Next Article in Journal
Nitrogen Additions Suppress Microbial Diversity but Enhance Carbon Accumulation in Desert Soil Profiles
Previous Article in Journal
Biochar Mitigates Root Exudate-Induced Priming of Native SOC Decomposition via Soil Phosphorus Availability and Microbial Structure
Previous Article in Special Issue
Cadmium Accumulation in Maize Grains in Chongqing: Key Limiting Soil Factors and Nonlinear Thresholds Identified by Random Forest–SHAP Models
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Editorial

From Agricultural Soils to Human Health: Heavy Metal Sources, Biogeochemical Controls, Crop Accumulation, and Risk Assessment

1
Co-Innovation Center for the Sustainable Forestry in Southern China, College of Ecology and Environment, Nanjing Forestry University, Nanjing 210037, China
2
College of Resources and Environmental Sciences, Nanjing Agricultural University, Nanjing 210095, China
*
Author to whom correspondence should be addressed.
Agriculture 2026, 16(11), 1249; https://doi.org/10.3390/agriculture16111249
Submission received: 1 June 2026 / Accepted: 3 June 2026 / Published: 5 June 2026
Heavy metals and metalloids (denoted as “HMs”) in agricultural soils remain a persistent concern for sustainable agriculture, food safety, ecosystem functioning, and human health [1,2]. Their effects are not uniformly adverse. Elements such as Cu, Zn, and Fe are essential micronutrients involved in plant growth, tissue metabolism, and human physiological functions [3]. However, toxic elements such as Cd, Pb, As, Hg, and Cr can pose serious risks to crop production and human health when their concentrations, mobility, or bioavailability exceed safe levels [4]. Compared with many organic pollutants, HMs are non-degradable and can be retained in agricultural soils for long periods, thereby posing sustained risks to crop safety and human health [5]. Once introduced into agricultural soils through parent material weathering, mining and smelting, atmospheric deposition, wastewater irrigation, fertilizers, pesticides, livestock manure, sludge-derived products, or other anthropogenic inputs, they may remain active in soil–plant systems for long periods and enter the human body through dietary and non-dietary exposure pathways [6,7,8,9].
This Special Issue, titled “From Agricultural Soils to Human Health: Exposure Sources, Intake Pathways, and Accumulation of Heavy Metals,” was established to promote integrated research on HM pollution in agricultural soils and its implications for human health. The topic requires more than the measurement of total soil concentrations. It demands a chain-based understanding that links exposure sources, biogeochemical control, soil mobility, crop uptake, dietary intake, non-dietary exposure, human accumulation, health risk assessment, and management strategies. This Special Issue ultimately collected six contributions, including one review article and five research articles. Together, these papers address paddy soil mechanisms, upland crop accumulation, regional source apportionment, ecological and human health risks, soil biological responses, and the safe use of waste-derived amendments.
A key contribution of this Special Issue is the emphasis on biogeochemical control as the mechanistic basis for understanding HM behavior in agricultural soils. In paddy ecosystems, alternating flooding and drainage events create pronounced redox gradients that place electron transfer at the core of HM transformation, mobilization, and bioavailability regulation [10,11,12,13]. Cao et al. reviewed electron transfer-mediated HM bioavailability, rice accumulation, and mitigation in paddy ecosystems [14]. The review summarized the roles of microbial extracellular electron transfer, Fe/Mn/S redox cycling, organic matter-mediated electron shuttling, and rice root-associated electron exchange in regulating HM transformation and bioavailability. This perspective is important because many critical processes in paddy soils, including As valence transformation [15,16], Fe oxide reduction [17,18], Cd release or immobilization [19,20,21,22], Cr reduction [23], iron plaque formation [24,25], and rice uptake [4], are closely related to electron transfer. By placing electron transfer at the center of paddy soil HM biogeochemistry, the review provides a coherent framework for understanding why metal mobility and crop accumulation can change markedly with water management, organic matter inputs, mineral transformations, microbial activity, and rhizosphere processes. It also highlights the need to develop mitigation strategies that explicitly consider redox dynamics and electron-transfer pathways rather than relying only on static soil properties.
