Effect of extraction solvents on the biomolecules and antioxidant properties of Scorzonera undulata (Asteraceae): Application of factorial design optimization phenolic extraction.

BACKGROUND

Phenolic compounds were extracted and isolated from S. undulata roots.

METHODS

Sample of roots from E. hirta was tested for phenolic compounds, and in vitro antioxidant activity by diphenyl-1-picrylhydrazyl (DPPH) assay, ABTS, FRAP and reducing power was measured using cyano- ferrate method.

RESULTS

The methanolic fraction exhibited the highest total phenol content (6.12 ±0.11 mg AGE/g DW). On the other hand, the highest flavonoids concentration was observed in ethyl acetate fraction (2.90 ±0.05 mg CE/g DW) in addition to anthocyanins (28.56 ±3.96 mg/l). Besides, the highest level of tannins content was measured in the polar aprotic solvent ethyl acetate extract (3.25 ±0.06 mg CE/g DW). The different extracts of S. undulata were evaluated for their radical scavenging activities by means of the DPPH assay. The strongest scavenging activity was observed in methanolic fraction scavenged radicals effectively with IC   values of 0.14 ±0.02 mg/ml. Similarly, the potassium ferricyanide reduction (FRAP) and ABTS•+ of methanol extract. On the other hand, the total reducing power of ethyl acetate extract was found higher than of other extracts. This paper presents the application of the design-of experiment method for optimizing the extraction of phenolic content using methanol solvent. The resulting regression model has shown that the effect of temperature is not statistically significant (with >95% certainty), while that of agitation speed is. The two main effects are contributed by the solvent concentration and the maceration period.

CONCLUSIONS

Our results clearly showed that the extraction of phenolic compounds and their antioxidant capacity is significantly affected by solvent combinations. S. undulata presented the highest total phenolic content, total flavonoids content and antioxidant capacity values. The resulting regression model has shown that the effect of temperature is not statistically significant (with >95% certainty), while that of agitation speed is.