Raman developmental markers in root cell walls are associated with lodging tendency in tef.

MAIN CONCLUSION: Using Raman micro-spectroscopy on tef roots, we could monitor cell wall maturation in lines with varied genetic lodging tendency. We describe the developing cell wall composition in root endodermis and cylinder tissue. Tef [Eragrostis tef (Zucc.) Trotter] is an important staple crop in Ethiopia and Eritrea, producing gluten-free and protein-rich grains. However, this crop is not adapted to modern farming practices due to high lodging susceptibility, which prevents the application of mechanical harvest. Lodging describes the displacement of roots (root lodging) or fracture of culms (stem lodging), forcing plants to bend or fall from their vertical position, causing significant yield losses. In this study, we aimed to understand the microstructural properties of crown roots, underlining tef tolerance/susceptibility to lodging. We analyzed plants at 5 and 10 weeks after emergence and compared trellised to lodged plants. Root cross sections from different tef genotypes were characterized by scanning electron microscopy, micro-computed tomography, and Raman micro-spectroscopy. Lodging susceptible genotypes exhibited early tissue maturation, including developed aerenchyma, intensive lignification, and lignin with high levels of crosslinks. A comparison between trellised and lodged plants suggested that lodging itself does not affect the histology of root tissue. Furthermore, cell wall composition along plant maturation was typical to each of the tested genotypes independently of trellising. Our results suggest that it is possible to select lines that exhibit slow maturation of crown roots. Such lines are predicted to show reduction in lodging and facilitate mechanical harvest.

Chemical Characterization of the Essential Oil Compositions of Mentha spicata and M. longifolia ssp. cyprica from the Mediterranean Basin and Multivariate Statistical Analyses.

This present study aims to characterize the essential oil compositions of the aerial parts of M. spicata L. and endemic M. longifolia ssp. cyprica (Heinr. Braun) Harley by using GC-FID and GC/MS analyses simultaneously. In addition, it aims to perform multivariate statistical analysis by comparing with the existing literature, emphasizing the literature published within the last two decades, conducted on both species growing within the Mediterranean Basin. The major essential oil components of M. spicata were determined as carvone (67.8%) and limonene (10.6%), while the major compounds of M. longifolia ssp. cyprica essential oil were pulegone (64.8%) and 1,8-cineole (10.0%). As a result of statistical analysis, three clades were determined for M. spicata: a carvone-rich chemotype, a carvone/trans-carveol chemotype, and a pulegone/menthone chemotype, with the present study result belonging to the carvone-rich chemotype. Carvone was a primary determinant of chemotype, along with menthone, pulegone, and trans-carveol. In M. longifolia, the primary determinants of chemotype were identified as pulegone and menthone, with three chemotype clades being pulegone-rich, combined menthone/pulegone, and combined menthone/pulegone with caryophyllene enrichment. The primary determinants of chemotype were menthone, pulegone, and caryophyllene. The present study result belongs to pulegone-rich chemotype.

The effects of different protease treatments on the techno-functional, structural, and bioactive properties of bovine casein.

In this study, bovine sodium caseinate (NaCas) was hydrolyzed with four proteases, alcalase, savinase, subtilisin A, and flavourzyme. In addition to the structural changes occurred through the enzymatic hydrolysis, the solubility, oil binding capacity, zeta potential, emulsification properties, and in vitro antioxidant capacity, anti-carcinogenic and antidiabetic properties of hydrolysates were determined. FTIR combined with hierarchical cluster analysis (HCA) made in Amide I region enable to classification of the samples based on the changes of the secondary structure depending on the enzyme type and degree of fragmentation. Technological properties of NaCas were enhanced through the enzymatic hydrolysis, and those were more prominent in serine-type enzymes, regardless of the enzyme type, all hydrolysates showed high antioxidant capacities. All hydrolysates, specifically those produced by savinase and alcalase, reduced the viability of the carcinogenic Caco-2 cells in a dose-dependent manner and showed a very low level of cytotoxicity against healthy HEK-293 cells. The hydrolysis treatment made a significant contribution to the antidiabetic activity of NaCas. Particularly alcalase and savinase hydrolysates suppressed the activity of α- amylase and α- glucosidase. Therefore, the generated milk protein hydrolysates could be used in functional food developments for specific dietary purposes.

Elucidation of Analytical-Compositional Fingerprinting of Three Different Species of Chili Pepper by Using Headspace Solid-Phase Microextraction Coupled with Gas Chromatography-Mass Spectrometry Analysis, and Sensory Profile Evaluation.

