NONE 20260625125449189 wseas/wseas content-registration-form@crossref.org content-registration-form EARTH SCIENCES AND HUMAN CONSTRUCTIONS 2944-9154 2944-9006 Allag Fateh Faculty of Snv Ufas Setif1 University Setif ALGERIA Harrag Abdelmalek Faculty of Snv Ufas Setif1 University Setif ALGERIA Fenni Mohamed Faculty of Snv Ufas Setif1 University Setif ALGERIA Bounechada Mustapha Faculty of Snv Ufas Setif1 University Setif ALGERIA The intent of this project was to determine if Helianthus annuus (sunflower) can be utilized as a remedial or phytoremediation plant, to remove and detoxify heavy metals from contaminated soils. Since there are growing concerns about the presence of heavy metals in soil due to industrial pollution, finding sustainable and effective ways to eliminate and mitigate these pollutants has become very important. We used ANNs to evaluate various parameters in phytoremediation, including type of soil, concentration of metals, moisture level, and climate/temporal conditions. The data was gathered from experimental tests in controlled pots, and an ANN was utilized to analyze the parameters affecting sunflower uptake efficiency and overall health. Findings: The input of an Artificial Neural Network (ANN) are essential to understanding how the selected variables related with Helainthus annuus (sunflower) phytoremediation of soil. Analysis resulted in identifying the best conditions for improving the ability of Helainthus annuus to Phyto-remediate soils. This research has led to some new insights into the capabilities of Helainthus annuus to Phyto remediate and proved that modern computer assisted methods provide credible support for researchers within the field of Environment Sciences. This research will also allow for greater use of Helainthus annuus for improving the sustainability of soil management and reducing pollution in the environment. 06 25 2026 06 25 2026 10 2 https://creativecommons.org/licenses/by/4.0/deed.en_US 10.37394/232024.2026.6.2 https://wseas.com/journals/eshc/2026/a04eshc-002(2026).pdf Alloway, B. J. (2013). Heavy Metals in Soils: Trace Metals and Metalloids in Soils and Their Bioavailability. Springer. Wuana, R. A., & Okieimen, F. E. (2011). Heavy metals in contaminated soils: A review of sources, chemistry, risks, and best available strategies for remediation. ISRN Ecology, 2011, 1-20. Tchounwou, P. B., Yedjou, C. G., Patlolla, A. K., & Sutton, D. J. (2012). Heavy metal toxicity and the environment. Experientia Supplementum, 101, 133-164. Järup, L. (2003). Hazards of heavy metal contamination. British Medical Bulletin, 68 (1), 167-182. Khan, S., Cao, Q., Zheng, Y. M., Huang, Y. Z., & Zhu, Y. G. (2008). Health risks of heavy metals in contaminated soils and food crops irrigated with wastewater in Beijing, China. Environmental Pollution, 152 (3), 686-692. Dermont, G., Bergeron, M., Mercier, G., & Richer-Laflèche, M. (2008). Soil washing for metal removal: A review of physical/chemical technologies and field applications. Journal of Hazardous Materials, 152 (1), 1-31. Ali, H., Khan, E., & Sajad, M. A. (2013). Phytoremediation of heavy metals, concepts and applications. Chemosphere, 91 (7), 869- 881. Salt, D. E., Smith, R. D., & Raskin, I. (1998). Phytoremediation. Annual Review of Plant Biology, 49 (1), 643-668. Ghosh, M., & Singh, S. P. (2005). A review on phytoremediation of heavy metals and utilization of its byproducts. Applied Ecology and Environmental Research, 3 (1), 1-18. Sun, Y., Zhou, Q., Wang, L., Liu, W., & An, J. (2009). Chelator-enhanced phytoextraction of heavy metals from contaminated soils using Helianthus annuus L. Ecotoxicology and Environmental Safety, 72 (8), 1914-1919. Mendez, M. O., & Maier, R. M. (2008). Phytostabilization of mine tailings in arid and semiarid environments—an emerging remediation technology. Environmental Health Perspectives, 116 (3), 278-283. Khan, M. A., Khan, S., Khan, A., Alam, M., & Ahmad, I. (2015). Heavy metal contamination of soils and vegetables in suburban areas of Peshawar, Pakistan. Environmental Monitoring and Assessment, 187 (7), 377. Zhang, Y., & Goh, A. T. C. (2016). Multivariate adaptive regression splines and neural network models for prediction of pile drivability. Geoscience Frontiers, 7 (1), 45- 52. Abba, S. I., Pham, Q. B., Saini, G., & Linh, N. T. T. (2020). Prediction of phytoremediation efficiency of Amaranthus hybridu* in toxic metals-spiked soil using artificial neural networks. Environmental Technology & Innovation, 18, 100684. Adesodun, J. K., & Owoeye, O. F. (2021). Phytoremediation of heavy metal contaminated soils using sunflower (Helianthus annuus L.). Environmental Science, 12(2), 123-135. Ahmed, K. A., Berhan, A., & Rizwan, M. (2018). Phytoremediation of Pb and Cd contaminated soils by using sunflower (Helianthus annuus) plant. Agricultural Sciences, 8(5), 471-485. Munive, A., Vázquez, M., & Loli, S. (2020). The role of vermicompost in enhancing the phytoremediation potential of sunflower in lead-contaminated soils. Journal of Environmental Management, 250(1), 109500. Ortiz-Bernad, I., Volke-Sepúlveda, T., & Velasco-Trejo, C. (2007). Lead recovery in artificially contaminated agricultural soil as a remediation strategy using sunflower and vermicompost. Journal of Environmental Quality, 36(4), 1169-1177. Rizwan, M., Ali Shah, A. Z., & Zia-UrRehman, M. (2016). Phytoremediation potential of sunflower (Helianthus annuus) for heavy metal removal from contaminated soils: A review. Environmental Science and Pollution Research, 23(14), 13982-13992. Chauhan, P., & Mathur, J. (2020). Phytoremediation efficiency of Helianthus annuus L. for reclamation of heavy metalscontaminated industrial soil. Environmental Science and Pollution Research, 27(29), 29954–29966. Ahmed, K. A., Berhan, A., & Rizwan, M. (2018). Phytoremediation of Pb and Cd contaminated soils by using sunflower (Helianthus annuus) plant. Agricultural Sciences, 8(5), 471-485. Vázquez, M., & Loli, S. (2018). Enhancing phytoremediation potential through artificial neural networks: A case study with sunflower (Helianthus annuus). Journal of Phytology, 10(1), 12-20. Moslehi, M., Feizian, M., Higueras, P., & Eisvand, H. R. (2019). Lead recovery in artificially contaminated agricultural soil as a strategy for remediation using sunflower (Helianthus annuus). Environmental Science, 11(2), 123-135. Glezakos, T., & Tsiligiridis, T. (2002). Neural Networks for Landscape Applications. InfoLab, Agricultural University of Athens. Ke, H., & Wang, Y. (2021). A review of artificial neural network techniques for environmental issues prediction. Journal of Thermal Analysis and Calorimetry, 145, 2191–2207.