] [CrossRef] [Green Version]
  48. Oostermeijer, J.G.B.; Luijten, S.H.; Křenová, Z.V.; Den Nijs, H.C.M. Relationships between Population and Habitat Characteristics and Reproduction of the Rare Gentiana pneumonanthe L. Conserv. Biol. 1998, 12, 1042–1053. [Google Scholar] [CrossRef]
  49. Kwak, M.M.; Velterop, O.; van Andel, J. Pollen and Gene Flow in Fragmented Habitats. Appl. Veg. Sci. 1998, 1, 37–54. [Google Scholar] [CrossRef]
  50. Fischer, M.; Matthies, D. Effects of Population Size on Performance in the Rare Plant Gentianella germanica. J. Ecol. 1998, 86, 195–204. [Google Scholar] [CrossRef]
  51. Popović, Z.; Krstić-Milošević, D.; Stefanović, M.; Matić, R.; Vidaković, V.; Bojović, S. Chemical and Morphological Inter- and Intrapopulation Variability in Natural Populations of Gentiana pneumonanthe L. Chem. Biodivers. 2019, 16, e1800509. [Google Scholar] [CrossRef]
  52. Popović, Z.; Krstić-Milošević, D.; Marković, M.; Vidaković, V.; Bojović, S. Gentiana asclepiadea L. from Two High Mountainous Habitats: Inter-and Intrapopulation Variability Based on Species’ Phytochemistry. Plants 2021, 10, 140. [Google Scholar] [CrossRef]
  53. Li, Y.; Kong, D.; Fu, Y.; Sussman, M.R.; Wu, H. The Effect of Developmental and Environmental Factors on Secondary Metabolites in Medicinal Plants. Plant Physiol. Biochem. 2020, 148, 80–89. [Google Scholar] [CrossRef]
  54. Liu, J.; Liu, Y.; Wu, K.; Pan, L.; Tang, Z.H. Comparative Analysis of Metabolite Profiles from Panax Herbs in Specific Tissues and Cultivation Conditions Reveals the Strategy of Accumulation. J. Pharm. Biomed. Anal. 2020, 188, 113368. [Google Scholar] [CrossRef]
  55. Xu, J.; Yu, Y.; Shi, R.; Xie, G.; Zhu, Y.; Wu, G.; Qin, M. Organ-Specific Metabolic Shifts of Flavonoids in Scutellaria baicalensis at Different Growth and Development Stages. Molecules 2018, 23, 428. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  56. Vázquez-León, L.A.; Páramo-Calderón, D.E.; Robles-Olvera, V.J.; Valdés-Rodríguez, O.A.; Pérez-Vázquez, A.; García-Alvarado, M.A.; Rodríguez-Jimenes, G.C. Variation in Bioactive Compounds and Antiradical Activity of Moringa oleifera Leaves: Influence of Climatic Factors, Tree Age, and Soil Parameters. Eur. Food Res. Technol. 2017, 243, 1593–1608. [Google Scholar] [CrossRef]
  57. Li, Y.; Kong, D.; Lin, X.; Xie, Z.; Bai, M.; Huang, S.; Nian, H.; Wu, H. Quality Evaluation for Essential Oil of Cinnamomum verum Leaves at Different Growth Stages Based on GC–MS, FTIR and Microscopy. Food Anal. Methods 2016, 9, 202–212. [Google Scholar] [CrossRef]
  58. Figueiredo, A.C.; Barroso, J.G.; Pedro, L.G.; Scheffer, J.J.C. Factors Affecting Secondary Metabolite Production in Plants: Volatile Components and Essential Oils. Flavour Fragr. J. 2008, 23, 213–226. [Google Scholar] [CrossRef]
  59. Lepelley, M.; Cheminade, G.; Tremillon, N.; Simkin, A.; Caillet, V.; McCarthy, J. Chlorogenic Acid Synthesis in Coffee: An Analysis of CGA Content and Real-Time RT-PCR Expression of HCT, HQT, C3H1, and CCoAOMT1 Genes during Grain Development in C. Canephora. Plant Sci. 2007, 172, 978–996. [Google Scholar] [CrossRef]
  60. Nelson, A.S.; Whitehead, S.R. Fruit Secondary Metabolites Shape Seed Dispersal Effectiveness. Trends Ecol. Evol. 2021, 36, 1113–1123. [Google Scholar] [CrossRef]
  61. Wink, M. Introduction: Biochemistry, Physiology and Ecological Functions of Secondary Metabolites. In Biochemistry of Plant Secondary Metabolism, 2nd ed.; Wiley Publishing: New York, NY, USA, 2010; Volume 40, pp. 1–19. [Google Scholar] [CrossRef]
  62. Popović, Z.; Matić, R.; Stefanović, M.; Vidaković, V.; Bojović, S. Chemodiversity in Natural Plant Populations as a Base for Biodiversity Conservation. In Biodiversity and Biomedicine: Our Future; Academic Press: London, UK, 2020; pp. 11–41. ISBN 9780128195413. [Google Scholar]
