Evaluation of water quality and trophic status in relation to seasonal water mixing in a highland Lake Ardibo, Ethiopia.

The aim of the present study was to evaluate the spatio-temporal variability of various physical and chemical parameters of water quality and to determine the trophic state of Lake Ardibo. Water samples were collected from October 2020 to September 2021 at three sampling stations in four different seasons. A total of 14 physico-chemical parameters, such as water temperature, pH, dissolved oxygen (DO), electrical conductivity, turbidity, alkalinity, Secchi-depth, nitrate, ammonia, silicon dioxide, soluble reactive phosphorus, total phosphorus, chloride, and fluoride were measured using standard methods. The results demonstrated that temporal variation existed throughout the study period. Except for turbidity, the water quality of the lake varied significantly within the four seasons (ANOVA, p < 0.05). DO levels decreased significantly during the dry season following water mixing events. Chlorophyll-a measurements showed significant seasonal differences ranging from 0.58 µg L-1 in the main-rainy season to 8.44 µg L-1 in the post-rainy period, indicating moderate algal biomass production. The overall category of Lake Ardibo was found to be under a mesotrophic state with medium biological productivity. A holistic lake basin approach management is suggested to maintain water quality and ecological processes and to improve the lake ecosystem services.

Examining drinking water quality: analysis of physico-chemical properties and bacterial contamination with health implications for Shangla district, Khyber Pakhtunkhwa, Pakistan.

A comprehensive understanding of water quality is essential for assessing the complex relationship between surface water and sources of pollution. Primarily, surface water pollution is linked to human and animal waste discharges. This study aimed to investigate the physico-chemical characteristics of drinking water under both dry and wet conditions, assess the extent of bacterial contamination in samples collected from various locations in District Shangla, and evaluate potential health risks associated with consuming contaminated water within local communities. For this purpose, 120 groundwater and surface water samples were randomly collected from various sources such as storage tanks, user sites, streams, ponds and rivers in the study area. The results revealed that in Bisham, lakes had the highest fecal coliform levels among seven tested sources, followed by protected wells, reservoirs, downstream sources, springs, rivers, and ditches; while in Alpuri, nearly 80% of samples from five sources contained fecal coliform bacteria. Similarly, it was observed that the turbidity level, total dissolved solids, electrical conductivity, biological oxygen demand, and dissolved oxygen in the surface drinking water sources of Bisham were significantly higher than those in the surface drinking water sources of Alpuri. Furthermore, the results showed that in the Alpuri region, 14% of the population suffers from dysentery, 27% from diarrhea, 22% from cholera, 13% from hepatitis A, and 16% and 8% from typhoid and kidney problems, respectively, while in the Bisham area, 24% of residents are affected by diarrhea, 17% by cholera and typhoid, 15% by hepatitis A, 14% by dysentery, and 13% by kidney problems. These findings underscore the urgent need for improved water quality management practices and public health interventions to mitigate the risks associated with contaminated drinking water. It is recommended to implement regular water quality monitoring programs, enhance sanitation infrastructure, and raise awareness among local communities about the importance of safe drinking water practices to safeguard public health.

Time series (2003-15) analysis of selected physicochemical parameters in Indian Ocean: Cumulative impacts prediction on coral bleaching using machine learning.

Coral bleaching is an important ecological threat worldwide, as the coral ecosystem supports a rich marine biodiversity to survive. Sea surface temperature was considered a major culprit; however, later it was observed that other water parameters like pH, tCO2, fCO2, salinity, dissolved oxygen, etc. also play a significant role in bleaching. In the present study, all these parameters of the Indian Ocean area for 15 years (2003-2017) were collected and analysed using machine learning language. The main aim is to see the cumulative impacts of various ocean parameters on coral bleaching. Introducing machine learning in environmental impact assessment studies is a new approach, and the prediction of coral bleaching using simulation of physico-chemical parameters interactions shows 94.4 % accuracy for the prediction of the future bleaching event. This study can be probably the first step in the application of the machine learning language for the prediction of coral bleaching in the field of marine science.

