UV-Visible Spectroscopic Technique-Data Mining Tool as a Reliable, Fast, and Cost-Effective Method for the Prediction of Total Polyphenol Contents: Validation in a Bunch of Medicinal Plant Extracts
Medicinal plants extracts are a rich natural source of bioactive phytochemicals (mainly polyphenols). This study aims at determining the total polyphenols content (TPC) of nine medicinal plants extracted using the UV-visible (UV-Vis) spectroscopic method, along with the Orange Data Mining Tool (ODMT...
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MDPI AG
2022-09-01
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| Online Access: | https://www.mdpi.com/2076-3417/12/19/9430 |
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| author | Fathi Guemari Salah Eddine Laouini Abdelkrim Rebiai Abderrhmane Bouafia Souhaila Meneceur Ali Tliba Kamlah Ali Majrashi Sohad Abdulkaleg Alshareef Farid Menaa Ahmed Barhoum |
| author_facet | Fathi Guemari Salah Eddine Laouini Abdelkrim Rebiai Abderrhmane Bouafia Souhaila Meneceur Ali Tliba Kamlah Ali Majrashi Sohad Abdulkaleg Alshareef Farid Menaa Ahmed Barhoum |
| author_sort | Fathi Guemari |
| collection | DOAJ |
| description | Medicinal plants extracts are a rich natural source of bioactive phytochemicals (mainly polyphenols). This study aims at determining the total polyphenols content (TPC) of nine medicinal plants extracted using the UV-visible (UV-Vis) spectroscopic method, along with the Orange Data Mining Tool (ODMT). The TPC for the selected medicinal plant extracts (i.e., <i>Daucus carota</i> L. root, <i>Ruta Chalepensis</i> L. Leaves, <i>Anisosciadium</i> DC. Leaves, <i>Thymus vulgaris</i> L. Leaves, <i>Senna alexandrina</i> leaves, <i>Myrtus communis</i> L. leaves, <i>Silybum Marianum</i> L. Flower, <i>Silybum marianum</i> L. Leaves, and <i>Rosa moschata</i> Flower) was measured using gallic acid (GA) as a standard. The intended method requires a maximum of 1 mg of GA and only 1 mg of the plant extract. The wavelength range of the maximum absorption in the UV-vis spectrum was about 270 nm. For polyphenols, the purposed method linear dynamic concertation range (44.67 to 334.7 mg GA equivalent (GAE)/g dry weight (DW)) with a recovery percentage range of 95.3% to 104.3%, and the good regression value, was found to be R<sup>2</sup> = 0.999. This method was easy, fast, accurate, and less expensive than the conventional Folin–Ciocalteu method. |
| first_indexed | 2024-03-09T22:06:39Z |
| format | Article |
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| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-09T22:06:39Z |
| publishDate | 2022-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-7d9d162eca604a64b34ee359e406a2022023-11-23T19:39:23ZengMDPI AGApplied Sciences2076-34172022-09-011219943010.3390/app12199430UV-Visible Spectroscopic Technique-Data Mining Tool as a Reliable, Fast, and Cost-Effective Method for the Prediction of Total Polyphenol Contents: Validation in a Bunch of Medicinal Plant ExtractsFathi Guemari0Salah Eddine Laouini1Abdelkrim Rebiai2Abderrhmane Bouafia3Souhaila Meneceur4Ali Tliba5Kamlah Ali Majrashi6Sohad Abdulkaleg Alshareef7Farid Menaa8Ahmed Barhoum9Department of Process Engineering and Petrochemistry, Faculty of Technology, University of El Oued, El-Oued 39000, AlgeriaDepartment of Process Engineering and Petrochemistry, Faculty of Technology, University of El Oued, El-Oued 39000, AlgeriaDepartment of Chemistry, Faculty of Exact Sciences, University of El Oued, El-Oued 39000, AlgeriaDepartment of Process Engineering and Petrochemistry, Faculty of Technology, University of El Oued, El-Oued 39000, AlgeriaDepartment of Process Engineering and Petrochemistry, Faculty of Technology, University of El Oued, El-Oued 39000, AlgeriaDepartment of Process Engineering and Petrochemistry, Faculty of Technology, University