Application of multivariate analysis for detection of crude palm oil adulteration through fatty acid composition and triacylglycerol profile
This study focused on developing a reliable procedure for the identification of the adulteration of crude palm oil (CPO) by blending sludge oils (SO) and used vegetable oils (UVO) ranging from 1 to 20% (v/v). Fatty acids methyl esters (FAME) and Triacylglycerol composition consisting of all single a...
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Universiti Putra Malaysia Press
2015
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Online Access: | http://psasir.upm.edu.my/id/eprint/41834/1/Application%20of%20multivariate%20analysis%20for%20detection%20of%20crude%20palm%20oil%20adulteration%20through%20fatty%20acid%20composition%20and%20triacylglycerol%20profile.pdf http://psasir.upm.edu.my/id/eprint/41834/ http://www.pertanika.upm.edu.my/Pertanika%20PAPERS/JTAS%20Vol.%2038%20(3)%20Aug.%202015/07%20JTAS%200633-2014.pdf |
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my.upm.eprints.418342016-02-11T05:45:40Z http://psasir.upm.edu.my/id/eprint/41834/ Application of multivariate analysis for detection of crude palm oil adulteration through fatty acid composition and triacylglycerol profile Inthiram, Anand Kumar Mirhosseini, Hamed Tan, Chin Ping Mohamad, Rosfarizan Lai, Oi Ming This study focused on developing a reliable procedure for the identification of the adulteration of crude palm oil (CPO) by blending sludge oils (SO) and used vegetable oils (UVO) ranging from 1 to 20% (v/v). Fatty acids methyl esters (FAME) and Triacylglycerol composition consisting of all single and blended CPO were analysed using a gas chromatography (GC)-flame ionisation detector (GC-FID) and high performance liquid chromatography evaporative light scattering detector (HPLC-ELSD), respectively. The results were processed using the multivariate analysis i.e. principal component analysis (PCA) and cluster observation (CO) to discriminate the most applicable factors useful for detecting this adulteration. The results revealed that the combination of chemical properties and multivariate analysis resulted in a strong differentiation between the blends according to the amount of adulterant in the CPO. PCA and CO provided good results, allowing detection of the adulteration of the CPO with the SO and UVO as low as 5% and 2% respectively for each multivariate analysis. Universiti Putra Malaysia Press 2015-08 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/41834/1/Application%20of%20multivariate%20analysis%20for%20detection%20of%20crude%20palm%20oil%20adulteration%20through%20fatty%20acid%20composition%20and%20triacylglycerol%20profile.pdf Inthiram, Anand Kumar and Mirhosseini, Hamed and Tan, Chin Ping and Mohamad, Rosfarizan and Lai, Oi Ming (2015) Application of multivariate analysis for detection of crude palm oil adulteration through fatty acid composition and triacylglycerol profile. Pertanika Journal of Tropical Agricultural Science, 38 (3). pp. 389-398. ISSN 1511-3701; ESSN: 2231-8542 http://www.pertanika.upm.edu.my/Pertanika%20PAPERS/JTAS%20Vol.%2038%20(3)%20Aug.%202015/07%20JTAS%200633-2014.pdf |
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This study focused on developing a reliable procedure for the identification of the adulteration of crude palm oil (CPO) by blending sludge oils (SO) and used vegetable oils (UVO) ranging from 1 to 20% (v/v). Fatty acids methyl esters (FAME) and Triacylglycerol composition consisting of all single and blended CPO were analysed using a gas chromatography (GC)-flame ionisation detector (GC-FID) and high performance liquid chromatography evaporative light scattering detector (HPLC-ELSD), respectively. The results were processed using the multivariate analysis i.e. principal component analysis (PCA) and cluster observation (CO) to discriminate the most applicable factors useful for detecting this adulteration. The results revealed that the combination of chemical properties and multivariate analysis resulted in a strong differentiation between the blends according to the amount of adulterant in the CPO. PCA and CO provided good results, allowing detection of the adulteration of the CPO with the SO and UVO as low as 5% and 2% respectively for each multivariate analysis. |
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Article |
author |
Inthiram, Anand Kumar Mirhosseini, Hamed Tan, Chin Ping Mohamad, Rosfarizan Lai, Oi Ming |
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Inthiram, Anand Kumar Mirhosseini, Hamed Tan, Chin Ping Mohamad, Rosfarizan Lai, Oi Ming Application of multivariate analysis for detection of crude palm oil adulteration through fatty acid composition and triacylglycerol profile |
author_facet |
Inthiram, Anand Kumar Mirhosseini, Hamed Tan, Chin Ping Mohamad, Rosfarizan Lai, Oi Ming |
author_sort |
Inthiram, Anand Kumar |
title |
Application of multivariate analysis for detection of crude palm oil adulteration through fatty acid composition and triacylglycerol profile |
title_short |
Application of multivariate analysis for detection of crude palm oil adulteration through fatty acid composition and triacylglycerol profile |
title_full |
Application of multivariate analysis for detection of crude palm oil adulteration through fatty acid composition and triacylglycerol profile |
title_fullStr |
Application of multivariate analysis for detection of crude palm oil adulteration through fatty acid composition and triacylglycerol profile |
title_full_unstemmed |
Application of multivariate analysis for detection of crude palm oil adulteration through fatty acid composition and triacylglycerol profile |
title_sort |
application of multivariate analysis for detection of crude palm oil adulteration through fatty acid composition and triacylglycerol profile |
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Universiti Putra Malaysia Press |
publishDate |
2015 |
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http://psasir.upm.edu.my/id/eprint/41834/1/Application%20of%20multivariate%20analysis%20for%20detection%20of%20crude%20palm%20oil%20adulteration%20through%20fatty%20acid%20composition%20and%20triacylglycerol%20profile.pdf http://psasir.upm.edu.my/id/eprint/41834/ http://www.pertanika.upm.edu.my/Pertanika%20PAPERS/JTAS%20Vol.%2038%20(3)%20Aug.%202015/07%20JTAS%200633-2014.pdf |
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