The influence of humic substance on Cd accumulation of phytostabilizer Athyrium wardii (Hook.) grown in Cd-contaminated soils

Potential mechanism of humic acid attenuating toxicity of Pb2+ and Cd2+ in Vallisneria natans

Humic substances are widely present in aquatic environments. Due to the high affinity of humic substances for metals, the interactions have been particularly studied. To assess the effect of humic acid (HA) on submerged macrophytes and biofilms exposed to heavy metal stress, Vallisneria natans was exposed to solutions containing different concentrations of HA (0.5-2.0 mg·L^-1), Pb²⁺ (1 mg·L^-1) and Cd²⁺ (1 mg·L^-1). Results suggested that HA positively affected the plant growth and alleviated toxicity by complexing with metals. HA increased the accumulation of metals in plant tissues and effectively induced antioxidant responses and protein synthesis. It was also noted that the exposure of HA and metals promoted the abundance and altered the structure of microbial communities in biofilms. Moreover, the positive effects of HA were considered to be related to the expression of related genes resulting from altered DNA methylation levels, which were mainly reflected in the altered type of demethylation. These results demonstrate that HA has a protective effect against heavy metal stress in Vallisneria natans by inducing effective defense mechanisms, altering biofilms and DNA methylation patterns in aquatic ecosystems.

Phytoremediation technologies and their mechanism for removal of heavy metal from contaminated soil: An approach for a sustainable environment

The contamination of soils with heavy metals and its associated hazardous effects are a thrust area of today's research. Rapid industrialization, emissions from automobiles, agricultural inputs, improper disposal of waste, etc., are the major causes of soil contamination with heavy metals. These contaminants not only contaminate soil but also groundwater, reducing agricultural land and hence food quality. These contaminants enter the food chain and have a severe effect on human health. It is important to remove these contaminants from the soil. Various economic and ecological strategies are required to restore the soils contaminated with heavy metals. Phytoremediation is an emerging technology that is non-invasive, cost-effective, and aesthetically pleasing. Many metal-binding proteins (MBPs) of the plants are significantly involved in the phytoremediation of heavy metals; the MBPs include metallothioneins; phytochelatins; metalloenzymes; metal-activated enzymes; and many metal storage proteins, carrier proteins, and channel proteins. Plants are genetically modified to enhance their phytoremediation capacity. In Arabidopsis, the expression of the mercuric ion-binding protein in Bacillus megaterium improves the metal accumulation capacity. The phytoremediation efficiency of plants is also enhanced when assisted with microorganisms, biochar, and/or chemicals. Removing heavy metals from agricultural land without challenging food security is almost impossible. As a result, crop selections with the ability to sequester heavy metals and provide food security are in high demand. This paper summarizes the role of plant proteins and plant-microbe interaction in remediating soils contaminated with heavy metals. Biotechnological approaches or genetic engineering can also be used to tackle the problem of heavy metal contamination.

Transforming approach for assessing the performance and applicability of rice arsenic contamination forecasting models based on regression and probability methods

Probability models are preferred over regression models recently in contamination evaluation but lacking proper performance comparison between two model types. Linear regression, logistic regression, XGBoost-based regression, and probability models were built considering soil arsenic and certain soil physicochemical properties of 287 samples to predict arsenic in rice grains. The outputs of all models were binarily classified uniformly for comparison. The complex algorithm-based models--XGBoost-based regression (R² =0.046 ± 0.036) and probability models (cross-entropy = 0.697 ± 0.020)-did not surpass the simple linear regression (R² =0.046 ± 0.031) and logistic regression models (cross-entropy = 0.694 ± 0.021). Accuracy, sensitivity, specificity, precision, and F1 score showed that the probability models exhibit no advantage on regression models, although the indicators above did not serve as proper scoring rules for the probability model. When discretizing the contaminant concentration in grains for probabilistic modeling, the limit concentration was considered as the splitting point but not the structure of the datasets, which would reduce the inherent advantage of the probability model. When predicting the contamination of crops, the probability model cannot eliminate the regression model, and simple but robust algorithm-based models are preferred when the quality and quantity of the dataset are undesirable.

