aceExplainable machine learning-driven targeted modification of biochar and its remediation performance for saline-alkaline soil
Biochar is a low-cost, eco-friendly candidate for saline-alkali soil remediation. Its practical efficacy, however, is constrained by high alkalinity, an underdeveloped pore structure, and limited surface functional sites, all of which conventional modification methods have yet to adequately address. To bridge this gap, this study developed an explainable machine learning prediction system that integrates multi-source data spanning biochar preparation parameters, physicochemical properties, and remediation outcom…
Machine-learning-guided biochar modification cut saline-alkali soil pH from 10.26 to 9.28 in 14 days, while unmodified biochar left it near 10.2.
The modified biochar's SSA and O/C ratio fell outside the model's recommended ranges, so only EC matched the ideal range, and the validation described covers a single 14-day comparison.
Evidence
- Peer-reviewedEnvironmental Research2026-09-28
How should this claim be treated?
Truvace Impact Record TRV-2026-1507, v1: “Explainable machine learning-driven targeted modification of biochar and its remediation performance for saline-alkaline soil.” Truvace, 2026-10-15. /record/TRV-2026-1507 (accessed at citation time). sha256 12d832fce9da6817…
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