RSM/ANN based optimized recovery of phenolics from mulberry leaves by enzyme-assisted extraction

Rahman Qadir, Farooq Anwar, Mazhar Amjad Gilani, Sadaf Zahoor, Muhammad Misbah ur Rehman and Muhammad Mustaqeem
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Rahman Qadir: Department of Chemistry, University of Sargodha, Sargodha, Pakistan
Farooq Anwar: Department of Chemistry, University of Sargodha, Sargodha, Pakistan
Mazhar Amjad Gilani: Department of Chemistry, COMSATS University, Lahore Campus, Lahore, Pakistan
Sadaf Zahoor: Department of Chemistry, University of Sargodha, Sargodha, Pakistan
Muhammad Misbah ur Rehman: Department of Chemistry, University of Lahore, Sargodha Campus, Sargodha, Pakistan
Muhammad Mustaqeem: Department of Chemistry, University of Sargodha, Bhakkar Campus, Bhakkar, Pakistan

Czech Journal of Food Sciences, 2019, vol. 37, issue 2, 99-105

Abstract: Recovery of phenolics from Morus alba leaves (MAL) and extraction into the solvent was optimized using enzyme-assisted extraction. The influence of four parameters, including enzyme concentration (EC), temperature (T), incubation time (t) and pH were investigated using rotatable central composite design (RCCD). Two factors, namely enzyme concentration and pH, exhibited significant effect on extraction efficacy yield of extractable phenolics from MAL. Furthermore, artificial neural network (ANN) model was executed to predict the relationship between dependent and independent variables. Among enzyme complexes (kemzyme dry-plus, natuzyme and zympex-014) employed for extraction, zympex-014 assisted extract depicted maximum amount of phenolic bioactives from MAL. Morphological changes in the cell wall of MAL residue were elucidated by scanning electron microscopy (SEM). The main phenolic compounds identified and quantified by gas chromatography mass spectrometry (GC/MS) in MAL extract were found to be quercetin, gallic acid, m-coumaric acid, cinnamic acid, syrinigc acid and vanillic acid.

Keywords: artificial neural network; GC/MS; Morus alba leaves; response surface methodology; SEM (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:caa:jnlcjf:v:37:y:2019:i:2:id:147-2018-cjfs

DOI: 10.17221/147/2018-CJFS

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