Study on drying of bitter gourd slices based on halogen dryer
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...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Czech Academy of Agricultural Sciences
2023-09-01
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| Series: | Research in Agricultural Engineering |
| Subjects: | |
| Online Access: | https://rae.agriculturejournals.cz/artkey/rae-202303-0005_study-on-drying-of-bitter-gourd-slices-based-on-halogen-dryer.php |
| _version_ | 1797692527234514944 |
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| author | Dinh Anh Tuan Tran Tuan Nguyen Van Dinh Nhat Hoai Le Thi Khanh Phuong Ho |
| author_facet | Dinh Anh Tuan Tran Tuan Nguyen Van Dinh Nhat Hoai Le Thi Khanh Phuong Ho |
| author_sort | Dinh Anh Tuan Tran |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-12T02:29:54Z |
| format | Article |
| id | doaj.art-594d2e37ff564dc18b7121289eccac31 |
| institution | Directory Open Access Journal |
| issn | 1212-9151 1805-9376 |
| language | English |
| last_indexed | 2024-03-12T02:29:54Z |
| publishDate | 2023-09-01 |
| publisher | Czech Academy of Agricultural Sciences |
| record_format | Article |
| series | Research in Agricultural Engineering |
| spelling | doaj.art-594d2e37ff564dc18b7121289eccac312023-09-05T08:25:50ZengCzech Academy of Agricultural SciencesResearch in Agricultural Engineering1212-91511805-93762023-09-0169314315010.17221/97/2022-RAErae-202303-0005Study on drying of bitter gourd slices based on halogen dryerDinh Anh Tuan Tran0Tuan Nguyen Van1Dinh Nhat Hoai Le2Thi Khanh Phuong Ho3Faculty of Heat and Refrigeration engineering, Industrial University of Ho Chi Minh city, Ho Chi Minh city, Viet NamFaculty of Heat and Refrigeration engineering, Industrial University of Ho Chi Minh city, Ho Chi Minh city, Viet NamFaculty of Heat and Refrigeration engineering, Industrial University of Ho Chi Minh city, Ho Chi Minh city, Viet NamFaculty of Heat and Refrigeration engineering, Industrial University of Ho Chi Minh city, Ho Chi Minh city, Viet NamIn 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.https://rae.agriculturejournals.cz/artkey/rae-202303-0005_study-on-drying-of-bitter-gourd-slices-based-on-halogen-dryer.phpanndrying temperaturemachine learningmars modelmoisture content |
| spellingShingle | Dinh Anh Tuan Tran Tuan Nguyen Van Dinh Nhat Hoai Le Thi Khanh Phuong Ho Study on drying of bitter gourd slices based on halogen dryer Research in Agricultural Engineering ann drying temperature machine learning mars model moisture content |
| title | Study on drying of bitter gourd slices based on halogen dryer |
| title_full | Study on drying of bitter gourd slices based on halogen dryer |
| title_fullStr | Study on drying of bitter gourd slices based on halogen dryer |
| title_full_unstemmed | Study on drying of bitter gourd slices based on halogen dryer |
| title_short | Study on drying of bitter gourd slices based on halogen dryer |
| title_sort | study on drying of bitter gourd slices based on halogen dryer |
| topic | ann drying temperature machine learning mars model moisture content |
| url | https://rae.agriculturejournals.cz/artkey/rae-202303-0005_study-on-drying-of-bitter-gourd-slices-based-on-halogen-dryer.php |
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