This Special Issue also includes studies that connect soil contamination with regional ecological and human health risks. Wen et al. investigated HM pollution and associated health risks in agricultural soils from Zhenjiang and Yangzhou, China [26]. Based on high-density sampling at 449 sites in the core area of the Yangtze River Delta, the study showed that although As and Cd concentrations remained below national Risk Intervention Values, Cd exceeded the national background value, and the potential ecological risk index indicated very high ecological risk at many sites, mainly driven by Hg and Cd. The authors further applied Monte Carlo simulations to assess health risks for adults and children. Their results showed generally acceptable non-carcinogenic risks but elevated carcinogenic risks, especially those associated with As. This work demonstrates that compliance with national concentration-based intervention values does not necessarily mean that regional ecological or health risks are negligible [27,28,29,30]. In densely populated and intensively cultivated agricultural regions, probabilistic risk assessment can better incorporate uncertainty, exposure variability, and population-specific vulnerability, thereby supporting more refined local soil management and food safety policies [31,32].
Source identification is an essential step from risk recognition to risk control. Wei et al. integrated geospatial analysis, source apportionment, ecological risk assessment, and health risk assessment for topsoil HMs in a typical agricultural area [33]. The study analyzed Zn, Cr, Ni, Pb, Cu, As, Cd, and Hg in 153 topsoil samples. Although the overall pollution level was classified as no or slight contamination, Cd was the only element exceeding its background level. Using positive matrix factorization, the authors identified three main sources: natural sources, coal burning and waste disposal, and agricultural activities. The health risk assessment further showed that children faced higher risks than adults, with As and Cr being important contributors to non-carcinogenic and carcinogenic risks, respectively. The study illustrates the importance of distinguishing between geogenic background, agricultural inputs, industrial emissions, coal combustion, waste disposal, and other sources. Such source-oriented information is indispensable because different sources require different prevention and control measures. For example, risks derived mainly from a natural background may require crop selection and soil management, whereas risks related to anthropogenic inputs require source reduction and regulatory intervention [34,35,36].
Crop accumulation is the most direct bridge between agricultural soil contamination and dietary exposure. Zhang et al. investigated Cd accumulation in maize grains in Chongqing, China, using 499 paired soil–maize samples [37]. The study showed that the average Cd concentration in maize grains was 0.03 mg kg−1, with 9.6% of samples exceeding the Chinese National Standard, indicating a potential food safety risk. By combining Random Forest and SHAP approaches, the authors identified soil available Cd as the core factor controlling maize grain Cd accumulation. Soil pH, cation exchange capacity, and total phosphorus also influenced grain Cd mainly by regulating Cd availability. More importantly, the study identified nonlinear thresholds for available Cd, pH, CEC, and total phosphorus. The work advances the study of soil–crop HM transfer from a simple linear correlation toward interpretable and threshold-based modeling [38,39]. Such models are valuable for upland soils because they can help define risk zoning, amendment targets, and safe production thresholds for dryland crops such as maize [38,39].
In addition to chemical mobility and crop accumulation, HMs also affect soil biological processes. Wu et al. examined Cd-induced hormesis in soil enzyme activity, focusing on the relative importance of enzymatic reaction kinetics and microbial communities [40]. The authors investigated urease, denitrification enzyme, dehydrogenase, and alkaline phosphatase activities under low-dose Cd exposure. Their results showed hormetic responses in all four soil enzymes after 24 h of exposure; Cd did not significantly change microbial community diversity, but it inhibited the capacity of soil microbial communities to secrete extracellular enzymes, reduced the soil enzyme pool, and altered overall enzyme activities. The study provides an important biological perspective on HM risk. It indicates that the ecological effects of Cd are not always expressed as simple linear inhibition. Instead, soil biological systems may show dynamic dose–response patterns involving enzyme kinetics, extracellular enzyme secretion, and microbial functional regulation [41,42,43]. Such biological mechanisms are essential for interpreting early warning signals and improving ecological risk assessment in agricultural soils.
