The relationship between mountain wetland health and water quality: A case study of the upper Hanjiang River Basin, China

This study investigates the degradation process of mountain wetlands in the upper Hanjiang River Basin (HRB) over a 30-year span from 1990 to 2020. In particular, the landscape development intensity (LDI) index was employed to conduct a comprehensive assessment of the wetland health. This was subsequently combined with the spatio-temporal changes of water quality in the basin to explore the potential correlations between the health status of mountain wetlands and the associated watershed water quality. The results show that over the past three decades, wetland ecosystems have shrunk by 18% due to conversion into farmland, grass, construction land and forest land. This was significant between 2010 and 2020, as shown by a land use dynamic index of -1.121% during 2010-2020, which was significantly higher than that in the preceding two decades (0.003%, 0.367%) (p < 0.05). LDI values for individual sub-watersheds across different years ranged from 2.39 to 4.93, demonstrating an increasing trend since 2010. This indicates a heightened level of human interference in mountain wetlands. Although the water quality within the basin generally adhered to the Class II surface water quality standard, total nitrogen (TN) (primarily from farming) was a concern. Areas with relatively more human activity were observed to exhibit increased pollution levels, as demonstrated by a positive correlation between LDI and the concentrations of total phosphorus (TP), ammonium nitrogen (NH4+-N), and chemical oxygen demand (COD) in the basin. The LDI of the mountain wetland exhibited a consistent positive correlation with the water quality comprehensive function, both during the flood (r = 0.77-0.81) and non-flood (r = 0.61-0.70) seasons (p < 0.05). This indicates the significant impact of the wetland landscape structure on the water quality within a 1000 m radius on either side of the river. Special attention should be paid to the management and allocation of wetland landscapes within this 1000 m buffer zone. Furthermore, efforts to control upstream pollutant emission should be strengthened.

A holistic approach to the assessment of heavy metal levels and associated risks in the coastal sediment of Giresun, southeast Black Sea

A seasonal study was conducted to assess the levels, sources, and potential ecological risks of heavy metals (HM) in coastal sediments along the Giresun Coast, located on the southeast coast of the Black Sea. The mean concentrations of HMs as mg/kg were ranked as Fe (27646.37) > Al (27348.55) > Mn (571.87) > Zn (94.16) > Cr (60.64) > Cu (45.66) > Pb (41.37) > Ni (27.29) > Co (14.47) > As (7.36) > Cd (0.20), respectively. At all stations through the year, Al, Cr, Mn, Fe, Co, and Ni were in "the minimum enrichment" class as evaluated by the enrichment factor (EF). As assessed by the contamination factor (CF), all HM levels except Pb, Fe and Cu were "low" or "moderately polluted" at all stations and seasons. With the exception of Cd levels, all HMs in all seasons and stations pointed out "low ecological risk" according to the ecological risk index (E_rⁱ). According to the sediment quality guidelines, Ni, Cu and Pb were observed to pose a high ecological risk to habitat. The combined risk assessment indices pointed out low to moderate ecological risk. The study concluded that the region is subject to minimum anthropogenic disturbances in the aquatic environment.

A holistic approach to the eco-geochemical risk assessment of trace elements in the estuarine sediments of the Southeastern Black Sea

The estuarine sediments were sampled seasonally along the southeast coast of the Black Sea, to assess the concentrations, sources, distributions, and possible ecological risks of trace elements (TEs). The mean concentrations of TEs (mg/kg) were ranked as Fe (56,659.83) > Al (39,758.00) > Mn (1168.53) > Zn (155.03) > Cr (120.75) > Pb (93.71) > Cu (82.66) > Ni (44.93) > Co (17.98) > As (13.66) > Cd (0.99) > Hg (0.18), respectively. The stations S4 and S6 showed "very high contamination" for Pb, "significantly enrichment" for Pb and Cd, "high ecological risk" for Cd, and "heavily polluted" for Pb and Cd according to the results of CF, EF, E_rⁱ, I_geo, respectively. The rest of the stations were in the low or moderate contamination through the all seasons as assessed by different eco-geochemical risk assessment indices. The integrated risk evaluation indices indicated no contamination in stations S3 and S5.