Pharmacognostic standardization and evaluation of antiulcer potential of Olax psittacorum leaf extract.

The modern medicine has received many plants as a gift from ethnobotany. It is an efficient method of discovering new medicines. The leaves of Olax psittacorum (Lam.) Vahl. were extracted with ethanol, and the phytoconstituents present in the leaf extract were identified using Gas chromatography-mass spectrometric analysis (GC-MS), followed by determination of physico-chemical parameters and anti-ulcer properties. The leaf ethanolic extract (LEE) yield was observed to be 43.2%. The quantitative surface microscopy analysis revealed a stomatal index of 30 and 22 epidermal cells and qualitatively confirms presence of quinone, flavonoid, phenol, carbohydrate, tannin, saponin and absence of alkaloids using various screening techniques. The LEE confirms its anti-ulcer potency by inhibiting ulceration by 58% and 75% respectively, thus proving the hypothesis. These identified parameters may be helpful in developing some botanical standards for the standardisation and identification of O. psittacorum leaves with anti-ulcer properties.

Metagenomics analysis of water samples collected from the Yamuna River of Agra city, India.

Yamuna River water in Agra city of India is contaminated with toxic pollutants, including heavy metals that cause damage to the environment and human health. At present, the direct use of river water for drinking purposes and household activities lead to the direct exposure of society to the contaminants. In this study, Yamuna River water samples were collected from three different sites in Agra city during the monsoon, summer, and winter seasons. The physico-chemical parameters were estimated along with heavy metals. In physico-chemical parameter, the values found were mostly above the permissible limits. The results water samples contain high levels of cadmium, chromium, lead, and nickel above the desirable levels in most cases. The metagenomic analysis revealed that Proteobacteria, Bacteroidetes, Verrucomicrobia, Actinobacteria, and Planctobacteria were the most abundant phyla with a relative abundance of 61%, 9.34%, 5.23%, 4.64%, and 4.3%, respectively. The Comamonadaceae, the most abundant family consists of the genera involved in hydrogen oxidation, iron reduction, degraders of polycyclic aromatic hydrocarbons, and fermentation. The presence of Pseudomonas, Nitrosomonas sp., Thauera humireducens and Dechloromonas denitrificans (decomposition of sewage and organic matter) and Pseudomonas aeruginosa indicates the presence of heavy metal degrading bacteria in water sample. Functional prediction showed the presence of genes responsible for different metabolic pathways that could help developing new bioremediation strategies. The study concludes the status of water contamination, the presence of complex microbial community and suggests the futuristic use and their role in bioremediation.

Long-term and seasonal trends of water parameters in the karst riverine catchment and general literature overview based on CiteSpace.

Although Europe is the continent with the highest proportion of karst areas, where hydrological systems are essential but extremely sensitive, data on the ecological status of karst riverine catchments are scarce. The aim of the present study was to assess the spatial and temporal (long-term and seasonal) variability of the physico-chemical and organic water parameters in the headwaters of the Krka River and its tributaries, as representatives of a typical karst ecosystem, situated in one of the largest karst areas in Europe, Dinarides in Croatia. It is affected in its upper reaches by improperly treated wastewaters, so anthropogenic influences and ecological status were estimated with the aim to present consequences of pollution exposure and importance of strict monitoring of such sensitive karst ecosystems worldwide. Results indicated degraded water quality, poor ecological status, and disturbed seasonal fluctuations at wastewater-influenced sites, primarily due to high levels of nutrients and organic matter. However, improvement was observed downstream in the Krka National Park, confirming the self-purification as important processes in dynamic karst rivers. Natural seasonality, observed at sites without wastewater influence, was mainly driven by fluctuations in water levels and primary production during the year. Literature analysis by CiteSpace pointed to scarce data on this topic worldwide (China and the USA account for 49% of all publications) and in Europe (34%). Therefore, such study is a valuable contribution in presenting the long-term and seasonal variability of ecological water parameters and in providing a more comprehensive understanding of the health of catchment under influence of multiple stressors.

