Rosa damascene Mill. moisture modeling in hot air dryer using mathematic models and artificial neural network

Karimi Akandi, S.R.; Banakar, A.

doi:10.22092/ijmapr.2014.6129

Document Type : Research Paper

Authors

S.R. Karimi Akandi ¹
A. Banakar ²

¹ MSc. student, Mechanical Agriculture Department, Tarbiat Modares University, Tehran, Iran

² Mechanical Agriculture Department, Tarbiat Modares University, Tehran, Iran

https://doi.org/10.22092/ijmapr.2014.6129

Abstract

Damask rose with scientific name of Rosa damascena Mill. contains essential oils with large medicinal properties. Qualitative and quantitative extraction of essential oils as well as its economic justification depends on appropriate methods of drying. Appropriate method of drying reduces loss and damage during storage and helps maintain product quality. The purpose of this study was to predict Rose moisture content during the drying process with hot air flowing as a function of temperature at four levels (40, 50, 60 and 70^°C) and air velocity at three levels (0.5, 1 and 1.5 m/s), using artificial neural networks. The average initial and final moisture contents were calculated to be 78% and 9%, respectively. The drying process was modeled by mathematical models using matlab and then the moisture content graphs were achieved by excel. Then, the drying process was modeled using neural networks with three inputs including temperature, air velocity and time. Results showed that neural network was more accurate than mathematic models in modeling and predicting the drying process of damask rose and could be used in on-line controlling.

Keywords

References

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Iranian Journal of Medicinal and Aromatic Plants Research

Rosa damascene Mill. moisture modeling in hot air dryer using mathematic models and artificial neural network

References

References

Volume 30, Issue 2 - Serial Number 64
June 2014
Pages 250-259

Rosa damascene Mill. moisture modeling in hot air dryer using mathematic models and artificial neural network

References

References

Volume 30, Issue 2 - Serial Number 64June 2014Pages 250-259

Volume 30, Issue 2 - Serial Number 64
June 2014
Pages 250-259