| Autor: |
Picchi, Carolina, Giorgetti, Lucia, Morelli, Elisabetta, Landi, Marco, Rosellini, Irene, Grifoni, Martina, Franchi, Elisabetta, Petruzzelli, Gianniantonio, Barbafieri, Meri |
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| Zdroj: |
Environmental Science & Pollution Research; Mar2022, Vol. 29 Issue 11, p15983-15998, 16p |
| Abstrakt: |
Phytoremediation represents a natural method to remove contaminants from soil. The goal of this study was to investigate the potential of phosphate-assisted phytoremediation by two energy crops, Cannabis sativa L. and Brassica juncea L., for the sustainable remediation of heavily arsenic-contaminated industrial soil. The two species were investigated for uptake, translocation, and physiological effects of arsenic and phosphate in a microcosm test. Although C. sativa and B. juncea were symptomless when grown in arsenic-contaminated soil, an important reduction of biomass (50 and 25%, respectively) was observed as a stress marker. Phytotoxicity and cytotoxicity effects promoted by contaminated soils were investigated in both the species and a model plant for ecotoxicity studies, Vicia faba L., which is the most developed model to test genotoxicity effects in terms of chromosomal aberration and micronuclei presence. The higher amount of arsenic was found in C. sativa and B. juncea roots (on average 1473 and 778 mg kg−1, respectively), but both species were able to uptake and translocate arsenic in leaves and stems, up to 47.0 and 189 mg kg−1, respectively. Phosphate treatment had no effect on arsenic uptake in none of the crop, but significantly improved the plant performance. Biomass production resulted similar to that of B. juncea control plants. Antioxidant enzymatic activities and photosynthetic performance responded differently in the two crops. The present investigation provides new insight for a proficient selection of the most suitable crop species for sustainable phytomanagement of a highly polluted As-contaminated site by coupled phytoremediation-bioenergy approach. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
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