The aim of the present study was to determine the volatile compounds of three different species of chili peppers, using solid-phase microextraction (SPME) methods in combination with gas chromatography-mass spectrometry (GC-MS). The detection of marker aroma compounds could be used as a parameter to differentiate between species of chili peppers for their detection and traceability in chili pepper food. The sensorial contribution was also investigated to identify the predominant notes in each species and to evaluate how they can influence the overall aroma. Three different pepper species belonging to the Capsicum genus were analyzed: Chinense, Annuum, and Baccatum. A total of 269 volatile compounds were identified in these species of chili peppers. The Capsicum annum species were characterized by a high number of acids and ketones, while the Capsicum chinense and Capsicum baccatum were characterized by esters and aldehydes, respectively. The volatile profile of extra virgin olive oils (EVOOs) flavored with chili peppers was also investigated, and principal component analysis (PCA) and hierarchical cluster analysis (HCA) of the volatile profiles were demonstrated to be a powerful analytical strategy for building a model that highlights the potential of a volatile characterization approach for use in evaluating food traceability and authenticity.

Using Canadian Water Quality Index method to evaluate the spatio-variation of water quality and the impacts of quality parameters: a case study of Amasya's surface water (Northern Turkey).

In this study, the spatial variation of water quality in Yesilirmak River passing through Amasya was investigated using the Canadian Water Quality Index (CWQI). For this aim, the measured 15 parameters in 3-month periods between the years 2008 and 2015 were used at 11 sample points from the Yesilirmak River and its tributaries. The calculated CWQI scores using parameters of pH, Dissolved Oxygen (DO), Chemical Oxygen Demand (COD), ammonia, ammonium, nitrite, nitrate, phosphate, iron, copper, zinc, potassium, sulfate, sulfite and chlorine range from 33 to 64. These scores indicate that the surface waters in the studied area are poor to marginal in quality. The effect of each parameter on the CWQI scores by excluding each parameter, one by one, considering the water quality of the Yesilirmak River was investigated using the Hierarchical Cluster Analysis (HCA) method. It was determined that the presence and/or absence of the parameters, which caused an increase or decrease in CWQI scores, were ammonia, phosphate, COD, sulfide, iron, ammonium, nitrite, DO. On the other hand, the parameters having positive effects on CWQI are nitrate, chlorine and potassium. The HCA statistical analysis method is suitable for interpreting complex water quality datasets and understanding time/location dependent changes in water quality. HCA can be used effectively to group parameters in river water quality monitoring programs.

Volatile Composition and Biological Activity of Jordanian Commercial Samples of R. coriaria L. Fruits.

The present paper reports the GC-HS-SPME analysis of volatile emission and GC-MS analysis of chemical composition of essential oil of R. coriaria fruits of eight different samples of R. coriaria L. fruits ("sumac" folk name), collected from Jordanian agricultural field and the local market. The analyses show an important variability among the Sumac samples probably due to the origin, cultivation, harvesting period, drying, and conservation of the plant material. The main class of component present in all samples was monoterpenes (43.1 to 72.9%), except for one sample which evidenced a high percentage of sesquiterpene hydrocarbons (38.5%). The oxygenated monoterpenes provided a contribution to total class of monoterpenes ranging from 10.1 to 24.3%. A few samples were rich in monoterpene hydrocarbons. Regarding the single components present in all the volatile emissions, ß-caryophyllene was the main compound in most of the analyzed samples, varying from 34.6% to 7.9%. Only two samples were characterized by α-pinene as the main constituent (42.2 and 40.8% respectively). Essential oils were collected using hydro-distillation method. Furfural was the main constituent in almost all the analyzed EOs (4.9 to 48.1%), except in one of them, where ß-caryophyllene was the most abundant one. ß-caryophyllene ranged from 1.2 to 10.6%. Oxygenated monoterpenes like carvone and carvacrol ranged from 3.2-9.1% and 1.0-7.7% respectively. Cembrene was present in good amount in EO samples EO-2 to EO-8. The antioxidant capacities of the fruit essential oils from R. coriaria were assessed using spectrophotometry to measure free radical scavenger 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical and inhibition of ß-carotene bleaching (BCB). The essential oils from the fruits of the different samples of R. coriaria exhibited the MIC value ranging from 32.8 to 131.25 µg/mL against S. aureus ATCC 6538 and 131.25 to 262.5 µg/mL against E. coli ATCC 8739. The MIC values of ciprofloxacin were 0.59 and 2.34 µg/mL against S. aureus ATCC 6538 and E. coli ATCC 8739, respectively.