Discriminative algorithm approach to forecast Cd threshold exceedance probability for rice grain based on soil characteristics

The relationship between cadmium (Cd) concentration in rice grains and the soil that they are cultivated in is highly uncertain due to the influence of soil properties, rice varieties, and other undetermined factors. In this study, we introduce the probability of exceeding the threshold to characterize this uncertainty and then, build a probabilistic forewarning model. Additionally, a number of associated factors have been used as parameters to improve model performance. Considering that the physicochemical properties and Cd concentration in the soil (Cd_soil) do not follow a normal distribution, and are not independent of each other, a discriminative algorithm, represented by a logistic regression (LR), performed better than generative algorithms, such as the naive Bayes and quadratic discriminant analysis models. The performance of the LR based model was found to be 0.5% better in the case of the univariate model (Cd_soil) and 4.1% better with a multivariate model (soil properties used as additional factors) (p < 0.01). The output of the LR based model predicted probabilities that were positively correlated to the true exceedance rate (R² = 0.949,p < 0.01), within an exceedance threshold range of 0.1-0.4 mg kg^-1 and a mean deviation of 5.75%. A sensitivity analysis showed that the effect of soil properties on the exceedance probability weakens with an increase in Cd concentration in rice grains. When the threshold is below 0.15 mg kg^-1, soil pH strongly influences the exceedance probability. As the threshold increases, the influence of pH on the exceedance probability is gradually superseded. By quantifying the uncertainty regarding the relationship between Cd concentration in rice grains and soil, the discriminative algorithm-based probabilistic forecasting model offers a new way to assess Cd pollution in rice grown in contaminated paddy fields.

Lead accumulation and soil microbial activity in the rhizosphere of the mining and non-mining ecotypes of Athyrium wardii (Hook.) Makino in adaptation to lead-contaminated soils

Better understanding of microbial activity in the rhizosphere soils associated with lead (Pb) uptake by plants may help with the phytoremediation of Pb-contaminated soils. In this work, the effects of Pb exposure (0, 200, 400, 600, 800 mg kg^-1) on Pb accumulation and soil microbial activity in the rhizosphere of the mining ecotype (ME) and corresponding non-mining ecotype (NME) of Athyrium wardii (Hook.) Makino were investigated through a pot experiment. Although the plant growth of the two ecotypes was inhibited under Pb stress, the ME showed a less biomass decrease (12.6-44.0%) for aboveground than the NME, showing a greater tolerance to Pb stress. Pb concentrations as well as Pb accumulation in the two ecotypes showed an increasing trend with increasing soil Pb concentrations. The ME presented greater Pb accumulation ability than the NME, especially in underground parts. Pb availability in the rhizosphere soils of the two ecotypes after harvest decreased compared with those before transplantation. Available Pb in the rhizosphere of the ME was 1.4-4.8 times higher than that of the NME under exposure to 200-800 mg kg^-1 Pb. The ME shows a greater ability to mobilize Pb in the rhizosphere soils. Pb exposure resulted in an inhibition of microbial activity in the rhizosphere of the two ecotypes. The ME demonstrated greater soil respiration and microbial biomass carbon (MBC) in the rhizosphere than the NME when treated with 200-800 mg kg^-1 Pb. The ME showed a less decrease for MBC and a less increase for metabolic quotient in the rhizosphere soils than the NME when exposed to Pb generally. Microorganisms in the rhizosphere soils of the ME seem to be much more adapted to Pb stress, thus showing a great benefit for Pb accumulation and the phytostabilization of Pb-contaminated soils by the ME.

Arbuscular mycorrhizal fungus modulates the phytotoxicity of Cd via combined responses of enzymes, thiolic compounds, and essential elements in the roots of Phragmites australis

The positive effects of arbuscular mycorrhizal (AM) fungi on host plants under heavy metal (HM) stress conditions have been widely recognized. HMs are known to induce phytotoxicity through 1) the production of reactive oxygen species (ROS), 2) the direct interaction with thiol groups or 3) the competition with essential elements. However, how AM fungus inoculation can affect defense mechanisms against cadmium (Cd) stress, which can regulate and alleviate the phytotoxicity via different pathways, is still unclear. We hypothesized that one or some factors in each pathway of phytotoxicity were involved in detoxifying Cd by inoculating with AM fungus. In this study, the involvements of enzymes, thiolic compounds, and divalent essential elements in the roots of Phragmites australis (Cav.) Trin. ex Steud. were assessed. In addition, we also worked to elucidate the significant factors among three possible pathways involved in biosynthesis with AM fungus inoculation, using principal component analysis (PCA). The results presented here indicate that AM symbiosis can result in a marked tolerance to Cd via accumulating Cd with a shorter exposure treatment time, and obvious fluorescence in the roots was also observed. The decrease in phytotoxicity was mainly accomplished by changes in superoxide dismutase (SOD), catalase (CAT), non-protein thiols (NPT), calcium (Ca), manganese (Mn), and copper (Cu). These results provide comprehensive insights for elucidating the defense mechanisms by which inoculation with AM fungus has beneficial roles in helping P. australis cope with the deleterious effects of Cd.