Green synthesis, antibacterial and antifungal evaluation of new thiazolidine-2,4-dione derivatives: molecular dynamic simulation, POM study and identification of antitumor pharmacophore sites.

In this study, a series of thiazolidine-2,4-dione derivatives 3a-i were synthesized and evaluated for antibacterial activity against Gram-positive and Gram-negative strains of Bacillus licheniformis, Escherichia coli, Pseudomonas aeruginosa and Staphylococcus aureus. Newly prepared thiazolidine (TZD) derivatives were further screened separately for in vitro antifungal activity against cultures of fungal species, namely, Aspergillus niger, Alternaria brassicicola, Chaetomium murorum, Fusarium oxysporum, Lycopodium sp. and Penicillium notatum. The electron-donating substituents (-OH and -OCH3) and electron-withdrawing substituents (-Cl and -NO2) on the attached arylidene moieties of five-membered heterocyclic ring enhanced the broad spectrum of antimicrobial and antifungal activities. The molecular docking study has revealed that compound 3h strongly interacts with the catalytic residues of the active site of the ß-carbonic anhydrase (P. aeruginosa) and has the best docking score. In silico pharmacokinetics studies showed the drug-likeness and non-toxic nature of the synthesized compounds, which indicates the combined antibacterial, antiviral and antitumor pharmacophore sites of the targeted drug. This work demonstrates that potential TZD derivatives bind to different types of bacterial and fungal pathogens for circumventing their activities and opens avenues for the development of newer drug candidates that can target bacterial and fungal pathogens.Communicated by Ramaswamy H. Sarma.

Evaluation of uranium content and annual ingestion dose in the surface and ground water bodies of Chittorgarh, Rajasthan, India.

Uranium, naturally occurring radionuclide is chemotoxic and nephrotoxic beyond acceptable limit. The presence of uranium beyond acceptable limit in surface and ground water, adversely affecting people's health. In the present investigation, the uranium concentration in surface and ground water of Chittorgarh, Rajasthan was studied along with the physico-chemical parameters of water (n = 87). The ground water was further sub-categorised into well water, handpump water, and borewell water. The mean uranium concentration was observed at 2.5 ± 1.9 µgL-1 and 16.5 ± 1.4 µgL-1 in the surface and ground water samples, respectively. In sub-categories of ground water, the highest uranium concentration was found in borewell water (23.3 ± 17.0 µgL-1), followed by handpump water (13.5 ± 9.1 µgL-1) and well water (6.0 ± 5.5 µgL-1). The uranium concentration was correlated significantly with the depth of the ground water table. It also correlated significantly with electrical conductivity, total dissolved solids and nitrate concentration. 100% of surface water and 88.9% of ground water samples carried uranium concentration within the acceptable limit of WHO (30 µgL-1). The annual ingestion dose was found at 3.8 µSvy-1 (for males) and 2.8 µSvy-1 (for females) in surface water and 25.4 µSvy-1 (for males) and 18.5 µSvy-1 (for females) in ground water. In the sub-categories of the ground water sample, the annual ingestion dose followed the trend in males 35.8 µSvy-1 (borewell water) > 20.7 µSvy-1 (hand pump water) > 9.2 µSvy-1 (well water) and in females 26.1 µSvy-1 (borewell water) > 15.1 µSvy-1 (hand pump water) > 6.7 µSvy-1 (well water).

An Intensive Study on Algal Diversity in the Ancient Man-Made Aquatic Ecosystem of Tiruvallur, South India: Exploration for Sustainable Development.

