Enzymatic hydrolysis and modelling of fermentable sugar production from kitchen waste / Sharifah Iziuna Sayed Jamaludin

Enzymatic hydrolysis and modelling of fermentable sugar production from kitchen waste / Sharifah Iziuna Sayed Jamaludin

This study focused on maximizing the amount of reducing sugar produced from enzymatic hydrolysis of kitchen waste catalyzed by cellulase from Trichoderma viride and Trichoderma reesei, which was used separately to compare the results obtained from each enzyme. Effects of enzyme dosage (X/), substrat...

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Main Author: Sayed Jamaludin, Sharifah Iziuna
Format: Thesis
Language:English
Published: 2014
Online Access:http://ir.uitm.edu.my/id/eprint/16445/
http://ir.uitm.edu.my/id/eprint/16445/1/TM_SHARIFAH%20IZIUNA%20SAYED%20JAMALUDIN%20EH%2014_5.pdf
id uitm-16445
recordtype eprints
spelling uitm-164452019-02-21T02:23:33Z http://ir.uitm.edu.my/id/eprint/16445/ Enzymatic hydrolysis and modelling of fermentable sugar production from kitchen waste / Sharifah Iziuna Sayed Jamaludin Sayed Jamaludin, Sharifah Iziuna This study focused on maximizing the amount of reducing sugar produced from enzymatic hydrolysis of kitchen waste catalyzed by cellulase from Trichoderma viride and Trichoderma reesei, which was used separately to compare the results obtained from each enzyme. Effects of enzyme dosage (X/), substrate concentration (X2), hydrolysis time (X3) and temperature (X4) were evaluated by Full Factorial Design (FFD) to determine the significant parameters affecting the production of reducing sugar. Optimization of process conditions were also performed using Central Composite Design (CCD) within the range employed for each independent variable. All the variables evaluated using FFD was found to have a significant effect towards the production of reducing sugar. The study has shown that enzymatic hydrolysis catalyzed by cellulase from T. viride is efficient in producing high amount of reducing sugar. A modelling study on enzymatic hydrolysis of kitchen waste was also performed to predict the reducing sugar yield using the datasets obtained from Response Surface Methodology (RSM) studies. A multi-layer feed-forward backpropagation artificial neural network (ANN) models were developed for enzymatic hydrolysis with input variables chosen from RSM studies. A comparative observation between ANN model and RSM model was also performed. Based on the R2 (correlation coefficient) and MSE (mean square error) values, it was concluded that ANN model is more accurate in predicting the reducing sugar yield than RSM model. 2014 Thesis NonPeerReviewed text en http://ir.uitm.edu.my/id/eprint/16445/1/TM_SHARIFAH%20IZIUNA%20SAYED%20JAMALUDIN%20EH%2014_5.pdf Sayed Jamaludin, Sharifah Iziuna (2014) Enzymatic hydrolysis and modelling of fermentable sugar production from kitchen waste / Sharifah Iziuna Sayed Jamaludin. Masters thesis, Universiti Teknologi MARA.
repository_type Digital Repository
institution_category Local University
institution Universiti Teknologi MARA
building UiTM Institutional Repository
collection Online Access
language English
description This study focused on maximizing the amount of reducing sugar produced from enzymatic hydrolysis of kitchen waste catalyzed by cellulase from Trichoderma viride and Trichoderma reesei, which was used separately to compare the results obtained from each enzyme. Effects of enzyme dosage (X/), substrate concentration (X2), hydrolysis time (X3) and temperature (X4) were evaluated by Full Factorial Design (FFD) to determine the significant parameters affecting the production of reducing sugar. Optimization of process conditions were also performed using Central Composite Design (CCD) within the range employed for each independent variable. All the variables evaluated using FFD was found to have a significant effect towards the production of reducing sugar. The study has shown that enzymatic hydrolysis catalyzed by cellulase from T. viride is efficient in producing high amount of reducing sugar. A modelling study on enzymatic hydrolysis of kitchen waste was also performed to predict the reducing sugar yield using the datasets obtained from Response Surface Methodology (RSM) studies. A multi-layer feed-forward backpropagation artificial neural network (ANN) models were developed for enzymatic hydrolysis with input variables chosen from RSM studies. A comparative observation between ANN model and RSM model was also performed. Based on the R2 (correlation coefficient) and MSE (mean square error) values, it was concluded that ANN model is more accurate in predicting the reducing sugar yield than RSM model.
format Thesis
author Sayed Jamaludin, Sharifah Iziuna
spellingShingle Sayed Jamaludin, Sharifah Iziuna
Enzymatic hydrolysis and modelling of fermentable sugar production from kitchen waste / Sharifah Iziuna Sayed Jamaludin
author_facet Sayed Jamaludin, Sharifah Iziuna
author_sort Sayed Jamaludin, Sharifah Iziuna
title Enzymatic hydrolysis and modelling of fermentable sugar production from kitchen waste / Sharifah Iziuna Sayed Jamaludin
title_short Enzymatic hydrolysis and modelling of fermentable sugar production from kitchen waste / Sharifah Iziuna Sayed Jamaludin
title_full Enzymatic hydrolysis and modelling of fermentable sugar production from kitchen waste / Sharifah Iziuna Sayed Jamaludin
title_fullStr Enzymatic hydrolysis and modelling of fermentable sugar production from kitchen waste / Sharifah Iziuna Sayed Jamaludin
title_full_unstemmed Enzymatic hydrolysis and modelling of fermentable sugar production from kitchen waste / Sharifah Iziuna Sayed Jamaludin
title_sort enzymatic hydrolysis and modelling of fermentable sugar production from kitchen waste / sharifah iziuna sayed jamaludin
publishDate 2014
url http://ir.uitm.edu.my/id/eprint/16445/
http://ir.uitm.edu.my/id/eprint/16445/1/TM_SHARIFAH%20IZIUNA%20SAYED%20JAMALUDIN%20EH%2014_5.pdf
first_indexed 2023-09-18T22:56:05Z
last_indexed 2023-09-18T22:56:05Z
_version_ 1777417863140737024

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