Evaluation of drying modelling on common herbs leaves: application to hibiscus rosa-sinensis / Khairunnisa Nabilah Fairul Azahar and Dr Nor Fariza Ismail

Hibiscus rosa-sinensis is well known for its medicinal benefits, particularly the leaves which are abundance in anti-inflammatory, anti-infectious, antifungal, antimicrobial, anti-diarrhoeal, antioxidant, and antipyretic activities. The medicinal plants are high in value and the post-harvest causes...

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Bibliographic Details
Main Authors: Fairul Azahar, Khairunnisa Nabilah, Ismail, Nor Fariza
Format: Conference or Workshop Item
Language:English
Published: 2020
Subjects:
Online Access:https://ir.uitm.edu.my/id/eprint/82785/1/82785.pdf
https://ir.uitm.edu.my/id/eprint/82785/
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Summary:Hibiscus rosa-sinensis is well known for its medicinal benefits, particularly the leaves which are abundance in anti-inflammatory, anti-infectious, antifungal, antimicrobial, anti-diarrhoeal, antioxidant, and antipyretic activities. The medicinal plants are high in value and the post-harvest causes losses due to the reduction quality of the product. The plant can be less disposed to the damage from other microbial degradation and become manageable in storage and transport by reducing the content of moisture through drying. Drying leaves must ensure the required final moisture content that maintains the original high nutrient level as that of fresh leaves. The present review work focus on valuating the parameters associate with modelling of moisture contents and drying time for the drying method. The drying methods selected are sun drying, tray drying, oven drying and microwave drying. By making the comparison study on previous article, the parameter can be evaluated by drying rate constant which is “k” value from the best-fit drying model. The effect of the parameters of drying are temperature of drying air, thickess of spread, relative humidity, water activity and properties of different types of leaves. Also, evaluation of suitable drying model applied to Hibiscus rosa-sinensis leaves needed to understanding the drying process by selecting the most best fit model. The most suitable drying model applied are Page, Diffusion approach, Logarithm, Midilli and Two term model.