Metabolomics with multi-block modelling of mass spectrometry and nuclear magnetic resonance in order to discriminate Haplosclerida marine sponges

A comprehensive metabolomic strategy, integrating ¹H NMR and MS-based multi-block modelling in conjunction with multi-informational molecular networking, has been developed to discriminate sponges of the order Haplosclerida, well known for being taxonomically contentious. An in-house collection of 33 marine sponge samples belonging to three families (Callyspongiidae, Chalinidae, Petrosiidae) and four different genera (Callyspongia, Haliclona, Petrosia, Xestospongia) was investigated using LC-MS/MS, molecular networking, and the annotations processes combined with NMR data and multivariate statistical modelling. The combination of MS and NMR data into supervised multivariate models led to the discrimination of, out of the four genera, three groups based on the presence of metabolites, not necessarily previously described in the Haplosclerida order. Although these metabolomic methods have already been applied separately, it is the first time that a multi-block untargeted approach using MS and NMR has been combined with molecular networking and statistically analyzed, pointing out the pros and cons of this strategy.

Source apportionment of heavy metals in sediments of the urban rivers flowing into Haizhou Bay, Eastern China: using multivariate statistical analyses and Pb-Sr isotope fingerprints

Urban river runoff carrying various anthropogenic sources of heavy metals (HMs) is the most important input pathways for HM pollutions in the coastal region, apportioning sources of environmental pollutants is key to controlling coastal HM pollution. In the study, surface sediments were collected from seven urban rivers flowing through Lianyungang City and discharging into Haizhou Bay, Eastern China. The concentrations of HMs of the river sediments were, in mg/kg (mean value ± standard deviation): Mn (550 ± 227) > Zn (67 ± 61) > Cr (33 ± 12) > Ni (21 ± 8.5) > Cu (16 ± 7.6) > Pb (15 ± 5.6) > Cd (0.11 ± 0.06), which were slightly to moderately polluted. As important outlets for municipal and industrial sewages, the Shawang River and Linhong River were the most polluted. Based on the multivariate statistical analysis, HMs were attributed to anthropogenic source (industrial, domestic, and agricultural discharges) and natural source (soil parent materials and atmospheric deposition). Based on isotope source apportionment, Pb was mainly from natural source, exhausts of leaded gasoline vehicles, and coal combustion, with the mean contributions of 39.3%, 23.7%, and 37.0%, respectively, and Sr originated from natural source and anthropogenic source, with mean contributions of 31.8% and 68.2%, respectively. Pb-Sr isotopes illustrated that anthropogenic inputs were the dominant source for HMs in urban river sediments flowing into Haizhou Bay, and the isotope tracing results make up the discriminating deficiency of the multivariate statistical analysis.

Recognition of pathogens in food matrixes based on the untargeted in vivo microbial metabolite profiling via a novel SPME/GC × GC-QTOFMS approach

Foodborne diseases incurred by pathogenic bacteria are one of the major threats in food safety, and thus it is important to develop facile and effective recognition methodology of pathogens in food. Herein, a new automatic approach for detection of in vivo volatile metabolites emitted from foodborne pathogens was proposed by coupling solid phase microextraction (SPME) technique with a comprehensive two-dimensional gas chromatography quadrupole time-of-flight mass spectrometry (GC × GC-QTOFMS). A novel polymer composite based SPME probe which possessed high-coverage of microbial metabolites was utilized in this contribution to realize the sensitive extraction of untargeted metabolites. As a result, a total of 126 in vivo metabolites generated by the investigated pathogens were detected and identified, with 33, 29, 25, 21 and 18 volatile metabolites belonging to Shigella sonnei, Escherichia coli, Salmonella typhimurium, Vibrio parahaemolyticus and Staphylococcus aureus, respectively. Multivariate statistical analyses were applied for further analysis of metabolic data and separation of responsive metabolic features among different microbial systems were found, which were also successfully verified in foodstuffs contaminated by microorganisms. The growth trend of the potential volatile markers of each pathogen in food samples kept consistent with that of the pure strain incubated in medium during the whole incubation time. This study promotes the application of SPME technology in microbial volatile metabolomics and contributes to the development of new approaches for foodborne pathogens recognition.

