Modeling for the efficient separation of bio-active catechins from green tea leaves. Issue 4 (4th March 2017)

• Record Type: Journal Article
• Authors: Shishodia, Abhishek; Kumar, Krishna; Manna, Mriganka Sekhar
• Is Part Of: Separation science and technology. Volume 52:Issue 4(2017)
• Page Start: 671
• Page End: 678
• Publication Date: 2017-03-04
• Subjects: ANN -- catechin -- recovery -- yield -- tributyl phosphate; Separation (Technology) -- Periodicals; 660.284205
• DOI: 10.1080/01496395.2016.1252777
• Languages: English
• ISSNs: 0149-6395

Abstract

ABSTRACT: Catechins are important bio-actives for the prevention of free radical induced diseases such as cancer, autoimmune disorders, aging etc. The extraction and recovery of catechins from their most abundant source, green tea leaves employ specific extractants (tributyl phosphate, TBP) in solvent ( n -decane) for higher selectivity, and ethanol as extracting and recovery agents, respectively. The yields of extraction and recovery of catechins vary nonlinearly with the various process variables. Consequently, the influences of the variables on the yields are found out and satisfactory models ( R 2 = 0.9866 and 0.9993 for extraction and recovery, respectively) are predicted through the Artificial Neural Network (ANN).