Regression models for monitoring trace metal accumulations by Faba sativa Bernh. plants grown in soils amended with different rates of ... View Full Text


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Article Info

DATE

2019-12

AUTHORS

Ebrahem M. Eid, Sulaiman A. Alrumman, Tarek M. Galal, Ahmed F. El-Bebany

ABSTRACT

The present study was conducted using a pot experiment to develop regression models for the prediction of trace metal concentrations in faba bean (Faba sativa Bernh.) plants cultivated in soils amended with different rates of sewage sludge to monitor possible human health risks. The trace metal concentrations in the different tissues of faba bean showed that most of the investigated trace metals were accumulated in the plant roots rather than in the other tissues. Meanwhile, the fruits accumulated the lowest concentration of most trace metals. The trace metal concentrations of the faba bean plants had a significant positive correlation with the organic matter content and a significant negative correlation with the soil pH. Transfer of trace metals from the soil to faba bean roots indicated that Al, Cu, Pb and Zn had a transfer factor that exceeded one, whereas the TF of the investigated trace metals from the roots to the fruits did not exceed one. The daily intake rate of the investigated trace metals did not exceed one in both adults and children. On the other side, the hazard quotient of trace metals from consuming faba bean fruits had values <1 for most investigated trace metals except Al and Mn in adults and in children. It is worth mentioning that the predicted trace metal concentrations via the established regression models and measured values from the validation data set were not significantly different (P > 0.05). Therefore, these developed models will be useful for prediction of trace metals uptake by faba bean grown in soil amended with sewage sludge so possible human risks can be identified. More... »

PAGES

5443

References to SciGraph publications

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  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1038/s41598-019-41807-9

    DOI

    http://dx.doi.org/10.1038/s41598-019-41807-9

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1113158015

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/30931965


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