Eco-friendly and beneficial nature algae make it prominent in our earth as well as for human life. In recent decades, microalgal applications is sought in varied fields from the remediation of wastes to the production of pharmaceutical products. Still, more extensive research on bioprospecting should to conducted to get the genus-specific or species-specific applications of microalgae with high efficiency. This inquiry was carried out (October 2021 to September 2022) for the effectual understanding of microalgal composition structure along with seasonal physicochemical variations in the age-old holy tank at Tiruvallur, southeast India. This inquiry also acts as the source data and makes the bioprospecting process easier. It also ignites the researchers to address the microalgae seasonal composition structure of peculiar wet environments. A total of 41 microalgae species were recorded, in which six major algal groups were in order of, Chlorophyceae > Bacillariophyceae > Cyanophyceae > Euglenophyceae > Zygnematophyceae > Trebouxiophyceae. Mean seasonal abundance was highest in the summer season (351 cells/L) and lowest in the monsoon (113 cells/L). One-way ANOVA showed seasonal variations of physicochemical parameters, in which the majority of them attained their peak during summer. Mean values of water temperature, pH, salinity, total dissolved solids, total solids, electrical conductivity, chemical oxygen demand, total hardness, total alkalinity, ammonia, nitrite-nitrogen, and nitrate-nitrogen for the summer were 31.43 °C, 8.53, 0.56 ppt, 383 mg/L, 525 mg/L, 0.85 mS/cm, 46.27 mg/L, 300 ppm, 251.67 ppm, 1.51 mg/L, 0.62 mg/L, and 0.70 mg/L, respectively. Karl Pearson's correlation revealed a most significant relationship between water quality factors and algal density. The Shannon's diversity index (2.78-3.39) indicated moderately rich microalgal diversity in the study area. Palmer's pollution index stated that the temple tank was organically polluted all over the study period except November.

Trace metals in surface water of the Pechora River and its tributaries: Content, water quality and risks assessment (Arctic Ocean basin).

The article is devoted to the study of trace metals content in the Pechora River and its tributaries, which is the largest river in the Arctic Ocean basin. The study of physico-chemical properties of water showed aerobic conditions of low-mineralised water with pH values suitable for drinking water. Analysis of the content of trace metals has revealed that the main flow of Al, Mn, Co, Cu, Zn, V, As, Mg and Fe into the Pechora River comes from its tributaries. The average content of Cr, Mn, Cu, Zn, Pb, V, As, Mg and Fe in the water of the Pechora River delta was higher than for the main river channel, which indicates the transfer of a large mass of trace metals to the Barents Sea and the Arctic water ecosystem. For the studied river and tributaries, chronic pollution of the Pechora River with Al, Mn, Ba, Fe, Cu, U and Pb metals has adverse effects on waterborne organisms. The degree of contamination of natural waters by metals has been assessed using water quality indices (TMPI, TMEI, TMTI) and public health risks (HI and CR). Low contamination and weak toxicity of the Pechora River water has been determined, but serious contamination, toxicity and high non-carcinogenic risk of some of its tributaries have been observed. A high carcinogenic risk has been established for the consumption of all water sampled. Al, Ni, As, Fe, Mn, Cr, Cd, and Ba were found to be the highest priority contaminating trace metals. At present, contamination of the Pechora River and its tributaries with trace metals is formed under the influence of dissolution processes of rocks of the Ural Mountains, the Taminsky Ridge, underlying mineral deposits, permafrost degradation processes and glacier melting. Anthropogenic factors include oil and gas production and transportation.

The effects of water quality parameters, water level changes, and mixing on zooplankton community dynamics in a tropical high-mountain Lake Ardibo, Ethiopia.

The diversity and abundance of the zooplankton community are affected by changes in physico-chemical parameters, trophic interactions, water level changes, and periodic mixing. In this study, the influence of environmental variables, water level changes, and periodic mixing on zooplankton distribution and abundance was seasonally studied for Lake Ardibo from October 2020 to September 2021 collected from 3 sites. Results on the physico-chemical variables indicated that all variables, except turbidity, varied significantly (p < 0.05) in all sampling seasons. A total of 33 zooplankton species were recorded, comprising 18 rotifers, 11 cladocerans, and 4 cyclopoid copepods. Zooplankton abundance significantly varied seasonally with peak abundance (4232.13 ind. L-1) recorded in the dry season and lowest numbers (402.42 ind. L-1) during the long rainy period. Redundancy analysis (RDA) results indicated that total phosphorus, ammonia, water temperature, silicon dioxide, and conductivity were the most significant driving forces for the seasonal successions in the abundance and distribution of zooplankton communities. Cyclopoid copepod abundance was significantly (p < 0.05) higher in the dry season, which could be correlated with the partial mixing (atelomixis) phenomenon that occurred during the dry period.

