Box–Behnken experimental design for extraction optimization of alkaloids from Erythrina verna Vell. trunk barks and LC Method Validation - Rambo, Douglas F.; Biegelmeyer, Renata; Toson, Natally S.B.; Dresch, Roger R.; Moreno, Paulo R.H.; Henriques, Amélia T. (Industrial crops and products, 2019)
[Display omitted] •An HPLC-DAD method for alkaloid quantification of E. verna trunk barks was validated.•11-hydroxyerythratidinone was identified as the major compound of E. verna.•The alkaloid extraction of E. verna was optimized by a Box-Behnken design.•The predicted optimal yield was 0.625 g% of alkaloids.•The second-order polynomial model showed a predictive capacity of 95.57%. The Erythrina genus is well studied due to the presence of tetracyclic alkaloids with anxiolytic properties. Erythrina verna and other species are known by the collective popular name “mulungu”. Thus, it is very important to establish analytical methods to standardize marketed herbal products. The purpose of this study was to develop and validate a method by HPLC-DAD for quantification of total alkaloid content of E. verna Vell. trunk barks. It also sought the chemical characterization of E. verna fraction of total alkaloids (FTA). In order to maximize the yield of the total alkaloid content from E. verna, a three-level three-factor Box-Behnken design (BBD) was employed to determine the optimal conditions for dynamic maceration. The HPLC-DAD method was validated using galantamine hydrobromide as internal standard, and showed to be linear, precise, accurate, specific, and robust. GC–MS and HRMS-ESI analyses identified the alkaloids 11-hydroxyerythravine (1), 11-hydroxyerythratidinone (2), 3-demetoxyerythratidinone (3), erythratidinone (4), and dihydroerysotrine (5). The HPLC method developed enabled us to distinguish E. verna barks from other species (E. velutina and E. falcata) and different parts of E. verna (barks, flowers and leaves). For BBD design, it was applied plant:solvent ratio (X1), extraction time (X2), and granulometry (X3) as factors. The adjusted regression coefficient (R2 = 0.9404) and the lack-of-fit test (P > 0.05) showed a good accuracy of the derived model and no inadequacy was detected, being adequate to explain the data. Linear terms of XI, X2, and quadratic terms related to it were statistically significant (P <  0.05). On the other hand, only the linear term of X3 showed to affect the extraction yield of alkaloids. The predicted optimal yield was 0.625 g% using plant:solvent ratio of 1:60 (m/v), 5.47 h, and granulometry range of 710–1000 μm. The second-order polynomial model showed a predictive capacity of 95.57%. Bearing in mind that there is no available pharmacopoeia data for E. verna barks, these results may be useful for quality control and for maximizing yields of alkaloids for industry purpose.