Quality Assessment of Medicinal Plants via Chemometric Exploration of Quantitative NMR Data: A Review
Abdelkrim Rebiai, Bachir Ben Seghir, Hadia Hemmami, Soumeia Zeghoud, Ilham Ben Amor, Imane Kouadri, Mohammed Messaoudi, Ardalan Pasdaran, Gianluca Caruso, Somesh Sharma, Maria Atanassova, Paweł Pohl
Abstract
Since ancient times, herbal medicines (HM) have played a vital role in worldwide healthcare systems. It is therefore critical that a thorough evaluation of the quality and control of its complicated chemical makeup be conducted, in order to ensure its efficacy and safety. The notion of HM chemical prints, which aim to acquire a full characterization of compound chemical matrices, has become one of the most persuasive techniques for HM quality evaluation during the last few decades. The link between NMR and chemometrics is discussed in this article. The chemometric latent variable technique has been shown to be extremely valuable in inductive studies of biological systems as well as in solving industrial challenges. The results of unsupervised data exploration utilizing main component analysis as well as the multivariate curve resolution, were various. On the other hand, many contemporary NMR applications in metabolomics and quality control are based on supervised regression or classification analyses.