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Co-application of biochar and hydroxyapatite suppresses lead accumulation in rice via a soil–plant-microbe cascade

Open access

Abstract

Stabilizing soil lead (Pb) with single amendments often requires a trade-off between immobilization durability and cost-effectiveness, restricting their large-scale use. Here, we demonstrate that co-applying hydroxyapatite (HAP) with either rice straw biochar (RBP) or maize straw biochar (MBP) overcomes these limitations through synergistic soil–plant-microbe interactions. Compared to the un-amended control, the combined treatments reduced CaCl 2 -extractable Pb by 93.2–95.5% and the acid-soluble Pb fraction by 39.4–41.8%. Spectroscopic analyses confirmed the direct binding of Pb to biochar surfaces, while an amendment-induced increase in soil pH further enhanced Pb immobilization. Consequently, this reduced Pb availability in the rhizosphere was associated with diminished iron plaque formation on root surfaces, ultimately decreasing root Pb accumulation. At the subcellular level in leaves, the combined treatments promoted Pb sequestration within vacuoles and reduced the organelle-bound Pb fraction by 16.1–31.9%. This subcellular shift significantly lowered the leaf-to-grain transfer factor by 49.4–54.3%. Furthermore, the combined treatments (RBP) enhanced soil bacterial alpha diversity and shifted community composition; notably, the enrichment of Bacteroidota and suppression of Desulfobacterota suggest their potential contribution to further Pb stabilization. Through these integrated mechanisms, Pb concentrations in brown rice were reduced below Chinese national food safety limits. These findings highlight that the co-application of biochar and HAP provides a cost-effective, multi-barrier strategy to mitigate soil-to-grain Pb transfer, enabling the sustainable utilization of Pb-contaminated paddy soils.

Overview

CoChat Summary

TL;DR

Co-applying hydroxyapatite with rice or maize straw biochar suppressed Pb availability and rice grain accumulation through soil immobilization, reduced root iron plaque, leaf vacuolar sequestration, and shifts in rhizosphere bacteria. In pot trials, combined treatments reduced CaCl2-extractable Pb by 93.2–95.5% and grain Pb to 0.077–0.091 mg/kg, below the 0.2 mg/kg limit.

Key findings

  • Combined RBP and MBP treatments reduced CaCl2-extractable Pb by 93.2–95.5% and the acid-soluble Pb fraction by 39.4–41.8% versus the un-amended control; XANES indicated 32.9% of soil Pb in the biochar-amended treatment was associated with the biochar matrix.
  • Iron plaque DCB-Pb was reduced by the combined treatments; the Results report decreases of 53.46% (RBP) and 61.39% (MBP), while the Discussion reports 61.4% (RBP) and 46.3% (MBP). Root Pb at maturity decreased by 52.6% and 38.4% under RBP and MBP, respectively.
  • Leaf organelle-bound Pb decreased by 16.1–31.9%, and the leaf-to-grain transfer factor decreased by 49.4–54.3%. Brown rice Pb was 0.077 mg/kg (RBP) and 0.091 mg/kg (MBP) versus 0.22 mg/kg in the control; grain yield increased by 62.0–72.6% under combined treatments.
  • RBP increased OTUs by 42.38%, ACE by 46.09%, Chao1 by 43.19%, and Shannon by 6.80%; Bacteroidota increased from 0.12% to 4.97%, while Desulfobacterota decreased from 1.67% to 0.54%.

Methods

  • Pot experiment with six treatments in triplicate: un-amended control (CK), 2.5% rice straw biochar (RB), 2.5% maize straw biochar (MB), 0.6% hydroxyapatite (P), RBP, and MBP. Soil was from a mining-area farmland in Youxi County, Fujian, China, with initial Pb approximately 1699.2 mg/kg; rice cultivar Donglian 5 was sampled at tillering (60 days) and maturity (132 days).
  • Analyses included soil pH, EC, Eh, SOM, N, C/N, CaCl2- and DTPA-extractable Pb, BCR sequential extraction, Pb L3-edge XANES, DCB-extractable Fe/Mn/Pb in iron plaque, tissue Pb by ICP-MS, leaf subcellular Pb fractions, and full-length 16S rRNA PacBio sequencing for CK, RB, P, and RBP at 45 days after flooding. Statistics used one-way ANOVA, Mantel tests, RDA, and Chao1/Shannon/ACE diversity indices.

