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Abstract Evaluation of water quality is crucial for managing surface water effectively, ensuring its suitability for human use, and sustaining the environment. In the lower Danube River basin, various methods were employed to assess surface water quality for irrigation, drinking, human health risk purposes and the main mechanism control the surface water chemistry. These methods included water quality indicators (WQIs), complex statistical analyses, geographic information systems (GIS), Monte Carlo simulation, and geochemical modeling. Physicochemical analyses of surface water samples revealed primarily Ca–Mg–HCO3 − is the dominant water types. Principal component analysis (PCA), ionic ratios and piper, chloro alkaline index, Chadha, and Gibbs diagrams identified three distinct water characteristics influenced by water-rocks interaction, evaporation, ions exchange, and human activities. The geochemical modeling showed Danube River water’s strong ability to dissolve gypsum, halite, and anhydrite (SI 1) compared to adults, indicating a 2.1 times higher overall non-carcinogenic risk hazard index. However, Monte Carlo simulation demonstrated negligible iron, manganese, and nitrate health hazards for both age groups. These findings are valuable for water quality management decisions, contributing to long-term resource sustainability.

Evaluation of water quality is crucial for managing surface water effectively, ensuring its suitability for human use, and sustaining the environment. In the lower Danube River basin, various methods were employed to assess surface water quality for irrigation, drinking, human health risk purposes and the main mechanism control the surface water chemistry. These methods included water quality indicators (WQIs), complex statistical analyses, geographic information systems (GIS), Monte Carlo simulation, and geochemical modeling. Physicochemical analyses of surface water samples revealed primarily Ca–Mg–HCO3− is the dominant water types. Principal component analysis (PCA), ionic ratios and piper, chloro alkaline index, Chadha, and Gibbs diagrams identified three distinct water characteristics influenced by water-rocks interaction, evaporation, ions exchange, and human activities. The geochemical modeling showed Danube River water's strong ability to dissolve gypsum, halite, and anhydrite (SI < 0) and precipitate aragonite, dolomite, and calcite with saturation index (SI) value greater than 0 along its flow path. The irrigation water quality index (IWQI = 99.6–107.6), sodium adsorption ratio (SAR = 0.37–0.68), sodium percentage (Na% = 13.7–18.7), soluble sodium percentage (SSP = 12.5–17.5), Potential Salinity (PS = 0.73–1.6), and Residual Sodium Carbonate (RSC = − 1.27–0.58) values were used, mainly indicating acceptable quality with some limitations. Danube River water was unsuitable for drinking based on WQI value (WQI = 81–104). Oral exposure of children to specific components showed a higher hazard index (HI > 1) compared to adults, indicating a 2.1 times higher overall non-carcinogenic risk hazard index. However, Monte Carlo simulation demonstrated negligible iron, manganese, and nitrate health hazards for both age groups. These findings are valuable for water quality management decisions, contributing to long-term resource sustainability. [ABSTRACT FROM AUTHOR]

The aim of this study is to examine and analyze the mandible of Morkaraman sheep without any skeletal disorders using the geometric morphometric method. For this purpose, a total of 14 mandibles from male and female individuals were used in the study. The main components in multidimensional data sets were determined with Principal Component Analysis, used within the scope of the geometric morphometry method, and the differences between the samples were determined with Discriminant Function Analysis. Statistical and formal analyzes of these variances were also performed. A total of 12 principal components were obtained with 12 punctuations selected on a total of 14 mandibular (7 female, 7 male) images. Among these principal components, the first principal component (PC1) alone accounted for 30.409% of the total variation. The second principal component (PC2) alone accounted for 22.265% of the total variation, and the third principal component (PC3) alone accounted for 14.893% of the total variation. The first three of the variances obtained explained 67,567 of the shape differences. Discriminant Function Analysis (DFA) was used to objectively evaluate gender differences. In the discriminant function analysis, the p value was above 0.05 (p = 0.7). Although there was a complete separation between genders formally and statistically, no significant p value was obtained. In line with these analyses, information was obtained about the anatomical features and adaptations of the Morkaraman sheep mandible, which is one of the important economic resources of our country and is bred in a wide area, and it has become an exemplary study in this field. [ABSTRACT FROM AUTHOR]

The aim of the study was to assess the genetic diversity of 27 rye (Secale cereale L.) accessions by using multivariate statistical methods. The experiment was carried in the block method with 3 replications on plots of 2.5 m² during 2017/2018, 2018/2019 and 2019/2020 growing seasons. Nine qualitative and fifteen quantitative morpho-agronomical characters were evaluated. General Shannon-Weaver diversity index for all included in the study traits was moderate (H' = 0.631). The analysis of variance exhibited the presence of significant differences among the tested genotypes for all quantitative characters indicating the existence of variability. The high heritability with high genetic advance was recorded for leaf area of a flag leaf, leaf area of a sub-flag leaf, weight of the main spike, weight of the grain in the main spike, number of spikelets in the main spike and grain yield combined indicating that they are important characters to be considered for selection and improvement of Secale cereale L. Cluster analysis based on the Between groups linkage and Squared Euclidean Distance grouped the genotypes into six clusters. The highest distance values were measured for the following pair wise genotype combinations: B4000206-B7000123, B4000205-B7000123 and B4000210-B7000123. The first 8 principal components explained a very large proportion of the total variation (81.80%). The results of the study will be useful for the breeding improvement programs of rye. [ABSTRACT FROM AUTHOR]

In July 2022, strong and high-frequency northern sector winds blew over the Aegean Sea. The low tropospheric circulation in combination with air quality and human comfort is of great importance for the climate and human health. This study investigates the variation in pollutants' concentrations (PM10, NO2, O3 and SO2), meteorological factors (temperature, relative humidity, wind speed and direction) and the discomfort index in the city of Rhodes during July 2022. Additionally, the impact of Etesians on pollution levels is studied. The strength of the Etesian flow is quantified by calculating a statistical index that takes the July pressure gradient (ΔP) over the Aegean Sea into consideration. For the analysis, pollutants' concentration recordings from a mobile air-quality-monitoring system during July 2022 and mean sea level pressure (MSLP) data from ERA5 reanalysis during July for the period from 1980 to 2022 are analyzed. The results indicate that traffic affects the pollution level although the pollution limits, according to the European directive for air quality (2008/50/EC), are not exceeded. The findings also reveal an increase in ΔP, about 1.8 hPa, during 2022 compared to the period from 1980 to 2022 and the dipole of high (over Balkans) and low (over eastern Mediterranean) pressure centers also strengthens, leading to stronger winds over the Aegean Sea. The ΔP is strongly correlated (0.8) to the first principal component of MSLP over the eastern Mediterranean. Finally, this study shows that the Etesian flow tends to reduce the concentration of PM10, NO2 and O3, and improving the air quality in the city of Rhodes. [ABSTRACT FROM AUTHOR]

The study was conducted in the period 2019-2021 on the experimental field of IRGR "K. Malkov" Sadovo. Twenty advanced breeding lines and four common winter wheat varieties were studied according to important economic traits. Grain yield, plant height, thousand grain weight and test weight were reported. To assess the genetic similarity and distance between the different genotypes, cluster analysis and analysis of the main components were applied. Based on the results of the cluster analysis, the studied genotypes were divided into five large cluster groups. The applied analysis of the main components shows that the components PC 1 and PC 2 explain 67.9% of the total variation of all traits by genotypes. The line MX 270/86 and the Enola variety, located in the most distant parts of the coordinate system, can be mentioned as a source of strong variation and genetic difference. [ABSTRACT FROM AUTHOR]