Optimization of native plant selection for phytomining of strategic/critical raw materials using Artificial Bee Colony algorithm

The concentration range (lowest to highest value) was between 0.01 (for La) and 3,910 mg/kg_dw for the studied plants. Principal component analysis (PCA) corroborated these findings, explaining cumulative variances of 80.4% (MT), 89.4% (CD), and 76.4% (JS). The innovation of this study lies in the application of the ABC algorithm to the field of phytomining, which offers a more dynamic and flexible alternative to traditional regression-based models.

The primary advantage of this proposed method is its superior global search capability and ability to handle multi-elemental interactions with high predictive accuracy. However, a potential disadvantage remains the computational complexity and the requirement for fine-tuning control parameters to ensure consistent convergence. Overall, MT is identified as a highly promising candidate for the phytomining of SCRMs, with Mg emerging as the most effectively accumulated element under the optimized ABC model.</p> <p>This study contributes to the field of environmental biotechnology by integrating the Artificial Bee Colony (ABC) optimization algorithm to assess the phytomining potential of native flora for a comprehensive suite of strategic/critical raw materials (SCRMs).

Unlike conventional phytoremediation research, which predominantly focuses on soil decontamination using standard statistical approaches, this work utilizes meta-heuristic optimization to evaluate SCRM recovery potential within extreme geothermal ecosystems. A significant finding of this research is the identification of the Musk thistle (MT) as a potent magnesium (Mg) accumulator, with leaf concentrations reaching 3,910 mg/kg_dw.

By systematically analyzing SCRM partitioning through bioconcentration factor (BCF) and translocation factor (TF), this study offers a refined methodological framework for identifying high-efficiency accumulators in specialized mineralized environments, thereby bridging the gap between traditional pollution studies and resource-oriented phytomining.</p> <p></p><p>Optimal strategic/critical raw material (SCRM) accumulation was determined by Artificial Bee Colony algorithm.</p><p>Mg accumulation in Musk thistle leaves reached a peak of 3,910 mg/kg.</p><p>This study confirmed Musk thistle as a strategic secondary source for SCRMs.</p><p></p> <p>Optimal strategic/critical raw material (SCRM) accumulation was determined by Artificial Bee Colony algorithm.</p> <p>Mg accumulation in Musk thistle leaves reached a peak of 3,910 mg/kg.</p> <p>This study confirmed Musk thistle as a strategic secondary source for SCRMs.</p>