Management of HM risks in agricultural systems must also consider soil fertility, crop production, and the safety of agricultural inputs. Ji et al. investigated artificial humic acids derived from municipal sludge and their effects on rice growth, soil fertility, and dissolved organic matter using multi-chamber root box experiments [44]. The study showed that artificial humic acids promoted rice shoot and root biomass, improved nutrient distribution in different rhizosphere zones, limited soil pH decline, reduced electrical conductivity, increased dissolved organic carbon in the root zone, and promoted dissolved organic matter humification in near- and far-rhizosphere soils. Importantly, HM concentrations in rice remained within safe limits. This research suggests that properly treated sludge-derived artificial humic acids may have potential as green liquid organic fertilizers. At the same time, it emphasizes that waste-derived amendments must be evaluated comprehensively. Their agronomic benefits should be considered together with their effects on dissolved organic matter, rhizosphere chemistry, HM mobility, crop accumulation, and potential human exposure [45,46].
Taken together, the papers in this Special Issue reflect a clear transition in the field. First, research on HMs in agricultural soils is moving from total concentration-based assessment toward process-based understanding. Soil pH, redox conditions, mineral transformations, organic matter reactivity, microbial activity, root processes, and electron transfer collectively determine whether HMs remain immobilized or become bioavailable [47]. Second, regional assessment is moving from deterministic evaluation toward probabilistic and population-sensitive risk assessment. Monte Carlo simulations, spatial analysis, and source apportionment can provide more realistic information for regional management than single-value risk estimates [48]. Third, crop accumulation studies are increasingly using paired soil–crop datasets, nonlinear modeling, and interpretable machine learning to identify the actual soil factors and thresholds controlling food safety risks [49]. Fourth, ecological assessment is expanding from chemical indicators to biological mechanisms, including enzyme activity, microbial function, and hormetic responses [50]. Finally, management strategies are becoming more integrated, linking soil remediation, safe utilization, waste recycling, and crop safety.
Despite these advances, important knowledge gaps remain. One major gap is the incomplete connection between soil contamination and actual human intake. Many studies still assess health risks primarily from soil concentrations and standard exposure parameters, whereas fewer studies integrate soil–crop transfer, dietary consumption, non-dietary exposure, contaminant bioaccessibility, food processing, and human accumulation. Future studies should strengthen paired investigations of soil, crops, food intake, and human exposure, especially in regions where local populations consume crops produced from contaminated farmland. Another gap concerns multi-element interactions. Agricultural soils often contain Cd, As, Pb, Hg, Cr, Cu, Zn, and Ni simultaneously. However, management strategies designed for one element may unintentionally increase the mobility or uptake of another. This issue is particularly important in paddy soils, where water management may reduce Cd uptake while increasing As mobility, or vice versa [51]. Therefore, future risk assessment and mitigation strategies should explicitly consider multi-metal trade-offs.
Future research should further integrate mechanistic tools and decision-oriented models. Techniques such as synchrotron-based spectroscopy, isotope tracing, diffusive gradients in thin films, rhizosphere imaging, electrochemical monitoring, microbial multi-omics, and high-resolution spatial mapping can provide direct evidence of metal speciation, mobility, and bioavailability. At the same time, interpretable machine learning, uncertainty analysis, and process-based models can help translate complex mechanisms into practical thresholds, risk maps, and management options. For paddy soils, electron transfer-based regulation may provide new opportunities for controlling HM bioavailability and rice accumulation. For upland soils, identifying key soil thresholds and crop-specific accumulation mechanisms may support safe production of maize, vegetables, and other crops. Across both systems, risk-based management should combine source reduction, water and fertilizer regulation, soil amendments, crop variety selection, safe recycling of organic wastes, and long-term monitoring.
In conclusion, this Special Issue provides an interdisciplinary collection of studies addressing HM pollution in agricultural soils and its implications for crop safety, ecological function, and human health. The six contributions collectively cover exposure sources, biogeochemical control, paddy soil processes, upland soil–crop transfer, biological mechanisms, health risk assessment, and management strategies. They demonstrate that the pathway from agricultural soils to human health is not linear but is instead shaped by interactions among sources, soil processes, crop uptake, exposure routes, and population vulnerability. We hope that this Special Issue will stimulate further research linking soil science, environmental chemistry, agronomy, microbiology, food safety, exposure science, and public health and will contribute to more precise, sustainable, and health-oriented strategies for controlling HM risks in agricultural systems.

