Optimization of extraction conditions of flavonoids from celery seed using response surface methodology

Abstract

Celery seed is a potential medicinal material for the development of anti-gout agents because of its uric acid-lowering, xanthine oxidase inhibitory, anti-inflammatory and analgesic effects. In this study, the process of extraction of flavonoid from celery seed was optimized using response surface methodology. Various algorithms were used in order to model the relationship between output response (yield of extraction, total flavonoid content) and input parameters (ethanol concentration, temperature and solvent/solid ratio). The best model was established using multiple linear regression (MLR) algorithm. The optimal conditions were determined as follows: ethanol concentration: 90%; temperature: 90°C and the solvent/solid ratio: 4 ml/g. At these conditions, the yield of extraction was 11.57 ± 1.46% and the total flavonoid content was 4.922 ± 0.312 mg/g. The xanthine oxidase inhibitory effect of apigenin - the main flavonoid of celery seed, was evaluated with the IC₅₀ value of 0.247 µg/ml (95% CI 0.129–0.617 µg/ml). It was suggested that flavonoid might play a key role in the xanthine oxidase inhibitory activity of celery seed extract.

Appendix

See Figs. 3, 4, 5, 6 and Tables 4, 5, 6.

Fig. 3

RMSE of kNN models for yield of extraction (Y₁) with different values of k

Fig. 4

RMSE of kNN models for total flavonoid content (Y₂) with different values of k

Fig. 5

Desirability plot for optimization of the process of extraction of flavonoid from celery seed

Fig. 6

Superposition of the docking pose and the complexed ligand (RMSD = 0.5263 Å)

Table 4 ANOVA table of MLR model for yield of extraction (Y₁)

Table 5 ANOVA table of MLR model for total flavonoid content (Y₂)

Table 6 RMSE of ANNs with different number of neurons in hidden layer