Geochemical evolution and tracing of groundwater salinization using different ionic ratios, multivariate statistical and geochemical modeling approaches in a typical semi-arid basin

The vulnerability of semi-arid basin aquifers to long-term salinization due to the dissolution of groundwater chemical constituents is a major global problem. Despite this, resilient techniques of tracing the sources of groundwater salinization in semi-arid basin aquifers are still evolving due to the aquifer complexities. This study proves the effectiveness of the use of different ionic ratios, multivariate statistical, and geochemical modeling approaches to understand groundwater evolution and trace salinization in the semi-arid Pru Basin of Ghana. The basin is homogeneously composed of argillaceous sediments of the Oti/Pendjari Group of the Voltaian Supergroup. A total of 81 samples from hand-dug wells and boreholes within the Pru Formation of the Oti/Pendjari Group in the basin were collected for this study. Quantitative analysis of the data shows that the abundance of major ions follows the order: Na⁺ > Ca²⁺ > Mg²⁺ > K⁺ and Cl^- > HCO₃^- > SO₄^2-. The groundwater evolved from Na-HCO3, Na-HCO3-Cl, Na-Ca-HCO3 to Na-Mg-HCO3 water types in a decreasing order of abundance. Calculated meteoric genesis index (r2) indicates the dominance of deep meteoric water percolation effects on groundwater chemistry. Groundwater chemistry is principally controlled by water-rock interaction, ion exchange reactions, weathering (carbonate and silicate), salinization, and anthropogenic activities. Different ionic ratio plots and spatial distribution maps reveal the prevalence of salinization in the aquifer system, especially around the southwestern part of the basin. Revelle index assessment of the groundwater salinization level indicates that about 19.8% of the groundwater samples with RI values >0.5 is influenced by salinization. The groundwater salinization results from saline water intrusion from adjacent aquifers, mixing effects, ion exchange reactions, water-rock interaction, and anthropogenic activities. The geochemical modeling involving thermodynamic calculation of mineral saturation indices in PHREEQC indicates that groundwater is largely saturated with respect to majority of the carbonate and silicate mineral phases.