Rapid detection of green-pea adulteration in pistachio nuts using Raman spectroscopy and chemometrics.

BACKGROUND: Ground pistachio nut is prone to adulteration because of its high economic value and wide usage. Green pea is known as the main adulterant in frauds involving pistachio nuts. The present study developed a new, rapid, reliable and low-cost methodology by using a portable Raman spectrometer in combination with chemometrics for the detection of green pea in pistachio nuts. RESULTS: Three different methods of Raman spectroscopy-based chemometrics analysis were developed for the determination of green-pea adulteration in pistachio nuts. The first method involved the development of hierarchical cluster analysis (HCA) and principal component analysis (PCA), which differentiated authentic pistachio nuts from green pea and green pea-adulterated samples. The best classification pattern was observed in the adulteration range of 20-80% (w/w). In addition to classification methods, partial least squares regression (PLSR) and genetic algorithm-based inverse least squares (GILS) were also used to develop multivariate calibration models to determine quantitatively the degree of green-pea adulteration in grounded pistachio nuts. The spectral range of 1790-283 cm-1 was used in the case of multivariate data analysis. A green-pea adulteration level of 5-80% (w/w) was successfully identified by PLSR and GILS. The correlation coefficient of determination (R2 ) was determined as 0.91 and 0.94 for the PLSR and GILS analyses, respectively. CONCLUSION: A Raman spectrometer combined with chemometrics has a high capability with regard to the detection of adulteration in pistachio nuts, combined with low cost, strong reliability, a high level of accuracy, rapidity of analysis, and minimum sample preparation. © 2020 Society of Chemical Industry.

Graph based analysis for gene segment organization In a scrambled genome.

DNA recombinant processes can involve gene segments that overlap or interleave with gene segments of another gene. Such gene segment appearances relative to each other are called here gene segment organization. We use graphs to represent the gene segment organization in a chromosome locus. Vertices of the graph represent contigs resulting after the recombination and the edges represent the gene segment organization prior to rearrangement. To each graph we associate a vector whose entries correspond to graph properties, and consider this vector as a point in a higher dimensional Euclidean space such that cluster formations and analysis can be performed with a hierarchical clustering method. The analysis is applied to a recently sequenced model organism Oxytricha trifallax, a species of ciliate with highly scrambled genome that undergoes massive rearrangement process after conjugation. The analysis shows some emerging star-like graph structures indicating that segments of a single gene can interleave, or even contain all of the segments from fifteen or more other genes in between its segments. We also observe that as many as six genes can have their segments mutually interleaving or overlapping.

SERS-based immunocapture and detection of pathogenic bacteria using a boronic acid-functionalized polydopamine-coated Au@Ag nanoprobe.

A surface-enhanced Raman scattering (SERS)-based immunocapture nanoprobe is described for the detection of pathogenic bacteria. The probe uses boronic acid-functionalized polydopamine-coated Au@Ag nanoparticles as an advanced SERS nanotag. Modified magnetic IgG@Fe3O4 nanoparticles are used for magnetic separation. Au@Ag@PDA nanoparticles, where PDA stands for polydopamine, were functionalized with boronic acid to bind to pathogenic bacteria and induce signal amplification. The Raman signal is amplified 108 times when the SERS tag binds the surface of bacteria. The SERS spectra exhibit fingerprint-like patterns that enable bacterial classification. The results of principal component analysis (PCA) and hierarchical cluster analysis (HCA) of the spectral regions were compared. The bacterial surface protein and glycan signals (1300-1450 cm-1) were the best regions for bacterial classification. Staphylococcus aureus, Escherichia coli, Shigella dysenteriae, Pseudomonas aeruginosa, and Klebsiella pneumonia were successfully classified by this method. The lowest detection limit was 10 colonies/mL (CFU·mL). The assay can be completed within 30 min. Conceivably, this method may be extended to the quantitative detection or classification of bacteria under various other conditions. Graphical abstract Schematic representation of immunocapture and detection of pathogenic bacteria using boronic acid-functionalized polydopamine-coated Au@Ag nanoprobe through the bacterial surface protein and glycan signals. Green arrow: laser; black arrow: SERS; red ball: bacteria; grey ball: IgG@Fe3O4; golden ball: boronic acid-functionalized Au@Ag@PDA.

Key Aroma Compounds of Dark Chocolates Differing in Organoleptic Properties: A GC-O Comparative Study.

