Mercury levels were determined in feathers from 83 birds belonging to 18 species (eight families), all collected from the northern region of Iran. Mercury levels were evaluated in relation to taxonomic affiliation and feeding strategies. Mercury levels in the feathers were between 0.05 ± 0.01 and 1.10 ± 0.15 μg g(-1) dry weight, and there was a significant effect of taxonomic groups (p < 0.05). The highest mercury levels were found in Accipitridae, and mercury was not detected in the family Upupidae. The pattern for mercury levels was Accipitridae > Pelecanidae > Sternidae > Ardeidae > Anatidae > Rallidae > Phasianidae (p < 0.05). Significant differences (p < 0.05) in the mean mercury levels were found among species as a function of feeding method and trophic level. Mercury levels were highest in the carnivorous species and lowest in the herbivorous species. Mercury levels in feathers of birds in this study were generally below the thresholds reported to affect reproduction.
In the present study, a simple, rapid and efficient dispersive liquid–liquid microextraction (DLLME) coupled with spectrofluorimetry and chemometrics methods have been proposed for the preconcentration and determination of fenthion in water samples. Box–Behnken design was applied for multivariate optimization of the extraction conditions (sample pH, the volume of dispersive solvent and volume of extraction solvent). Analysis of variance was performed to study the statistical significance of the variables, their interactions and the model. Under the optimum conditions, the calibration graph was linear in the range of 5.0–110.0 ng mL-1 with the detection limit of 1.23 ng mL-1 (3Sb/m). Parallel factor analysis (PARAFAC) and partial least square (PLS) modelling were applied for the multivariate calibration of the spectrofluorimetric data. The orthogonal signal correction (OSC) was applied for preprocessing of data matrices and the prediction results of model, and the analysis results were statistically compared. The accuracy of the methods, evaluated by the root mean square error of prediction (RMSEP) for fenthion by OSC-PARAFAC and OSC-PLS models were 0.37 and 0.78, respectively. The proposed procedure could be successfully applied for the determination of fenthion in water samples.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.