Multivariate regression and artificial neural network to predict phenolic content in Schinus terebinthifolius stem bark through TLC images-Reference-Cited by-同舟云学术

Multivariate regression and artificial neural network to predict phenolic content in Schinus terebinthifolius stem bark through TLC images

Published:2021-05-09 Issue:7-8 Volume:44 Page:350-357
ISSN:1082-6076
Container-title:Journal of Liquid Chromatography & Related Technologies
language:en
Short-container-title:Journal of Liquid Chromatography & Related Technologies

Author:

de Moraes Ramos Rhayanne Thaís¹²,Santana Maíra Araújo de³,Sousa Patrícia Andrade¹⁴,Assunção Ferreira Magda Rhayanny¹^ORCID,dos Santos Wellington Pinheiro⁵^ORCID,Lira Soares Luiz Alberto¹²⁴^ORCID

Affiliation:

1. Laboratory of Pharmacognosy, Department of Pharmaceutical Sciences, Federal University of Pernambuco, Recife, Brazil

2. Postgraduate Program in Therapeutic Innovation, Federal University of Pernambuco, Recife, Brazil

3. Postgraduate Program in Computer Engineering, University of Pernambuco, Recife, Brazil

4. Postgraduate Program in Pharmaceutical Sciences, Federal University of Pernambuco, Recife, Brazil

5. Postgraduate Program in Biomedical Engineering, Federal University of Pernambuco, Recife, Brazil

Funder

FACEPE

CNPq

Publisher

Informa UK Limited

Subject

Clinical Biochemistry,Pharmaceutical Science,Biochemistry,Analytical Chemistry

Link

https://www.tandfonline.com/doi/pdf/10.1080/10826076.2021.1932521

Reference20 articles.

1. Chromatography in the Detection and Characterization of Illegal Pharmaceutical Preparations

2. Biennial Review of Planar Chromatography: 2009–2011

3. A review on the recent advances in HPLC, UHPLC and UPLC analyses of naturally occurring cannabinoids (2010–2019)

4. Breast cancer diagnosis based on mammary thermography and extreme learning machines

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Determination of Libidibia ferrea Markers Using Spectrophotometry and Chemometric Tools with Comparison to a Standard High-Performance Liquid Chromatography (HPLC) Protocol;Analytical Letters;2022-02-07