Besalatpour, A., Hajabbasi, M., Khoshgoftarmanesh, A., Sheikholeslam, F. (2011). Decision Making Using Genetic Algorithm to Select the Best Plant Genotype for Phytoremediation of Petroleum - Contaminated Soils. , 25(1), 61-70. doi: 10.22092/ijsr.2011.126465
A. A. Besalatpour; Mohammad Hajabbasi; A. H. Khoshgoftarmanesh; F. Sheikholeslam. "Decision Making Using Genetic Algorithm to Select the Best Plant Genotype for Phytoremediation of Petroleum - Contaminated Soils". , 25, 1, 2011, 61-70. doi: 10.22092/ijsr.2011.126465
Besalatpour, A., Hajabbasi, M., Khoshgoftarmanesh, A., Sheikholeslam, F. (2011). 'Decision Making Using Genetic Algorithm to Select the Best Plant Genotype for Phytoremediation of Petroleum - Contaminated Soils', , 25(1), pp. 61-70. doi: 10.22092/ijsr.2011.126465
Besalatpour, A., Hajabbasi, M., Khoshgoftarmanesh, A., Sheikholeslam, F. Decision Making Using Genetic Algorithm to Select the Best Plant Genotype for Phytoremediation of Petroleum - Contaminated Soils. , 2011; 25(1): 61-70. doi: 10.22092/ijsr.2011.126465

Decision Making Using Genetic Algorithm to Select the Best Plant Genotype for Phytoremediation of Petroleum - Contaminated Soils

پژوهش های خاک
Volume 25, Issue 1, June 2011, Pages 61-70    PDF (299.72 K)
Document Type: Research Paper
DOI: 10.22092/ijsr.2011.126465
Authors
A. A. Besalatpour* 1; Mohammad Hajabbasi2; A. H. Khoshgoftarmanesh2; F. Sheikholeslam2
1PhD. Student, Professor and Associate Professor of Soil Sci., respectively, Department of Soil Sci., College of Agriculture, Isfahan University of Technology, Isfahan, Iran
2Associate Professor of Elect., Department of Elect., and Computer Sci., Isfahan University of Technology, Isfahan, Iran
Abstract
Genetic algorithm is an optimization method for finding the best solution in large design spaces in a way similar to chromosomes and genes in biological systems. In this study, the potential use of classical statistical analysis is compared with genetic algorithm optimization methods for finding the best plant cultivation and the best mixing petroleum-contamination level (1:1 and 3:1, contaminated: uncontaminated soil) for phytoremediation of petroleum-contaminated soil around the Tehran Oil Refinery. Results from the germination and subsequent growth trials showed that, according to the classical statistical analysis method, agropyron, tall fescue, and puccinellia were the optimum plant species for both contamination levels (1:1 and 3:1). In contrast, selection of agropyron, tall fescue, sunflower, and safflower was the optimum solution using the genetic algorithm optimization method. In the phytoremediation experiments, agropyron and contamination level 1:1 were the optimum solutions for achieving successful phytoremediation of the investigated petroleum-contaminated soil using genetic algorithm optimization method. Furthermore, the agropyron-tall fescue combined species and the level 1:1 were the best combined two-plant cultivations and the best mixing petroleum-contamination level, respectively. Therefore, the agropyron-tall fescue combined cultivation and level 1:1 were recommended for phytoremediation of the investigated petroleum-contaminated soil.
Keywords
Genetic algorithm; Classical statistical analysis; Phytoremediation; Petroleum contaminants
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