Open access peer-reviewed chapter

Gas Chromatographic: Mass Spectrometric Mining the Volatilomes Associated to Rhizobiota Exposed to Commonly Used Pharmaceuticals

Written By

Emoke Dalma Kovacs and Melinda-Haydee Kovacs

Submitted: 25 January 2022 Reviewed: 27 January 2022 Published: 10 March 2022

DOI: 10.5772/intechopen.102895

From the Edited Volume

Biodegradation Technology of Organic and Inorganic Pollutants

Edited by Kassio Ferreira Mendes, Rodrigo Nogueira de Sousa and Kamila Cabral Mielke

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Rhizobiota are involved in plant protection through plant development facilitation and plant defense against stress factors. Pressures of global change either as abiotic or biotic stress factor could modify rhizobiota abundance, community structure, or functioning. Such change could result in anomalies of plant development. Human and veterinary medicines are widely used pharmaceuticals. Their active ingredients are not fully adsorbed and metabolized by living organisms and are therefore excreted unmodified. As current technologies of wastewater treatment plants are not designed to remove these contaminants, pharmaceuticals may be discharged into the environment and reach the soil in multiple ways. At present, there are no standard procedures or methodologies that could be easily applied and cover pharmaceuticals impact on soil microbiota. Besides that, available molecular and genetic approach through which soil microdiversity abundance, structure, and functions are evaluated involves high and expensive technology, which is not easily available to laboratories widespread. In this chapter, we propose an effortless way to address this issue by using gas chromatography–mass spectrometry (GC–MS) approaches to assess soil microbiota responses to commonly used pharmaceuticals. The chapter will refer to gas chromatographic techniques applied in assessment of soil microbiota diversity structure, abundance, and health status.


  • microorganisms
  • volatile organic compounds
  • anthropogenic stress

1. Introduction

Microorganisms support essential roles in soil environment with important effects on ecosystem functioning and stability. They assure soil fertility, sustainability, and plant development [1]. However, global change pressures with increasing contaminant inputs and changing climate and environment have influenced native microbiota in different extent. Changes in soil microbiota community abundance, structure, and functioning could limit soil-provided ecosystem services that they mediate [2, 3].

Rhizosphere refers to the plant roots and soils adhering to them. It is considered the most dynamic and biologically active region of soil. Through the large variety and quantity of metabolites that are released by plant root fibrous system or root hair [4], rhizosphere sustains the large diversity of rhizobiota. This includes microorganisms such as algae, protozoa, slime molds, fungi, bacteria, archaea, viruses, etc. [5]. Most of these microorganisms are responsible for plant protection against pathogenic organisms, plant growth and development facilitation, and plant defense against abiotic stress factors [6].

Rhizobiota abundance and community structure modify once with plant root development and changes of soil environment property. Such changes could convert their functions either positively or negatively. Further, that potentially could impact the plant development [7]. There have been developed several approaches that allow assessment and monitoring of soil microbiota diversity and activity to better understand the soil ecology. These could be culture-based or culture-independent approaches. Culture-based techniques have been shown unable to isolate and grow a large domain of soil microorganisms [1]. Phospholipid-derived fatty acids (PLFA) profile analysis for monitoring soil microbiota phenotypic structure is a common culture-independent approach [8]. Additionally, in situ analysis of nucleic acids, direct analysis of DNA/RNA and polymerase chain reaction (PCR)-amplified segment of DNA molecules are frequently applied culture-independent methods [9, 10]. These culture-independent analytical tools are applied for microbial biomass, diversity, and activity assessment based on taxon richness and evenness. Commonly cited disadvantages are those related to sample storage and sample handling, which could limit results’ accuracy. Soil samples’ physicochemical properties also could restrict DNA/RNA extraction efficiency because of potential presence of inhibiting organic compounds or due to binding properties of nucleic acid molecules to soil particles. Further, DNase and RNase contamination could be easily acquired, which reduces results’ accuracy too [1, 9]. Therefore, in the context of global changes that resulted in imminent abiotic and biotic pressures, as well of the importance of microorganism’s key role in assuring soil-provided ecosystem services, it has become a requirement to find optimal evaluation tools for soil microbiota abundance, structure, and functioning assessment. Such biomonitoring tools help to improve ecosystem management strategies and consequently to protect biodiversity and conserve its functionality before loss of delivered ecoservices.

