Essential oil from black currant buds as chemotaxonomy marker and antimicrobial agent

Abstract

Dormant buds are recognized as valuable side product of the blackcurrant cultivation. Four blackcurrant varieties cultivated in Serbia, i.e., Ben Sarek, Ometa, Ben Lomond, and Ben Nevis, were evaluated for the content, chemical composition, and antimicrobial activity of their bud essential oils. The oil yields of buds harvested during two different growth periods ranged from 1.2-2.0%, and the variety Ometa had the highest yield among the tested varieties. GC-FID and GC/MS analysis of the oils allowed the identification of eight main components, i.e., α-pinene (1.6-5.4%), sabinene (1.9-38.4%), δ-car-3-ene (13.0-50.7%), β-phellandrene (2.9-18.0%), terpinolene (6.6-11.9%), terpinen-4-ol (0.9-6.6%), β-caryophyllene (3.8-10.4%), and α-humulene (0.2-4.1%). In addition, the similarity degree of the essential-oil compositions of buds harvested from the upper and lower parts of the shrubs was investigated by hierarchical clustering. All essential oils originating from the same genotype were grouped in the same cluster, indicating the reliability of essential oils as chemotaxonomic markers. For more detailed chemotaxonomic investigations, the three compounds with the greatest variance were chosen, i.e., sabinene, δ-car-3-ene, and β-phellandrene, which proved to be efficient for the variety distinction. Factor analysis showed that the essential-oil composition as chemotaxonomic marker in blackcurrants was more reliable for variety Ben Sarek than for variety Ben Nevis. Moreover, it was demonstrated that the essential oils had very strong inhibitory activity against all tested microorganisms. Fungi were more sensitive than bacteria; indeed their growth was completely inhibited at much lower concentrations. In comparison to commercial antibiotics, significantly lower concentrations of the oils were necessary for the complete inhibition of fungal growth.

Keywords: Antimicrobial activity; Blackcurrants; Chemotaxonomy; Essential oils; Hierarchical cluster analysis (HCA); Principal component analysis (PCA); Ribes nigrum.