Modelling and Optimization of the Removal of Congo-Red Dye from Waste Water Using Agricultural Waste

Adepoju Tunde Folorunsho; Uzono Romokere Isotuk; Akwayo Iniobong Job

doi:doi:10.11648/j.jcebe.20170101.11

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Modelling and Optimization of the Removal of Congo-Red Dye from Waste Water Using Agricultural Waste

Adepoju Tunde Folorunsho, Uzono Romokere Isotuk, Akwayo Iniobong Job

Published in Journal of Chemical, Environmental and Biological Engineering (Volume 1, Issue 1)

Received: 22 October 2016 Accepted: 2 November 2016 Published: 14 December 2016

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Abstract

The continuous utilization of dye in the industries and commodity products has necessitate its development by sustainable approach. However, for the success and commercialization of these products, their cost of production should be compared to the existing products available in the market. To do these, there is a need to introduce cheap feedstock for Congo red dye removal (CDRRR). Its optimization will ease the process of production and give the optimum acceptable yield. Result showed that highest CRDRR yield was 104.00 (mg/L) at pH(X₁) = 1, AD(X₂) = 0 and Time (X₃) = -1, respectively. Box-Behnken response surface methodology (BBSRM) predicted a yield of 91.233 (mg/L) for CRDRR at X₁ = -0.423, X₂ = -1.00 and X₃ = -1.00 variables condition, which was validated as 90.87 (mg/L). ANN genetic algorithm predicted CRDRR of 92.561 (mg/L) at variables condition X₁ = -0.567, X₂ = -0.89 and X₃ = -1.00, which was validated as 91.53 (mg/L). Modelling and optimization derived equations that showed the relationship between the CRDRR and variables (X₁， X₂ and X₃) in term of coded for RSM: CRDRR(%)= 92.67+0.72X₁-5.67X₂+6.50X₃-7.66X₁X₂-4.59X₁X₃+6.20X₂X₃-0.35X₁ ²-1.14X₂²-0.12X₃²; actual factors for ANN: CRDRR(%)=55.70808+7.18508X₁+9.74067X₂+5.77729X₃-3.40222X₁X₂-1.22467X₁X₃+6.61867X₂X₃-0.039194X₁²-2.02711X₂²-0.078560 The study concluded that agro waste is suitable feedstock for Congo red dye removal and the statistical software proved suitable for modelling and optimization.

Published in	Journal of Chemical, Environmental and Biological Engineering (Volume 1, Issue 1)
DOI	10.11648/j.jcebe.20170101.11
Page(s)	1-7
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Congo- Red Dye, Agricultural Waste, Optimisation, Modelling, Response Surface Methodology, Artificial Neural Network

References

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APA Style

Adepoju Tunde Folorunsho, Uzono Romokere Isotuk, Akwayo Iniobong Job. (2016). Modelling and Optimization of the Removal of Congo-Red Dye from Waste Water Using Agricultural Waste. Journal of Chemical, Environmental and Biological Engineering, 1(1), 1-7. https://doi.org/10.11648/j.jcebe.20170101.11

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ACS Style

Adepoju Tunde Folorunsho; Uzono Romokere Isotuk; Akwayo Iniobong Job. Modelling and Optimization of the Removal of Congo-Red Dye from Waste Water Using Agricultural Waste. J. Chem. Environ. Biol. Eng. 2016, 1(1), 1-7. doi: 10.11648/j.jcebe.20170101.11

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AMA Style

Adepoju Tunde Folorunsho, Uzono Romokere Isotuk, Akwayo Iniobong Job. Modelling and Optimization of the Removal of Congo-Red Dye from Waste Water Using Agricultural Waste. J Chem Environ Biol Eng. 2016;1(1):1-7. doi: 10.11648/j.jcebe.20170101.11

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@article{10.11648/j.jcebe.20170101.11,
  author = {Adepoju Tunde Folorunsho and Uzono Romokere Isotuk and Akwayo Iniobong Job},
  title = {Modelling and Optimization of the Removal of Congo-Red Dye from Waste Water Using Agricultural Waste},
  journal = {Journal of Chemical, Environmental and Biological Engineering},
  volume = {1},
  number = {1},
  pages = {1-7},
  doi = {10.11648/j.jcebe.20170101.11},
  url = {https://doi.org/10.11648/j.jcebe.20170101.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.jcebe.20170101.11},
  abstract = {The continuous utilization of dye in the industries and commodity products has necessitate its development by sustainable approach. However, for the success and commercialization of these products, their cost of production should be compared to the existing products available in the market. To do these, there is a need to introduce cheap feedstock for Congo red dye removal (CDRRR). Its optimization will ease the process of production and give the optimum acceptable yield. Result showed that highest CRDRR yield was 104.00 (mg/L) at pH(X1) = 1, AD(X2) = 0 and Time (X3) = -1, respectively. Box-Behnken response surface methodology (BBSRM) predicted a yield of 91.233 (mg/L) for CRDRR at X1 = -0.423, X2 = -1.00 and X3 = -1.00 variables condition, which was validated as 90.87 (mg/L). ANN genetic algorithm predicted CRDRR of 92.561 (mg/L) at variables condition X1 = -0.567, X2 = -0.89 and X3 = -1.00, which was validated as 91.53 (mg/L). Modelling and optimization derived equations that showed the relationship between the CRDRR and variables (X1， X2 and X3) in term of coded for RSM: CRDRR(%)= 92.67+0.72X1-5.67X2+6.50X3-7.66X1X2-4.59X1X3+6.20X2X3-0.35X1 2-1.14X22-0.12X32; actual factors for ANN: CRDRR(%)=55.70808+7.18508X1+9.74067X2+5.77729X3-3.40222X1X2-1.22467X1X3+6.61867X2X3-0.039194X12-2.02711X22-0.078560 The study concluded that agro waste is suitable feedstock for Congo red dye removal and the statistical software proved suitable for modelling and optimization.},
 year = {2016}
}

