Predicting the Trace Element Levels in Caspian Kutum (Rutilus kutum) from South of the Caspian Sea Based on Locality, Season and Fish Tissue
Autor: | Javid Imanpour Namin, Mohammad Forouhar Vajargah, Mehdi Bibak, Masoud Sattari |
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Rok vydání: | 2021 |
Předmět: |
Endocrinology
Diabetes and Metabolism Clinical Biochemistry Fishing Cyprinidae 010501 environmental sciences 01 natural sciences Biochemistry Inorganic Chemistry 03 medical and health sciences Metals Heavy Environmental monitoring Animals Humans Caspian kutum 0105 earth and related environmental sciences Hydrology 0303 health sciences biology 030302 biochemistry & molecular biology Biochemistry (medical) Sediment Sampling (statistics) Regression analysis General Medicine biology.organism_classification Trace Elements Salinity Environmental science Caspian Sea Seasons Akaike information criterion Water Pollutants Chemical Environmental Monitoring |
Zdroj: | Biological Trace Element Research. 200:354-363 |
ISSN: | 1559-0720 0163-4984 |
DOI: | 10.1007/s12011-021-02622-4 |
Popis: | Elements are the shared result of the erosion of rocks in the catchment area and human activities. Nutritional habits, ecological needs, heavy metal concentrations in water and sediment, duration of fishing in the aquatic environment, fishing season, and physicochemical properties of water (salinity, pH, hardness, and temperature) are among the effective factors in the accumulation of heavy metals in various fish organs. In this study, 150 specimens of Rutilus kutum were collected from the southern shores of the Caspian Sea including Astara, Anzali, and Kiashahr in Guilan Province, Farahabad in Mazandaran Province, and Bandar Torkaman in Golestan Province from December 2018 through October 2019. It is possible to predict the metal concentrations using the variables such as fish tissue, sampling region, and season. Akaike information criterion (AIC) was used to select the best regression model. We used fish muscle tissue and Anzali sampling site which were considered reference variables in the regression model. For some elements, a better model is obtained by considering all variables (AIC criterion is its lowest value). The best model obtained for Cu, Mn, and Si was only with region (as a variable). The best model obtained for Sn and Sr only concerns the region and tissue variables. The best model obtained for Sb only related to tissue variable. Using these models, environmental monitoring becomes easier and cheaper. We suggest further studies to be carried out in the shortest possible time along with the least laboratory cost. |
Databáze: | OpenAIRE |
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