Enzymatic assisted citronella essential oil extraction from Cymbopogan Winterianus

Master of Science in Bioprocess Engineering

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Bibliographic Details
Main Author: Norhidayah, Abd. Aziz
Other Authors: Arbain, Dachyar, Assoc. Prof. Dr.
Format: Thesis
Language:English
Published: Universiti Malaysia Perlis (UniMAP) 2015
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Online Access:http://dspace.unimap.edu.my:80/xmlui/handle/123456789/72275
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Institution: Universiti Malaysia Perlis
Language: English
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spelling my.unimap-722752023-04-04T01:58:00Z Enzymatic assisted citronella essential oil extraction from Cymbopogan Winterianus Norhidayah, Abd. Aziz Arbain, Dachyar, Assoc. Prof. Dr. Mohd Noor, Ahmad, Prof. Citronella oil Steam distillation Essential oil Cymbopogan winterianus Master of Science in Bioprocess Engineering The essential oil of Citronella is commonly extracted via typical steam distillation of citronella plan parts. However, the oil yield is generally low (0.22% - 1.0%), causing burden to many entrepreneurs to meet the strong demand. Therefore, the study was conducted to improve the yield of citronella oil recovery by introducing an optimised enzymatic assisted pre-treatment using crude microbial enzymes isolated from the soil surrounding the citronella roots. Firstly, the lignocellulosic components of dried citronella roots were investigated to evaluate the most abundance component for selection of enzymes useful for pre-treatment. The composition analysis has identified cellulose as the major lignocellulosic component (38.21%±1.65), followed by hemicellulose (30.49%±0.93), lignin (21.12%±1.86) and extractives (4.97%±0.22). 31 out of 52 isolated strains have been identified as positive cellulase producer. Based on the calculated cellulolytic indexes, 4 strains i.e; UniMAPF7, UniMAPF16, UniMAPF24, and UniMAPF27 were selected for application in the laboratory scale pre-treatment process. Results from the growth curve analysis and enzyme activity study suggested that the optimal time for enzyme harvesting occurred at day 5 for UniMAPF7, day 4 for UniMAPF24 and day 3 for UniMAPF16 and UniMAPF27. Laboratory scale oil extraction of pre-treated citronella root with crude enzymes of UniMAPF7 and UniMAPF24 yielded in a significant 2.5-fold and 1.7-fold increased in citronella oil recovery, respectively, when compared to the untreated citronella root as control. 2015 2021-09-30T02:48:02Z 2021-09-30T02:48:02Z Thesis http://dspace.unimap.edu.my:80/xmlui/handle/123456789/72275 en Universiti Malaysia Perlis (UniMAP) Universiti Malaysia Perlis (UniMAP) School of Bioprocess Engineering
institution Universiti Malaysia Perlis
building UniMAP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Perlis
content_source UniMAP Library Digital Repository
url_provider http://dspace.unimap.edu.my/
language English
topic Citronella oil
Steam distillation
Essential oil
Cymbopogan winterianus
spellingShingle Citronella oil
Steam distillation
Essential oil
Cymbopogan winterianus
Norhidayah, Abd. Aziz
Enzymatic assisted citronella essential oil extraction from Cymbopogan Winterianus
description Master of Science in Bioprocess Engineering
author2 Arbain, Dachyar, Assoc. Prof. Dr.
author_facet Arbain, Dachyar, Assoc. Prof. Dr.
Norhidayah, Abd. Aziz
format Thesis
author Norhidayah, Abd. Aziz
author_sort Norhidayah, Abd. Aziz
title Enzymatic assisted citronella essential oil extraction from Cymbopogan Winterianus
title_short Enzymatic assisted citronella essential oil extraction from Cymbopogan Winterianus
title_full Enzymatic assisted citronella essential oil extraction from Cymbopogan Winterianus
title_fullStr Enzymatic assisted citronella essential oil extraction from Cymbopogan Winterianus
title_full_unstemmed Enzymatic assisted citronella essential oil extraction from Cymbopogan Winterianus
title_sort enzymatic assisted citronella essential oil extraction from cymbopogan winterianus
publisher Universiti Malaysia Perlis (UniMAP)
publishDate 2015
url http://dspace.unimap.edu.my:80/xmlui/handle/123456789/72275
_version_ 1772813060482793472