Author Contributions

Conceptualization, H.H. and M.L.; writing—original draft preparation, M.L.; writing—review and editing, H.H. and H.G.; supervision, H.H. All authors have read and agreed to the published version of the manuscript.

Funding

This material is based upon work that is supported by the National Natural Science Foundation of China (grant no. 42307025) and the Jiangsu Provincial Natural Science Foundation (BK20220433).

Acknowledgments

We sincerely thank all authors who contributed their work to this Special Issue. We are also grateful to the reviewers for their constructive comments and valuable suggestions and to the editorial staff of Agriculture for their professional support throughout the editorial process.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Gu, Y.; Zhai, Z.-Q.; Kopittke, P.M.; Zhao, F.-J.; Wang, P. Gene-diet interaction amplifies toxic cadmium and lead burdens in Asian populations. Innov. 2026; in press. [CrossRef]
  2. Zhao, F.-J.; Ma, Y.-B.; Zhu, Y.-G.; Tang, Z.; McGrath, S.-P. Soil Contamination in China: Current Status and Mitigation Strategies. Environ. Sci. Technol. 2015, 49, 750–759. [Google Scholar] [PubMed]
  3. Lilay, G.H.; Thiébaut, N.; du Mee, D.; Assunção, A.G.L.; Schjoerring, J.K.; Husted, S.; Persson, D.P. Linking the key physiological functions of essential micronutrients to their deficiency symptoms in plants. New Phytol. 2024, 242, 881–902. [Google Scholar] [CrossRef] [PubMed]
  4. Zhao, F.-J.; Wang, P. Arsenic and cadmium accumulation in rice and mitigation strategies. Plant Soil 2020, 446, 1–21. [Google Scholar]
  5. Zhao, D.; Wang, P.; Zhao, F.-J. Dietary cadmium exposure, risks to human health and mitigation strategies. Crit. Rev. Environ. Sci. Technol. 2022, 53, 939–963. [Google Scholar] [CrossRef]
  6. Chen, H.-Y.; Teng, Y.-G.; Lu, S.-J.; Wang, Y.-Y.; Wang, J.-S. Contamination features and health risk of soil heavy metals in China. Sci. Total Environ. 2015, 512–513, 143–153. [Google Scholar] [CrossRef]
  7. Li, H.-B.; Chen, K.; Juhasz, A.L.; Huang, L.; Ma, L.Q. Childhood lead exposure in an industrial town in China: Coupling stable isotope ratios with bioaccessible lead. Environ. Sci. Technol. 2015, 49, 5080–5087. [Google Scholar] [CrossRef]
  8. Planer-Friedrich, B.; Härtig, C.; Lohmayer, R.; Suess, E.; McCann, S.H.; Oremland, R. Anaerobic Chemolithotrophic Growth of the Haloalkaliphilic Bacterium Strain MLMS-1 by Disproportionation of Monothioarsenate. Environ. Sci. Technol. 2015, 49, 6554–6563. [Google Scholar] [CrossRef]
  9. Chen, H.-P.; Yang, X.-P.; Wang, P.; Wang, Z.-X.; Li, M.; Zhao, F.-J. Dietary cadmium intake from rice and vegetables and potential health risk: A case study in Xiangtan, southern China. Sci. Total Environ. 2018, 639, 271–277. [Google Scholar] [CrossRef]
  10. Chen, N.; Fu, Q.-L.; Wu, T.-L.; Cui, P.-X.; Fang, G.-D.; Liu, C.; Chen, C.-M.; Liu, G.-X.; Wang, W.-C.; Wang, D.-X.; et al. Active Iron Phases Regulate the Abiotic Transformation of Organic Carbon during Redox Fluctuation Cycles of Paddy Soil. Environ. Sci. Technol. 2021, 55, 14281–14293. [Google Scholar] [CrossRef]
