Optimization of Coconut (<i>Cocos nucifera</i>) Milk Extraction Using Response Surface Methodology

Victor Ephraim Edem; Aniekpeno Isaac Elijah

doi:doi:10.11648/j.ijnfs.20160506.13

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Optimization of Coconut (Cocos nucifera) Milk Extraction Using Response Surface Methodology

Victor Ephraim Edem, Aniekpeno Isaac Elijah

Published in International Journal of Nutrition and Food Sciences (Volume 5, Issue 6)

Received: 23 August 2016 Accepted: 3 September 2016 Published: 18 October 2016

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Abstract

Coconut milk provides health benefits due to its medium chain fatty acids and is widely utilized in the food industry. However, there seems to be inadequate information on the optimal extraction conditions for coconut milk. In this study, a response surface methodology (RSM) based on central composite design (CCD) was employed to optimize the extraction time (X₁), extraction temperature (X₂) and particle size of coconut meat (X₃) for coconut milk extraction. Yield, pH, viscosity and total solid content of coconut milk were evaluated as responses. Regression models were generated and adequacy tested with lack of fit test and coefficient of determination (R²). The results showed that extraction time; extraction temperature and particle size of coconut meat had significant (p˂ 0.05) effects on responses. The R² for yield, pH, viscosity, and total solid content of coconut milk were 0.9976, 0.7352, 0.6748 and 0.9787 respectively. Optimum extraction time, temperature and particle size of coconut meat with the highest desirability index of 0.797 was 15 min, 40°C and ≤ 1617 µm respectively, while optimum yield, pH, viscosity, and total solid content of coconut milk were estimated at 61.129%, 6.6, 2.85 cp and 16.01% respectively. The experimental results obtained validate the predicted model within the acceptable range of the responses. The results also suggest that the obtained model is acceptable for the maximum milk yield and improved quality consistency.

Published in	International Journal of Nutrition and Food Sciences (Volume 5, Issue 6)
DOI	10.11648/j.ijnfs.20160506.13
Page(s)	384-394
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), 2016. Published by Science Publishing Group

Keywords

Coconut Milk, Optimization, Response Surface Methodology, Central Composite Design

References

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APA Style

Victor Ephraim Edem, Aniekpeno Isaac Elijah. (2016). Optimization of Coconut (Cocos nucifera) Milk Extraction Using Response Surface Methodology. International Journal of Nutrition and Food Sciences, 5(6), 384-394. https://doi.org/10.11648/j.ijnfs.20160506.13

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ACS Style

Victor Ephraim Edem; Aniekpeno Isaac Elijah. Optimization of Coconut (Cocos nucifera) Milk Extraction Using Response Surface Methodology. Int. J. Nutr. Food Sci. 2016, 5(6), 384-394. doi: 10.11648/j.ijnfs.20160506.13

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AMA Style

Victor Ephraim Edem, Aniekpeno Isaac Elijah. Optimization of Coconut (Cocos nucifera) Milk Extraction Using Response Surface Methodology. Int J Nutr Food Sci. 2016;5(6):384-394. doi: 10.11648/j.ijnfs.20160506.13