Distribution and origin of potentially toxic elements in a multi-aquifer system

Pollution of the potentially toxic elements (PTEs) is a major concern in the metal ore-mining environment. Active polymetallic industries and mines cause great continuous devastation of both terrestrial and aquatic environments on a local and regional scale. This study investigated the pollution of surface water and groundwater in the area containing six large-scale iron ore mines, which have been in operation for more than a few decades. In order to assess the PTEs pollution, the spatial and temporal distributions of 13 different PTEs (Al, As, Co, Li, Mn, Mo, Ni, Pb, Rb, Se, Si, Sr, and Zn) were measured in 42 water samples collected from the multi-aquifer system including three distinct aquifers (upper alluvial aquifer (UAA), lower alluvial aquifer (LAA), and hard-rock aquifer (HRA)) of the Gohar-Zamin mining area in Iran. The highest concentrations of total dissolved solids (TDS = 164,000 mg/l) and PTEs were measured in HRA. Three trends were identified between the PTE concentration and increasing of TDS based on Spearman correlation analysis: (1) an increasing trend for Al, Co, Li, Mn, Rb, Se, Sr, and Ni; there were strong positive correlations in HRA between TDS and Mn (0.83), Al (0.65), Co (0.74), Li (0.90), Ni (0.83), Rb (0.91), Se (0.82), and Sr (0.84), suggesting a common origin for these elements; (2) no obvious trend for As and Mo, no correlation was founded between As and Mo with other PTEs and TDS, indicating a natural geogenic origin and mutual dependencies of these elements; and (3) a decreasing trend for Si, Zn, and Pb; TDS had a significantly negative correlation with the PTEs and attributing to different chemical properties of infiltrated groundwater. In the principal component analysis (PCA), the first PC that covers 85.09% of the total observed variance is mainly attributed the groundwater salinization. This component is composed of Al, Co, Li, Mn, Rb, Se, Sr, and Ni. The second PC contains elements As and Mo. This PC explain 14.4% of total variance and may be referred to natural origin of PTEs. Si, Zn, and Pb are in the third principal component and cover 9.64% of the variance of the data. Third PC have been attributed to lithogenic and/or primary water chemistry factors. The PTE pollution were evaluated based on heavy metal evaluation index (HEI), heavy metal pollution index (HPI), and degree of contamination (C_d). The results indicated that all of the groundwater samples collected from HRA had HEI, HPI, and C_d values greater than 21, 264, and 14 (highly pollution limits of indices), respectively, and were classified as highly polluted groundwater. HPI values within the UAA, LAA, and salt playa (SP) were lower than the critical level of 100, suggesting a threshold for the drinking water pollution. Moreover, HEI and C_d with values of less than 10 and 7 suggested low-level pollution in UAA, LAA, and SP. However, the contaminated level of PTEs exceeded the WHO standard for drinking water in HRA only. Since groundwater in HRA is a brine with the high values of PTEs, pumping of this water out to the surrounding natural environment may cause harmful impacts on the environment and perhaps living species in Bahram-e-Goor protected area. Graphical abstract.

Metabolomic profiling of Zanthoxylum species: Identification of anti-cholinesterase alkaloids candidates

The isolation of bioactive compounds from natural sources is a key step in drug discovery and development, however, this procedure is usually expensive and difficult due to the complexity and the limited amounts of the metabolites in the extracts. Thus, rational or targeting isolations are becoming more popular to reduce the bottlenecks in bioactive natural products research. In this study, we used a LC-MS-based metabolomic approach and biochemometric statistical tools (PCA and OPLS-DA) to identify potential anti-cholinesterase alkaloids predictors in Zanthoxylum genus (Rutaceae). For this purpose, 41 alkaloid extracts from nine Colombian Zanthoxylum species were screened by UHPLC-UV-HRMS and inhibitory activity against Acetylcholinesterase (AChE) and Butyrylcholinesterase (BChE). Based on the screening results, a multivariate statistical analysis (MVA) and selection of anti-cholinesterase candidates were performed using the S-plot from the OPLS-DA model. The supervised analysis (OPLS-DA) paring the anti-cholinesterase screening and LC-HRMS data showed at least 11 ChE inhibition markers which could have contributed in the differentiation of active and inactive extracts. The predictors were tentatively identified by comparing chromatographic retention times (R_t) and accurate mass and MS² fragmentation patterns. In general, the inhibition markers correspond to four types of isoquinoline alkaloids: tetrahydroprotoberberines, protoberberines, dihydrobenzophenanthridines and benzophenanthridines. The most active extracts from Z. schreberi and Z. monophylum showed the highest presence of berberine and chelerythrine, previously reported as cholinesterase inhibitors. Thus, to validate the results of the OPLS-DA model, three alkaloids from the bark of Z. schreberi (identified as berberine, chelerythrine and columbamine) were bio-directed isolated, and all of them showed strong inhibition against both enzymes. These findings support our statistical models and contribute to the rational search of anticholinesterase alkaloids. Therefore, LC-MS-based metabolomic approach combined with chemometric statistical analysis are shown as useful tools for the isolation of targeted bioactive natural products, contributing to improve the research and development stages of lead compounds.