Impact of nutrients and trace elements on freshwater microbial communities in Croatia: identifying bacterial bioindicator taxa.

Since aquatic microbial communities promptly respond to environmental changes, it is now evident that they can complement traditional taxa such as fish, macroinvertebrates and algae as bioindicators of water quality. The aim of this study was to correlate the physico-chemical parameters of water with the microbial community structure and the occurrence of putative bioindicator taxa. Thirty-five water samples were collected throughout Croatia and their physico-chemical parameters, including the concentration of trace elements using the high-resolution inductively coupled plasma mass spectrometry (HR-ICP-MS), and the composition of the microbial communities by high-throughput sequencing of the 16S rRNA marker gene, were analysed in parallel. Partial least squares regression (PLS-R) modelling revealed that a number of microbial taxa were positively correlated with some of the water parameters. For example, some taxa from the phylum Proteobacteria were positively correlated with the ion content of the water (e.g. Erythrobacter, Rhodobacteraceae, Alteromonadaceae), while some Firmicutes taxa, such as the well-known faecal indicators Enterococcus and Clostridium, were correlated with nutrient content (ammonium and total phosphorus). Among the trace elements, uranium was positively correlated with a highest number of microbial taxa. The results obtained will aid in development of protocols for eDNA-based biological assessment of water quality.

Comparative study on seasonal variations in physico-chemical characteristics of four soda lakes of Ethiopia (Arenguade, Beseka, Chitu and Shala).

Soda lakes are productive natural ecosystems with substantial economic and non-economic values. Currently, they are facing considerable environmental threats that can lead to further degradation. The objective of this study was to investigate comparative spatiotemporal variations of physicochemical properties of four Ethiopian soda lakes in comparison with their historical data. Central (open-water) sampling sites were selected from four Ethiopian soda lakes: Arenguade, Beseka, Chittu and Shala. Water samples were collected from open sampling stations from January to December 2020 and analyzed at Limnology laboratory of Addis Ababa University. The geographical position of each lake was determined by means of Global Positioning System (GPS). All physicochemical factors exhibited significant differences between seasons (ANOVA, P < 0.05), except salinity in Lake Shala. The concentrations of physicochemical parameters were generally high during the dry seasons in the studied lakes due to the low incidence of rainfall, caused by recurrent drought, resulting in higher evapotranspiration rates as they are characterized by a long dry season. Lakes Arenguade and Beseka showed considerable decrease in conductivity, alkalinity and salinity, compared to data from the 1960s and 1990s, which might be attributed to dilution effect. The same parameters show slightly increasing trend in Lake Arenguade which might be due to high evaporation rate. In general, the physicochemical parameters of the study lakes showed temporal variations, which could be attributed to the dilution effect, evaporation, and hydrological characteristics of the Ethiopian Rift Valley. In the face of climate change and recurring droughts, in the Ethiopian Rift Valley, the outcomes of this study might be used as input for the long-term planning, of water resources management and devising mitigation strategies.

Influence of barrages on hydrological parameters and functional groups of phytoplankton of a subtropical river Ganga, India.

The current study used phytoplankton functional groups (FGs) to assess the impact of barrages on the ecological function of subtropical river Ganga. A total of 101 phytoplankton species were identified, including 20 phytoplankton FGs with MP and D having the highest prevalence rates of more than 50%. Other FGs with higher occurrence rates, such as N, A, and J, displayed seasonal and spatial advantages on occasion, indicating the randomness of exogenous influx from catchment areas. Based on phytoplankton FGs similarities, a non-metric multidimensional scaling analysis (NMDS) revealed geographical and seasonal discrepancies. The higher concentration of chemical components in Kanpur was linked to decreased water discharged from preceding reservoirs, resulting in a highly polluted stretch in terms of spatial variation, according to our findings. During the monsoon season, however, the diluting process caused by precipitation and surface runoff significantly improved water quality. As a result, we hypothesized that a sequence of barrages alters the hydrological characteristics of cascading reservoirs, which was related to spatial and seasonal fluctuation in FG diversity and phytoplankton FGs could be useful bioindicators of water quality. In conclusion, the phytoplankton FGs approach is useful for identifying the geographical and seasonal aspects of aquatic ecosystems that are heavily influenced by human activities, but its sensitivity to changes in spatial and seasonal water quality warrants more exploration.