Biomonitoring tools are important to provide quick answer to changes in soil system offering insight on microbiota and its activity without disturbing soil. Gas chromatographic approaches could provide such information. Soil microbiota profiling based on phospholipids-derived fatty acids profile allows quantitative evaluation of living microbiota abundance and phenotypic structure. Bacterial released volatile organic compounds assessment permits evaluation of microbial metabolism status. Therefore, using such analytical approaches is possible to obtain a wider view on microbiota evolution and function under abiotic and biotic pressures raised by global change.

In the following chapter two chromatographic approaches will be presented that allow soil rhizosphere microorganisms’ assessment and monitoring under a common abiotic pressure, the increased presence of pharmaceuticals in our surrounding environment.


2. Rhizobiota functions and related ecosystem services

Rhizosphere could comprise either free living or symbiotic microorganisms. Rhizobiota-related ecosystem services are the benefic outputs for human well-being resulted from microbial activities of the rhizosphere. These benefits are the end results of biotic and abiotic interactions and processes. Microbial communities are involved in organic matter decomposition, nutrient cycling, and pollutants degradation. They could stimulate or inhibit plants through the metabolites that they release. Those, they are directly involved in soil regulating, supporting, and provisioning services.

Rhizobiota involvement in soil regulating services: Main regulating services managed by soil microorganism are diseases and pest regulation, organic waste matter degradation, and pollutants degradation.

Diseases and pest regulation: Biological factors induced plant diseases cause decline of crop yields and quality. In the context of increased food demand once with global population increases, this resulted in frequent use of chemicals that prevent and control plant diseases and that warrant required fertilizers. Although extensive use of these chemicals has achieved the proposed objectives, their use has also resulted in unwanted side effects such as environment pollution, food products contamination and ecosystem alteration. The potential amplitude in time of these side effects ended in the necessity to find alternative eco-friendly solutions that minimize these associated health risks. Studies revealed that use of biological control agents could become a suitable alternative [11]. This started from the evidences that there are numerous mechanisms throughout microorganisms, including rhizobiota also, that influence directly or indirectly pathogen diseases. Soil bacteria and fungi life support functions could be summarized as antagonism, resistance, competition, and stimulation of plant defenses. At the moment is an increased interest in identifying and further the applying of beneficial plant-associated microorganisms instead of classical pesticides for pest and disease management. There are studies that identified different bacterial or fungal species that could control or act against several pests or diseases. Pseudomonas strains, which could be located also in rhizosphere, act against Phytophthora infestans oomycetes, which are a frequent damaging pathogen of potato [12, 13]. Trichoderma harzianum biocontrol Rhizoctonia solani, a soil-born pathogen, and Fusarium oxysporum f.sp., a fungus, act against crops of the Solanaceae family and other plants [12, 14]. The biocontrol ability of these microorganisms against pests and diseases is directly correlated with production of numerous organic and inorganic molecules.

Organic waste degradation: Organic waste degradation is considered a two-stage biotic process. Through this process, organic waste is first fragmented into smaller pieces by deprives, followed by deconstruction of these fragments into organic and inorganic molecules by microorganisms [15]. Rhizosphere microbiota are involved in decomposition of organisms and plants waste. Obtained components after decomposition processes are easily taken up by living organisms or removed from soil environment through leaching and runoff processes. Their ability to enhance decomposition processes of organic wastes resulted in raising the use in different fields of organic waste management areas (municipal solid waste, agricultural waste, etc.). They started to be used successfully in different biotechnology fields as renewable biogas production or composting for soil fertility enrichment [16].

Pollutant degradation: Presence of pollutants increased over years in all environmental compartments. Although abiotic treatment processes (physical and chemical) are widely applied and considered most of the time efficient in decontamination processes, these processes are often associated with potential few constraints. One of such constraints is the generation of secondary pollutants through the decontamination process. Also, the high cost required in such treatment processes also limits their applicability in low-income regions. Use of biological treatment was found as an advantageous approach [17]. It is widely used all over the world for emerging pollutants removal from wastewater. Also, different microbial strains started to prove their efficiency in degradation of different pollutants. Mycobacterium sp. and Bacillus megaterium, for example, are efficient in polycyclic aromatic hydrocarbons degradation in the presence of specific enzymes (e.g., ring hydroxylating and ring cleavage dioxygenase) [18]. Acidisphaera, Burkholderia, Geobacillus, Pseudomonas, and Rhodococcus bacteria are considered alkane-degrading bacteria [19]. Sphingomonas sp. and Burkholderia sp. degrade fenitrothion pesticide [20].