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@article{10.11648/j.ijnfs.20160506.13,
  author = {Victor Ephraim Edem and Aniekpeno Isaac Elijah},
  title = {Optimization of Coconut (Cocos nucifera) Milk Extraction Using Response Surface Methodology},
  journal = {International Journal of Nutrition and Food Sciences},
  volume = {5},
  number = {6},
  pages = {384-394},
  doi = {10.11648/j.ijnfs.20160506.13},
  url = {https://doi.org/10.11648/j.ijnfs.20160506.13},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijnfs.20160506.13},
  abstract = {Coconut milk provides health benefits due to its medium chain fatty acids and is widely utilized in the food industry. However, there seems to be inadequate information on the optimal extraction conditions for coconut milk. In this study, a response surface methodology (RSM) based on central composite design (CCD) was employed to optimize the extraction time (X1), extraction temperature (X2) and particle size of coconut meat (X3) for coconut milk extraction. Yield, pH, viscosity and total solid content of coconut milk were evaluated as responses. Regression models were generated and adequacy tested with lack of fit test and coefficient of determination (R2). The results showed that extraction time; extraction temperature and particle size of coconut meat had significant (p˂ 0.05) effects on responses. The R2 for yield, pH, viscosity, and total solid content of coconut milk were 0.9976, 0.7352, 0.6748 and 0.9787 respectively. Optimum extraction time, temperature and particle size of coconut meat with the highest desirability index of 0.797 was 15 min, 40°C and ≤ 1617 µm respectively, while optimum yield, pH, viscosity, and total solid content of coconut milk were estimated at 61.129%, 6.6, 2.85 cp and 16.01% respectively. The experimental results obtained validate the predicted model within the acceptable range of the responses. The results also suggest that the obtained model is acceptable for the maximum milk yield and improved quality consistency.},
 year = {2016}
}

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TY  - JOUR
T1  - Optimization of Coconut (Cocos nucifera) Milk Extraction Using Response Surface Methodology
AU  - Victor Ephraim Edem
AU  - Aniekpeno Isaac Elijah
Y1  - 2016/10/18
PY  - 2016
N1  - https://doi.org/10.11648/j.ijnfs.20160506.13
DO  - 10.11648/j.ijnfs.20160506.13
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  - 384
EP  - 394
PB  - Science Publishing Group
SN  - 2327-2716
UR  - https://doi.org/10.11648/j.ijnfs.20160506.13
AB  - Coconut milk provides health benefits due to its medium chain fatty acids and is widely utilized in the food industry. However, there seems to be inadequate information on the optimal extraction conditions for coconut milk. In this study, a response surface methodology (RSM) based on central composite design (CCD) was employed to optimize the extraction time (X1), extraction temperature (X2) and particle size of coconut meat (X3) for coconut milk extraction. Yield, pH, viscosity and total solid content of coconut milk were evaluated as responses. Regression models were generated and adequacy tested with lack of fit test and coefficient of determination (R2). The results showed that extraction time; extraction temperature and particle size of coconut meat had significant (p˂ 0.05) effects on responses. The R2 for yield, pH, viscosity, and total solid content of coconut milk were 0.9976, 0.7352, 0.6748 and 0.9787 respectively. Optimum extraction time, temperature and particle size of coconut meat with the highest desirability index of 0.797 was 15 min, 40°C and ≤ 1617 µm respectively, while optimum yield, pH, viscosity, and total solid content of coconut milk were estimated at 61.129%, 6.6, 2.85 cp and 16.01% respectively. The experimental results obtained validate the predicted model within the acceptable range of the responses. The results also suggest that the obtained model is acceptable for the maximum milk yield and improved quality consistency.
VL  - 5
IS  - 6
ER  -

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Author Information

Victor Ephraim Edem

Department of Food Science and Technology, University of Uyo, Uyo, Nigeria
Aniekpeno Isaac Elijah

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

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APA Style

Victor Ephraim Edem, Aniekpeno Isaac Elijah. (2016). Optimization of Coconut (Cocos nucifera) Milk Extraction Using Response Surface Methodology. International Journal of Nutrition and Food Sciences, 5(6), 384-394. https://doi.org/10.11648/j.ijnfs.20160506.13

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ACS Style

Victor Ephraim Edem; Aniekpeno Isaac Elijah. Optimization of Coconut (Cocos nucifera) Milk Extraction Using Response Surface Methodology. Int. J. Nutr. Food Sci. 2016, 5(6), 384-394. doi: 10.11648/j.ijnfs.20160506.13