Interaction of physico-chemical parameters with Shannon-Weaver Diversity Index based on phytoplankton diversity in coastal water of Diu, India.

Phytoplankton acts as carbon sinks due to photosynthetic efficacy and their diversity is expressed by SWDI (Shannon-Weaver Diversity Index), which depends on water quality parameters. The coastal water of Diu was studied for three seasons, and the relationship between different parameters and SWDI was established. Subsequently, an attempt was made to build up a prediction model of SWDI based on multilayer perceptron Artificial neural network (ANN) using the R programme. Analysis shows interrelationship between the water quality parameters and phytoplankton diversity is same in linear principal component analysis (PCA) and neural network model. Variations of different parameters depend on seasonal changes. The ANN model shows that ammonia and phosphate are key parameters that influence the SWDI of phytoplankton. Seasonal variation in SWDI is related to variation in water quality parameters, as explained by both ANN and PCA. Hence, the ANN model can be an important tool for coastal environmental interaction study.

Deterioration of the quality of packaged potable water (bottled water) exposed to sunlight for a prolonged period: An implication for public health.

The exposure of bottled water to sunlight leaches heavy metals into the water, thereby deteriorating its quality and this informed the study. Three plastic bottle brands (n = 100 per brand) were exposed to sunlight for different durations. The leaching of contaminants was exposure duration dependent. The following ranges were recorded for temperature (26.67-29.83 °C), pH (4.73-6.12), conductivity (159.00-298.67 µs/cm), turbidity (0.92-1.22 N.T.U), TDS (98.17-192.77 mg/l), hardness (38.12-78.17 mg/l), Fe (0.01-0.57 mg/l), Mn (BDL - 0.46), Cr (BDL - 0.37 mg/l), Al (BDL - 0.53 mg/l), Cd (0.02-0.21 mg/l), Zn (1.18-9.90 mg/l), Pb (0.03-1.68 mg/l), As (BDL - 1.48 mg/l), and Ni (0.05-1.55 mg/l). Health risk evaluation in all bottled water brands revealed possible Cr, Cd, Pb, As, and Ni toxicity. The carcinogenic risk of Cr, As, and, Ni, indicated potential cancer. Arsenic posed the highest non-carcinogenic risk, while Ni posed the highest carcinogenic risk in all brands after 42 days of exposure. The microbial parameters failed to meet the WHO safety limits. The exposure of bottled water to sunlight should be avoided, to ensure a healthy population.

Application of ultrasonication as pre-treatment for freeze drying: An innovative approach for the retention of nutraceutical quality in foods.

Freeze drying (FD) is an important and highly effective technology in food industry for retaining the quality in final dried product. This drying technique is performed at lower temperatures, restricting the damage suffered by thermally sensitive ingredients. However, FD consumes large amount of energy and required more time than conventional drying methods. The utilization of ultrasonic technology (US) as pre-treatment before FD represents a promising alternative in accelerating the drying process, decreases energy consumption and maintaining quality as compared to the non pre-treated sample. This review summarizes research progress and current studies in ultrasonic as pre-treatment for freeze drying (US + FD) technique. The impact of US + FD on phytochemical, color, texture and micro-structure of food are well summarized. The review also suggests that the optimised US treatment parameters are required to improve heat and mass transfer in food samples which help in speed up the drying process and reduction of drying time.

Application and recent progress of inland water monitoring using remote sensing techniques.