Rhizobiota involvement in soil supporting services: Supporting services are that services that hold up ecosystem functions that are indirectly used by humans. Soil microorganisms are critically involved in soil nutrients cycling and primary production.

Nutrients cycling: Plant development and production require adequate nutrient resources. Rhizosphere bacterial and fungal community are involved in organic matter breakdown and recycling. Through their related catabolic reaction, they breakdown, transform, and mineralize macro- and micro-nutrients [21]. Proteobacteria and Rhizobia bacteria are involved in nitrogen fixation. Cianobacteria and Eubacterium enhance Zn and Fe translocation into plant.

Primary production: Plant production is influenced by numerous microbial processes. Proteobacteria and Firmicutes enhance plant root system proliferation through produced organic compounds. Rhizobium sp., and Frankia sp. are involved in nitrogen fixation. Streptomyces and Pseudomonas produce iron-chelating compounds that facilitate Fe availability for plants. Agrobacterium sp. and Bacillus sp. are involved in phosphate solubilization. Numerous microorganisms increase plant stress tolerance through their produced organic and inorganic compounds [22].

Rhizobiota involvement in soil provisioning services: Provisioning services are those products that are obtained from ecosystem. Generally, these refer at food, fiber, genetic resources, chemicals, pharmaceuticals, etc. Microorganisms are considered important resources for numerous chemicals and pharmaceuticals with a broad range of applications.

Bioresource: Bacterial and fungal population of rhizosphere influences plant communities, pathogens abundance, nutrient acquisition, and stress tolerance [15]. In most cases these are controlled by the produced bacterial and fungal origin molecules. Rhizosphere microorganisms were acknowledged as important bioresources for bioactive substances. They produce antibiotics, bacteriocins, lipopeptides, toxins, siderophores, enzymes, biosurfactants, osmoprotective substances, and other secondary metabolites [23].


3. Microbial volatilome: challenges under pressures of pharmaceuticals’ presence in environment

Rhizosphere microorganisms either free-living or biofilm-forming or root-colonizing emit numerous volatile organic compounds through metabolic processes and biochemical processes that synthesize. Microbial volatile organic compounds are small molecules with low boiling points. These compounds diffuse quickly through soil particles. As many microbial volatile organic compounds are acknowledged for their pathogen’s suppression activity, the physicochemical properties of these molecules increase their efficiency [24].

Garcia-Delgado et al. [25] evidenced that repeated application of herbicides reduced significantly fungal community abundance while that of Actinobacteria has been increased. Presence of metal pollutants also could exert pressures on soil microbial community phenotypic structure [26, 27]. Studies revealed that presence of pollutants changes soil microbiology through microbiota community structure and activity, lowering both their abundance and metabolic activity.

Human and veterinary pharmaceutical’s presence in environment increased over the years. Nonsteroidal anti-inflammatory drugs (NSAIDs) are popular over-the-counter drugs used for mild-to-moderate pain such as headache, muscle, or other inflammation issues [28]. These medicines reach environment through wastewater treatment plants’ end products, treated water, and sludge. This is because current wastewater treatment plants are not adequate enough to remove pharmaceuticals from wastewater body [29]. NSAIDs could pollute soil environment through sludge dispersal as fertilizer on agricultural soils or through wastewater reuse for irrigation purposes. Among NSAIDs, diclofenac and ibuprofen are the most reported drugs. Both ibuprofen and diclofenac were reported in environmental samples within ranges of ppb–ppm [28]. Concern of NSAIDs’ presence in environmental compartments is heightened by their potential chronic adverse effect on nontargeted organisms because of long-term exposure. Studies present that diclofenac may induce changes in the physiology of Hediste diversicolor and Solea senegalensis and other marine species [30]. Kidney and liver damage was reported by Hussain et al. [31] in case of Gallus gallus, Columba livia, Coturnix japonica, and Acridotheres tristis exposed to diclofenac.

Earlier studies have shown that management practices influence microbial community structure and abundance. This in turn could change microbial volatile organic compounds in composition as well as in quantity. However, at the moment there are no data reported on how the presence of these pharmaceuticals could affect rhizosphere microbiota and its functioning. Based on the importance of rhizobiota-emitted volatile organic compounds in plant protection and development enhancement and potential toxic effects of such pharmaceuticals on rhizosphere microbiota, it has become important to understand microbiota community change and behavior under such challenges.


