Article Versions Notes

Guemari F, Laouini SE, Rebiai A, Bouafia A, Meneceur S, Tliba A, Majrashi KA, Alshareef SA, Menaa F, Barhoum A. 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. 2022; 12(19):9430. https://doi.org/10.3390/app12199430

Guemari, Fathi, Salah Eddine Laouini, Abdelkrim Rebiai, Abderrhmane Bouafia, Souhaila Meneceur, Ali Tliba, Kamlah Ali Majrashi, Sohad Abdulkaleg Alshareef, Farid Menaa, and Ahmed Barhoum. 2022. "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 12, no. 19: 9430. https://doi.org/10.3390/app12199430

Guemari, F., Laouini, S. E., Rebiai, A., Bouafia, A., Meneceur, S., Tliba, A., Majrashi, K. A., Alshareef, S. A., Menaa, F., & Barhoum, A. (2022). 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, 12(19), 9430. https://doi.org/10.3390/app12199430