Comparison of partial least squares and random forests for evaluating relationship between phenolics and bioactivities of Neptunia oleracea
Background: Neptunia oleracea is a plant consumed as a vegetable and which has been used as a folk remedy for several diseases. Herein, two regression models (partial least squares, PLS; and random forest, RF) in a metabolomics approach were compared and applied to the evaluation of the relationship...
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| Format: | Article |
| Language: | English |
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John Wiley & Sons
2018
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| Online Access: | http://psasir.upm.edu.my/id/eprint/72072/ http://psasir.upm.edu.my/id/eprint/72072/1/Comparison%20of%20partial%20least%20squares%20and%20random%20forests%20for%20evaluating%20relationship%20between%20phenolics%20and%20bioactivities%20of%20Neptunia%20oleracea.pdf |
| _version_ | 1848857033073229824 |
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| author | Lee, Soo Yee Mediani, Ahmed Maulidiani, Maulidiani Khatib, Alfi Ismail, Intan Safinar Zawawi, Norhasnida Abas, Faridah |
| author_facet | Lee, Soo Yee Mediani, Ahmed Maulidiani, Maulidiani Khatib, Alfi Ismail, Intan Safinar Zawawi, Norhasnida Abas, Faridah |
| author_sort | Lee, Soo Yee |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | Background: Neptunia oleracea is a plant consumed as a vegetable and which has been used as a folk remedy for several diseases. Herein, two regression models (partial least squares, PLS; and random forest, RF) in a metabolomics approach were compared and applied to the evaluation of the relationship between phenolics and bioactivities of N. oleracea. In addition, the effects of different extraction conditions on the phenolic constituents were assessed by pattern recognition analysis. Results: Comparison of the PLS and RF showed that RF exhibited poorer generalization and hence poorer predictive performance. Both the regression coefficient of PLS and the variable importance of RF revealed that quercetin and kaempferol derivatives, caffeic acid and vitexin-2-O-rhamnoside were significant towards the tested bioactivities. Furthermore, principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) results showed that sonication and absolute ethanol are the preferable extraction method and ethanol ratio, respectively, to produce N. oleracea extracts with high phenolic levels and therefore high DPPH scavenging and α-glucosidase inhibitory activities. Conclusion: Both PLS and RF are useful regression models in metabolomics studies. This work provides insight into the performance of different multivariate data analysis tools and the effects of different extraction conditions on the extraction of desired phenolics from plants. |
| first_indexed | 2025-11-15T11:51:07Z |
| format | Article |
| id | upm-72072 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T11:51:07Z |
| publishDate | 2018 |
| publisher | John Wiley & Sons |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-720722020-02-05T04:26:46Z http://psasir.upm.edu.my/id/eprint/72072/ Comparison of partial least squares and random forests for evaluating relationship between phenolics and bioactivities of Neptunia oleracea Lee, Soo Yee Mediani, Ahmed Maulidiani, Maulidiani Khatib, Alfi Ismail, Intan Safinar Zawawi, Norhasnida Abas, Faridah Background: Neptunia oleracea is a plant consumed as a vegetable and which has been used as a folk remedy for several diseases. Herein, two regression models (partial least squares, PLS; and random forest, RF) in a metabolomics approach were compared and applied to the evaluation of the relationship between phenolics and bioactivities of N. oleracea. In addition, the effects of different extraction conditions on the phenolic constituents were assessed by pattern recognition analysis. Results: Comparison of the PLS and RF showed that RF exhibited poorer generalization and hence poorer predictive performance. Both the regression coefficient of PLS and the variable importance of RF revealed that quercetin and kaempferol derivatives, caffeic acid and vitexin-2-O-rhamnoside were significant towards the tested bioactivities. Furthermore, principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) results showed that sonication and absolute ethanol are the preferable extraction method and ethanol ratio, respectively, to produce N. oleracea extracts with high phenolic levels and therefore high DPPH scavenging and α-glucosidase inhibitory activities. Conclusion: Both PLS and RF are useful regression models in metabolomics studies. This work provides insight into the performance of different multivariate data analysis tools and the effects of different extraction conditions on the extraction of desired phenolics from plants. John Wiley & Sons 2018-01 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/72072/1/Comparison%20of%20partial%20least%20squares%20and%20random%20forests%20for%20evaluating%20relationship%20between%20phenolics%20and%20bioactivities%20of%20Neptunia%20oleracea.pdf Lee, Soo Yee and Mediani, Ahmed and Maulidiani, Maulidiani and Khatib, Alfi and Ismail, Intan Safinar and Zawawi, Norhasnida and Abas, Faridah (2018) Comparison of partial least squares and random forests for evaluating relationship between phenolics and bioactivities of Neptunia oleracea. Journal of the Science of Food and Agriculture, 98 (1). 240 - 252. ISSN 0022-5142; ESSN: 1097-0010 https://onlinelibrary.wiley.com/doi/full/10.1002/jsfa.8462 10.1002/jsfa.8462 |
| spellingShingle | Lee, Soo Yee Mediani, Ahmed Maulidiani, Maulidiani Khatib, Alfi Ismail, Intan Safinar Zawawi, Norhasnida Abas, Faridah Comparison of partial least squares and random forests for evaluating relationship between phenolics and bioactivities of Neptunia oleracea |
| title | Comparison of partial least squares and random forests for evaluating relationship between phenolics and bioactivities of Neptunia oleracea |
| title_full | Comparison of partial least squares and random forests for evaluating relationship between phenolics and bioactivities of Neptunia oleracea |
| title_fullStr | Comparison of partial least squares and random forests for evaluating relationship between phenolics and bioactivities of Neptunia oleracea |
| title_full_unstemmed | Comparison of partial least squares and random forests for evaluating relationship between phenolics and bioactivities of Neptunia oleracea |
| title_short | Comparison of partial least squares and random forests for evaluating relationship between phenolics and bioactivities of Neptunia oleracea |
| title_sort | comparison of partial least squares and random forests for evaluating relationship between phenolics and bioactivities of neptunia oleracea |
| url | http://psasir.upm.edu.my/id/eprint/72072/ http://psasir.upm.edu.my/id/eprint/72072/ http://psasir.upm.edu.my/id/eprint/72072/ http://psasir.upm.edu.my/id/eprint/72072/1/Comparison%20of%20partial%20least%20squares%20and%20random%20forests%20for%20evaluating%20relationship%20between%20phenolics%20and%20bioactivities%20of%20Neptunia%20oleracea.pdf |