Fraction spatial distributions and ecological risk assessment of heavy metals in the sediments of Baiyangdian Lake

Baiyangdian Lake has been the ecological foundation of the Xiongan New Area, a newly developing economic zone in northern China since 2017, meaning that it is increasingly significant to recognize the contamination of the lake. In this work, the spatial distribution and ecological risk of heavy metals in the lake sediments were examined based on field investigation, multivariate statistical analyses and X-ray diffraction techniques (XRD). The results showed that the heavy metals in sediments pose moderate to high risks in most of the sample sites. The heavily contaminated sites presented more unstable chemical (exchangeable and reducible) fractions, and the ecological risk is highly sensitive to the exchangeable fraction in highly contaminative sites. The results of statistical analyses demonstrated that metal fractions were significantly correlated with physicochemical properties, and TP, TN and TOC exhibited a strong correlation with the exchangeable fraction of As, Cd, Pb and Zn. In contrast, Fe and Mn were weakly correlated with the fractions, which due to the high proportion of the nutrient elements in the sediment. Furthermore, the results from the XRD patterns demonstrated that the mineralogy phases of the various heavy metals contributed to the different chemical fractions. Those results demonstrated that further research on metal fraction distribution and influencing factors in the sediment should be implemented to ascertain the degree of toxicity to carry out effective strategies to remediate the lake sediment.

Wine evolution during bottle aging, studied by 1H NMR spectroscopy and multivariate statistical analysis

The study of wine evolution during bottle aging is an important aspect of wine quality. Ten different red wines (Vitis vinifera) from Piedmont region were analysed 3 months after bottling and after a further 48 month conservation in a climate controlled wine cellar kept at a constant/controlled temperature of 12 °C. Two white wines (Vitis vinifera) were included in this study for comparison purposes. White wines were analysed 3 months after bottling and after further 24 months of bottle aging in the same climate controlled wine cellar. Metabolite changes during this period were evaluated using ¹H NMR spectroscopy combined with statistical analysis. Metabolite variations due to wine aging were minimal compared to those that resulted from a different wine type and wine geographical origin. Therefore, it was necessary to remove this source of variability to discriminate between fresh and refined samples. The storage at low and controlled temperature for 2 or 4 years permitted a slow but progressive evolution of all wines under investigation. 1H NMR spectroscopy, implemented with statistical data analysis, allowed identifying and differentiating wine samples from the two aging stages. In most wines, a decrease in organic acids (lactic acid, succinic acid and tartaric acid) and an increase in esters (ethyl acetate and ethyl lactate) was observed. Catechin and epicatechin decreased during aging in all wines while gallic acid increased in almost all red wines.

High correlation of chemical composition with genotype in cryptic species of the liverwort Aneura pinguis

Chemical constituents of cryptic species detected within the liverwort Aneura pinguis were identified using headspace solid-phase microextraction gas chromatography-mass spectrometry (HS-SPME-GC-MS). Fibre coating with divinylbenzene/carboxen/polydimethylsiloxane (DVB/CAR/PDMS) was used. A total of 48 samples of A. pinguis were analysed. The studied plants were identified genetically based on barcode DNA sequences and represented three cryptic species (A, B and F) of A. pinguis. Cryptic species A and B are genetically diverse; both represent three evolutionary lineages: A1, A2, A3 and B1, B2, B3, respectively. The cryptic species F that was recently detected is not diverse. The most characteristic compounds in analysed samples were sesquiterpene hydrocarbons (up to 17.7% for A1; 15.7% for A2; 20.6% for A3; 7.7% for B1; 2.0% for B2; 3.7% for B3; 10.2% for F), oxygenated sesquiterpenoids (up to 68.0% for A1; 54.7% for A2; 52.6% for A3; 63.5% for B1; 88.7% for B2; 82.7% for B3; 78.8% for F), and linear aliphatic hydrocarbons (up to 14.8% for A1; 1.1% for A2; 12.1% for A3; 6.9 for B1; 5.2% for B2; 1.1% for B3; 7.0% for F). The dominant compound in the studied samples was pinguisone. The second dominant compound present in the tested plant material was deoxopinguisone, except for lineage B2, where only a small relative concentration of this compound was found. A high content of deoxopinguisone in cryptic species A (lineages A1, A2 and A3) was accompanied by the presence of isopinguisone and methyl norpinguisonate, whereas these two compounds were not detected in cryptic species B (lineages B1 and B3) and F. The chemical compounds detected in the studied samples of A. pinguis were subjected to multivariate statistical analysis. The results showed that the chemical composition depends mainly on the genotype of the plant and slightly on the habitat. However, there was no clear correlation between the volatile compounds and the date of collection of the studied plants.

