N-alkane profiles of lard and vegetable oils, and their chemometrics differentiation
This research aims to examine fat from various vegetable oils using n-alkane profiles, as well as chemometrics and machine learning. Unsaponifiable vegetable oils (coconut, peanut, palm and soybean oils) were separated and analysed using gas chromatography-mass spectrometry (GC-MS) to investigate th...
| Main Authors: | , , , , , , , , , |
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| Format: | Article |
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Malaysian Palm Oil Board
2023
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| Online Access: | http://psasir.upm.edu.my/id/eprint/109375/ |
| _version_ | 1848865354571317248 |
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| author | Sapian, Nur Ain Syaqirah Mohamad Roslan, Muhamad Aidilfitri Mohd Hashim, Amalia Abdul Manaf, Yanty Noorzianna Mohd Desa, Mohd Nasir Halim, Murni Abdullah Sani, Muhamad Shirwan Yusof, Mohd Termizi Pak Dek, Mohd Sabri Wasoh, Helmi |
| author_facet | Sapian, Nur Ain Syaqirah Mohamad Roslan, Muhamad Aidilfitri Mohd Hashim, Amalia Abdul Manaf, Yanty Noorzianna Mohd Desa, Mohd Nasir Halim, Murni Abdullah Sani, Muhamad Shirwan Yusof, Mohd Termizi Pak Dek, Mohd Sabri Wasoh, Helmi |
| author_sort | Sapian, Nur Ain Syaqirah |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | This research aims to examine fat from various vegetable oils using n-alkane profiles, as well as chemometrics and machine learning. Unsaponifiable vegetable oils (coconut, peanut, palm and soybean oils) were separated and analysed using gas chromatography-mass spectrometry (GC-MS) to investigate the n-alkane profiles of each fat. The authenticity of the detected n-alkane profiles was determined by comparing to the retention time of C7-C40 n-alkane standards. The test designs were developed using Principal Component Analysis (PCA), Hierarchical Clustering Analysis (HCA), Partial Least Squares-Discriminant Analysis (PLS-DA), and Random Forest (RF). Both PCA and HCA appeared to provide a clear distinction between each of the vegetable oil tests. Based on the PLS-DA and RF determination, tetracosane (C24) and octadecane (C18) are proposed as the key n-alkane markers for separating lard from vegetable oils. These findings suggest that additional work may be required to achieve and determine the different characteristics across oils in numerous statistical applications, notably chemometrics and machine learning. |
| first_indexed | 2025-11-15T14:03:23Z |
| format | Article |
| id | upm-109375 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-15T14:03:23Z |
| publishDate | 2023 |
| publisher | Malaysian Palm Oil Board |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-1093752024-08-05T03:40:06Z http://psasir.upm.edu.my/id/eprint/109375/ N-alkane profiles of lard and vegetable oils, and their chemometrics differentiation Sapian, Nur Ain Syaqirah Mohamad Roslan, Muhamad Aidilfitri Mohd Hashim, Amalia Abdul Manaf, Yanty Noorzianna Mohd Desa, Mohd Nasir Halim, Murni Abdullah Sani, Muhamad Shirwan Yusof, Mohd Termizi Pak Dek, Mohd Sabri Wasoh, Helmi This research aims to examine fat from various vegetable oils using n-alkane profiles, as well as chemometrics and machine learning. Unsaponifiable vegetable oils (coconut, peanut, palm and soybean oils) were separated and analysed using gas chromatography-mass spectrometry (GC-MS) to investigate the n-alkane profiles of each fat. The authenticity of the detected n-alkane profiles was determined by comparing to the retention time of C7-C40 n-alkane standards. The test designs were developed using Principal Component Analysis (PCA), Hierarchical Clustering Analysis (HCA), Partial Least Squares-Discriminant Analysis (PLS-DA), and Random Forest (RF). Both PCA and HCA appeared to provide a clear distinction between each of the vegetable oil tests. Based on the PLS-DA and RF determination, tetracosane (C24) and octadecane (C18) are proposed as the key n-alkane markers for separating lard from vegetable oils. These findings suggest that additional work may be required to achieve and determine the different characteristics across oils in numerous statistical applications, notably chemometrics and machine learning. Malaysian Palm Oil Board 2023-08-22 Article PeerReviewed Sapian, Nur Ain Syaqirah and Mohamad Roslan, Muhamad Aidilfitri and Mohd Hashim, Amalia and Abdul Manaf, Yanty Noorzianna and Mohd Desa, Mohd Nasir and Halim, Murni and Abdullah Sani, Muhamad Shirwan and Yusof, Mohd Termizi and Pak Dek, Mohd Sabri and Wasoh, Helmi (2023) N-alkane profiles of lard and vegetable oils, and their chemometrics differentiation. Journal of Oil Palm Research. pp. 1-10. ISSN 2811-4701 http://jopr.mpob.gov.my/n-alkane-profiles-of-lard-and-vegetable-oils-and-their-chemometrics-differentiation/ 10.21894/jopr.2023.0038 |
| spellingShingle | Sapian, Nur Ain Syaqirah Mohamad Roslan, Muhamad Aidilfitri Mohd Hashim, Amalia Abdul Manaf, Yanty Noorzianna Mohd Desa, Mohd Nasir Halim, Murni Abdullah Sani, Muhamad Shirwan Yusof, Mohd Termizi Pak Dek, Mohd Sabri Wasoh, Helmi N-alkane profiles of lard and vegetable oils, and their chemometrics differentiation |
| title | N-alkane profiles of lard and vegetable oils, and their chemometrics differentiation |
| title_full | N-alkane profiles of lard and vegetable oils, and their chemometrics differentiation |
| title_fullStr | N-alkane profiles of lard and vegetable oils, and their chemometrics differentiation |
| title_full_unstemmed | N-alkane profiles of lard and vegetable oils, and their chemometrics differentiation |
| title_short | N-alkane profiles of lard and vegetable oils, and their chemometrics differentiation |
| title_sort | n-alkane profiles of lard and vegetable oils, and their chemometrics differentiation |
| url | http://psasir.upm.edu.my/id/eprint/109375/ http://psasir.upm.edu.my/id/eprint/109375/ http://psasir.upm.edu.my/id/eprint/109375/ |