Evaluation of parameters for subcritical water extraction of zingiber zerumbet using fractional factorial design

Zingiber zerumbet (Z. zerumbet) is recognized for decades for its usability as spice and condiment in food flavoring as well as having high medicinal properties. Up to date, there are limited literature on evaluation of the effects of multiple variables in details especially in pilot-scale subcritic...

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Bibliographic Details
Main Authors: Amir, S. N. K. M., Nordin, M. F. M., Shameli, K., Wahab, I. M. A., Hamid, M. A.
Format: Article
Language:English
Published: Penerbit UTM Press 2021
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Online Access:http://eprints.utm.my/id/eprint/94370/1/MariamFirdhausNordin2021_EvaluationofParametersforSubcriticalWater.pdf
http://eprints.utm.my/id/eprint/94370/
http://dx.doi.org/10.11113/jurnalteknologi.v83.14545
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Summary:Zingiber zerumbet (Z. zerumbet) is recognized for decades for its usability as spice and condiment in food flavoring as well as having high medicinal properties. Up to date, there are limited literature on evaluation of the effects of multiple variables in details especially in pilot-scale subcritical water extraction (SWE) of Z. zerumbet. The aim for this study is to implement the fractional factorial design with five variables which are temperature (100-170°C), time (10-40 minutes), pressure (10-20 bar), particle size (0.89-3.56 mm) and solvent to solid ratio (20-40 ml/g) in SWE of Z. zerumbet. Analysis of variance for all responses stated that temperature, time, particle size and solvent to solid ratio are significant variables. Temperature is the most significant factor for zerumbone concentration and antioxidant activity with a p-value of <0.0001 and 0.0002, respectively. The solvent to solid ratio was the most significant factor for the yield of extraction with a p-value of 0.0002. Time and particle size were significant towards all responses, however pressure was not significant on zerumbone concentration and yield. Thus, the fractional factorial design could give a broad overview in selecting the significant variables for further optimization in SWE from the findings.