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Kinetic modeling of heavy metal uptake and translocation in Brassica juncea L. for phytoremediation engineering
Open accessAbstract
Heavy metal contamination of soil and water resources poses a significant global environmental challenge. Brassica juncea L. is a promising candidate for phytoremediation due to its high biomass and metal tolerance. However, a quantitative understanding of its metal-specific uptake kinetics and translocation patterns under realistic conditions is essential for optimizing remediation strategies. This study investigated the uptake, translocation, and kinetic modeling of lead, nickel, zinc, and mercury in Brassica juncea L. cv. Balady cultivated in soil irrigated with industrial wastewater over 90 days. The plant exhibited distinct metal-specific remediation strategy. Zinc and Ni showed the highest accumulation, with significant translocation to shoots, indicating strong phytoextraction potential. In contrast, Pb and Hg were primarily sequestered in the roots, suggesting a predominant role in phytostabilization. A first-order kinetic model effectively described the temporal uptake, demonstrating an excellent fit for Ni (R 2 = 0.9983) and a strong fit for Hg (R 2 = 0.8755). The phytoremediation potential was quantitatively confirmed by the bioconcentration factor (BCF) and translocation factor (TF), with Zn showing the highest root concentration (BCF = 5.92) and Hg uniquely exhibiting a TF > 1. Brassica juncea proves to be a versatile species for managing multi-metal contamination, capable of both phytoextraction and phytostabilization depending on the target metal. The validated kinetic models provide a predictive framework for estimating metal accumulation, thereby enhancing the planning and efficiency of B. juncea -based phytoremediation interventions in wastewater-impacted environments. This work bridges the gap between controlled experimentation and field application by integrating empirical data with mathematical modeling.
Overview
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TL;DR
This 90-day pot study irrigated *Brassica juncea* L. cv. Balady with industrial wastewater and modeled Pb, Ni, Zn, and Hg uptake and translocation. It found metal-specific behavior, with Zn and Ni showing the highest accumulation, Pb and Hg mainly root-sequestered, and a first-order kinetic model fitting Ni best (R² = 0.9983) and Hg strongly (R² = 0.8755).
Key findings
- Zn had the highest root accumulation (maximum 65 µg/g; BCF = 5.92) and Ni also accumulated strongly (maximum 40 µg/g in roots; BCF = 3.85), but their translocation factors were < 1 (Zn TF = 0.54; Ni TF = 0.68), leading the paper to propose phytostabilization for Zn and phytostabilization/moderate phytoextraction for Ni.
- Pb and Hg were primarily sequestered in roots: Pb BCF = 2.02, TF = 0.58; Hg BCF = 1.38 but uniquely TF = 1.22 (> 1), suggesting moderate phytoextraction potential for Hg despite low absolute concentrations.
- First-order kinetic model fits: Ni R² = 0.9983, Hg R² = 0.8755, Pb R² = 0.8522, Zn R² = 0.7932.
- Post-irrigation enrichment factors were significant for Zn (EF = 11.2) and Ni (EF = 9.8), and moderate for Pb (EF = 4.5) and Hg (EF = 3.8).
Methods
- Pot experiment with *B. juncea* L. cv. Balady: 15 × 15 cm pots filled with 15 kg soil, five seedlings per pot, three biological replicates, completely randomized design, irrigated daily with 0.5 L industrial wastewater for 90 days; roots, stems, and leaves harvested at 15-day intervals and analyzed by ICP-MS.
- Soil was collected from Cairo, Egypt; industrial wastewater was from El Tebin industrial zone, Egypt, with Pb 12.36, Ni 10.64, Zn 30.45, and Hg 6.5 mg/L. Soil pH was 7.4; n = 3 biological replicates with analytical triplicates.
- Analyses included a linearized first-order kinetic model, bioconcentration factor (BCF) and translocation factor (TF) at 90 DAS, enrichment factor (EF) using Fe and upper continental crust background, one-way ANOVA with LSD post hoc, Kruskal-Wallis checks, and SPSS with p < 0.05.
Limitations
- The paper states the kinetic regression used only six data points per metal-tissue and that a larger dataset, ideally from independent experiments, would be required for full statistical validation and robust predictive power; high R² values are interpreted as fit to the controlled temporal trend, not universal predictive validity.
- The paper states n = 3 biological replicates limited the power of normality tests and notes persistent challenges from variable metal bioavailability, soil heterogeneity, and long-term field performance; future field trials are recommended.
- Evident from the text: the study used a single cultivar, one soil source, one industrial wastewater source, and pot/greenhouse conditions rather than field conditions; Hg volatilization is suggested as a possible explanation for low tissue recovery but was not directly measured.