Metabolomic analysis applied to chemosystematics and evolution of megadiverse Brazilian Vernonieae (Asteraceae)

Vernonia sensu lato is the largest and most complex genus of the tribe Vernonieae (Asteraceae). The tribe is chemically characterized by the presence of sesquiterpene lactones and flavonoids. Over the years, several taxonomic classifications have been proposed for Vernonia s.l. and for the tribe; however, there has been no consensus among the researches. According to traditional classification, Vernonia s.l. comprises more than 1000 species divided into sections, subsections and series (sensu Bentham). In a more recent classification, these species have been segregated into other genera and some subtribes were proposed, while the genus Vernonia sensu stricto was restricted to 22 species distributed mainly in North America (sensu Robinson). In this study, species from the subtribes Vernoniinae, Lepidaploinae and Rolandrinae were analyzed by UHPLC-UV-HRMS followed by multivariate statistical analysis. Data mining was performed using unsupervised (HCA and PCA) and supervised methods (OPLS-DA). The HCA showed the segregation of the species into four main groups. Comparing the HCA with taxonomical classifications of Vernonieae, we observed that the groups of the dendogram, based on metabolic profiling, were in accordance with the generic classification proposed by Robinson and with previous phylogenetic studies. The species of the genera Stenocephalum, Stilpnopappus, Strophopappus and Rolandra (Group 1) were revealed to be more related to the species of the genus Vernonanthura (Group 2), while the genera Cyrtocymura, Chrysolaena and Echinocoryne (Group 3) were chemically more similar to the genera Lessingianthus and Lepidaploa (Group 4). These findings indicated that the subtribes Vernoniinae and Lepidaploinae are non-chemically homogeneous groups and highlighted the application of untargeted metabolomic tools for taxonomy and as indicators of species evolution. Discriminant compounds for the groups obtained by OPLS-DA were determined. Groups 1 and 2 were characterized by the presence of 3',4'-dimethoxyluteolin, glaucolide A and 8-tigloyloxyglaucolide A. The species of Groups 3 and 4 were characterized by the presence of putative acacetin 7-O-rutinoside and glaucolide B. Therefore, untargeted metabolomic approach combined with multivariate statistical analysis, as proposed herein, allowed the identification of potential chemotaxonomic markers, helping in the taxonomic classifications.

Magnetic assessment and pollution status of beach sediments from Kerala coast (southwestern India)

Natural and anthropogenic activities along the coastal region of densely populated Kerala may introduce hazardous components into the coastal environment. The present study aimed to investigate the sources and impacts of hazardous components in beach sediments by environmental magnetism methods as additional tools. Magnetic parameters (such as mass-specific magnetic susceptibility χ=-1.2-154.4×10^-8m³kg^-1) and ratios that describe the magnetic properties of minerals such as Fe-oxides, indicate variable concentration of mixtures of magnetite and hematite (magnetite/hematite). The direct significant relationships between the variables indicate that higher concentration magnetic parameters are associated with higher radionuclides and metal contents. Magnetic properties and multivariate statistical analyses evidence the presence of contrasting groups defined only using a reduced number of magnetic variables. One of these groups, the central area of the Kerala coastline, showed the highest magnetic concentrations of mixtures of magnetite/hematite and higher values (up to 6.7) of pollution load index because of extensive anthropogenic activities.

