TY - JOUR
T1 - Biotreatment of a triphenylmethane dye solution using a Xanthophyta alga
T2 - Modeling of key factors by neural network
AU - Khataee, A. R.
AU - Zarei, M.
AU - Dehghan, G.
AU - Ebadi, E.
AU - Pourhassan, M.
PY - 2011/5
Y1 - 2011/5
N2 - In this paper biotreatment of triphenylmethane dye, Malachite Green (MG), by a Xanthophyta alga, Vaucheria species, was investigated. The results obtained from batch experiments revealed the ability of Vaucheria sp. to remove MG. The effects of operational parameters such as initial dye concentration, temperature, pH and algal amount on biological decolorization efficiency were examined. The results showed that the biological decolorization efficiency decreased with increasing initial MG concentration. The decolorization rate also enhanced with increasing the temperature, initial pH of the dye solution and the amount of biomass rose. Biological treatment of MG solution by live and dead alga was compared. The reusability and efficiency of the live alga in long-term repetitive operations were also examined. The batch experiments results revealed the ability of algal species in biological degradation of the dye. An artificial neural network (ANN) model was developed to predict the biological decolorization of MG solution. The findings indicated that artificial neural network provided reasonable predictive performance (R2=0.979). The influence of each parameter on the variable studied was assessed, and reaction time and initial dye concentration were found to be the most significant factors, followed by initial pH, amount of alga and temperature.
AB - In this paper biotreatment of triphenylmethane dye, Malachite Green (MG), by a Xanthophyta alga, Vaucheria species, was investigated. The results obtained from batch experiments revealed the ability of Vaucheria sp. to remove MG. The effects of operational parameters such as initial dye concentration, temperature, pH and algal amount on biological decolorization efficiency were examined. The results showed that the biological decolorization efficiency decreased with increasing initial MG concentration. The decolorization rate also enhanced with increasing the temperature, initial pH of the dye solution and the amount of biomass rose. Biological treatment of MG solution by live and dead alga was compared. The reusability and efficiency of the live alga in long-term repetitive operations were also examined. The batch experiments results revealed the ability of algal species in biological degradation of the dye. An artificial neural network (ANN) model was developed to predict the biological decolorization of MG solution. The findings indicated that artificial neural network provided reasonable predictive performance (R2=0.979). The influence of each parameter on the variable studied was assessed, and reaction time and initial dye concentration were found to be the most significant factors, followed by initial pH, amount of alga and temperature.
KW - ANN modeling
KW - Biodegradation
KW - Decolorization
KW - Macroalgae
KW - Textile dye
UR - http://www.scopus.com/inward/record.url?scp=79958196142&partnerID=8YFLogxK
U2 - 10.1016/j.jtice.2010.08.006
DO - 10.1016/j.jtice.2010.08.006
M3 - Article
AN - SCOPUS:79958196142
SN - 1876-1070
VL - 42
SP - 380
EP - 386
JO - Journal of the Taiwan Institute of Chemical Engineers
JF - Journal of the Taiwan Institute of Chemical Engineers
IS - 3
ER -