Application of Response Surface Methodology (RSM) for the Production and Optimization of Extruded Instant Porridge from Broken Rice Fractions Blended with Cowpea

Danbaba Nahemiah; Iro Nkama; Mamudu Halidu Badau

doi:doi:10.11648/j.ijnfs.20160502.13

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Application of Response Surface Methodology (RSM) for the Production and Optimization of Extruded Instant Porridge from Broken Rice Fractions Blended with Cowpea

Danbaba Nahemiah, Iro Nkama, Mamudu Halidu Badau

Published in International Journal of Nutrition and Food Sciences (Volume 5, Issue 2)

Received: 2 October 2015 Accepted: 13 October 2015 Published: 8 March 2016

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Abstract

Instant porridge from low grade broken rice fractions blended with cowpea to enhance protein quantity and quality was developed in this study through extrusion cooking technology. Response Surface Methodology (RSM) and Central Composite Rotatable Design (CCRD) were adopted for the formulation and optimization of the process variables. The main objective was to obtain the optimum level of extruder barrel temperature (X₁), feed moisture level (X₂) and feed cowpea level (X₃) that will produce optimum porridge having appreciably high protein, water dispersibility, lysine content and calorie value. ANOVA indicated significance (p˂0.05) of the models fitted in describing the relationship between the input and output variables in its natural state. The coefficient of the determination was also greater than 80% and non-significant lack-of-fit test. Numerical optimization results indicated that the optimum input variables were 120°C barrel temperature, 24g/100g cowpea formulation and 20g/100g feed moisture composition which produce 99.02% dispersibility, 24.13g/100g protein, 73.44% carbohydrate and 388.82kcal/100g calorie, and lysine of 5.02mg/g protein. These data will sharpen the weaning food industry by providing wide opportunity for new food production using low grade rice and common legumes, thereby increasing the economic values of both locally grown rice and cowpea.

Published in	International Journal of Nutrition and Food Sciences (Volume 5, Issue 2)
DOI	10.11648/j.ijnfs.20160502.13
Page(s)	105-116
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

Rice, Cowpea, Response Surface Methodology, Optimization, Instant Porridge

References

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APA Style

Danbaba Nahemiah, Iro Nkama, Mamudu Halidu Badau. (2016). Application of Response Surface Methodology (RSM) for the Production and Optimization of Extruded Instant Porridge from Broken Rice Fractions Blended with Cowpea. International Journal of Nutrition and Food Sciences, 5(2), 105-116. https://doi.org/10.11648/j.ijnfs.20160502.13

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ACS Style

Danbaba Nahemiah; Iro Nkama; Mamudu Halidu Badau. Application of Response Surface Methodology (RSM) for the Production and Optimization of Extruded Instant Porridge from Broken Rice Fractions Blended with Cowpea. Int. J. Nutr. Food Sci. 2016, 5(2), 105-116. doi: 10.11648/j.ijnfs.20160502.13

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AMA Style

Danbaba Nahemiah, Iro Nkama, Mamudu Halidu Badau. Application of Response Surface Methodology (RSM) for the Production and Optimization of Extruded Instant Porridge from Broken Rice Fractions Blended with Cowpea. Int J Nutr Food Sci. 2016;5(2):105-116. doi: 10.11648/j.ijnfs.20160502.13

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@article{10.11648/j.ijnfs.20160502.13,
  author = {Danbaba Nahemiah and Iro Nkama and Mamudu Halidu Badau},
  title = {Application of Response Surface Methodology (RSM) for the Production and Optimization of Extruded Instant Porridge from Broken Rice Fractions Blended with Cowpea},
  journal = {International Journal of Nutrition and Food Sciences},
  volume = {5},
  number = {2},
  pages = {105-116},
  doi = {10.11648/j.ijnfs.20160502.13},
  url = {https://doi.org/10.11648/j.ijnfs.20160502.13},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijnfs.20160502.13},
  abstract = {Instant porridge from low grade broken rice fractions blended with cowpea to enhance protein quantity and quality was developed in this study through extrusion cooking technology. Response Surface Methodology (RSM) and Central Composite Rotatable Design (CCRD) were adopted for the formulation and optimization of the process variables. The main objective was to obtain the optimum level of extruder barrel temperature (X1), feed moisture level (X2) and feed cowpea level (X3) that will produce optimum porridge having appreciably high protein, water dispersibility, lysine content and calorie value. ANOVA indicated significance (p˂0.05) of the models fitted in describing the relationship between the input and output variables in its natural state. The coefficient of the determination was also greater than 80% and non-significant lack-of-fit test. Numerical optimization results indicated that the optimum input variables were 120°C barrel temperature, 24g/100g cowpea formulation and 20g/100g feed moisture composition which produce 99.02% dispersibility, 24.13g/100g protein, 73.44% carbohydrate and 388.82kcal/100g calorie, and lysine of 5.02mg/g protein. These data will sharpen the weaning food industry by providing wide opportunity for new food production using low grade rice and common legumes, thereby increasing the economic values of both locally grown rice and cowpea.},
 year = {2016}
}

