OBJECTIVETo explore the feasibility of genetic algorithm (GA) on multiple objective blending technology for extractions of Cortex Fraxini.

METHODAccording to that the optimization objective was the combination of fingerprint similarity and the root-mean-square error of multiple key constituents, a new multiple objective optimization model of 10 batches extractions of Cortex Fraxini was built. The blending coefficient was obtained by genetic algorithm. The quality of 10 batches extractions of Cortex Fraxini that after blending was evaluated with the finger print similarity and root-mean-square error as indexes.

RESULTThe quality of 10 batches extractions of Cortex Fraxini that after blending was well improved. Comparing with the fingerprint of the control sample, the similarity was up, but the degree of variation is down. The relative deviation of the key constituents was less than 10%.

CONCLUSIONIt is proved that genetic algorithm works well on multiple objective blending technology for extractions of Cortex Fraxini. This method can be a reference to control the quality of extractions of Cortex Fraxini. Genetic algorithm in blending technology for extractions of Chinese medicines is advisable.

Algorithms ; Chromatography, High Pressure Liquid ; Drugs, Chinese Herbal ; analysis ; Medicine, Chinese Traditional ; standards ; Plants, Medicinal ; chemistry ; genetics ; Quality Control