Limitations

  • Paper-stated: only one rice cultivar was tested; the initial soil Pb concentration (about 1699.2 mg/kg) is representative of severely contaminated mining-area paddy fields but higher than most agricultural soils, limiting direct generalizability. Future work is needed across Pb gradients, multiple cultivars, long-term field conditions, co-contaminants, and fluctuating redox conditions.
  • Paper-stated: microbial sequencing covered only CK, RB, P, and RBP, not MBP; Bacteroidota EPS production, Pb-binding capacity, in situ Pb speciation, sulfur speciation, and sulfide production were not directly measured, so those microbial mechanisms remain correlative or hypothetical.
  • Evident from the text: DCB-Pb reduction magnitudes are inconsistent between the Results and Discussion; the study is a pot experiment with one soil and short-term sampling, which limits field extrapolation.

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Integrity signals

Registry

Crossref · 10.1038/s41598-026-62191-1

Cites

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Statistics

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Figures

Fig. 1 The soil organic matter (a), N content (b), C/N ratio (c), pH (d), EC (e), and Eh (f) of soils at the maturity stage under different amendment treatments. Treatments: CK, un-amended control; RB, 2.5% rice straw biochar; MB, 2.5% corn straw biochar; P, 0.6% hydroxyapatite; RBP, 2.5% rice straw biochar + 0.6% hydroxyapatite; MBP, 2.5% corn straw biochar + 0.6% hydroxyapatite. Black dots represent raw data points for each independent biological replicate ( n = 3), and different letters indicate significant differences among treatments as determined by Duncan's multiple range test ( p < 0.05). ARTICLE IN PRESS
Fig. 1 The soil organic matter (a), N content (b), C/N ratio (c), pH (d), EC (e), and Eh (f) of soils at the maturity stage under different amendment treatments. Treatments: CK, un-amended control; RB, 2.5% rice straw biochar; MB, 2.5% corn straw biochar; P, 0.6% hydroxyapatite; RBP, 2.5% rice straw biochar + 0.6% hydroxyapatite; MBP, 2.5% corn straw biochar + 0.6% hydroxyapatite. Black dots represent raw data points for each independent biological replicate ( n = 3), and different letters indicate significant differences among treatments as determined by Duncan's multiple range test ( p < 0.05). ARTICLE IN PRESSCC-BY-NC-ND · From the PDF
Fig. 2 CaCl2-extractable Pb concentration (mg·kg -1 ) (a) and DTPA-extractable Pb concentration (mg·kg -1 ) (b) in soil at the tillering stage and the maturity stage subjected to different treatments in
Fig. 2 CaCl2-extractable Pb concentration (mg·kg -1 ) (a) and DTPA-extractable Pb concentration (mg·kg -1 ) (b) in soil at the tillering stage and the maturity stage subjected to different treatments inCC-BY-NC-ND · From the PDF
Fig. 3 Concentrations of dithionite-citrate-bicarbonate (DCB)-extractable Fe (a), Mn (b), Pb (c) in iron plaques under different treatments, and the correlation between DCB-extractable Pb and root Pb concentrations (d). Treatments: CK, un-amended control; RB, 2.5% rice straw biochar; MB, 2.5% corn straw biochar; P, 0.6% hydroxyapatite; RBP, 2.5% rice straw biochar + 0.6% hydroxyapatite; MBP, 2.5% corn straw biochar + 0.6% hydroxyapatite. Different letters indicate significant differences among treatments as determined by Duncan's multiple range test ( p < 0.05). 3.4 Pb concentrations in rice tissues and grain yield ARTICLE IN PRESS 一 0 RB
Fig. 3 Concentrations of dithionite-citrate-bicarbonate (DCB)-extractable Fe (a), Mn (b), Pb (c) in iron plaques under different treatments, and the correlation between DCB-extractable Pb and root Pb concentrations (d). Treatments: CK, un-amended control; RB, 2.5% rice straw biochar; MB, 2.5% corn straw biochar; P, 0.6% hydroxyapatite; RBP, 2.5% rice straw biochar + 0.6% hydroxyapatite; MBP, 2.5% corn straw biochar + 0.6% hydroxyapatite. Different letters indicate significant differences among treatments as determined by Duncan's multiple range test ( p < 0.05). 3.4 Pb concentrations in rice tissues and grain yield ARTICLE IN PRESS 一 0 RBCC-BY-NC-ND · From the PDF
Fig. 4 Pb concentrations in rice tissues at the tillering and maturity stages (a-d) and rice grain weight (e). Treatments: CK, un-amended control; RB, 2.5% rice straw biochar; MB, 2.5% corn straw biochar; P, 0.6% hydroxyapatite; RBP, 2.5% rice straw biochar + 0.6% hydroxyapatite; MBP, 2.5% corn straw biochar + 0.6% hydroxyapatite. Black dots represent raw data points for each
Fig. 4 Pb concentrations in rice tissues at the tillering and maturity stages (a-d) and rice grain weight (e). Treatments: CK, un-amended control; RB, 2.5% rice straw biochar; MB, 2.5% corn straw biochar; P, 0.6% hydroxyapatite; RBP, 2.5% rice straw biochar + 0.6% hydroxyapatite; MBP, 2.5% corn straw biochar + 0.6% hydroxyapatite. Black dots represent raw data points for eachCC-BY-NC-ND · From the PDF
Fig. 5 Bacterial alpha diversity indices (a-d) and dominant community composition at the phylum (e) and family (f) levels. Treatments: CK, un-amended control; RB, 2.5% rice straw biochar; P, 0.6% hydroxyapatite; RBP, 2.5% rice straw biochar + 0.6% hydroxyapatite. Different letters indicate significant differences among treatments as determined by Duncan's multiple range test ( p < 0.05). ARTICLE IN PRESS 0.2 0.0
Fig. 5 Bacterial alpha diversity indices (a-d) and dominant community composition at the phylum (e) and family (f) levels. Treatments: CK, un-amended control; RB, 2.5% rice straw biochar; P, 0.6% hydroxyapatite; RBP, 2.5% rice straw biochar + 0.6% hydroxyapatite. Different letters indicate significant differences among treatments as determined by Duncan's multiple range test ( p < 0.05). ARTICLE IN PRESS 0.2 0.0CC-BY-NC-ND · From the PDF
Fig. 6 Relationships between bacterial communities and environmental factors. (a) Correlations between bacterial composition, diversity, and environmental factors. Line width represents the magnitude of partial Mantel's r statistic, and line color denotes statistical significance (orange, p < 0.001; blue, 0.001 ≤ p < 0.01; green, 0.01 ≤ p < 0.05; grey, p ≥ 0.05). All p-values were adjusted for multiple comparisons using the Bonferroni-Holm method. (b) Heatmap of Spearman correlations between environmental factors and individual bacterial phyla. (c) Redundancy analysis (RDA) of bacterial communities and environmental factors.
Fig. 6 Relationships between bacterial communities and environmental factors. (a) Correlations between bacterial composition, diversity, and environmental factors. Line width represents the magnitude of partial Mantel's r statistic, and line color denotes statistical significance (orange, p < 0.001; blue, 0.001 ≤ p < 0.01; green, 0.01 ≤ p < 0.05; grey, p ≥ 0.05). All p-values were adjusted for multiple comparisons using the Bonferroni-Holm method. (b) Heatmap of Spearman correlations between environmental factors and individual bacterial phyla. (c) Redundancy analysis (RDA) of bacterial communities and environmental factors.CC-BY-NC-ND · From the PDF