4. Key study: rhizobiota volatilome changes under challenges of pharmaceuticals

4.1 Experimental setup

Based on the frequency of their presence in the environment, the following nonsteroidal anti-inflammatory drugs were choosing for experiment: ibuprofen, ketoprofen, and diclofenac. Commonly consumed aromatic plants such as sage (Salvia officinalis L.), dill (Anethum graveolens), and rosemary (Rosmarinus officinalis L.) were used in the experiment. Argic phaeozem soil, free of studied pharmaceuticals, was used in this experiment. Soil material was contaminated individually with each of these pharmaceuticals with the following theoretical concentrations: 0.7 mg⋅kg−1 diclofenac, 0.5 mg⋅kg−1 ibuprofen, and 0.2 mg⋅kg−1 ketoprofen. Ten-day seeds of the selected plant materials were planted in pots containing approximately 1.2 kg of contaminated soils and allowed for development until maturity. Plant growth was performed in laboratory in a climate chamber with the following conditions: day – 24°C, 12 h of light; night – 18°C, 12 h; soil water-holding capacity was adjusted to 58% during the experiment. Control samples without soil contamination were grown in similar conditions. Each experiment was performed with three pots in parallel. Rhizosphere soil samples were collected after each plant has reached maturity. The schematic presentation of experiment setup is shown in Figure 1. From each rhizosphere 1 g of soil was collected for soil microbiota community assessment and 1 g of soil for microbial volatile organic compounds analysis.

Figure 1.

Experiment setup.

4.2 Gas chromatographic assessment of rhizosphere microbiota community

One gram of lyophilized rhizosphere soil was used for microbiota phenotypic structure and abundance analysis. Assessment was performed applying phospholipids-derived fatty acids (PLFA) gas chromatographic approach. Phospholipids-derived fatty acids were extracted according to the method presented by Blight and Dyer [32], and Frostegard et al. [33] and derivatized for gas chromatographic analysis (7890A GC-FID, Agilent Technologies, Santa Clara, CA, USA). Their detection was done with flame ionization detector. Separation of all fatty acid methyl esters from each extract was done with a 5% phenyl-methyl polysiloxane column (25 mm × 0.2 mm id., 0.33 μm film thickness, HP-Ultra 2, J&W Scientific, Folsom, CA, USA). Helium was used as carrier with 1.2 mL·min−1 flow. Detector and injector temperature was set at 300 and 280°C, respectively. Oven temperature program starts at 170°C followed by an increase with 28°C·min−1 until 288°C, continued with an increase with 60°C·min−1 until 310°C. This final temperature was maintained isotherm for 1.25 min. Phenotypic profile of rhizobiota based on PLFA profile was determined using the MIDI SherlockTM Microbial Identification System software (Microbial ID, Inc., Newark, DE, USA). Also, the following PLFA biomarkers were used to identify saprotrophic fungi, ectomycorrhizal fungi, nitrogen-reducing bacteria and sulfur-reducing bacteria: 18: 2ω6c – saprotrophic fungi; 18:2ω9c – ectomycorrhizal fungi; 18:2ω6c and 18:3ω3 – nitrogen-reducing bacteria; and 17:1ω7c, 10Me16:0, 17:1ω6, 15:1, i17:1ω7c, cy18:0ω7.8, i15:1ω7c and i19:1ω7c for sulfur-reducing bacteria [32, 33].