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TY  - JOUR
T1  - Application of Response Surface Methodology (RSM) for the Production and Optimization of Extruded Instant Porridge from Broken Rice Fractions Blended with Cowpea
AU  - Danbaba Nahemiah
AU  - Iro Nkama
AU  - Mamudu Halidu Badau
Y1  - 2016/03/08
PY  - 2016
N1  - https://doi.org/10.11648/j.ijnfs.20160502.13
DO  - 10.11648/j.ijnfs.20160502.13
T2  - International Journal of Nutrition and Food Sciences
JF  - International Journal of Nutrition and Food Sciences
JO  - International Journal of Nutrition and Food Sciences
SP  - 105
EP  - 116
PB  - Science Publishing Group
SN  - 2327-2716
UR  - https://doi.org/10.11648/j.ijnfs.20160502.13
AB  - Instant porridge from low grade broken rice fractions blended with cowpea to enhance protein quantity and quality was developed in this study through extrusion cooking technology. Response Surface Methodology (RSM) and Central Composite Rotatable Design (CCRD) were adopted for the formulation and optimization of the process variables. The main objective was to obtain the optimum level of extruder barrel temperature (X1), feed moisture level (X2) and feed cowpea level (X3) that will produce optimum porridge having appreciably high protein, water dispersibility, lysine content and calorie value. ANOVA indicated significance (p˂0.05) of the models fitted in describing the relationship between the input and output variables in its natural state. The coefficient of the determination was also greater than 80% and non-significant lack-of-fit test. Numerical optimization results indicated that the optimum input variables were 120°C barrel temperature, 24g/100g cowpea formulation and 20g/100g feed moisture composition which produce 99.02% dispersibility, 24.13g/100g protein, 73.44% carbohydrate and 388.82kcal/100g calorie, and lysine of 5.02mg/g protein. These data will sharpen the weaning food industry by providing wide opportunity for new food production using low grade rice and common legumes, thereby increasing the economic values of both locally grown rice and cowpea.
VL  - 5
IS  - 2
ER  -

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Author Information

Danbaba Nahemiah

Food Technology and Value Addition Research Program, National Cereals Research Institute (NCRI), Badeggi, Bida, Niger State, Nigeria; Department of Food Science and Technology, University of Maiduguri, Maiduguri, Nigeria
Iro Nkama

Department of Food Science and Technology, University of Nigeria, Nsukka, Nigeria; Department of Food Science and Technology, University of Maiduguri, Maiduguri, Nigeria
Mamudu Halidu Badau

Department of Food Science and Technology, University of Maiduguri, Maiduguri, Nigeria

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Danbaba Nahemiah, Iro Nkama, Mamudu Halidu Badau. (2016). Application of Response Surface Methodology (RSM) for the Production and Optimization of Extruded Instant Porridge from Broken Rice Fractions Blended with Cowpea. International Journal of Nutrition and Food Sciences, 5(2), 105-116. https://doi.org/10.11648/j.ijnfs.20160502.13

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ACS Style

Danbaba Nahemiah; Iro Nkama; Mamudu Halidu Badau. Application of Response Surface Methodology (RSM) for the Production and Optimization of Extruded Instant Porridge from Broken Rice Fractions Blended with Cowpea. Int. J. Nutr. Food Sci. 2016, 5(2), 105-116. doi: 10.11648/j.ijnfs.20160502.13