  11. Cheng, D.; Yuan, S.-H.; Liao, P.; Zhang, P. Oxidizing Impact Induced by Mackinawite (FeS) Nanoparticles at Oxic Conditions due to Production of Hydroxyl Radicals. Environ. Sci. Technol. 2016, 50, 11646–11653. [Google Scholar] [CrossRef]
  12. Fan, K.-Q.; Lin, C.-X.; Li, L.-L.; Huang, Q.-X.; Dai, J.; Wang, P.; Qin, J.-H.; Lim, J.W.; Qiu, R.-L. Rainwater-Derived Reactive Oxygen Species Diminish Environmental Risk from Arsenic in Paddy Rice Systems. Environ. Sci. Technol. 2025, 59, 7530–7540. [Google Scholar] [CrossRef]
  13. Zhang, X.-W.; Huang, H.; Zhu, Y.-P.; Chen, M.-M.; Lu, H.-Y.; Zhu, C.-Y.; Han, J.-G.; Zhao, F.-J.; Wang, P. Near-Surface Hydroxyl Radical Hotspots Mobilize Cadmium and Immobilize Arsenic during Paddy Soil Drainage. Environ. Sci. Technol. 2025, 59, 24035–24043. [Google Scholar] [CrossRef]
  14. Cao, Z.-X.; Tian, Z.-Q.; Guan, H.; Lv, Y.-W.; Zhang, S.-N.; Song, T.; Wu, G.-Y.; Zhu, F.-Y.; Huang, H. Electron Transfer-Mediated Heavy Metal(loid) Bioavailability, Rice Accumulation, and Mitigation in Paddy Ecosystems: A Critical Review. Agriculture 2026, 16, 202. [Google Scholar] [CrossRef]
  15. Chi, J.-L.; Liu, K.; Wu, S.-Y.; Zhang, W.-J.; Shi, Q.-T.; Fang, L.-P.; Li, F.-B. Dual-Ligand-Driven Dark Reactive Oxygen Species Generation on Iron Oxyhydroxides: Implications for Environmental Remediation. Environ. Sci. Technol. 2024, 58, 20751–20760. [Google Scholar] [CrossRef] [PubMed]
  16. Hong, Z.-B.; Li, F.-B.; Borch, T.; Shi, Q.-T.; Fang, L.-P. Incorporation of Cu into Goethite Stimulates Oxygen Activation by Surface-Bound Fe (II) for Enhanced As (III) Oxidative Transformation. Environ. Sci. Technol. 2023, 57, 2162–2174. [Google Scholar] [CrossRef] [PubMed]
  17. Fulda, B.; Voegelin, A.; Kretzschmar, R. Redox-Controlled Changes in Cadmium Solubility and Solid-Phase Speciation in a Paddy Soil As Affected by Reducible Sulfate and Copper. Environ. Sci. Technol. 2013, 47, 12775–12783. [Google Scholar] [CrossRef] [PubMed]
  18. Weber, F.-A.; Voegelin, A.; Kaegi, R.; Kretzschmar, R. Contaminant mobilization by metallic copper and metal sulphide colloids in flooded soil. Nat. Geosci. 2009, 2, 267–271. [Google Scholar] [CrossRef]
  19. Furuya, M.; Hashimoto, Y.; Yamaguchi, N. Time-Course Changes in Speciation and Solubility of Cadmium in Reduced and Oxidized Paddy Soils. Soil Sci. Soc. Am. J. 2016, 80, 870–877. [Google Scholar] [CrossRef]
  20. Hashimoto, Y.; Furuya, M.; Yamaguchi, N.; Makino, T. Zerovalent iron with high sulfur content enhances the formation of cadmium sulfide in reduced paddy soils. Soil Sci. Soc. Am. J. 2016, 80, 55–63. [Google Scholar] [CrossRef]
  21. Huang, H.; Chen, H.-P.; Kopittke, P.-M.; Kretzschmar, R.; Zhao, F.-J.; Wang, P. The Voltaic Effect as a Novel Mechanism Controlling the Remobilization of Cadmium in Paddy Soils during Drainage. Environ. Sci. Technol. 2021, 55, 1750–1758. [Google Scholar] [CrossRef]
