Vasilache Nicoleta, Diacu Elena, Cananau Sorin, Tenea Anda Gabriela, Vasile Gabriela Geanina
Faculty of Chemical Engineering and Biotechnologies, University Politehnica of Bucharest, 1-7, Polizu, 011061 Bucharest, Romania.
National Research and Development Institute for Industrial Ecology ECOIND, 57-73 Drumul Podu Dambovitei, Sector 6, 060652 Bucharest, Romania.
Plants (Basel). 2023 Aug 30;12(17):3123. doi: 10.3390/plants12173123.
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 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-CaCl, 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 plant.
测试土壤植物修复的可行性需要开发适用于大规模应用的模型。植物修复机制包括强化根际生物降解、植物积累、植物降解和植物稳定化。本研究的目的是评估在适合评估三种溶液（M1 - CaCl、M2 - DTPA和M3 - EDTA）中这些金属植物有效性的实验室系统中，影响从污染土壤中提取金属过程的因素，包括以下方面：金属在溶液中的分布（Kd）、土壤性质和可移动部分（有机碳、阳离子交换量、pH值）、响应面方法（RSM）和主成分分析（PCA）。使用生物积累系数（BACs）评估白芥植物的植物修复潜力。植物中重金属的积累与土壤中金属的浓度和可溶部分相对应。了解土壤中可提取的金属部分和金属的有效性对于土壤管理很重要。可提取的可溶部分在总金属含量方面作为植物中金属生物浓缩预测指标可能更具优势。在本研究中，最合适提取剂中可用金属的量被用于预测白芥植物中金属的吸收。已经建立了多元回归预测模型来估计植物器官中砷和镉的含量。基于实验数据生成的预测模型的性能通过调整后的决定系数（aR2）、模型效率（RMSE）、杜宾 - 沃森（DW）检验和夏皮罗 - 威尔克（SW）检验进行评估。在不同金属浓度污染的土壤中，分析的金属积累遵循以下模式：对于砷，根＞荚＞叶＞种子，茎＞花；对于镉，叶＞根＞茎＞荚＞种子＞花。所得结果表明该植物具有植物修复潜力。
