Evaluation of the Phytoremediation Potential of the Sinapis alba Plant Using Extractable Metal Concentrations

Author:

Vasilache Nicoleta12ORCID,Diacu Elena1,Cananau Sorin3ORCID,Tenea Anda Gabriela2,Vasile Gabriela Geanina2ORCID

Affiliation:

1. Faculty of Chemical Engineering and Biotechnologies, University Politehnica of Bucharest, 1-7, Polizu, 011061 Bucharest, Romania

2. National Research and Development Institute for Industrial Ecology ECOIND, 57-73 Drumul Podu Dambovitei, Sector 6, 060652 Bucharest, Romania

3. Faculty of Mechanical and Mechatronic Engineering, University of Science and Technology Politehnica Bucharest, 313, Splaiul Independentei, 060042 Bucharest, Romania

Abstract

Testing the feasibility of soil phytoremediation requires the development of models applicable on a large scale. Phytoremediation mechanisms include advanced rhizosphere biodegradation, phytoaccumulation, phytodegradation, and phytostabilization. The aim of this study was to evaluate the phytoremediation potential of the Sinapis alba. Identification of the factors influencing the extraction process of metals from contaminated soils in a laboratory system suitable for evaluating the phytoavailability of these metals in three solutions (M1-CaCl2, M2-DTPA, and M3-EDTA) included the following: distribution of metals in solution (Kd), soil properties and mobile fractions (SOC, CEC, pH), response surface methodology (RSM), and principal component analysis (PCA). The evaluation of the phytoremediation potential of the Sinapis alba plant was assessed using bioaccumulation coefficients (BACs). The accumulation of heavy metals in plants corresponds to the concentrations and soluble fractions of metals in the soil. Understanding the extractable metal fractions and the availability of metals in the soil is important for soil management. Extractable soluble fractions may be more advantageous in total metal content as a predictor of bioconcentrations of metals in plants. In this study, the amount of metal available in the most suitable extractors was used to predict the absorption of metals in the Sinapis alba plant. Multiple regression prediction models have been developed for estimating the amounts of As and Cd in plant organs. The performance of the predictive models generated based on the experimental data was evaluated by the adjusted coefficient of determination (aR2), model efficiency (RMSE), Durbin–Watson (DW) test, and Shapiro–Wilk (SW) test. The accumulation of the analyzed metals followed the pattern Root > Pods > Leaves > Seeds, stems > Flowers for As and Leaves > Root > Stem > Pods > Seeds > Flowers for Cd in soil contaminated with different metal concentrations. The obtained results showed a phytoremediation potential of the Sinapis alba plant.

Funder

Ministry of Research, Innovation of Romania

European Social Fund from the Sectoral Operational Programme Human Capital

Publisher

MDPI AG

Subject

Plant Science,Ecology,Ecology, Evolution, Behavior and Systematics

Reference71 articles.

1. Heavy metal loss from agricultural watershed to aquatic system: A scientometrics review;Ouyang;Sci. Total Environ.,2018

2. A Review on Heavy Metals Contamination in Soil: Effects, Sources, and Remediation Techniques;Li;Soil Sediment Contam. Int. J.,2019

3. Three amendments reduced the bioavailability of heavily contaminated soil with arsenic and cadmium and increased the relative feeding value of Lolium perenne L.;Yang;Sci. Total Environ.,2022

4. Study of metal mobility and phytotoxicity in bottom sediments that have been influenced by former mining activities in Eastern Slovakia;Environ. Earth Sci.,2015

5. Mobility and bioavailability of heavy metals and metalloids in soil environments;Violante;J. Soil. Sci. Plant Nutr.,2010

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