Dark chocolate samples were previously classified into four sensory categories. The classification was modelled based on volatile compounds analyzed by direct introduction mass spectrometry of the chocolates' headspace. The purpose of the study was to identify the most discriminant odor-active compounds that should characterize the four sensory categories. To address the problem, a gas chromatography-olfactometry (GC-O) study was conducted by 12 assessors using a comparative detection frequency analysis (cDFA) approach on 12 exemplary samples. A nasal impact frequency (NIF) difference threshold combined with a statistical approach (Khi² test on k proportions) revealed 38 discriminative key odorants able to differentiate the samples and to characterize the sensory categories. A heatmap emphasized the 19 most discriminant key odorants, among which heterocyclic molecules (furanones, pyranones, lactones, one pyrrole, and one pyrazine) played a prominent role with secondary alcohols, acids, and esters. The initial sensory classes were retrieved using the discriminant key volatiles in a correspondence analysis (CA) and a hierarchical cluster analysis (HCA). Among the 38 discriminant key odorants, although previously identified in cocoa products, 21 were formally described for the first time as key aroma compounds of dark chocolate. Moreover, 13 key odorants were described for the first time in a cocoa product.

Molecular Spectroscopic Markers of Abnormal Protein Aggregation.

Abnormal protein aggregation has been intensively studied for over 40 years and broadly discussed in the literature due to its significant role in neurodegenerative diseases etiology. Structural reorganization and conformational changes of the secondary structure upon the aggregation determine aggregation pathways and cytotoxicity of the aggregates, and therefore, numerous analytical techniques are employed for a deep investigation into the secondary structure of abnormal protein aggregates. Molecular spectroscopies, including Raman and infrared ones, are routinely applied in such studies. Recently, the nanoscale spatial resolution of tip-enhanced Raman and infrared nanospectroscopies, as well as the high sensitivity of the surface-enhanced Raman spectroscopy, have brought new insights into our knowledge of abnormal protein aggregation. In this review, we order and summarize all nano- and micro-spectroscopic marker bands related to abnormal aggregation. Each part presents the physical principles of each particular spectroscopic technique listed above and a concise description of all spectral markers detected with these techniques in the spectra of neurodegenerative proteins and their model systems. Finally, a section concerning the application of multivariate data analysis for extraction of the spectral marker bands is included.

A subject-transfer framework for obviating inter- and intra-subject variability in EEG-based drowsiness detection.

Inter- and intra-subject variability pose a major challenge to decoding human brain activity in brain-computer interfaces (BCIs) based on non-invasive electroencephalogram (EEG). Conventionally, a time-consuming and laborious training procedure is performed on each new user to collect sufficient individualized data, hindering the applications of BCIs on monitoring brain states (e.g. drowsiness) in real-world settings. This study proposes applying hierarchical clustering to assess the inter- and intra-subject variability within a large-scale dataset of EEG collected in a simulated driving task, and validates the feasibility of transferring EEG-based drowsiness-detection models across subjects. A subject-transfer framework is thus developed for detecting drowsiness based on a large-scale model pool from other subjects and a small amount of alert baseline calibration data from a new user. The model pool ensures the availability of positive model transferring, whereas the alert baseline data serve as a selector of decoding models in the pool. Compared with the conventional within-subject approach, the proposed framework remarkably reduced the required calibration time for a new user by 90% (18.00 min-1.72 ±â€¯0.36 min) without compromising performance (p = 0.0910) when sufficient existing data are available. These findings suggest a practical pathway toward plug-and-play drowsiness detection and can ignite numerous real-world BCI applications.

A pilot study on fingerprinting Leishmania species from the Old World using Fourier transform infrared spectroscopy.

