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Hyperaccumulators are the material basis and key to the phytoremediation of heavy metal contaminated soils. Conventional methods for screening hyperaccumulators are highly dependent on the time- and labor-consuming sampling and chemical analysis. In this study, a novel spectral approach assisted with multi-task deep learning was proposed to streamline accumulating ecotype screening, heavy metal stress discrimination, and heavy metals quantification in plants. The significant Cd/Zn co-hyperaccumulator Sedum alfredii and its non-accumulating ecotype were stressed by Cd, Zn, and Pb. Spectral images of leaves were rapidly acquired by hyperspectral imaging. The self-designed deep learning architecture was composed of a shallow network (ENet) for accumulating ecotype identification, and a multi-task network (HMNet) for heavy metal stress type and accumulation prediction simultaneously. To further assess the robustness of the networks, they were compared with conventional machine learning models (i.e., partial least squares (PLS) and support vector machine (SVM)) on a series of evaluation metrics of classification, multi-label classification, and regression. S. alfredii with heavy metals accumulation capability was identified by ENet with 100 % accuracy. HMNet reduced overfitting and outperformed machine learning models with the average exact match ratio (EMR) of heavy metal stress discrimination increased by 7.46 %, and residual prediction deviations (RPD) of heavy metal concentrations prediction increased by 53.59 %. The method succeeded in rapidly and accurately discriminating heavy metal stress with EMRs over 91 % and accuracies over 96 %, and in predicting heavy metals accumulation with an average RPD of 3.29 for Zn, 2.57 for Cd, and 2.53 for Pb, indicating the satisfactory practicability and potential for sensing heavy metals accumulation. This study provides a relatively novel spectral method to facilitate hyperaccumulator screening and heavy metals accumulation prediction in the phytoremediation process.

Hyperaccumulators are the material basis and key to the phytoremediation of heavy metal contaminated soils. Conventional methods for screening hyperaccumulators are highly dependent on the time- and labor-consuming sampling and chemical analysis. In this study, a novel spectral approach assisted with multi-task deep learning was proposed to streamline accumulating ecotype screening, heavy metal stress discrimination, and heavy metals quantification in plants. The significant Cd/Zn co-hyperaccumulator Sedum alfredii and its non-accumulating ecotype were stressed by Cd, Zn, and Pb. Spectral images of leaves were rapidly acquired by hyperspectral imaging. The self-designed deep learning architecture was composed of a shallow network (ENet) for accumulating ecotype identification, and a multi-task network (HMNet) for heavy metal stress type and accumulation prediction simultaneously. To further assess the robustness of the networks, they were compared with conventional machine learning models (i.e., partial least squares (PLS) and support vector machine (SVM)) on a series of evaluation metrics of classification, multi-label classification, and regression. S. alfredii with heavy metals accumulation capability was identified by ENet with 100 % accuracy. HMNet reduced overfitting and outperformed machine learning models with the average exact match ratio (EMR) of heavy metal stress discrimination increased by 7.46 %, and residual prediction deviations (RPD) of heavy metal concentrations prediction increased by 53.59 %. The method succeeded in rapidly and accurately discriminating heavy metal stress with EMRs over 91 % and accuracies over 96 %, and in predicting heavy metals accumulation with an average RPD of 3.29 for Zn, 2.57 for Cd, and 2.53 for Pb, indicating the satisfactory practicability and potential for sensing heavy metals accumulation. This study provides a relatively novel spectral method to facilitate hyperaccumulator screening and heavy metals accumulation prediction in the phytoremediation process., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Quorum sensing (QS) plays an important role in the intensive communication between plants and microbes in the rhizosphere during the phytoremediation. This study explored the influence of the root exudates of hyperaccumulator Sedum alfredii on Pseudomonas aeruginosa based on QS. The effects of the components of root exudates, genes expression and transcription regulation of QS system (especially the las system) in Pseudomonas aeruginosa wild-type strain (WT) and rhl system mutant strain (ΔrhlI) were systematically analyzed and discussed. The WT and ΔrhlI exposed to gradient root exudates (0×, 1×, 2×, 5× and 10×) showed a concentration-corrective inhibition on protease production, with the inhibition rates of 51.4–74.5% and 31.2–50.0%, respectively. Among the components of the root exudates of Sedum alfredii, only thymol had an inhibition effects to the root exudates on the activity of protease and elastase. The inhibition rates of 50 μmol/L thymol on protease and elastase in WT were 44.7% and 24.3%, respectively, which was consistent with the variation in ΔrhlI. The gene expression of lasB declined 36.0% under the 1× root exudate treatment and 73.0% under the 50 μmol/L thymol treatment. Meanwhile, there was no significant impact on N-3-oxo-dodecanoyl-L-homoserine lactone signal production and the gene expression of lasI and lasR. Therefore, thymol from Sedum alfredii root exudates could inhibit the formation of protease and elastase in Pseudomonas aeruginosa by suppressing the expression of lasB, without any significant influence on the main las system as a potential natural QS inhibitor.

