%0 Journal Article
%@ 09608524
%A Mohajeri, L.
%A Aziz, H.A.
%A Isa, M.H.
%A Zahed, M.A.
%D 2010
%F scholars:1310
%J Bioresource Technology
%K Central composite; Coastal sediments; Coefficient of determination; Dependent variables; Desirability function; Independent variables; Nitrogen nutrient; Numerical optimizations; Oil concentration; Oil removal; Phosphorus concentration; Regression model; Response Surface Methodology; Statistical experiments; Statistically significant models; Weathered crude oil, Biodegradation; Biomass; Bioremediation; Biotechnology; Crude petroleum; Nitrogen; Nutrients; Optimization; Phosphorus; Pollution; Probability density function; Regression analysis; Sedimentology, Nitrogen removal, nitrogen; petroleum; phosphorus, biodegradation; bioremediation; coastal sediment; concentration (composition); crude oil; experimental design; nitrogen; numerical model; optimization; phosphorus; pollutant removal; sediment pollution, article; biomass; bioremediation; concentration (parameters); controlled study; Malaysia; mathematical analysis; priority journal; probability; process optimization; response surface method; seashore; sediment; statistical analysis; statistical significance; waste component removal, Biodegradation, Environmental; Biomass; Geologic Sediments; Industrial Waste; Models, Statistical; Nitrogen; Oils; Petroleum; Phosphorus; Regression Analysis; Reproducibility of Results; Software; Temperature; Time Factors; Waste Disposal, Fluid; Water Pollutants, Chemical
%N 3
%P 893-900
%R 10.1016/j.biortech.2009.09.013
%T A statistical experiment design approach for optimizing biodegradation of weathered crude oil in coastal sediments
%U https://khub.utp.edu.my/scholars/1310/
%V 101
%X This work studied the bioremediation of weathered crude oil (WCO) in coastal sediment samples using central composite face centered design (CCFD) under response surface methodology (RSM). Initial oil concentration, biomass, nitrogen and phosphorus concentrations were used as independent variables (factors) and oil removal as dependent variable (response) in a 60 days trial. A statistically significant model for WCO removal was obtained. The coefficient of determination (R2 = 0.9732) and probability value (P < 0.0001) demonstrated significance for the regression model. Numerical optimization based on desirability function were carried out for initial oil concentration of 2, 16 and 30 g per kg sediment and 83.13, 78.06 and 69.92 per cent removal were observed respectively, compare to 77.13, 74.17 and 69.87 per cent removal for un-optimized results. © 2009 Elsevier Ltd. All rights reserved.
%Z cited By 112