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  1. Li, H. . et al. Antagonistic effects of exogenous zinc on uptake and accumulation of cadmium in various rice organs. Acta Sci. Circumst. 38, 4854–4863. https://doi.org/10.13671/j.hjkxxb.2018.0356 (2018). · doi:10.13671/j.hjkxxb.2018.0356

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Metadata

Authors
Li, H., Khaliq, M. A., Long, J., Wang, G., & Li, Z.
Affiliations
  • Fujian Agriculture and Forestry University (CN)
  • Minnan Normal University (CN)
  • Fujian Academy of Agricultural Sciences (CN)
Corresponding author
  • Wang, Guo
  • Li, Zhou
Venue
Scientific Reports
Published
2026-07-14
Volume
16
Issue
1
ISSN
2045-2322 (ISSN-L)
OpenAlex
W7168253562
Cited by
0
References
67
FWCI
0.00
Type
journal article
Language
en
Open access
Licence
Locations
  • Scientific Reports (publishedVersion, cc-by-nc-nd)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
Funders
  • Natural Science Foundation of Fujian Province (2025J01984, 2023J01373)
  • Natural Science Foundation of Zhangzhou City (ZZ2023J12)
Topics
  • Physical Sciences › Environmental Science › Pollution › Heavy metals in environment
  • Physical Sciences › Environmental Science › Water Science and Technology › Adsorption and biosorption for pollutant removal
  • Physical Sciences › Environmental Science › Health, Toxicology and Mutagenesis › Chromium effects and bioremediation
Keywords
lead immobilization, biochar, hydroxyapatite, rice, plant-soil-microbe interactions, iron plaque, soil bacterial communities, paddy soil remediation, lead-contaminated soil, straw biochar, transfer factor, food safety

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CoChat. (2026). Citation check: Co-application of biochar and hydroxyapatite suppresses lead accumulation in rice via a soil–plant-microbe cascade. https://app.cochat.ai/papers/10.1038/s41598-026-62191-1
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Li, H., Khaliq, M. A., Long, J., Wang, G., & Li, Z. (2026). Co-application of biochar and hydroxyapatite suppresses lead accumulation in rice via a soil–plant-microbe cascade. Scientific Reports. https://doi.org/10.1038/s41598-026-62191-1

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