Optimizing isolation process of kaempferitrin from leaves of Prunus cerasifera. (6th October 2019)

• Record Type: Journal Article
• Authors: Wu, Bo; Peng, Lijuan; Yang, Guoyan
• Is Part Of: Journal of food process engineering. Volume 42:Number 7(2019)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2019-10-06
• Subjects: Food industry and trade -- Periodicals; Food -- Analysis -- Periodicals; 664.005
• DOI: 10.1111/jfpe.13260
• Languages: English
• ISSNs: 0145-8876

Abstract

Abstract: Kaempferitrin was extracted from leaves of Prunus cerasifera with an average yield of 1.3 ± 0.18% ( n = 20). The purity of the product was over 98.5% as determined by high‐performance liquid chromatography. Dried and smashed leaves of P. cerasifera were subjected to extraction with 70% ethanol (vol/vol) at room temperature and the extract was concentrated by vacuum evaporation. The extract was separated using nonpolar and medium polar macroporous resin in series. The post‐column collecting solution was concentrated under reduced pressure and its product was obtained through secondary crystallization. Kaempferitrin obtained was structurally analyzed and characterized. The absorption of kaempferitrin to macroporous resin was analyzed thermodynamically and kinetically to determine its melting and turbidity point. After purification of mother liquor, the recovery rate was over 70%. Practical Applications: Prunus cerasifera is a plant resource that has yet to be tapped. Kaempferitrin in its leaves, with a content of 1.8–2.2%, is an important bioactive substance. Pharmacologically, kaempferitrin induces immune reactions in vitro, stimulates the secretion of adiponectin in adipocytes, elicits apoptosis, and possess antitumor effects. Separation of kaempferitrin from P. cerasifera leaves using the macroporous resin double‐column system is cost‐effective and simple. Moreover, the method can achieve high extraction efficiency. After crystallization, the purity was higher than 98.5%. The technology can be widely used in the preparation processes of medical agents. In addition, the results showed that the optimized parameters can be applied to the parameter prediction of related designs. Abstract :