  22. Huang, H.; Ji, X.-B.; Cheng, L.-Y.; Zhao, F.-J.; Wang, P. Free Radicals Produced from the Oxidation of Ferrous Sulfides Promote the Remobilization of Cadmium in Paddy Soils During Drainage. Environ. Sci. Technol. 2021, 55, 9845–9853. [Google Scholar] [CrossRef]
  23. Zulfiqar, U.; Haider, F.U.; Ahmad, M.; Hussain, S.; Maqsood, M.F.; Ishfaq, M.; Shahzad, B.; Waqas, M.M.; Ali, B.; Tayyab, M.N.; et al. Chromium toxicity, speciation, and remediation strategies in soil-plant interface: A critical review. Front. Plant Sci. 2023, 13, 1081624. [Google Scholar] [CrossRef] [PubMed]
  24. Liu, W.-J.; Zhu, Y.-G.; Hu, Y.; Williams, P.-N.; Gault, A.-G.; Meharg, A.A.; Charnock, J.-M.; Smith, F.-A. Arsenic sequestration in iron plaque, its accumulation and speciation in mature rice plants (Oryza sativa L.). Environ. Sci. Technol. 2006, 40, 5730–5736. [Google Scholar] [CrossRef] [PubMed]
  25. Meng, F.-L.; Zhang, X.; Hu, Y.; Sheng, G.-P. New Barrier Role of Iron Plaque: Producing Interfacial Hydroxyl Radicals to Degrade Rhizosphere Pollutants. Environ. Sci. Technol. 2024, 58, 795–804. [Google Scholar] [CrossRef]
  26. Wen, Y.-B.; Wang, Y.-Y.; Ji, W.-B.; Wu, S.-M.; Gong, Y.; Meng, X.-Q. Pollution Levels and Associated Health Risks of Heavy Metals in Agricultural Soils in Zhenjiang and Yangzhou, China. Agriculture 2025, 15, 2552. [Google Scholar] [CrossRef]
  27. Huang, Y.; Chen, Q.-Q.; Deng, M.-H.; Japenga, J.; Li, T.-Q.; Yang, X.-E.; He, Z.-L. Heavy metal pollution and health risk assessment of agricultural soils in a typical peri-urban area in southeast China. J. Environ. Manag. 2018, 207, 159–168. [Google Scholar] [CrossRef] [PubMed]
  28. Tóth, G.; Hermann, T.; Da Silva, M.R.; Montanarella, L. Heavy metals in agricultural soils of the European Union with implications for food safety. Environ. Int. 2016, 88, 299–309. [Google Scholar] [CrossRef]
  29. Wen, Y.-B.; Wang, Y.-Y.; Ji, W.-B.; Wei, N.; Liao, Q.-L.; Huang, D.-L.; Meng, X.-Q.; Song, Y.-X. Influencing Factors of Elevated Levels of Potentially Toxic Elements in Agricultural Soils from Typical Karst Regions of China. Agronomy 2023, 13, 2230. [Google Scholar] [CrossRef]
  30. Yang, Y.-J.; Wang, Y.-N.; Chen, C.-L.; Luo, M.-X.; Huo, Z.-T.; Wu, F.; Fu, J.-H. Integrating heavy metal concentration and slope gradient for ecological risk assessment in mountainous regions: Insights from China’s Dabie Mountain region. Environ. Res. 2025, 285, 122744. [Google Scholar] [CrossRef]
  31. Wang, H.-D.; Liu, Y.-J.; Feng, S.-S.; Fu, J.; Li, Y. Probabilistic Risk Assessment of Soil Heavy Metals in an Agate Industry Concentration Area Based on Different Sources. Int. J. Environ. Res. 2026, 20, 152. [Google Scholar] [CrossRef]
  32. Wei, A.-N.; Jia, J.; Chang, P.-Y.; Wang, S.-L. Probabilistic risk assessment and source identification of heavy metals in soil-rice systems in northern area of Fujian Province, China. Ecol. Indic. 2025, 174, 113504. [Google Scholar] [CrossRef]