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AMA Style

Victor Ephraim Edem, Aniekpeno Isaac Elijah. Optimization of Coconut (Cocos nucifera) Milk Extraction Using Response Surface Methodology. Int J Nutr Food Sci. 2016;5(6):384-394. doi: 10.11648/j.ijnfs.20160506.13

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@article{10.11648/j.ijnfs.20160506.13,
  author = {Victor Ephraim Edem and Aniekpeno Isaac Elijah},
  title = {Optimization of Coconut (Cocos nucifera) Milk Extraction Using Response Surface Methodology},
  journal = {International Journal of Nutrition and Food Sciences},
  volume = {5},
  number = {6},
  pages = {384-394},
  doi = {10.11648/j.ijnfs.20160506.13},
  url = {https://doi.org/10.11648/j.ijnfs.20160506.13},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijnfs.20160506.13},
  abstract = {Coconut milk provides health benefits due to its medium chain fatty acids and is widely utilized in the food industry. However, there seems to be inadequate information on the optimal extraction conditions for coconut milk. In this study, a response surface methodology (RSM) based on central composite design (CCD) was employed to optimize the extraction time (X1), extraction temperature (X2) and particle size of coconut meat (X3) for coconut milk extraction. Yield, pH, viscosity and total solid content of coconut milk were evaluated as responses. Regression models were generated and adequacy tested with lack of fit test and coefficient of determination (R2). The results showed that extraction time; extraction temperature and particle size of coconut meat had significant (p˂ 0.05) effects on responses. The R2 for yield, pH, viscosity, and total solid content of coconut milk were 0.9976, 0.7352, 0.6748 and 0.9787 respectively. Optimum extraction time, temperature and particle size of coconut meat with the highest desirability index of 0.797 was 15 min, 40°C and ≤ 1617 µm respectively, while optimum yield, pH, viscosity, and total solid content of coconut milk were estimated at 61.129%, 6.6, 2.85 cp and 16.01% respectively. The experimental results obtained validate the predicted model within the acceptable range of the responses. The results also suggest that the obtained model is acceptable for the maximum milk yield and improved quality consistency.},
 year = {2016}
}

Copy | Download

TY  - JOUR
T1  - Optimization of Coconut (Cocos nucifera) Milk Extraction Using Response Surface Methodology
AU  - Victor Ephraim Edem
AU  - Aniekpeno Isaac Elijah
Y1  - 2016/10/18
PY  - 2016
N1  - https://doi.org/10.11648/j.ijnfs.20160506.13
DO  - 10.11648/j.ijnfs.20160506.13
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  - 384
EP  - 394
PB  - Science Publishing Group
SN  - 2327-2716
UR  - https://doi.org/10.11648/j.ijnfs.20160506.13
AB  - Coconut milk provides health benefits due to its medium chain fatty acids and is widely utilized in the food industry. However, there seems to be inadequate information on the optimal extraction conditions for coconut milk. In this study, a response surface methodology (RSM) based on central composite design (CCD) was employed to optimize the extraction time (X1), extraction temperature (X2) and particle size of coconut meat (X3) for coconut milk extraction. Yield, pH, viscosity and total solid content of coconut milk were evaluated as responses. Regression models were generated and adequacy tested with lack of fit test and coefficient of determination (R2). The results showed that extraction time; extraction temperature and particle size of coconut meat had significant (p˂ 0.05) effects on responses. The R2 for yield, pH, viscosity, and total solid content of coconut milk were 0.9976, 0.7352, 0.6748 and 0.9787 respectively. Optimum extraction time, temperature and particle size of coconut meat with the highest desirability index of 0.797 was 15 min, 40°C and ≤ 1617 µm respectively, while optimum yield, pH, viscosity, and total solid content of coconut milk were estimated at 61.129%, 6.6, 2.85 cp and 16.01% respectively. The experimental results obtained validate the predicted model within the acceptable range of the responses. The results also suggest that the obtained model is acceptable for the maximum milk yield and improved quality consistency.
VL  - 5
IS  - 6
ER  -

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