of El Oued, El-Oued 39000, AlgeriaBiological Sciences Department, College of Science & Arts, King Abdulaziz University, Rabigh 21911, Saudi ArabiaDepartment of Biology, Faculty of Science, University of Tabuk, Tabuk 71491, Saudi ArabiaDepartment of Nanomedicine and Advanced Technologies, California Innovations Corporation-Fluorotronics, Inc., San Diego, CA 92037, USANanoStruc Research Group, Chemistry Department, Faculty of Science, Helwan University, Helwan 11795, Cairo, EgyptMedicinal plants extracts are a rich natural source of bioactive phytochemicals (mainly polyphenols). This study aims at determining the total polyphenols content (TPC) of nine medicinal plants extracted using the UV-visible (UV-Vis) spectroscopic method, along with the Orange Data Mining Tool (ODMT). The TPC for the selected medicinal plant extracts (i.e., <i>Daucus carota</i> L. root, <i>Ruta Chalepensis</i> L. Leaves, <i>Anisosciadium</i> DC. Leaves, <i>Thymus vulgaris</i> L. Leaves, <i>Senna alexandrina</i> leaves, <i>Myrtus communis</i> L. leaves, <i>Silybum Marianum</i> L. Flower, <i>Silybum marianum</i> L. Leaves, and <i>Rosa moschata</i> Flower) was measured using gallic acid (GA) as a standard. The intended method requires a maximum of 1 mg of GA and only 1 mg of the plant extract. The wavelength range of the maximum absorption in the UV-vis spectrum was about 270 nm. For polyphenols, the purposed method linear dynamic concertation range (44.67 to 334.7 mg GA equivalent (GAE)/g dry weight (DW)) with a recovery percentage range of 95.3% to 104.3%, and the good regression value, was found to be R<sup>2</sup> = 0.999. This method was easy, fast, accurate, and less expensive than the conventional Folin–Ciocalteu method.https://www.mdpi.com/2076-3417/12/19/9430medicinal plantsphytochemistryphytochemicalsphenolic compoundsgallic acidherbal drugs |
| spellingShingle | Fathi Guemari Salah Eddine Laouini Abdelkrim Rebiai Abderrhmane Bouafia Souhaila Meneceur Ali Tliba Kamlah Ali Majrashi Sohad Abdulkaleg Alshareef Farid Menaa Ahmed Barhoum UV-Visible Spectroscopic Technique-Data Mining Tool as a Reliable, Fast, and Cost-Effective Method for the Prediction of Total Polyphenol Contents: Validation in a Bunch of Medicinal Plant Extracts Applied Sciences medicinal plants phytochemistry phytochemicals phenolic compounds gallic acid herbal drugs |
| title | UV-Visible Spectroscopic Technique-Data Mining Tool as a Reliable, Fast, and Cost-Effective Method for the Prediction of Total Polyphenol Contents: Validation in a Bunch of Medicinal Plant Extracts |
| title_full | UV-Visible Spectroscopic Technique-Data Mining Tool as a Reliable, Fast, and Cost-Effective Method for the Prediction of Total Polyphenol Contents: Validation in a Bunch of Medicinal Plant Extracts |
| title_fullStr | UV-Visible Spectroscopic Technique-Data Mining Tool as a Reliable, Fast, and Cost-Effective Method for the Prediction of Total Polyphenol Contents: Validation in a Bunch of Medicinal Plant Extracts |
| title_full_unstemmed | UV-Visible Spectroscopic Technique-Data Mining Tool as a Reliable, Fast, and Cost-Effective Method for the Prediction of Total Polyphenol Contents: Validation in a Bunch of Medicinal Plant Extracts |
| title_short | UV-Visible Spectroscopic Technique-Data Mining Tool as a Reliable, Fast, and Cost-Effective Method for the Prediction of Total Polyphenol Contents: Validation in a Bunch of Medicinal Plant Extracts |
| title_sort | uv visible spectroscopic technique data mining tool as a reliable fast and cost effective method for the prediction of total polyphenol contents validation in a bunch of medicinal plant extracts |
| topic | medicinal plants phytochemistry phytochemicals phenolic compounds gallic acid herbal drugs |
| url | https://www.mdpi.com/2076-3417/12/19/9430 |
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