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AMA Style

Danbaba Nahemiah, Iro Nkama, Mamudu Halidu Badau. Application of Response Surface Methodology (RSM) for the Production and Optimization of Extruded Instant Porridge from Broken Rice Fractions Blended with Cowpea. Int J Nutr Food Sci. 2016;5(2):105-116. doi: 10.11648/j.ijnfs.20160502.13

Copy | Download

@article{10.11648/j.ijnfs.20160502.13,
  author = {Danbaba Nahemiah and Iro Nkama and Mamudu Halidu Badau},
  title = {Application of Response Surface Methodology (RSM) for the Production and Optimization of Extruded Instant Porridge from Broken Rice Fractions Blended with Cowpea},
  journal = {International Journal of Nutrition and Food Sciences},
  volume = {5},
  number = {2},
  pages = {105-116},
  doi = {10.11648/j.ijnfs.20160502.13},
  url = {https://doi.org/10.11648/j.ijnfs.20160502.13},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijnfs.20160502.13},
  abstract = {Instant porridge from low grade broken rice fractions blended with cowpea to enhance protein quantity and quality was developed in this study through extrusion cooking technology. Response Surface Methodology (RSM) and Central Composite Rotatable Design (CCRD) were adopted for the formulation and optimization of the process variables. The main objective was to obtain the optimum level of extruder barrel temperature (X1), feed moisture level (X2) and feed cowpea level (X3) that will produce optimum porridge having appreciably high protein, water dispersibility, lysine content and calorie value. ANOVA indicated significance (p˂0.05) of the models fitted in describing the relationship between the input and output variables in its natural state. The coefficient of the determination was also greater than 80% and non-significant lack-of-fit test. Numerical optimization results indicated that the optimum input variables were 120°C barrel temperature, 24g/100g cowpea formulation and 20g/100g feed moisture composition which produce 99.02% dispersibility, 24.13g/100g protein, 73.44% carbohydrate and 388.82kcal/100g calorie, and lysine of 5.02mg/g protein. These data will sharpen the weaning food industry by providing wide opportunity for new food production using low grade rice and common legumes, thereby increasing the economic values of both locally grown rice and cowpea.},
 year = {2016}
}

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TY  - JOUR
T1  - Application of Response Surface Methodology (RSM) for the Production and Optimization of Extruded Instant Porridge from Broken Rice Fractions Blended with Cowpea
AU  - Danbaba Nahemiah
AU  - Iro Nkama
AU  - Mamudu Halidu Badau
Y1  - 2016/03/08
PY  - 2016
N1  - https://doi.org/10.11648/j.ijnfs.20160502.13
DO  - 10.11648/j.ijnfs.20160502.13
T2  - International Journal of Nutrition and Food Sciences
JF  - International Journal of Nutrition and Food Sciences
JO  - International Journal of Nutrition and Food Sciences
SP  - 105
EP  - 116
PB  - Science Publishing Group
SN  - 2327-2716
UR  - https://doi.org/10.11648/j.ijnfs.20160502.13
AB  - Instant porridge from low grade broken rice fractions blended with cowpea to enhance protein quantity and quality was developed in this study through extrusion cooking technology. Response Surface Methodology (RSM) and Central Composite Rotatable Design (CCRD) were adopted for the formulation and optimization of the process variables. The main objective was to obtain the optimum level of extruder barrel temperature (X1), feed moisture level (X2) and feed cowpea level (X3) that will produce optimum porridge having appreciably high protein, water dispersibility, lysine content and calorie value. ANOVA indicated significance (p˂0.05) of the models fitted in describing the relationship between the input and output variables in its natural state. The coefficient of the determination was also greater than 80% and non-significant lack-of-fit test. Numerical optimization results indicated that the optimum input variables were 120°C barrel temperature, 24g/100g cowpea formulation and 20g/100g feed moisture composition which produce 99.02% dispersibility, 24.13g/100g protein, 73.44% carbohydrate and 388.82kcal/100g calorie, and lysine of 5.02mg/g protein. These data will sharpen the weaning food industry by providing wide opportunity for new food production using low grade rice and common legumes, thereby increasing the economic values of both locally grown rice and cowpea.
VL  - 5
IS  - 2
ER  -

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