  63. Tian, L.Y.; Bai, X.; Chen, X.H.; Fang, J.B.; Liu, S.H.; Chen, J.C. Anti-Diabetic Effect of Methylswertianin and Bellidifolin from Swertia punicea Hemsl. and Its Potential Mechanism. Phytomedicine 2010, 17, 533–539. [Google Scholar] [CrossRef] [PubMed]
  64. Zhao, Z.; Gao, Y.; Gao, L.; Zhang, M.; Wang, H.; Zhang, C. hong Protective Effects of Bellidifolin in Hypoxia-Induced in Pheochromocytoma Cells (PC12) and Underlying Mechanisms. J. Toxicol. Environ. Health Part A Curr. Issues 2017, 80, 1187–1192. [Google Scholar] [CrossRef]
  65. Sharma, B.; Mittal, A.; Dabur, R. Mechanistic Approach of Anti-Diabetic Compounds Identified from Natural Sources. Chem. Biol. Lett. 2018, 5, 63–99. [Google Scholar]
  66. Urbain, A.; Marston, A.; Queiroz, E.F.; Ndjoko, K.; Hostettmann, K. Xanthones from Gentiana campestris as New Acetylcholinesterase Inhibitors. Planta Med. 2004, 70, 1011–1014. [Google Scholar] [CrossRef]
  67. Krstić-Milošević, D.; Banjac, N.; Janković, T.; Vinterhalter, D.; Vinterhalter, B. Gentianella lutescens subsp. carpatica J. Holub.: Shoot Propagation In Vitro and Effect of Sucrose and Elicitors on Xanthones Production. Plants 2021, 10, 1651. [Google Scholar] [CrossRef] [PubMed]
  68. Tutin, T.G.; Heywood, V.H.; Burges, N.A.; Valentine, D.H.; Walters, S.M.; Webb, D.A. 1964–1980: Flora Europaea 1–5; Cambridge University Press: Cambridge, UK, 1972. [Google Scholar]
  69. R Core Team. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. 2022. Available online: https://www.R-project.org/ (accessed on 31 October 2022).
Plants 12 02434 g001 550
Figure 1. Representative HPLC profile of methanol extract of G. austriaca aerial parts recorded at (a) λ = 260 nm and (b) λ = 320 nm. Peaks: 1—swertiamarin, 2—gentiopicrin, 3—swerodside, 4—mangiferin, 5—campestroside, 6—demethylbellidifolin-8-O-glucoside, 7—isoorientin, 8—swertisin, 9—bellidifolin-8-O-glucoside, 10—corymbiferin-1-O-glucoside, 11—bellidifolin, 12—corymbiferin.
Figure 1. Representative HPLC profile of methanol extract of G. austriaca aerial parts recorded at (a) λ = 260 nm and (b) λ = 320 nm. Peaks: 1—swertiamarin, 2—gentiopicrin, 3—swerodside, 4—mangiferin, 5—campestroside, 6—demethylbellidifolin-8-O-glucoside, 7—isoorientin, 8—swertisin, 9—bellidifolin-8-O-glucoside, 10—corymbiferin-1-O-glucoside, 11—bellidifolin, 12—corymbiferin.
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Plants 12 02434 g002 550
Figure 2. Representative HPLC profiles of methanol extract of G. austriaca (a) roots and (b) seeds recorded at λ = 260 nm. Peaks: 1—swertiamarin, 2—gentiopicrin, 3—swerodside, 4—mangiferin, 5—campestroside, 6—demethylbellidifolin-8-O-glucoside, 7—isoorientin, 8—swertisin, 9—bellidifolin-8-O-glucoside, 10—corymbiferin-1-O-glucoside, 11—bellidifolin, 12—corymbiferin.
Figure 2. Representative HPLC profiles of methanol extract of G. austriaca (a) roots and (b) seeds recorded at λ = 260 nm. Peaks: 1—swertiamarin, 2—gentiopicrin, 3—swerodside, 4—mangiferin, 5—campestroside, 6—demethylbellidifolin-8-O-glucoside, 7—isoorientin, 8—swertisin, 9—bellidifolin-8-O-glucoside, 10—corymbiferin-1-O-glucoside, 11—bellidifolin, 12—corymbiferin.
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Plants 12 02434 g003 550
Figure 3. Chemical structures of the secondary metabolites identified in G. austriaca plants. 1—swertiamarin, 2—gentiopicrin, 3—swerodside, 4—mangiferin, 5—campestroside, 6—demethylbellidifolin-8-O-glucoside, 7—isoorientin, 8—swertisin, 9—bellidifolin-8-O-glucoside, 10—corymbiferin-1-O-glucoside, 11—bellidifolin, 12—corymbiferin.
Figure 3. Chemical structures of the secondary metabolites identified in G. austriaca plants. 1—swertiamarin, 2—gentiopicrin, 3—swerodside, 4—mangiferin, 5—campestroside, 6—demethylbellidifolin-8-O-glucoside, 7—isoorientin, 8—swertisin, 9—bellidifolin-8-O-glucoside, 10—corymbiferin-1-O-glucoside, 11—bellidifolin, 12—corymbiferin.