  33. Wei, D.-H.; Yang, S.-M.; Li, H.-D.; Luo, M.; Wang, Y.; Wang, Y.-S.; Zhang, Y.-H.; Wang, B. Geospatial Analysis, Source Apportionment, and Ecological–Health Risks Assessment of Topsoil Heavy Metal(loid)s in a Typical Agricultural Area. Agriculture 2025, 15, 913. [Google Scholar] [CrossRef]
  34. Cheng, S.-P. Heavy metal pollution in China: Origin, pattern and control. Environ. Sci. Pollut. Res. 2003, 10, 192–198. [Google Scholar] [CrossRef]
  35. Hanfi, M.Y.; Mostafa, M.Y.A.; Zhukovsky, M.V. Heavy metal contamination in urban surface sediments: Sources, distribution, contamination control, and remediation. Environ. Monit. Assess. 2019, 192, 32. [Google Scholar] [CrossRef]
  36. Kumar, A.; Kumar, V.; Thakur, M.; Singh, K.; Jasrotia, R.; Kumar, R.; Radziemska, M. Global Perspectives on Lead Contamination and Health Risks in Surface Water, Rice Grains, and Soils. Land Degrad. Dev. 2025, 36, 2159–2169. [Google Scholar] [CrossRef]
  37. Zhang, Y.; Mu, Z.-J.; Jiang, Z.-M.; Wei, S.-Q. Cadmium Accumulation in Maize Grains in Chongqing: Key Limiting Soil Factors and Nonlinear Thresholds Identified by Random Forest–SHAP Models. Agriculture 2026, 16, 839. [Google Scholar] [CrossRef]
  38. Lü, Q.-X.; Tang, Z.-X.; Tang, Z.; Dong, G.; Xu, Z.-R.; Zhao, F.-J.; Wang, P. Interpretable machine learning models to predict cadmium in wheat for safe production and soil management. Fundam. Res. 2025; in press.
  39. Lu, X.-S.; Sun, L.; Zhang, Y.; Du, J.-Y.; Wang, G.-Q.; Huang, X.-H.; Li, X.-Z.; Wang, X.-Z. Predicting Cd accumulation in crops and identifying nonlinear effects of multiple environmental factors based on machine learning models. Sci. Total Environ. 2024, 951, 175787. [Google Scholar] [CrossRef] [PubMed]
  40. Wu, J.-Y.; Wu, Z.-W.; Agathokleous, E.; Zhu, Y.-L.; Fan, D.-W.; Han, J.-G. Unveiling a New Perspective on Cadmium-Induced Hormesis in Soil Enzyme Activity: The Relative Importance of Enzymatic Reaction Kinetics and Microbial Communities. Agriculture 2024, 14, 904. [Google Scholar] [CrossRef]
  41. Fan, D.-W.; Wang, S.-Y.; Guo, Y.-H.; Liu, J.; Agathokleous, E.; Zhu, Y.-L.; Han, J.-G. The role of bacterial communities in shaping Cd-induced hormesis in ‘living’ soil as a function of land-use change. J. Hazard. Mater. 2021, 409, 124996. [Google Scholar] [CrossRef] [PubMed]
  42. Niemeyer, J.C.; Lolata, G.B.; de Carvalho, G.M.; Da Silva, E.M.; Sousa, J.P.; Nogueira, M.A. Microbial indicators of soil health as tools for ecological risk assessment of a metal contaminated site in Brazil. Appl. Soil Ecol. 2012, 59, 96–105. [Google Scholar] [CrossRef]
  43. Wang, Y.-P.; Shi, J.-Y.; Wang, H.; Lin, Q.; Chen, X.-C.; Chen, Y.-X. The influence of soil heavy metals pollution on soil microbial biomass, enzyme activity, and community composition near a copper smelter. Ecotoxicol. Environ. Saf. 2007, 67, 75–81. [Google Scholar] [CrossRef] [PubMed]
  44. Ji, R.-T.; Liu, C.-W.; Xu, Q.-J.; Zhang, Y.; Chen, M.; Zhang, L.-J.; Hu, F.-L. Effect of Artificial Humic Acids Derived from Municipal Sludge on Plant Growth, Soil Fertility, and Dissolved Organic Matter. Agriculture 2024, 14, 1946. [Google Scholar] [CrossRef]
