Abstract

In this study, the drying of bitter gourd slices with a halogen dryer was done at different thicknesses of bitter gourd (3, 5, and 7 mm) and temperatures (60, 65, and 70 °C). The effect of varying drying characteristics in the experiment was explored. Experimental results were evaluated based on the drying time and moisture content. The results indicate that the material drying thickness and drying temperature significantly impact the drying time and the equilibrium moisture content. Furthermore, the Multivariate Adaptive Regression Splines (MARS) model is also used to train and predict the moisture content of bitter gourd in this research. The temperature, thickness of the bitter gourd, and drying time were used as input parameters for the model. Two measures R2 and Root Mean Ssquare Error (RMSE) were used to determine the accuracy of the trained MARS model. During training, the values of R2 and RMSE obtained were 0.9846 and 3.7324, respectively. The test of trained MARS was successful, with a satisfactory correlation between experimental data points and predicted points. The results show that MARS can accurately predict the moisture content of bitter gourd in a halogen dryer.

Details

Title
Study on drying of bitter gourd slices based on halogen dryer
Author
Dinh Anh Tuan Tran; Nguyen, Tuan, Van; Dinh Nhat Hoai Le; Thi Khanh Phuong Ho
Pages
143-150
Section
Original Paper
Publication year
2023
Publication date
2023
Publisher
Czech Academy of Agricultural Sciences (CAAS)
ISSN
12129151
e-ISSN
18059376
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
3152973367
Copyright
© 2023. This work is published under https://www.agriculturejournals.cz/web/about/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.