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TY  - JOUR
T1  - Modelling and Optimization of the Removal of Congo-Red Dye from Waste Water Using Agricultural Waste
AU  - Adepoju Tunde Folorunsho
AU  - Uzono Romokere Isotuk
AU  - Akwayo Iniobong Job
Y1  - 2016/12/14
PY  - 2016
N1  - https://doi.org/10.11648/j.jcebe.20170101.11
DO  - 10.11648/j.jcebe.20170101.11
T2  - Journal of Chemical, Environmental and Biological Engineering
JF  - Journal of Chemical, Environmental and Biological Engineering
JO  - Journal of Chemical, Environmental and Biological Engineering
SP  - 1
EP  - 7
PB  - Science Publishing Group
SN  - 2640-267X
UR  - https://doi.org/10.11648/j.jcebe.20170101.11
AB  - The continuous utilization of dye in the industries and commodity products has necessitate its development by sustainable approach. However, for the success and commercialization of these products, their cost of production should be compared to the existing products available in the market. To do these, there is a need to introduce cheap feedstock for Congo red dye removal (CDRRR). Its optimization will ease the process of production and give the optimum acceptable yield. Result showed that highest CRDRR yield was 104.00 (mg/L) at pH(X1) = 1, AD(X2) = 0 and Time (X3) = -1, respectively. Box-Behnken response surface methodology (BBSRM) predicted a yield of 91.233 (mg/L) for CRDRR at X1 = -0.423, X2 = -1.00 and X3 = -1.00 variables condition, which was validated as 90.87 (mg/L). ANN genetic algorithm predicted CRDRR of 92.561 (mg/L) at variables condition X1 = -0.567, X2 = -0.89 and X3 = -1.00, which was validated as 91.53 (mg/L). Modelling and optimization derived equations that showed the relationship between the CRDRR and variables (X1， X2 and X3) in term of coded for RSM: CRDRR(%)= 92.67+0.72X1-5.67X2+6.50X3-7.66X1X2-4.59X1X3+6.20X2X3-0.35X1 2-1.14X22-0.12X32; actual factors for ANN: CRDRR(%)=55.70808+7.18508X1+9.74067X2+5.77729X3-3.40222X1X2-1.22467X1X3+6.61867X2X3-0.039194X12-2.02711X22-0.078560 The study concluded that agro waste is suitable feedstock for Congo red dye removal and the statistical software proved suitable for modelling and optimization.
VL  - 1
IS  - 1
ER  -

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Author Information

Adepoju Tunde Folorunsho

Department of Chemical and Petrochemical Engineering, Akwa-Ibom State University, Ikot Akpaden, Mkpat Enin L.G.A., Nigeria
Uzono Romokere Isotuk

Department of Chemical and Petrochemical Engineering, Akwa-Ibom State University, Ikot Akpaden, Mkpat Enin L.G.A., Nigeria
Akwayo Iniobong Job

Department of Chemical and Petrochemical Engineering, Akwa-Ibom State University, Ikot Akpaden, Mkpat Enin L.G.A., Nigeria

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Plain Text BibTeX RIS

APA Style

Adepoju Tunde Folorunsho, Uzono Romokere Isotuk, Akwayo Iniobong Job. (2016). Modelling and Optimization of the Removal of Congo-Red Dye from Waste Water Using Agricultural Waste. Journal of Chemical, Environmental and Biological Engineering, 1(1), 1-7. https://doi.org/10.11648/j.jcebe.20170101.11

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ACS Style

Adepoju Tunde Folorunsho; Uzono Romokere Isotuk; Akwayo Iniobong Job. Modelling and Optimization of the Removal of Congo-Red Dye from Waste Water Using Agricultural Waste. J. Chem. Environ. Biol. Eng. 2016, 1(1), 1-7. doi: 10.11648/j.jcebe.20170101.11

