A multivariate modeling for analysis of factors controlling the particle size and viscosity in palm kernel oil esters-based nanoemulsions

An artificial neural network (ANN) was used to develop predictive models for studying and identifying factors that influence particle size and viscosity of sodium diclofenac-loaded palm kernel oil esters-nanomeulsions. The effect of four independent variables namely water content, oil and surfactant...

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Main Authors: Rezaee, Malahat, Basri, Mahiran, Raja Abdul Rahman, Raja Noor Zaliha, Salleh, Abu Bakar, Chaibakhsh, Naz, Masoumi, Hamid Reza Fard
Format: Article
Language:English
Published: Elsevier 2014
Online Access:http://psasir.upm.edu.my/id/eprint/36188/
http://psasir.upm.edu.my/id/eprint/36188/1/A%20multivariate%20modeling%20for%20analysis%20of%20factors%20controlling%20the%20particle%20size%20and%20viscosity%20in%20palm%20kernel%20oil%20esters.pdf
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author Rezaee, Malahat
Basri, Mahiran
Raja Abdul Rahman, Raja Noor Zaliha
Salleh, Abu Bakar
Chaibakhsh, Naz
Masoumi, Hamid Reza Fard
author_facet Rezaee, Malahat
Basri, Mahiran
Raja Abdul Rahman, Raja Noor Zaliha
Salleh, Abu Bakar
Chaibakhsh, Naz
Masoumi, Hamid Reza Fard
author_sort Rezaee, Malahat
building UPM Institutional Repository
collection Online Access
description An artificial neural network (ANN) was used to develop predictive models for studying and identifying factors that influence particle size and viscosity of sodium diclofenac-loaded palm kernel oil esters-nanomeulsions. The effect of four independent variables namely water content, oil and surfactant (O/S) ratio, mixing rate and mixing time were considered as inputs of the network trained. The particle size and viscosity of samples in various compositions prepared under different rate and time of high shear emulsification, were measured as output. Data, split into training, testing and validating sets, were modeled by incremental back propagation (IBP) algorithm. The developed model represents high quality performance of the neural network and its capability in modeling and identifying the critical factors that control preparation of the nanoemulsions. Water content with 30.82% importance was found to be the main parameter controlling the particle size and viscosity in the system, followed by O/S ratio, mixing rate and mixing time, with 27.28, 22.06 and 19.84% importance, respectively. The model was then employed to investigate the effect of composition and processing factors on particle size and viscosity of the nanoemulsions.
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institution Universiti Putra Malaysia
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spelling upm-361882015-10-29T07:36:22Z http://psasir.upm.edu.my/id/eprint/36188/ A multivariate modeling for analysis of factors controlling the particle size and viscosity in palm kernel oil esters-based nanoemulsions Rezaee, Malahat Basri, Mahiran Raja Abdul Rahman, Raja Noor Zaliha Salleh, Abu Bakar Chaibakhsh, Naz Masoumi, Hamid Reza Fard An artificial neural network (ANN) was used to develop predictive models for studying and identifying factors that influence particle size and viscosity of sodium diclofenac-loaded palm kernel oil esters-nanomeulsions. The effect of four independent variables namely water content, oil and surfactant (O/S) ratio, mixing rate and mixing time were considered as inputs of the network trained. The particle size and viscosity of samples in various compositions prepared under different rate and time of high shear emulsification, were measured as output. Data, split into training, testing and validating sets, were modeled by incremental back propagation (IBP) algorithm. The developed model represents high quality performance of the neural network and its capability in modeling and identifying the critical factors that control preparation of the nanoemulsions. Water content with 30.82% importance was found to be the main parameter controlling the particle size and viscosity in the system, followed by O/S ratio, mixing rate and mixing time, with 27.28, 22.06 and 19.84% importance, respectively. The model was then employed to investigate the effect of composition and processing factors on particle size and viscosity of the nanoemulsions. Elsevier 2014-01 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/36188/1/A%20multivariate%20modeling%20for%20analysis%20of%20factors%20controlling%20the%20particle%20size%20and%20viscosity%20in%20palm%20kernel%20oil%20esters.pdf Rezaee, Malahat and Basri, Mahiran and Raja Abdul Rahman, Raja Noor Zaliha and Salleh, Abu Bakar and Chaibakhsh, Naz and Masoumi, Hamid Reza Fard (2014) A multivariate modeling for analysis of factors controlling the particle size and viscosity in palm kernel oil esters-based nanoemulsions. Industrial Crops and Products, 52. pp. 506-511. ISSN 0926-6690; ESSN: 1872-633X 10.1016/j.indcrop.2013.10.046
spellingShingle Rezaee, Malahat
Basri, Mahiran
Raja Abdul Rahman, Raja Noor Zaliha
Salleh, Abu Bakar
Chaibakhsh, Naz
Masoumi, Hamid Reza Fard
A multivariate modeling for analysis of factors controlling the particle size and viscosity in palm kernel oil esters-based nanoemulsions
title A multivariate modeling for analysis of factors controlling the particle size and viscosity in palm kernel oil esters-based nanoemulsions
title_full A multivariate modeling for analysis of factors controlling the particle size and viscosity in palm kernel oil esters-based nanoemulsions
title_fullStr A multivariate modeling for analysis of factors controlling the particle size and viscosity in palm kernel oil esters-based nanoemulsions
title_full_unstemmed A multivariate modeling for analysis of factors controlling the particle size and viscosity in palm kernel oil esters-based nanoemulsions
title_short A multivariate modeling for analysis of factors controlling the particle size and viscosity in palm kernel oil esters-based nanoemulsions
title_sort multivariate modeling for analysis of factors controlling the particle size and viscosity in palm kernel oil esters-based nanoemulsions
url http://psasir.upm.edu.my/id/eprint/36188/
http://psasir.upm.edu.my/id/eprint/36188/
http://psasir.upm.edu.my/id/eprint/36188/1/A%20multivariate%20modeling%20for%20analysis%20of%20factors%20controlling%20the%20particle%20size%20and%20viscosity%20in%20palm%20kernel%20oil%20esters.pdf