Bioaugmentation and Biostimulation of Total Petroleum Hydrocarbon Degradation in a Petroleum-contaminated Soil with Fungi Isolated from Olive Oil Effluent

Essabri, Abduelbaset M. A.; Aydinlik, Nur Pasaoglulari; Williams, Ndifreke Etuk

Bioaugmentation and Biostimulation of Total Petroleum Hydrocarbon Degradation in a Petroleum-contaminated Soil with Fungi Isolated from Olive Oil Effluent

2019

Essabri, Abduelbaset M. A. | Aydinlik, Nur Pasaoglulari | Williams, Ndifreke Etuk

In degradation of total petroleum hydrocarbon, 35 isolates belonging to 11 genera were sanitized and 3 isolates as well as their consortium were initiated to be able to raise in association with petroleum hydrocarbon as sole source of carbon under in vitro circumstances. The isolated strains were grounded on internal transcribed spacer (ITS) rDNA sequence analysis. The fungal strains with the utmost potentiality to reduce petroleum hydrocarbon without emerging antagonistic activities were Aspergillus niger, Penicillium ochrochloron, and Trichodema viride. For fungal growth on petroleum hydrocarbon, P. ochrocholon gained weight of 44%, A. niger 49%, and T. viride 39% within the first 30–40 days. As compared to the controls, these fungi accumulated significantly higher biomass, produced extracellular enzymes, and degraded total petroleum hydrocarbon and A. niger strongly degraded total petroleum hydrocarbon with a degradation of about 71.19%. These observations with GC-MS data confirm that these isolates displayed rapid total petroleum hydrocarbon biodegradation within a period of 60 days and the half-life showed that A. niger was the shortest with t1/2 = 21.280 day⁻¹ corresponding to the highest percent degradation of 71.19% and first-order kinetic fitted into the present study. By multivariate analysis, five main factors were identified by factor analysis (FA). The first factor (F1) of the fungi species accounts for 20.0% which signifies that fungi species controls the degradation of petroleum variability and hierarchical cluster analysis (HCA) as a dendrogram with five observations and three variables shows two predominant clusters order cluster 1 > 2.

Mostrar más [+]