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0 Valid · 0 Not valid · 24 Not checked · 71 Own results and interpretations
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Zinc and Ni showed the highest accumulation, with significant translocation to shoots, indicating strong phytoextraction potential.”
§ Kinetic modeling of heavy metal uptake and translocation in Brassica juncea L. for phytoremediation engineering > Abstract
plain- Asserted: passes — The authors put it forward as true.
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None of the sources cited for this claim have been checked yet.
In the paper
“The moderate soil Enrichment Factor (EF = 4.5) confirms that a significant portion of the added Pb was immobilized in the soil matrix through low solubility precipitates and strong sorption to organic matter and clay particles [25,33], thereby limiting its phytoavailability.”
§ Kinetic modeling of heavy metal uptake and translocation in Brassica juncea L. for phytoremediation engineering > 3.4.1 Lead (Pb)
boosted- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
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In the paper
“The root sequestration efficiency observed here (Root Bioconcentration Factor > > 1) is comparable to that reported in other Pb-tolerant species like Miscanthus [34]”
§ Kinetic modeling of heavy metal uptake and translocation in Brassica juncea L. for phytoremediation engineering > 3.4.1 Lead (Pb)
What the sources say
- Not checked yetcites [34] Pogrzeba M, Rusinowski S, Krzyżak J. Macroelements and heavy metals content in energy crops cultivated on contaminated soil under different fertilization—case studies on autumn harvest. Environ Sci Pollut Res Int. 2018;25(12):12096–106. source
plain- Asserted: passes — The authors put it forward as true.
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A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The concentrations observed in our study (e.g., maximum of 65 mg kg⁻ 1 Zn and 40 mg kg⁻ 1 Ni in roots) are below these thresholds, confirming that B. juncea is not a true hyperaccumulator.”
§ Kinetic modeling of heavy metal uptake and translocation in Brassica juncea L. for phytoremediation engineering > 3.4 Heavy metal accumulation in plant tissues
boosted- Asserted: passes — The authors put it forward as true.
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In the paper
“Ni saturation in roots, observed after approximately 45 days, has also been documented by Gupta et al. [33], suggesting a plateau in storage capacity.”
§ Kinetic modeling of heavy metal uptake and translocation in Brassica juncea L. for phytoremediation engineering > 3.4.2 Nickel (Ni)
What the sources say
- Not checked yetcites [33] U. Gupta, S. Shukla, L. K. Bhardwaj, P. Rath, D. Upadhyay, B. Sharma, R. Rupam, H. Asthana, T. Jindal, and H. Singh, “Unraveling Urban Plant Strategies for Heavy Metal Uptake and Detoxification,” in Urban Forests, Climate Change and Environmental Pollution: Physio-Biochemical and Molecular Perspectives to Enhance Urban Resilience, H. Singh, Ed., Cham, Switzerland: Springer, 2024, pp. 93–119. doi:10.1007/978-3-031-67837-0_5. source
plain- Asserted: passes — The authors put it forward as true.
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- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
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Percentages, sums and reported differences re-computed from the paper’s own numbers.
Each contradiction between two passages listed here was confirmed by an independent check.
Rated major: it would touch a result — a value a result rests on, reported and recomputed p-values on opposite sides of the significance level, two passages that conflict with no sign which is right, or a cited work retracted before this paper was published.
In the paper
§ Kinetic modeling of heavy metal uptake and translocation in Brassica juncea L. for phytoremediation engineering > 4 Conclusions
“In contrast, Pb and Hg were largely immobilized in the roots, highlighting their potential for phytostabilization.”
§ Kinetic modeling of heavy metal uptake and translocation in Brassica juncea L. for phytoremediation engineering > 3.5 Phytoremediation potential of Brassica juncea
“Conversely, for Hg, the indices (BCF > 1, TF > 1) suggest a potential for moderate phytoextraction, although the overall extraction efficiency is low due to low absolute uptake.”
Rated major: it would touch a result — a value a result rests on, reported and recomputed p-values on opposite sides of the significance level, two passages that conflict with no sign which is right, or a cited work retracted before this paper was published.
In the paper
§ Kinetic modeling of heavy metal uptake and translocation in Brassica juncea L. for phytoremediation engineering > 3.4.4 Mercury (Hg)
“Hg levels in aerial tissues were nearly undetectable (< 0.07 mg/kg), indicating either effective root retention or volatilization”
§ Kinetic modeling of heavy metal uptake and translocation in Brassica juncea L. for phytoremediation engineering > 3.4.4 Mercury (Hg)
“Over the 90-day experimental period, root Hg levels showed a slight increase from 6 to 9 µg/g, whereas stems accumulated up to 10 µg/g.”