Leishmania species are protozoan parasites and the causative agents of leishmaniasis, a vector borne disease that imposes a large health burden on individuals living mainly in tropical and subtropical regions. Different Leishmania species are responsible for the distinct clinical patterns, such as cutaneous, mucocutaneous, and visceral leishmaniasis, with the latter being potentially fatal if left untreated. For this reason, it is important to perform correct species identification and differentiation. Fourier transform infrared spectroscopy (FTIR) is an analytical spectroscopic technique increasingly being used as a potential tool for identification of microorganisms for diagnostic purposes. By employing mid-infrared (MIR) spectral data, it is not only possible to assess the chemical structures but also to achieve differentiation supported by multivariate statistic analysis. This work comprises a pilot study on differentiation of Leishmania species of the Old World (L. major, L. tropica, L. infantum, and L. donovani) as well as hybrids of distinct species by using vibrational spectroscopic fingerprints. Films of intact Leishmania parasites and their deoxyribonucleic acid (DNA) were characterized comparatively with respect to their biochemical nature and MIR spectral patterns. The strains' hyperspectral datasets were multivariately examined by means of variance-based principal components analysis (PCA) and distance-based hierarchical cluster analysis (HCA). With the implementation of MIR spectral datasets we show that a phenotypic differentiation of Leishmania at species and intra-species level is feasible. Thus, FTIR spectroscopy can be further exploited for building up spectral databases of Leishmania parasites in view of high-throughput analysis of clinical specimens. Graphical abstract For Leishmania species discrimination, sample films of intact parasites and their extracted DNA were analyzed by FTIR micro-spectroscopy. Hyperspectral datasets that comprise mid-infrared fingerprints were submitted to multivariate analysis tools such as principal components analysis (PCA) and hierarchical cluster analysis (HCA).

Essential Oil Composition of Three Globularia Species.

The chemical composition of the essential oils obtained by hydrodistillation from the aerial parts of Globularia cordifolia L., G. meridionalis (Podp.) O.Schwarz, and G. punctata Lapeyr. was characterized by GC-FID and GC/MS analyses. Among the 33 identified compounds, the most abundant present in all investigated samples were oct-1-en-3-ol (2.9-47.0%), 6-(1,5-dimethylhex-4-enyl)-3-methylcyclohex-2-enone (8.2-40.9%), and fukinanolid (7.4-31.6%). Multivariate statistical analyses (PCA and HCA) of the hitherto studied Globularia volatile compounds confirmed to some extent the assumed phylogenetic relationships of the Globularia species studied, including the close relationship between the morphologically similar species G. cordifolia and G. meridionalis, but also evidenced several discrepancies in the current classification of Globularia species.

Essential-Oil Variability in Natural Populations of Pinus mugo Turra from the Julian Alps.

The composition and variability of the terpenes and their derivatives isolated from the needles of a representative pool of 114 adult trees originating from four natural populations of dwarf mountain pine (Pinus mugo Turra) from the Julian Alps were investigated by GC-FID and GC/MS analyses. In total, 54 of the 57 detected essential-oil components were identified. Among the different compound classes present in the essential oils, the chief constituents belonged to the monoterpenes, comprising an average content of 79.67% of the total oil composition (74.80% of monoterpene hydrocarbons and 4.87% of oxygenated monoterpenes). Sesquiterpenes were present in smaller amounts (average content of 19.02%), out of which 16.39% were sesquiterpene hydrocarbons and 2.62% oxygenated sesquiterpenes. The most abundant components in the needle essential oils were the monoterpenes δ-car-3-ene, ß-phellandrene, α-pinene, ß-myrcene, and ß-pinene and the sesquiterpene ß-caryophyllene. From the total data set of 57 detected compounds, 40 were selected for principal-component analysis (PCA), discriminant analysis (DA), and cluster analysis (CA). The overlap tendency of the four populations suggested by PCA, was as well observed by DA. CA also demonstrated similarity among the populations, which was the highest between Populations I and II.

Using LC and Hierarchical Cluster Analysis as Tools to Distinguish Timbó Collections into Two Deguelia Species: A Contribution to Chemotaxonomy.

The species Deguelia utilis and Deguelia rufescens var. urucu, popularly known as "timbó," have been used for many years as rotenone sources in insecticide formulations. In this work, a method was developed and validated using a high-performance liquid chromatography-photodiode array (HPLC-PDA) system, and results were analyzed using hierarchical cluster analysis (HCA). By quantifying the major rotenoids of these species, it was possible to establish a linear relation between them. The ratio between the concentrations of rotenone and deguelin for D. utilis is approximately 1:0.8, respectively, while for D. rufescens var. urucu it is 2:1. These results may help to distinguish these species contributing to their taxonomic identification.

Chemodiversity of volatile oils in Thapsia garganica L. (Apiaceae).