Hyperspectral remote sensing, which retrieves the water quality parameters by direct high-resolution analysis of the electromagnetic spectrum reflected from the water surface, has been widely applied for inland water quality detection. Such a new approach provides an opportunity to generate real-time data from water with the noncontact method, largely improving working efficiency. By summarizing the development and current applications of hyperspectral remote sensing, we compare the relative merits of varying remote sensing platforms, popular inversion models, and the application of hyperspectral monitoring of chlorophyll-a (Chl-a), transparency, total suspended solids (TSS), colored dissolved organic matter (CDOM), phycocyanin (PC), total phosphorus (TP), and total nitrogen (TN) water quality parameters. Most studies have focused on spaceborne remote sensing, which is usually used to monitor large waterbodies for Chl-a and other water quality parameters with optical properties; semiempirical, bio-optical, and semianalytical models are frequently used. With the rapid development of aerospace technology and near-surface remote sensing, the spectral resolution of remote sensing imaging technology has been dramatically improved and has begun to be applied to small waterbodies. In the future, the multiplatform linkage monitoring approach may become a new research direction. Advanced computer technology has also enabled machine learning models to be applied to water quality parameter inversion, and machine learning models have higher robustness than the three commonly used models mentioned above. Although nitrogen and phosphorus, with nonoptical properties, have also received attention and research from some scholars in recent years, the uncertainty of their mechanisms makes it necessary to maintain a cautious attitude when treating such research.

Evaluation of the effects of abattoir effluent on the physicochemical and bacteriological quality of River Benue, Nigeria.

This study investigated the impact of continual discharge of untreated abattoir effluents on the water quality of River Benue. Three major abattoirs (Wurukum, Wadata and Northbank) in Makurdi, Nigeria, and their polluting strength in river upstream and downstream were measured and compared. Two water quality parameters: physicochemical and bacteriological were investigated. Water quality index (WQI) was computed for all sampling sites. Results revealed that some of the physiochemical parameters were above recommended limits, especially in downstream river, in particular, the turbidity (24.0-55.5 mg/l), TSS (62.6-92.0 mg/l), DO (8.0 mg/l), and total hardness (160-240 mg/l). All sampling sites indicated an increased bacterial population while Salmonella spp. and Escherichia coli were the predominant bacteria among the ten genera identified in water upstream and downstream. Faecal coliforms increased from upstream to downstream in two sampling sites (Wurukum and Wadata). Strong positive correlations were observed between upstream and downstream samples for pH, EC, turbidity, TSS, DO, COD, SO42-, TC, and Shigella spp. WQI revealed that all sampling locations were heavily polluted and unsuitable for drinking purposes (WQI > 300) based on both the physicochemical and bacterial parameters. The sampling sites, however, showed excellent water quality based only on physicochemical properties especially upstream at both Wurukum and Northbank sampling sites (WQI < 50). It was suggested that anthropogenic activities around the river may be responsible for the high concentration of some physiochemical parameters and bacterial loads observed in the river downstream. Moreover, it was concluded that microbial loads should be fully considered in WQI computation in terms of water quality. Our results are useful for water resource and waste management in terms of practices and policy guidance, especially for developing countries.

Characterization and Differentiation of Fresh Orange Juice Variety Based on Conventional Physicochemical Parameters, Flavonoids, and Volatile Compounds Using Chemometrics.

The present study focused on the possibility of differentiating fresh-unprocessed orange juice according to botanical origin (variety), based on the use of conventional physico-chemical parameters, flavonoids, and volatile compounds, in combination with chemometrics. For this purpose, oranges from seven different varieties were collected during the harvest years of 2013−2014 and 2014−2015 from central and southern Greece. The physico-chemical parameters that were determined included: electrical conductivity, acidity, pH, and total soluble solids. The flavonoids: hesperidin, neohespseridin, quercetin, naringin, and naringenin were determined using high-performance liquid chromatography (HPLC-DAD). Finally, volatile compounds were determined using headspace solid-phase micro-extraction in combination with gas chromatography-mass spectrometry (HS-SPME/GC-MS). Statistical treatment of data by multivariate techniques showed that orange juice variety had a significant (p < 0.05) impact on the above analytical parameters. The classification rate for the differentiation of orange juice according to orange variety using multivariate analysis of variance (MANOVA) and linear discriminant analysis (LDA) was 89.3%, based on the cross-validation method.