Rated major: it would touch a result — a value a result rests on, reported and recomputed p-values on opposite sides of the significance level, two passages that conflict with no sign which is right, or a cited work retracted before this paper was published.
In the paper
§ Kinetic modeling of heavy metal uptake and translocation in Brassica juncea L. for phytoremediation engineering > 4 Conclusions
“Our key findings reveal that Zn and Ni were absorbed at the highest rates, and their significant root-to-shoot translocation confirms their suitability for phytoextraction.”
§ Kinetic modeling of heavy metal uptake and translocation in Brassica juncea L. for phytoremediation engineering > 3.5 Phytoremediation potential of Brassica juncea
“The plant is predominantly suited for phytostabilization of Pb, Ni, and Zn, as indicated by BCF > 1 and TF < 1 for these metals.”
Rated minor: it would not touch a result — a value no result rests on, a p-value that stays on the same side of the significance level, or a conflict that is clerical, resolved elsewhere in the paper, or outside its own findings.
In the paper
§ Kinetic modeling of heavy metal uptake and translocation in Brassica juncea L. for phytoremediation engineering > 3.4.1 Lead (Pb)
“By day 90, Pb concentrations in Brassica juncea roots increased markedly from 10 to 25 µg/g, while stems and leaves exhibited comparatively modest accumulation, reaching only 14 µg/g and 5 µg/g, respectively (Fig. 1).”
§ Kinetic modeling of heavy metal uptake and translocation in Brassica juncea L. for phytoremediation engineering > 3.4.1 Lead (Pb)
“Stems Pb 10.0 ± 0.9 a 12.0 ± 1.1 b 13.0 ± 1.0 bc 14.0 ± 1.3 cd 14.0 ± 1.2 cd 15.0 ± 1.4 d”
Rated minor: it would not touch a result — a value no result rests on, a p-value that stays on the same side of the significance level, or a conflict that is clerical, resolved elsewhere in the paper, or outside its own findings.
In the paper
§ Kinetic modeling of heavy metal uptake and translocation in Brassica juncea L. for phytoremediation engineering > 4 Conclusions
“The consistent metal distribution pattern, roots > stems > leaves, aligns with recognized hyperaccumulator characteristics”
§ Kinetic modeling of heavy metal uptake and translocation in Brassica juncea L. for phytoremediation engineering > 3.4.4 Mercury (Hg)
“Over the 90-day experimental period, root Hg levels showed a slight increase from 6 to 9 µg/g, whereas stems accumulated up to 10 µg/g.”
Citations
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Cited by
Khelil, M. N., & Ghrib, R. (2026) · Water · doi:10.3390/w18080981 · Cited by 1
Argiri, A., Molla, A., Tziouvalekas, M., & Emmanouil, C. (2026) · Toxics · doi:10.3390/toxics14060483 · Cited by 1
do Nascimento, S. A., Silva, E. D. B., Duque, T. S., de Souza, W. C. L., Nunes, A. C., Silva, W. C., Bezerra, I. R. S., & dos Santos, L. L. (2026) · Soil Systems · doi:10.3390/soilsystems10090104
Metadata
- Authors
- Kamal, M. A., & Alali, A. F.
- Affiliations
- King Saud University (SA)
- Corresponding author
- Kamal, Mohab Amin
- Venue
- Discover Environment
- Published
- 2025-12-27
- Volume
- 3
- Issue
- 1
- ISSN
- 2731-9431 (ISSN-L)
- OpenAlex
- W7117362448
- Cited by
- 3
- References
- 31
- Citations by year
- 2026: 3
- FWCI
- 0.61
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by-nc-nd
- creativecommons.org/licenses/by-nc-nd/4.0 (tdm)
- creativecommons.org/licenses/by-nc-nd/4.0 (vor)
- Locations
- Discover Environment (publishedVersion, cc-by-nc-nd)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Ongoing Research Funding program, King Saud University, Riyadh, Saudi Arabia (ORF-2025-910)
- Topics
- Physical Sciences › Environmental Science › Pollution › Heavy metals in environment
- Physical Sciences › Environmental Science › Water Science and Technology › Heavy Metal Pollution Remediation
- Physical Sciences › Environmental Science › Water Science and Technology › Environmental and Analytical Chemistry Studies
- Keywords
- Brassica juncea, phytoremediation, metal translocation, first-order kinetic model, lead, nickel, zinc, mercury, industrial wastewater irrigation, phytostabilization, phytoextraction, bioconcentration factor, translocation factor
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