Application of Superposition Technique for Modeling Drying Behavior of Avishan ( Zataria multiflora ) Leaves

Drying curves of agricultural products at different air temperatures and air velocities are often identical in shape, but shifted along the abscissa. The shift distance for each curve measured relative to a chosen reference curve is called the shift factor. This allows the drying curves to shift hor...

Full description

Saved in:
Bibliographic Details
Published inTransactions of the ASABE Vol. 51; no. 4; pp. 1383 - 1393
Main Authors Khazaei, J, Arabhosseini, A, Khosrobeygi, Z
Format Publication
LanguageEnglish
Published 2008
Subjects
activation energy
air drying
air flow
dried herbs
drying
drying curve
drying kinetics
drying temperature
Lamiaceae
leaves
master curve
mathematical models
medicinal plants
moisture ratio master curve
superposition technique
time-temperature superposition technique
Zataria multiflora
Online AccessGet more information

Cover

More Information
Summary:Drying curves of agricultural products at different air temperatures and air velocities are often identical in shape, but shifted along the abscissa. The shift distance for each curve measured relative to a chosen reference curve is called the shift factor. This allows the drying curves to shift horizontally along the time axis through a time multiplier (shift factor) until a smooth master curve is created. The master curves can be used to address air temperature and air velocity effects on the drying kinetics through the use of the shift factors. The purpose of the present work was to test the validity of this method, called the time-temperature superposition technique (TTST), in order to model the effects of air temperature (AT) and air velocity (AV) on drying kinetics of avishan ( Zataria multiflora L.) leaves (AL). The drying data at three AT (30°C, 40°C, and 50°C) as well as three AV levels (0.5, 0.8 and 1.2 m/s) were used for the modeling. The results showed that the TTST was adequate to generate a moisture ratio master curve for AL. The resulting master curves represented by the Page model (R 2 > 0.996) and its validity to predict the moisture ratio of AL were compared with a regression model. The master curve model performed better than the regression model in predicting the moisture ratio of AL as a function of AT and AV. The result confirmed the applicability of the TTST for determining the activation energy of avishan leaves.
Bibliography:http://www.asabe.org/pubs/trans.html