Uv–Vis molecular spectral resolution of multi-level mixture design-fingerprints of yerba mate leaves by chemometric methods

Abstract

This study proposes the use of multivariate curve resolution with alternating least squares (MCR-ALS) to comprehensively analyze mixture design-fingerprints in yerba mate leaves, investigating the influence of multi-level factors such as sexual dimorphism (male and female plants) and cultivation systems (monoculture and agroforestry). Plant extracts were obtained according to a mixture design with ethanol, dichloromethane, and hexane and their binary and ternary combinations. Through simultaneous resolution of the diverse profiles obtained using these different solvents, seven components were successfully identified, collectively explaining 98.57% of the data variance. Each component was associated with distinct absorption bands indicative of their chemical composition with compounds such as chlorogenic acids, xanthophylls, catechin, caffeine, kaempferol, lycopene, carotene, and chlorophyll. The MCR-ALS resolved profiles revealed significant variations in component concentrations across experimental conditions, facilitating the determination of the effects of sexual dimorphism and cultivation systems on yerba mate metabolism. The ANOVA-simultaneous component analysis (ASCA) highlighted the chemical differences of yerba mate leaves due to the cultivation system. Binary and ternary mixture extractants resulted to be more effective than pure solvents in determining the significance of effects on the chemical composition of yerba mate. Partial least squares discriminant analysis (PLS-DA) demonstrated the most distinct metabolic profiles of yerba mate leaves under monoculture and agroforestry conditions, with specific components playing crucial roles in their discrimination. This study shows the robustness of the MCR-ALS method in resolving complex chemical data, offering valuable insights into the diverse chemical composition of yerba mate under different experimental conditions. The congruence of results across various analyses reinforced the reliability and validity of the methodology, emphasizing its potential use for exploring the composition and properties of natural products.