4.3 Gas chromatographic–mass spectrometric in profiling rhizobiota volatilomes

Volatile organic compounds emitted by rhizobiota were assessed through headspace-solid-phase microextraction sampling using 85 μm polyacrylate fiber (Supelco Inc., Bellefonte, PA, USA). For this analysis, 1 g of rhizosphere soil was diluted with 2 mL of PBS solution in 20 mL headspace glass vials (Agilent Technologies). The tightly capped headspace vials were incubated for 72 h in dark at 25°C. After this period, the vials were equilibrated for 30 min at 60°C using a TriPlus RSH autosampler (Thermo Scientific, Austin, TX, USA). Thermally activated SPME fiber was inserted in the vial headspace surface and kept for 15 min to allow the adsorption of volatile organic compounds on the fiber extractive phase. Rhizobiota volatilome analysis was conducted on gas chromatography–mass spectrometry (GC–MS/MS, Trace 1310, TSQ 9000, Thermo Scientific, Austin, TX, USA). Ionization was carried out in electron impact mode at 70 eV ionization energy. Volatile organic compounds were separated on a HP-5MS capillary column 30 m × 0.25 mm, 0.25 μm). The carrier gas was He with 1.2 mL·min−1 flow. The SPME fiber with adsorbed volatile organic compounds was inserted into the GC injection port at 250°C for 5 min to allow the desorption of analytes. The volatile organic compounds were identified by comparison of their mass spectra with compounds corresponding to mass spectra library (NIST/EPA/NIH, Chromeleon 7.2 CDS Software, Thermo Scientific, Austin, TX, USA). All identified volatile organic compounds were expressed in percentages as a normalized amount of each volatile organic compound resulted after the division of peak areas of identified volatile organic compounds by total peak area of all identified volatile organic compounds.

4.4 Rhizobiota differentiation between studied plant species rhizosphere

Total abundance of control samples of rhizosphere soil of Rosmarinus officinalis L., Anethum graveolens, and Salvia officinalis L. microbiota varies within the range of 216.6–191.8 nmol⋅g−1. Higher abundance was identified in R. officinalis L. rhizosphere, followed by A. graveolens and S. officinalis L. Bacterial dominance was observed in all cases, bacterial PLFA:total PLFA being higher than 0.8. Representative bacterial groups were Gram-negative bacteria, followed by Gram-positive and aerobe bacteria group. Gram-negative bacteria abundance represented 82.3% in R. officinalis L., while in rhizosphere of A. graveolens and S. officinalis L. represented 79.1 and 68.5% (see Figure 2).

Figure 2.

Bacterial communities’ abundance variation in studied rhizosphere soils. a.) Rosmarinus officinalis L.; b.) Anethum graveolens; c.) Salvia officinalis L.

Fungal community represented approximately 14% of the total microbial abundance, with higher abundance in S. officinalis L. – 16.2%.

4.5 Rhizobiota emitted volatile organic compounds variation studied rhizosphere

In control rhizosphere of the three aromatic plants, the main emitted volatile organic compounds measured through GC–MS were terpenes, alcohols, aromatic compounds, ketones, and organic acids. Identified volatile organic compounds percentage amount is listed in Table 1.

GroupCompound nameVolatile organic compounds (%)
Salvia officinalis L.Anethum graveolensRosmarinus officinalis L.
Aromatic compounds2-phenylethanol3.152.650.78
germacrene D1.064.660.95
germacradien-1 l-ol1.250.881.62
methyl eugenol4.486.754.11
Organic acidsacetic acid0.843.510.32
dodecanoic acid1.550.651.71
propanoic acid3.680.542.21
2-methylbutanic acid1.751.620.55
pentanoic acid1.590.840.94
butanoic acid2.151.543.01
2-methylpentanoic acid1.880.561.84
Esterethyl acetate2.782.334.15
Nitrogen compoundsIndole2.152.083.54
methyl pyrazine0.440.240.44
2.5-dimethyl pyrazine0.580.642.15

Table 1.

Percentage value of emitted volatiles in control samples rhizosphere.

Terpenes were determined in higher amount in all rhizosphere soil with an average amount of 26%. Higher content of terpene compounds was measured in R. officinalis L. (30%) followed by A. graveolens (28%) and S. officinalis L. (20%). In case of S. officinalis L. rhizosphere, the second representative group of volatile organic compounds was organic acids (13.4%) followed by alkane compounds (12.6%). In the rhizosphere soil of A. graveolens and R. officinalis L., the second prevalent group was alkane for both cases. In all rhizosphere soils, ester compounds were found in lower amount (< 5%).

4.6 Pharmaceuticals’ influence on rhizobiota community and volatilome profile

Rhizosphere microbiota total PLFA ranged between 216.6 and 167.6 nmol⋅g−1 dry weight soil. Between studied plant species during all experiment cases, it was observed that the rhizosphere microbiota abundance was higher in case of R. officinalis L. rhizosphere soil followed by A. graveolens and S. officinalis L. (see Figure 3). Rhizobiota community phenotypic profile revealed bacterial dominance, bacterial PLFA:total PLFA >0.837. Gram-negative bacteria were the most representative bacterial group in studied rhizosphere soils. Their abundance was within 56.8–82.3 nmol⋅g−1. They were followed by Gram-positive bacteria and aerobe bacteria. PLFA ratio among aerobe bacteria and anaerobe bacteria was higher than 3.6 for S. officinalis L. rhizosphere and 1.4 for A. graveolens and R. officinalis L., these data clearly evidence aerobic bacteria dominance. Fungal community was represented within 9.5–16.3% of the total rhizobiota abundance in studied experiments.