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Figure 4. Inter-population differences in the content of 11 secondary metabolites of six G. austriaca populations based on ANOVA and Kruskal-Wallis test. Different letters (a, b, c) indicate statistically significant differences, and grouped letters (ab, abc, bc) indicate the lack of significant differences between grouped variables.
Figure 4. Inter-population differences in the content of 11 secondary metabolites of six G. austriaca populations based on ANOVA and Kruskal-Wallis test. Different letters (a, b, c) indicate statistically significant differences, and grouped letters (ab, abc, bc) indicate the lack of significant differences between grouped variables.
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Figure 5. The contents of 11 secondary metabolites in aboveground plant parts (A), belowground plant parts (B) and seed (S) in G. austriaca. Different letters (a, b, c) indicate statistically significant differences.
Figure 5. The contents of 11 secondary metabolites in aboveground plant parts (A), belowground plant parts (B) and seed (S) in G. austriaca. Different letters (a, b, c) indicate statistically significant differences.
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Figure 6. Discriminant analysis of the secondary metabolites from six G. austriaca populations. Positions of the analyzed individuals and populations within the first and second (a), and first and third (b) discriminant axes.
Figure 6. Discriminant analysis of the secondary metabolites from six G. austriaca populations. Positions of the analyzed individuals and populations within the first and second (a), and first and third (b) discriminant axes.
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Figure 7. A map of investigated area. An asterisk (*) denotes the central location (Divčibare) on the larger map (position of Serbia on the Balkan Peninsula) and the smaller map (investigated area). G. austriaca populations are denoted by numbers (I–VI).
Figure 7. A map of investigated area. An asterisk (*) denotes the central location (Divčibare) on the larger map (position of Serbia on the Balkan Peninsula) and the smaller map (investigated area). G. austriaca populations are denoted by numbers (I–VI).
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Table
Table 1. Standardized coefficients for the first three canonical axes (CA) of variation in G. austriaca secondary metabolites from the discriminant functional analysis of six a priori defined groups. The variables that contribute the most to distinguishing the populations are bolded.
Table 1. Standardized coefficients for the first three canonical axes (CA) of variation in G. austriaca secondary metabolites from the discriminant functional analysis of six a priori defined groups. The variables that contribute the most to distinguishing the populations are bolded.
CompoundCA1CA2CA3
SWM−0.222−1.364−0.982
GP−0.977−2.918−0.352
SWZ−0.247−0.506−0.321
DMB-8-O-glc0.169−2.0373.955
ISOOR0.084−1.038−0.334
SWE−1.3760.3900.475
BDF-8-O-glc1.1052.216−3.160
CBF-1-O-glc1.6501.7100.025
CBF−15.6493.4670.141
MGF−2.0291.894−0.441
BDF16.863−1.9030.854
Eigenvalue6.1713.5931.429
Explained variation (%)50.28629.27411.643
Table
Table 2. Means of canonical variables from the discriminant functional analysis of six a priori defined groups of G. austriaca. Distinct mean values are bothed.
Table 2. Means of canonical variables from the discriminant functional analysis of six a priori defined groups of G. austriaca. Distinct mean values are bothed.
PopulationCA1CA2CA3
I−2.7231.8140.584
II−0.5291.1240.062
III1.7420.427−2.246
IV−0.731−3.6770.215
V4.1170.4481.383
VI−1.877−0.1370.002
Table
Table 3. Geographic locations of the studied populations.
Table 3. Geographic locations of the studied populations.
PopulationLongitudeLatitudeAltitude (m)
I44°4′12″20°0′22″1075
II44°6′3″19°59′4″990
III44°3′33″19°35′19″998
IV44°4′16″20°0′5″1045
V44°4′19″20°0′28″1042
VI44°4′45″20°0′31″995
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Popović, Z.; Vidaković, V.; Mijalković, T.; Krstić-Milošević, D. Population-Related Variability in Qualitative and Quantitative Secondary Metabolite Profile of Gentianella austriaca (A. & J. Kern.) Holub. Plants 2023, 12, 2434. https://doi.org/10.3390/plants12132434

AMA Style

Popović Z, Vidaković V, Mijalković T, Krstić-Milošević D. Population-Related Variability in Qualitative and Quantitative Secondary Metabolite Profile of Gentianella austriaca (A. & J. Kern.) Holub. Plants. 2023; 12(13):2434. https://doi.org/10.3390/plants12132434

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Popović, Zorica, Vera Vidaković, Tatjana Mijalković, and Dijana Krstić-Milošević. 2023. "Population-Related Variability in Qualitative and Quantitative Secondary Metabolite Profile of Gentianella austriaca (A. & J. Kern.) Holub" Plants 12, no. 13: 2434. https://doi.org/10.3390/plants12132434

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