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<p>This review outlines the combined effects of climate change and heavy metal contamination on soil health and food security, focusing on how these factors increase the bioavailability and toxicity of metals such as cadmium (Cd), lead (Pb), and arsenic (As) in agricultural systems. Climate-related changes in water flow, temperature, and soil chemistry increase metal mobility and disrupt microbial and plant functions, threatening crop yield and safety. Conventional cleanup methods, including phytoremediation and bioremediation, are less effective under climate variability because stress affects plant–microbe interactions and soil conditions fluctuate. New strategies incorporate artificial intelligence (AI) with multi-omics and nanotechnology to understand heavy metal behavior, improve the use of hyperaccumulator plants, and develop resilient plant–microbe partnerships. This review proposes a climate‑adaptive remediation framework that converges AI‑driven causal models with multi‑omics‑informed plant–microbe engineering, explicitly linking molecular mechanistic insights to precision soil detoxification under climate variability. AI-powered models enable precise remediation by combining real-time IoT monitoring with biotechnological solutions, aiding soil detoxification and improving crop resilience. Additionally, targeting metal transporter genes with AI-based genomic selection accelerates breeding for climate-adapted, metal-tolerant crops. Ethical and socioeconomic issues emphasize the importance of fair AI use to avoid worsening disparities in global agritech. This review advocates integrated, climate-smart remediation approaches that combine advanced computational technologies, biotechnology, and sustainable land management to protect soil health and food systems amid growing environmental challenges.</p> Graphical Abstract <p></p>

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AI and Multi-Omics for Climate-Resilient Remediation of Heavy Metal Soil Toxicity

  • 期刊论文

  • 发表日期：

    2026年7月15日

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  • Isma Gul,
  • Muhammad Adil,
  • Siqi Lu,
  • Safdar Bashir,
  • Heli Lu,
  • Muhammad Daud,
  • Younas Iqbal,
  • Yu Tao

摘要

This review outlines the combined effects of climate change and heavy metal contamination on soil health and food security, focusing on how these factors increase the bioavailability and toxicity of metals such as cadmium (Cd), lead (Pb), and arsenic (As) in agricultural systems. Climate-related changes in water flow, temperature, and soil chemistry increase metal mobility and disrupt microbial and plant functions, threatening crop yield and safety. Conventional cleanup methods, including phytoremediation and bioremediation, are less effective under climate variability because stress affects plant–microbe interactions and soil conditions fluctuate. New strategies incorporate artificial intelligence (AI) with multi-omics and nanotechnology to understand heavy metal behavior, improve the use of hyperaccumulator plants, and develop resilient plant–microbe partnerships. This review proposes a climate‑adaptive remediation framework that converges AI‑driven causal models with multi‑omics‑informed plant–microbe engineering, explicitly linking molecular mechanistic insights to precision soil detoxification under climate variability. AI-powered models enable precise remediation by combining real-time IoT monitoring with biotechnological solutions, aiding soil detoxification and improving crop resilience. Additionally, targeting metal transporter genes with AI-based genomic selection accelerates breeding for climate-adapted, metal-tolerant crops. Ethical and socioeconomic issues emphasize the importance of fair AI use to avoid worsening disparities in global agritech. This review advocates integrated, climate-smart remediation approaches that combine advanced computational technologies, biotechnology, and sustainable land management to protect soil health and food systems amid growing environmental challenges.

Graphical Abstract