Evaluating the bio-removal of crude oil by vetiver grass (<i>Vetiveria zizanioides</i> L.) in interaction with bacterial consortium exposed to contaminated artificial soils

Kiamarsi, Z.; Kafi, Mohammad; Soleimani, Mohsen; Nezami, Ahmad; Lutts, Stanley

doi:10.1080/15226514.2021.1954876

Cited by 7 publications

(1 citation statement)

References 41 publications

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“…Despite their low solubility in water, they are rapidly degraded by microorganisms 6 . Biological methods are one of the most common methods in decomposition and removal of these substances 7,8 . In addition to its simplicity, cost effectiveness and feasibility, it is also environmentally friendly recently, researchers have sought to optimize this process and utilize it 3,[9][10][11] .…”

Section: Modelling Of N-hexadecane Bioremediation From Soil By Slurry...mentioning

confidence: 99%

Modelling of n-Hexadecane bioremediation from soil by slurry bioreactors using artificial neural network method

Morovati

Abbasi²,

Samaei³

et al. 2022

Sci Rep

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Diesel oil is known to be one of the major petroleum products that can pollute water and soil. Soil pollution caused by petroleum hydrocarbons has substantially impacted the environment, especially in the Middle East. In this study, modeling and optimization of hexadecane removal from soil was performed using two pure cultures of Acinetobacter and Acromobacter and consortium culture of both bacterial species using artificial neural network (ANN) method. Then the best ANN structure was proposed based on mean square error (MSE) as well as correlation coefficient (R) for pure cultures of Acinetobacter and Acromobacter as well as their consortium. The results showed that the correlations between the actual data and the data predicted by ANN (R2) in Acromobacter, Acinetobacter and consortium of both cultures were 0.50, 0.47 and 0.63, respectively. Despite the low correlation between the experimental data and the data predicted by the ANN, the correlation coefficient and the precision of ANN for the consortium was higher. As a result, ANN had desirable precision to predict hexadecan removal by the cobsertium culture of Ochromobater and Acintobacter.

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