Chemical Engineering Department, Universidad Católica del Norte, 1270709, Antofagasta, Chile.
Department of Computing and Systems Engineering, Universidad Católica del Norte, 1270709, Antofagasta, Chile.
Environ Geochem Health. 2023 Dec;45(12):8867-8880. doi: 10.1007/s10653-022-01342-5. Epub 2022 Aug 14.
Many vegetal species can accumulate great amounts of metallic elements in their tissues. For this reason, they are called metal hyperaccumulators. An indicator of great interest in environmental sciences is the bioconcentration factor because it is recognized for establishing the potential accumulation of chemicals in organisms. Particularly in soil phytoremediation processes, it measures the capacity of a certain plant to capture metals, in terms of soil concentration. According to their behavior, four types of plants can be distinguished regarding soil concentration increase: indicator, excluder, accumulator, and hyperaccumulator. This study proposes a new model to categorize plants according to their behavior related to soil concentration increase, using several characteristic curves obtained from 1288 experimental measurements collected from different bibliographic sources. The metals analyzed were Cu, Fe, Pb, and Zn. The proposed model is obtained through linear regression and nonlinear transformations to model the expected behavior of plants in high concentration conditions. In particular, the basic equation of the model has three key components to represent the expected concentration in the plant root given the final soil concentration level, the type of species, and specific metal: a linear factor that determines the growth for low concentration values, an exponential factor that determines its decrease for high concentration values, and a logarithmic factor that limits the maximum value that can be reached in practice and influences the decay for high concentration values. After fitting the experimental data using linear regression, the proposed model has a 0.084 R determination coefficient and all of its parameters are considered significant. Furthermore, it shows that 60 of the 257 species assessed behave as accumulators and 10 of them as hyperaccumulators. The main contribution of this model is its ability to handle soils with high concentrations, where it would be hard for plants to achieve concentrations similar to or higher than the substrate containing them. Thus, the conventional criterion of the bioconcentration factor would incorrectly categorize a plant as an excluder. In contrast, this new model allows assessing plant effectiveness in a phytoremediation process of highly concentrated affected sites, such as mine tailings.
许多植物物种可以在其组织中积累大量的金属元素。由于这个原因，它们被称为金属超积累植物。生物浓缩因子是环境科学中一个非常有趣的指标，因为它被认为是建立化学物质在生物体内潜在积累的指标。特别是在土壤植物修复过程中，它可以衡量某种植物从土壤浓度方面捕获金属的能力。根据其行为，可以将植物分为四种类型，以提高土壤浓度：指示植物、排斥植物、积累植物和超积累植物。本研究提出了一种新的模型，根据植物与土壤浓度增加相关的行为对植物进行分类，使用从不同文献来源收集的 1288 个实验测量结果得到的几个特征曲线。分析的金属是 Cu、Fe、Pb 和 Zn。所提出的模型是通过线性回归和非线性变换获得的，用于模拟植物在高浓度条件下的预期行为。特别是，模型的基本方程有三个关键组成部分，用于表示在给定最终土壤浓度水平、物种类型和特定金属的情况下，植物根部的预期浓度：一个线性因子，用于确定低浓度值的生长；一个指数因子，用于确定高浓度值的下降；一个对数因子，用于限制实际可达到的最大值并影响高浓度值的衰减。使用线性回归对实验数据进行拟合后，所提出的模型的决定系数为 0.084，并且其所有参数都被认为是显著的。此外，它表明评估的 257 种物种中有 60 种表现为积累者，其中 10 种为超积累者。该模型的主要贡献在于其能够处理高浓度的土壤，在这种土壤中，植物很难达到与含有它们的基质相似或更高的浓度。因此，生物浓缩因子的常规标准会错误地将植物归类为排斥者。相比之下，这种新模型可以评估植物在受影响的高浓度矿区尾矿等场地的植物修复过程中的有效性。
