DECISION MAKING USING GENETIC ALGORITHM TO SELECT THE BEST PLANT GENOTYPE FOR PHYTOREMEDIATION OF PETROLEUM - CONTAMINATED SOILS

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BESALATPOUR A.A.; HAJABBASI M.A.; KHOSHGOFTARMANESH H.; SHEIKHOLESLAMI F.

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Journal: Iranian Journal of Soil Research Year:2011 | Volume:25 | Issue:1 Page(s): 61-70

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Title

DECISION MAKING USING GENETIC ALGORITHM TO SELECT THE BEST PLANT GENOTYPE FOR PHYTOREMEDIATION OF PETROLEUM - CONTAMINATED SOILS

Author(s)

BESALATPOUR A.A. | HAJABBASI M.A. | KHOSHGOFTARMANESH H. | SHEIKHOLESLAMI F. | Issue Writer Certificate

Keywords

GENETIC ALGORITHMQ2

CLASSICAL STATISTICAL ANALYSISQ2

PHYTOREMEDIATIONQ2

PETROLEUM CONTAMINANTSQ2

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.

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APA: Copy

BESALATPOUR, A.A., HAJABBASI, M.A., KHOSHGOFTARMANESH, H., & SHEIKHOLESLAMI, F.. (2011). DECISION MAKING USING GENETIC ALGORITHM TO SELECT THE BEST PLANT GENOTYPE FOR PHYTOREMEDIATION OF PETROLEUM - CONTAMINATED SOILS. IRANIAN JOURNAL OF SOIL RESEARCH (FORMERLY SOIL AND WATER SCIENCES), 25(1), 61-70. SID. https://sid.ir/paper/159184/en

Vancouver: Copy

BESALATPOUR A.A., HAJABBASI M.A., KHOSHGOFTARMANESH H., SHEIKHOLESLAMI F.. DECISION MAKING USING GENETIC ALGORITHM TO SELECT THE BEST PLANT GENOTYPE FOR PHYTOREMEDIATION OF PETROLEUM - CONTAMINATED SOILS. IRANIAN JOURNAL OF SOIL RESEARCH (FORMERLY SOIL AND WATER SCIENCES)[Internet]. 2011;25(1):61-70. Available from: https://sid.ir/paper/159184/en

IEEE: Copy

A.A. BESALATPOUR, M.A. HAJABBASI, H. KHOSHGOFTARMANESH, and F. SHEIKHOLESLAMI, “DECISION MAKING USING GENETIC ALGORITHM TO SELECT THE BEST PLANT GENOTYPE FOR PHYTOREMEDIATION OF PETROLEUM - CONTAMINATED SOILS,” IRANIAN JOURNAL OF SOIL RESEARCH (FORMERLY SOIL AND WATER SCIENCES), vol. 25, no. 1, pp. 61–70, 2011, [Online]. Available: https://sid.ir/paper/159184/en

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