The high-performance liquid chromatography (HPLC) procedure based on gradient elution technique was used to separate flavonoids in leaves of Taxus baccata var. elegantissima and Metasequoia glyptostroboides. Optimization of chromatographic separations was supported by artificial neural networks. The best gradient conditions acquired to separate analyzed compounds were established and then used in experiments. Predictive errors were additionally calculated. Satisfactory correlation between predicted and experimental retention data were obtained.
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