The chemical composition of the volatile oils obtained from the roots, leaves, flowers, and stems of Thapsia garganica of Tunisian origin was investigated by GC-FID and GC/MS analyses. Sesquiterpene hydrocarbons and oxygenated monoterpenes were predominant in the oils of all plant parts. Bicyclogermacrene (21.59-35.09%) was the main component in the former compound class, whereas geranial (3.31-14.84%) and linalool (0.81-10.9%) were the most prominent ones in the latter compound class. Principal-component (PCA) and hierarchical-cluster (HCA) analyses revealed some common constituents, but also significant variability amongst the oils of the different plant parts. This organ-specific oil composition was discussed in relation to their biological and ecological functions. For the evaluation of the intraspecific chemical variability in T. garganica, the composition of the flower volatile oils from four wild populations was investigated. Bicyclogermacrene, linalool, and geranial were predominant in the oils of three populations, whereas epicubenol, ß-sesquiphellandrene, and cadina-1,4-diene were the most prominent components of the oil of one population. PCA and HCA allowed the separation of the flower oils into three distinct groups, however, no relationship was found between the volatile-oil composition and the geographical distribution and pedoclimatic conditions of the studied populations.

Essential-oil variability of Juniperus deltoides R.P.Adams along the east Adriatic coast - how many chemotypes are there?

The composition of the essential oils isolated from twigs of ten Juniperus deltoides R.P. Adams populations from the east Adriatic coast was determined by GC-FID and GC/MS analyses. Altogether, 169 compounds were identified, representing 95.6-98.4% of the total oil composition. The oils were dominated by monoterpenes (average content of 61.6%), which are characteristic oil components of species of the Juniperus section. Two monoterpenes, α-pinene and limonene, were the dominant constituents, comprising on average 46.78% of the essential oils. Statistical methods were deployed to determine the diversity of the terpene classes and the common terpenes between the investigated populations. These statistical analyses revealed the existence of three chemotypes within all populations, i.e., a α-pinene, limonene, and limonene/α-pinene type.

Chemical composition and allelopathic potential of essential oils obtained from Acacia cyanophylla Lindl. Cultivated in Tunisia.

Acacia cyanophylla Lindl. (Fabaceae), synonym Acacia saligna (Labill.) H. L.Wendl., native to West Australia and naturalized in North Africa and South Europe, was introduced in Tunisia for rangeland rehabilitation, particularly in the semiarid zones. In addition, this evergreen tree represents a potential forage resource, particularly during periods of drought. A. cyanophylla is abundant in Tunisia and some other Mediterranean countries. The chemical composition of the essential oils obtained by hydrodistillation from different plant parts, viz., roots, stems, phyllodes, flowers, and pods (fully mature fruits without seeds), was characterized for the first time here. According to GC-FID and GC/MS analyses, the principal compound in the phyllode and flower oils was dodecanoic acid (4), representing 22.8 and 66.5% of the total oil, respectively. Phenylethyl salicylate (8; 34.9%), heptyl valerate (3; 17.3%), and nonadecane (36%) were the main compounds in the root, stem, and pod oils, respectively. The phyllode and flower oils were very similar, containing almost the same compounds. Nevertheless, the phyllode oil differed from the flower oil for its higher contents of hexahydrofarnesyl acetone (6), linalool (1), pentadecanal, α-terpineol, and benzyl benzoate (5) and its lower content of 4. Principal component and hierarchical cluster analyses separated the five essential oils into four groups, each characterized by its main constituents. Furthermore, the allelopathic activity of each oil was evaluated using lettuce (Lactuca sativa L.) as a plant model. The phyllode, flower, and pod oils exhibited a strong allelopathic activity against lettuce.

Chemical Composition of Juniperus communis L. Cone Essential Oil and Its Variability among Wild Populations in Kosovo.

Ripe cones of Juniperus communis L. (Cupressaceae) were collected from five wild populations in Kosovo, with the aim of investigating the chemical composition and natural variation of essential oils between and within wild populations. Ripe cones were collected, air dried, crushed, and the essential oils obtained by hydrodistillation. The essential-oil constituents were identified by GC-FID and GC/MS analyses. The yield of essential oil differed depending on the population origins and ranged from 0.4 to 3.8% (v/w, based on the dry weight). In total, 42 compounds were identified in the essential oils of all populations. The principal components of the cone-essential oils were α-pinene, followed by ß-myrcene, sabinene, and D-limonene. Taking into consideration the yield and chemical composition, the essential oil originating from various collection sites in Kosovo fulfilled the minimum requirements for J. communis essential oils of the European Pharmacopoeia. Hierarchical cluster analysis (HCA) and principal component analysis (PCA) were used to determine the influence of the geographical variations on the essential-oil composition. These statistical analyses suggested that the clustering of populations was not related to their geographic location, but rather appeared to be linked to local selective forces acting on the chemotype diversity.