Chemotaxonomic study of Chrysobalanus icaco Linnaeus (Chrysobalanaceae) using ultra-high performance liquid chromatography coupled with diode array detection fingerprint in combination with multivariate analysis

Author(s)

Nunes Pinto Paracampo, Nadia Eligia ; Prance, Ghillean Tolmie ; Poppi, Ronei Jesus ; Fracassi da Silva, Jose Alberto

• Document type: Journal article
• Source: JOURNAL OF SEPARATION SCIENCE; v. 40, n. 10, p. 2161-2169, MAY 2017.
• Web of Science Citations: 0

Abstract

We investigated a strategy for the chemotaxonomy study of Chrysobalanus icaco Linnaeus (Chrysobalanaceae) based on ultra-high performance liquid chromatography coupled with diode array detection fingerprint in combination with multivariate analysis. Two models using principal component analysis and partial least squares discriminant analysis were developed, and the samples could be successfully classified into two classes: Class 1 (red morphotype) and Class 2 (white and black morphotypes). Furthermore, ultra-high performance liquid chromatography coupled with diode array and electrospray ionization tandem mass spectrometry was used to identify the main compounds responsible for class separation. The partial least squares discriminant analysis model accurately classified the C. icaco samples using an external validation subset with prediction ability of 100% and revealed the existence of two chemotypes. The most important finding obtained in this study is that the three morphotypes distinguished by the mature fruit color (white, red, and black) are not all phytoequivalent to each other. (AU)

• FAPESP's process: 13/22127-2 - Development of novel materials strategic for integrated analytical devices
• Grantee: Lauro Tatsuo Kubota
• Support Opportunities: Research Projects - Thematic Grants