Study of drying kinetics and activation energy for drying a pineapple piece in the crossflow dehydrator
Issued Date
2023-09-01
Resource Type
ISSN
2214157X
Scopus ID
2-s2.0-85166180505
Journal Title
Case Studies in Thermal Engineering
Volume
49
Rights Holder(s)
SCOPUS
Bibliographic Citation
Case Studies in Thermal Engineering Vol.49 (2023)
Suggested Citation
Chokngamvong S., Suvanjumrat C. Study of drying kinetics and activation energy for drying a pineapple piece in the crossflow dehydrator. Case Studies in Thermal Engineering Vol.49 (2023). doi:10.1016/j.csite.2023.103351 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/88211
Title
Study of drying kinetics and activation energy for drying a pineapple piece in the crossflow dehydrator
Author(s)
Author's Affiliation
Other Contributor(s)
Abstract
The drying process reduces the moisture of the pineapple resulting in a decrease in the humidity ratio to inhibit microbial growth and the enzyme level for spoilage prevention. Therefore, it is significant to understand the drying kinetics to control the process efficiently. This study developed the moisture ratio equation. The thin hollow cylinder of pineapple pieces was prepared for drying. The crossflow dehydrator was fabricated. It could adjust the airflow speeds and temperatures. The separation of variables was the method to solve the moisture transport equation of a pineapple piece for obtaining the moisture ratio. The moisture ratio equation fitted with experimental data with an average coefficient of determination (R2) varying from 0.91 to 0.99 presented various diffusion coefficients. Therefore, the diffusion coefficient function depended on both air temperature and Reynolds number was obtained. When substituting it into the moisture ratio equation, the novel moisture ratio function depended on the airflow velocity, temperature, drying time, and pineapple piece geometry was proposed with R2 of 0.97. In addition, various diffusion coefficients were fitted with Arrhenius's equation by linear regression. Therefore, the novel energy activation, which varied by Reynolds number, was proposed. It had an R2 of 0.9981. All proposed empirical models are unique guidance tools to improve drying efficiency, minimize energy consumption, and minimize postharvest losses in the future.
