Discriminative analysis of different grades of gaharu (Aquilaria malaccensis Lamk.) via 1H-NMR-based metabolomics using PLS-DA and random forests classification models
Gaharu (agarwood, Aquilaria malaccensis Lamk.) is a valuable tropical rainforest product traded internationally for its distinctive fragrance. It is not only popular as incense and in perfumery, but also favored in traditional medicine due to its sedative, carminative, cardioprotective and analgesic...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI
2017
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| Online Access: | http://psasir.upm.edu.my/id/eprint/15356/1/15356.pdf |
| _version_ | 1825945605297405952 |
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| author | Ismail, Siti Nazirah Maulidiani, M. Akhtar, Muhammad Tayyab Abas, Faridah Ismail, Intan Safinar Khatib, Alfi Mohamad Ali, Nor Azah Shaari, Khozirah |
| author_facet | Ismail, Siti Nazirah Maulidiani, M. Akhtar, Muhammad Tayyab Abas, Faridah Ismail, Intan Safinar Khatib, Alfi Mohamad Ali, Nor Azah Shaari, Khozirah |
| author_sort | Ismail, Siti Nazirah |
| collection | UPM |
| description | Gaharu (agarwood, Aquilaria malaccensis Lamk.) is a valuable tropical rainforest product traded internationally for its distinctive fragrance. It is not only popular as incense and in perfumery, but also favored in traditional medicine due to its sedative, carminative, cardioprotective and analgesic effects. The current study addresses the chemical differences and similarities between gaharu samples of different grades, obtained commercially, using 1H-NMR-based metabolomics. Two classification models: partial least squares-discriminant analysis (PLS-DA) and Random Forests were developed to classify the gaharu samples on the basis of their chemical constituents. The gaharu samples could be reclassified into a ‘high grade’ group (samples A, B and D), characterized by high contents of kusunol, jinkohol, and 10-epi-γ-eudesmol; an ‘intermediate grade’ group (samples C, F and G), dominated by fatty acid and vanillic acid; and a ‘low grade’ group (sample E and H), which had higher contents of aquilarone derivatives and phenylethyl chromones. The results showed that 1H- NMR-based metabolomics can be a potential method to grade the quality of gaharu samples on the basis of their chemical constituents. |
| first_indexed | 2024-03-06T07:34:06Z |
| format | Article |
| id | upm.eprints-15356 |
| institution | Universiti Putra Malaysia |
| language | English |
| last_indexed | 2024-03-06T07:34:06Z |
| publishDate | 2017 |
| publisher | MDPI |
| record_format | dspace |
| spelling | upm.eprints-153562019-07-08T07:30:25Z http://psasir.upm.edu.my/id/eprint/15356/ Discriminative analysis of different grades of gaharu (Aquilaria malaccensis Lamk.) via 1H-NMR-based metabolomics using PLS-DA and random forests classification models Ismail, Siti Nazirah Maulidiani, M. Akhtar, Muhammad Tayyab Abas, Faridah Ismail, Intan Safinar Khatib, Alfi Mohamad Ali, Nor Azah Shaari, Khozirah Gaharu (agarwood, Aquilaria malaccensis Lamk.) is a valuable tropical rainforest product traded internationally for its distinctive fragrance. It is not only popular as incense and in perfumery, but also favored in traditional medicine due to its sedative, carminative, cardioprotective and analgesic effects. The current study addresses the chemical differences and similarities between gaharu samples of different grades, obtained commercially, using 1H-NMR-based metabolomics. Two classification models: partial least squares-discriminant analysis (PLS-DA) and Random Forests were developed to classify the gaharu samples on the basis of their chemical constituents. The gaharu samples could be reclassified into a ‘high grade’ group (samples A, B and D), characterized by high contents of kusunol, jinkohol, and 10-epi-γ-eudesmol; an ‘intermediate grade’ group (samples C, F and G), dominated by fatty acid and vanillic acid; and a ‘low grade’ group (sample E and H), which had higher contents of aquilarone derivatives and phenylethyl chromones. The results showed that 1H- NMR-based metabolomics can be a potential method to grade the quality of gaharu samples on the basis of their chemical constituents. MDPI 2017 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/15356/1/15356.pdf Ismail, Siti Nazirah and Maulidiani, M. and Akhtar, Muhammad Tayyab and Abas, Faridah and Ismail, Intan Safinar and Khatib, Alfi and Mohamad Ali, Nor Azah and Shaari, Khozirah (2017) Discriminative analysis of different grades of gaharu (Aquilaria malaccensis Lamk.) via 1H-NMR-based metabolomics using PLS-DA and random forests classification models. Molecules, 22 (10). art. no. 1612. pp. 1-13. ISSN 1420-3049 https://www.mdpi.com/1420-3049/22/10/1612 10.3390/molecules22101612 |
| spellingShingle | Ismail, Siti Nazirah Maulidiani, M. Akhtar, Muhammad Tayyab Abas, Faridah Ismail, Intan Safinar Khatib, Alfi Mohamad Ali, Nor Azah Shaari, Khozirah Discriminative analysis of different grades of gaharu (Aquilaria malaccensis Lamk.) via 1H-NMR-based metabolomics using PLS-DA and random forests classification models |
| title | Discriminative analysis of different grades of gaharu (Aquilaria malaccensis Lamk.) via 1H-NMR-based metabolomics using PLS-DA and random forests classification models |
| title_full | Discriminative analysis of different grades of gaharu (Aquilaria malaccensis Lamk.) via 1H-NMR-based metabolomics using PLS-DA and random forests classification models |
| title_fullStr | Discriminative analysis of different grades of gaharu (Aquilaria malaccensis Lamk.) via 1H-NMR-based metabolomics using PLS-DA and random forests classification models |
| title_full_unstemmed | Discriminative analysis of different grades of gaharu (Aquilaria malaccensis Lamk.) via 1H-NMR-based metabolomics using PLS-DA and random forests classification models |
| title_short | Discriminative analysis of different grades of gaharu (Aquilaria malaccensis Lamk.) via 1H-NMR-based metabolomics using PLS-DA and random forests classification models |
| title_sort | discriminative analysis of different grades of gaharu aquilaria malaccensis lamk via 1h nmr based metabolomics using pls da and random forests classification models |
| url | http://psasir.upm.edu.my/id/eprint/15356/1/15356.pdf |
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