Figure 3.

Total microbial, bacterial, and fungal abundance variation in studied aromatic plants rhizosphere exposed at different NSAIDs.

Influence of studied NSAIDs on rhizosphere microbial community was observed from experimental data. Compared with control samples, in all cases was seen a decrease in total abundance. Rosmarinus officinalis L. rhizosphere total abundance decreased with 8.5% under exposure to ketoprofen, followed by a decrease with 7.4% at diclofenac exposure and 5.1% at ibuprofen exposure. Compared with control samples, Anethum graveolens rhizosphere microbiota decreased with 13% in case of exposure to diclofenac and ketoprofen and with 11% in case of exposure to ibuprofen. Salvia officinalis L. rhizosphere microbial community did not decrease when it was exposed at diclofenac but presented a lower abundance with 12.6% and 5.6% when it was exposed to ibuprofen and ketoprofen, respectively.

Principal component analysis revealed that rhizosphere microbial community structure could change under exposure to specific NSAIDs (Figure 4). Gram-positive bacteria, fungi, and methanotroph bacteria in S. officinalis L. rhizosphere presented a positive correlation in the presence of diclofenac while Gram-negative bacteria and ectomycorrhizal fungi decreased in the presence of ibuprofen (Figure 4a). This was explained by principal component analysis in 77.3%. Ibuprofen presence has a negative impact on methanotroph bacteria, N-reducing bacteria, and saprotrophic fungi in R. officinalis L. rhizosphere. Diclofenac’s presence did not show significant impact on Gram-positive and aerobe bacteria (PC1 58%, PC2 25%; Figure 4b). Diclofenac’s presence was also negatively correlated with N-reducing bacteria and Gram-positive bacteria abundance in A. graveolens rhizosphere (Figure 4c).

Figure 4.

Principal component analysis of NSAIDs’ impact on rhizosphere soils microbial communities. a.) Salvia officinalis L.; b.) Rosmarinus officinalis L.; c.) Anethum graveolens.

Emitted volatile organic compounds in studied rhizosphere changed over exposure to NSAIDs. In case of S. officinalis L. rhizosphere, the higher decrease was observed for alcohol compounds and organic acids in the presence of ibuprofen (< 15%), especially in case of hexan-1-ol, butane-2.3-diol and propanoic acid. Under contamination with diclofenac, aromatic compounds increased slightly (> 2%). Rhizosphere emitted volatile organic compounds of A. graveolens presented an increase with approximately 5–10% in case of phenol, germacrene, methyl eugenol, butanoic acid, and nonanal in the presence of ketoprofen while indole decreased with approximately 30% in case of exposure to ibuprofen and diclofenac. R. officinalis L. rhizosphere emitted volatile organic compounds changed significantly in the presence of ibuprofen and diclofenac. The following decrease was observed compared with control samples: terpene content <12%, organic acids <7% and alkane <4%.


5. Conclusion

Changes in both rhizosphere microbiota abundance and structure as well of emitted volatile organic compounds in the presence of commonly reported NSAIDs contaminants make us to suppose that microbiota rhizobiota functioning could be also changed. However, more studies in this area should be conducted to better understand the impact of pharmaceutical residues’ presence on rhizosphere microbiota mediated soil ecosystem services. These are important to conserve soil ecosystem provided ecosystem services.



This research was funded by ANCS, Program NUCLEU, grant number PN 19-18.01.01-18 N/08.02.2019 and project financed by the Ministry of Research, Innovation and Digitization through Program 1- Development of the national research and development system, Subprogram 1.2 - Institutional performance - Projects that finance the RDI excellence, Contract no. 18PFE/30.12.2021.


Conflict of interest

The authors declare no conflict of interest.


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Written By

Emoke Dalma Kovacs and Melinda-Haydee Kovacs

Submitted: 25 January 2022 Reviewed: 27 January 2022 Published: 10 March 2022