Application of activating agents can significantly improve efficiency of plants for remediation of soils contaminated by heavy metals, however, damage to soil and plants limits application of traditional activating agents. The aim of our experiments is to select an efficient,green and low-cost activating agent to improve efficiency of plant extraction technology. In this study, contaminated soil was remediated by Sedum alfredii. The effects of two plant extracts (i.e., Oxalis corniculata,OX and Medicago sativaextract, ME) in addition to citric acid (CA) were studied in oscillatory activation experiment and pot experiment. The oscillation activation experiment revealed that extraction quantity of heavy metals in the soil was enhanced significantly with concentration of plant extract. The extraction quantity of Zn from 100% OX extract and ME extract were significantly higher than 10 mmol/L CA (54.04% and 33.09%, respectively). The 10 mmol/L CA has best extraction efficiency for Cd, up to 41.36 µg/kg, which is significantly higher than CK (control) (p

Quorum sensing (QS) plays an important role in the intensive communication between plants and microbes in the rhizosphere during the phytoremediation. This study explored the influence of the root exudates of hyperaccumulator Sedum alfredii on Pseudomonas aeruginosa based on QS. The effects of the components of root exudates, genes expression and transcription regulation of QS system (especially the las system) in Pseudomonas aeruginosa wild-type strain (WT) and rhl system mutant strain (ΔrhlI) were systematically analyzed and discussed. The WT and ΔrhlI exposed to gradient root exudates (0×, 1×, 2×, 5× and 10×) showed a concentration-corrective inhibition on protease production, with the inhibition rates of 51.4-74.5% and 31.2-50.0%, respectively. Among the components of the root exudates of Sedum alfredii, only thymol had an inhibition effects to the root exudates on the activity of protease and elastase. The inhibition rates of 50 μmol/L thymol on protease and elastase in WT were 44.7% and 24.3%, respectively, which was consistent with the variation in ΔrhlI. The gene expression of lasB declined 36.0% under the 1× root exudate treatment and 73.0% under the 50 μmol/L thymol treatment. Meanwhile, there was no significant impact on N-3-oxo-dodecanoyl-L-homoserine lactone signal production and the gene expression of lasI and lasR. Therefore, thymol from Sedum alfredii root exudates could inhibit the formation of protease and elastase in Pseudomonas aeruginosa by suppressing the expression of lasB, without any significant influence on the main las system as a potential natural QS inhibitor., (Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.)

Application of activating agents can significantly improve efficiency of plants for remediation of soils contaminated by heavy metals, however, damage to soil and plants limits application of traditional activating agents. The aim of our experiments is to select an efficient,green and low-cost activating agent to improve efficiency of plant extraction technology. In this study, contaminated soil was remediated by Sedum alfredii. The effects of two plant extracts (i.e., Oxalis corniculata,OX and Medicago sativaextract, ME) in addition to citric acid (CA) were studied in oscillatory activation experiment and pot experiment. The oscillation activation experiment revealed that extraction quantity of heavy metals in the soil was enhanced significantly with concentration of plant extract. The extraction quantity of Zn from 100% OX extract and ME extract were significantly higher than 10 mmol/L CA (54.04% and 33.09%, respectively). The 10 mmol/L CA has best extraction efficiency for Cd, up to 41.36 µg/kg, which is significantly higher than CK (control) (p < 0.05). The pot experiment exhibited that application of CA has significantly reduced soil pH and organic matter content by 8.63% and 28.21%, respectively, however the two extracts have no significant effect on soil properties. The study indicated that application of CA has negative effects on root morphological parameters and chlorophyll fluorescence parameters of Sedum alfredii.The addition of extracts of two plants have not caused any harm to Sedum alfredii. The application of three activating agents was beneficial for purification of Cd and Zn in soils, and its repairing efficiency was improved by 3.92, 3.37, 3.33 times and 0.44, 0.20, 0.86 times, respectively. The combination of plant extracts and hyperaccumulators can effectively remove heavy metals from contaminated soils, which provided a theoretical basis for mitigation of pollution in soils., (Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.)