Spatial patterns and origins of heavy metals in Sheyang River catchment in Jiangsu, China based on geographically weighted regression

Multivariate statistical analyses combined with geographically weighted regression (GWR) were used to identify spatial variations of heavy metals in sediments and to examine relationships between metal pollution and land use practices in watersheds, including urban land, agriculture land, forest and water bodies. Seven metals (Cu, Zn, Pb, Cr, Ni, Mn and Fe) of sediments were measured at 31 sampling sites in Sheyang River. Most metals were under a certain degree enrichment based on the enrichment factors. Cluster analysis grouped all sites into four statistically significant cluster, severely contaminated areas were concentrated in areas with intensive human activities. Correlation analysis and PCA indicated Cu, Zn and Pb were derived from anthropogenic activities, while the sources of Cr and Ni were complicated. However, Fe and Mn originated from natural sources. According to results of GWR, there are stronger association between metal pollution with urban land than agricultural land and forest. Moreover, the relationships between land use and metal concentration were affected by the urbanization level of watersheds. Agricultural land had a weak associated with heavy metal pollution and the relationships might be stronger in less-urbanized. This study provided useful information for the assessment and management of heavy metal hazards in studied area.

Seasonal and spatial variations of water quality and trophic status in Daya Bay, South China Sea

Coastal water quality and trophic status are subject to intensive environmental stress induced by human activities and climate change. Quarterly cruises were conducted to identify environmental characteristics in Daya Bay in 2013. Water quality is spatially and temporally dynamic in the bay. Cluster analysis (CA) groups 12 monitoring stations into two clusters. Cluster I consists of stations (S1, S2, S4-S7, S9, and S12) located in the central, eastern, and southern parts of the bay, representing less polluted regions. Cluster II includes stations (S3, S8, S10, and S11) located in the western and northern parts of the bay, indicating the highly polluted regions receiving a high amount of wastewater and freshwater discharge. Principal component analysis (PCA) identified that water quality experience seasonal change (summer, winter, and spring-autumn seasons) because of two monsoons in the study area. Eutrophication in the bay is graded as high by Assessment of Estuarine Trophic Status (ASSETS).

Chemical Composition of Ballota macedonica Vandas and Ballota nigra L. ssp. foetida (Vis.) Hayek Essential Oils - The Chemotaxonomic Approach

The essential oils isolated from fresh aerial parts of Ballota macedonica (two populations) and Ballota nigra ssp. foetida were analyzed by GC and GC/MS. Eighty five components were identified in total; 60 components in B. macedonica oil (population from the Former Yugoslav Republic of Macedonia), 34 components in B. macedonica oil (population from the Republic of Serbia), and 33 components in the oil of B. nigra ssp. foetida accounting for 93.9%, 98.4%, and 95.8% of the total oils, respectively. The most abundant components in B. macedonica oils were carotol (13.7 - 52.1%), germacrene D (8.6 - 24.6%), and (E)-caryophyllene (6.5 - 16.5%), while B. nigra ssp. foetida oil was dominated by (E)-phytol (56.9%), germacrene D (10.0%), and (E)-caryophyllene (4.7%). Multivariate statistical analyses (agglomerative hierarchical cluster analysis and principal component analysis) were used to compare and discuss relationships among Ballota species examined so far based on their volatile profiles. The chemical compositions of B. macedonica essential oils are reported for the first time.