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AMA Style

Adepoju Tunde Folorunsho, Uzono Romokere Isotuk, Akwayo Iniobong Job. Modelling and Optimization of the Removal of Congo-Red Dye from Waste Water Using Agricultural Waste. J Chem Environ Biol Eng. 2016;1(1):1-7. doi: 10.11648/j.jcebe.20170101.11

Copy | Download

@article{10.11648/j.jcebe.20170101.11,
  author = {Adepoju Tunde Folorunsho and Uzono Romokere Isotuk and Akwayo Iniobong Job},
  title = {Modelling and Optimization of the Removal of Congo-Red Dye from Waste Water Using Agricultural Waste},
  journal = {Journal of Chemical, Environmental and Biological Engineering},
  volume = {1},
  number = {1},
  pages = {1-7},
  doi = {10.11648/j.jcebe.20170101.11},
  url = {https://doi.org/10.11648/j.jcebe.20170101.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.jcebe.20170101.11},
  abstract = {The continuous utilization of dye in the industries and commodity products has necessitate its development by sustainable approach. However, for the success and commercialization of these products, their cost of production should be compared to the existing products available in the market. To do these, there is a need to introduce cheap feedstock for Congo red dye removal (CDRRR). Its optimization will ease the process of production and give the optimum acceptable yield. Result showed that highest CRDRR yield was 104.00 (mg/L) at pH(X1) = 1, AD(X2) = 0 and Time (X3) = -1, respectively. Box-Behnken response surface methodology (BBSRM) predicted a yield of 91.233 (mg/L) for CRDRR at X1 = -0.423, X2 = -1.00 and X3 = -1.00 variables condition, which was validated as 90.87 (mg/L). ANN genetic algorithm predicted CRDRR of 92.561 (mg/L) at variables condition X1 = -0.567, X2 = -0.89 and X3 = -1.00, which was validated as 91.53 (mg/L). Modelling and optimization derived equations that showed the relationship between the CRDRR and variables (X1， X2 and X3) in term of coded for RSM: CRDRR(%)= 92.67+0.72X1-5.67X2+6.50X3-7.66X1X2-4.59X1X3+6.20X2X3-0.35X1 2-1.14X22-0.12X32; actual factors for ANN: CRDRR(%)=55.70808+7.18508X1+9.74067X2+5.77729X3-3.40222X1X2-1.22467X1X3+6.61867X2X3-0.039194X12-2.02711X22-0.078560 The study concluded that agro waste is suitable feedstock for Congo red dye removal and the statistical software proved suitable for modelling and optimization.},
 year = {2016}
}

Copy | Download

TY  - JOUR
T1  - Modelling and Optimization of the Removal of Congo-Red Dye from Waste Water Using Agricultural Waste
AU  - Adepoju Tunde Folorunsho
AU  - Uzono Romokere Isotuk
AU  - Akwayo Iniobong Job
Y1  - 2016/12/14
PY  - 2016
N1  - https://doi.org/10.11648/j.jcebe.20170101.11
DO  - 10.11648/j.jcebe.20170101.11
T2  - Journal of Chemical, Environmental and Biological Engineering
JF  - Journal of Chemical, Environmental and Biological Engineering
JO  - Journal of Chemical, Environmental and Biological Engineering
SP  - 1
EP  - 7
PB  - Science Publishing Group
SN  - 2640-267X
UR  - https://doi.org/10.11648/j.jcebe.20170101.11
AB  - The continuous utilization of dye in the industries and commodity products has necessitate its development by sustainable approach. However, for the success and commercialization of these products, their cost of production should be compared to the existing products available in the market. To do these, there is a need to introduce cheap feedstock for Congo red dye removal (CDRRR). Its optimization will ease the process of production and give the optimum acceptable yield. Result showed that highest CRDRR yield was 104.00 (mg/L) at pH(X1) = 1, AD(X2) = 0 and Time (X3) = -1, respectively. Box-Behnken response surface methodology (BBSRM) predicted a yield of 91.233 (mg/L) for CRDRR at X1 = -0.423, X2 = -1.00 and X3 = -1.00 variables condition, which was validated as 90.87 (mg/L). ANN genetic algorithm predicted CRDRR of 92.561 (mg/L) at variables condition X1 = -0.567, X2 = -0.89 and X3 = -1.00, which was validated as 91.53 (mg/L). Modelling and optimization derived equations that showed the relationship between the CRDRR and variables (X1， X2 and X3) in term of coded for RSM: CRDRR(%)= 92.67+0.72X1-5.67X2+6.50X3-7.66X1X2-4.59X1X3+6.20X2X3-0.35X1 2-1.14X22-0.12X32; actual factors for ANN: CRDRR(%)=55.70808+7.18508X1+9.74067X2+5.77729X3-3.40222X1X2-1.22467X1X3+6.61867X2X3-0.039194X12-2.02711X22-0.078560 The study concluded that agro waste is suitable feedstock for Congo red dye removal and the statistical software proved suitable for modelling and optimization.
VL  - 1
IS  - 1
ER  -

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