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Response of Soil Microbial Isolates to the Toxicity of Green Surfactant

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Iroegbu D. I., Adieze I. E., Nwanyanwu C. E., Mejeha O. K., Sinee B.
World News of Natural Sciences
|
2024
|
vol. 52
12-22
EN
In this study, microorganisms were obtained from hydrocarbon-polluted and unpolluted soil samples using Nutrient agar and Bushnell Hass agar for the enumeration of heterotrophic bacteria and hydrocarbon-utilizing bacteria respectively.The response of hydrocarbons utilizing soil bacterial isolates to the toxicity of green surfactant was assayed. The hydrocarbons utilizing bacterial isolates in soil extract broth were exposed to different concentrations; (1, 2, 3, 4, and 5) % w/v of green surfactants, and their responses (cell growth and viability) were time-dependent and monitored using spectrophotometer and total viable count. These hydrocarbon-utilizing bacteria isolates were two different species of Micrococcus (C and D), Bacillus sp. (F2) and Pseudomonas sp. (A2). They showed good response to high concentrations (4 and 5%) of the green surfactant in soil extract broth. This could be a result of a component of the green surfactant such as phosphorus which is an essential nutrient for microbial growth. Hence these tolerated green surfactant concentrations could be recommended to be used as surface active agents to enhance the bioavailability of hydrocarbon to microorganisms for bioremediation practices of hydrocarbon-contaminated sites.
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Prediction of properties of biodiesel-diesel blends using spectrofluorimetry and multivariate calibration

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Meira M., Quintella C., Pepe I., Costa Neto P., Santos Tanajura A., Silva H.
Open Chemistry
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2012
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vol. 10
|
issue 4
1328-1337
EN
Regressions based on fluorescence spectroscopy were developed to provide relatively inexpensive and rapid measurements of the concentration, viscosity, and specific gravity of biodiesel-diesel blends. The methods involved obtaining a mathematical model from spectrofluorimetric data and data from a given property (concentration, dynamic viscosity, or specific gravity) using partial least squares (PLS) regression, which was then applied as a model for predicting properties of interest. The predicted concentrations, dynamic viscosities, and specific gravities of the biodiesel-diesel blends were compared with actual values and agreed reasonably well with the obtained results. The models showed high correlation between real and predicted values. The R-square values near 1 indicated excellent model accuracy for predicting concentrations, specific gravities, and dynamic viscosities of biodiesel-diesel blends. The residual distribution did not follow a trend with respect to the predicted variables, indicating an excellent fit to the data. [...]
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