Essential-Oil Constituents and Alkanes of Cephalaria ambrosioides Roem. & Schult. (Family Caprifoliaceae, Subfamily Dipsacaceae) and (Chemo)taxonomic Discernment of the Subfamilies Dipsacaceae and Morinaceae

Herein, the results of the first study of the volatile and alkane profiles of Cephalaria ambrosioides Roem. & Schult. (Caprifoliaceae, subfamily Dipsacaceae) were reported. The GC-FID and GC/MS analyses of the essential oils hydrodistilled from leaves and stems (CA1) and flowers (CA2) of C. ambrosioides allowed the identification of 284 different components. The main compounds of the studied oil samples were palmitic acid (24.3 and 32.5% for CA1 and CA2, resp.), hexahydrofarnesyl acetone (1.4 and 10.8% for CA1 and CA2, resp.), (Z)-hex-3-en-1-ol (7.0 and <0.1% for CA1 and CA2, resp.), and linoleic acid (1.9 and 6.5% for CA1 and CA2, resp.). Essential-oil compositional data of selected plant species belonging to the Dipsacaceae (15) and Morinaceae (2) subfamilies were used to resolve taxonomical ambiguities regarding the genus Cephalaria and its infrageneric relations, especially concerning the subfamily Morinaceae (formerly a genus within Dipsacaceae). The results of multivariate statistical analyses (25 different essential-oil samples) supported the exclusion of Morina species from the Dipsacaceae subfamily. The relative abundances of alkanes from n-, iso-, and anteiso-series followed a (distorted) Gaussian-like distribution and suggested that the biosyntheses of n- and branched alkanes in C. ambrosioides are possibly not controlled by the same elongase. Also, the obtained results suggested that there was a difference in the biosynthesis/accumulation of alkanes in the vegetative and reproductive parts of C. ambrosioides.

Impact of sediment characteristics on the heavy metal concentration and their ecological risk level of surface sediments of Vaigai river, Tamilnadu, India

The distributions of the metals (Al, Fe, Mg, Cd, Cr, Cu, Ni, Pb and Zn) were measured for the surface sediments of the Vaigai river, Tamilnadu, India. These values are compared with different standard values to assess the level of toxicity of the heavy metals in the sediments. Risk indices (CF, PLI and PER) are also calculated to understand the level of toxicity of the metals. Multivariate statistical analyses (Pearson's correlation analysis, cluster analysis and factor analysis) are carried out to know the inter-relationship between sediment characteristics and the heavy metals. From this analysis, it is confirmed that the contents of clay and organic matter play an important role to raise the level of heavy metal contents as well as PLI and PER (level of toxicity). Heavy metal concentrations of the samples (after removing silt and clay fractions from bulk samples) show decrease in their concentrations and risk indices compared to the level of bulk samples.

Function of minerals in the natural radioactivity level of Vaigai River sediments, Tamilnadu, India--spectroscopical approach

Using Gamma ray and Fourier Transform Infrared (FTIR) spectroscopic techniques, level of natural radioactivity ((238)U, (232)Th and (40)K) and mineralogical characterization of Vaigai River sediments have been analyzed with the view of evaluating the radiation risk and its relation to available minerals. Different radiological parameters are calculated to know the entire radiological characterization. The average of activity concentrations and all radiological parameters are lower than the recommended safety limit. However, some sites are having higher radioactivity values than the safety limit. From the FTIR spectroscopic technique, the minerals such as quartz, microcline feldspar, orthoclase feldspar, kaolinite, gibbsite, calcite, montmorillonite and organic carbon are identified and they are characterized. The extinction co-efficient values are calculated to know the relative distribution of major minerals such as quartz, microcline feldspar, orthoclase feldspar and kaolinite. The calculated values indicate that the amount of quartz is higher than orthoclase feldspar, microcline feldspar and much higher than kaolinite. Crystallinity index is calculated to know the crystalline nature of quartz and the result indicates that the presence of ordered crystalline quartz in the present sediment. The role of minerals in the level of radioactivity is assessed by multivariate statistical analysis (Pearson's correlation and Cluster analysis). The statistical analysis confirms that the clay mineral kaolinite is the major factor than other major minerals to induce the important radioactivity variables such as absorbed dose rate and concentrations of (232)Th and (238)U.