  45. Smith, S.R. A critical review of the bioavailability and impacts of heavy metals in municipal solid waste composts compared to sewage sludge. Environ. Int. 2009, 35, 142–156. [Google Scholar] [CrossRef] [PubMed]
  46. Yang, F.; Tang, C.-Y.; Antonietti, M. Natural and artificial humic substances to manage minerals, ions, water, and soil microorganisms. Chem. Soc. Rev. 2021, 50, 6221–6239. [Google Scholar] [CrossRef]
  47. Hou, D.-Y.; O’Connor, D.; Igalavithana, A.D.; Alessi, D.S.; Luo, J.; Tsang, D.C.W.; Sparks, D.L.; Yamauchi, Y.; Rinklebe, J.; Ok, Y.S. Metal contamination and bioremediation of agricultural soils for food safety and sustainability. Nat. Rev. Earth Environ. 2020, 1, 366–381. [Google Scholar] [CrossRef]
  48. Yuan, B.; Cao, H.-L.; Du, P.; Ren, J.; Chen, J.; Zhang, H.; Zhang, Y.-H.; Luo, H.-L. Source-oriented probabilistic health risk assessment of soil potentially toxic elements in a typical mining city. J. Hazard. Mater. 2023, 443, 130222. [Google Scholar] [CrossRef]
  49. Hu, B.-F.; Xue, J.; Zhou, Y.; Shao, S.; Fu, Z.-Y.; Li, Y.; Chen, S.-C.; Qi, L.; Shi, Z. Modelling bioaccumulation of heavy metals in soil-crop ecosystems and identifying its controlling factors using machine learning. Environ. Pollut. 2020, 262, 114308. [Google Scholar] [CrossRef]
  50. Tang, B.; Xu, H.-P.; Song, F.-M.; Ge, H.-G.; Yue, S.-Y. Effects of heavy metals on microorganisms and enzymes in soils of lead–zinc tailing ponds. Environ. Res. 2022, 207, 112174. [Google Scholar] [CrossRef]
  51. Honma, T.; Ohba, H.; Kaneko-Kadokura, A.; Makino, T.; Nakamura, K.; Katou, H. Optimal soil Eh, pH, and water management for simultaneously minimizing arsenic and cadmium concentrations in rice grains. Environ. Sci. Technol. 2016, 50, 4178–4185. [Google Scholar] [CrossRef]
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Liang, M.; Guan, H.; Huang, H. From Agricultural Soils to Human Health: Heavy Metal Sources, Biogeochemical Controls, Crop Accumulation, and Risk Assessment. Agriculture 2026, 16, 1249. https://doi.org/10.3390/agriculture16111249

AMA Style

Liang M, Guan H, Huang H. From Agricultural Soils to Human Health: Heavy Metal Sources, Biogeochemical Controls, Crop Accumulation, and Risk Assessment. Agriculture. 2026; 16(11):1249. https://doi.org/10.3390/agriculture16111249

Chicago/Turabian Style

Liang, Min, Hui Guan, and Hui Huang. 2026. "From Agricultural Soils to Human Health: Heavy Metal Sources, Biogeochemical Controls, Crop Accumulation, and Risk Assessment" Agriculture 16, no. 11: 1249. https://doi.org/10.3390/agriculture16111249

APA Style

Liang, M., Guan, H., & Huang, H. (2026). From Agricultural Soils to Human Health: Heavy Metal Sources, Biogeochemical Controls, Crop Accumulation, and Risk Assessment. Agriculture, 16(11), 1249. https://doi.org/10.3390/agriculture16111249

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop