Artificial intelligence optimization for producing high quality foam-mat dried tomato powder and its application in nutritional soup
The present work aims to investigate the effect of foam-mat drying on drying rate and lycopene content of tomato powder using a three-level Box-Behnken experimental design of Response Surface Methodology (RSM). Three process parameters included egg albumin (EA) ranging from 3 to 9 % as a foaming age...
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Elsevier
2024-12-01
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| Series: | Case Studies in Chemical and Environmental Engineering |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666016424003992 |
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| author | Nguyen Minh Thuy Tran Ngoc Giau Hong Van Hao Vo Quang Minh Ngo Van Tai |
| author_facet | Nguyen Minh Thuy Tran Ngoc Giau Hong Van Hao Vo Quang Minh Ngo Van Tai |
| author_sort | Nguyen Minh Thuy |
| collection | DOAJ |
| description | The present work aims to investigate the effect of foam-mat drying on drying rate and lycopene content of tomato powder using a three-level Box-Behnken experimental design of Response Surface Methodology (RSM). Three process parameters included egg albumin (EA) ranging from 3 to 9 % as a foaming agent, carboxymethyl cellulose (CMC) from 0.2 to 0.6 % as a foam stabilizer and drying temperatures (60, 70, and 80oC). The responses measured drying rate (DR) and lycopene content, which are the indication of drying process and product quality. Optimization of drying process using RSM and artificial neural network coupled genetic algorithm (ANN-GA) models has been also investigated. Foam mat dried tomato powder produced under optimal conditions was then used to prepare a nutritious soup powder with 4 designed recipes with other nutritious ingredients. The results showed that the ANN-GA model (network structure of 3-10-2) could predict and optimize better than the RSM model. The optimal conditions for foam-mat drying process were EA of 6.67 %, CMC of 0.381 %, and drying temperature of 70.6oC. These gave the DR and lycopene to be 3.004 g water/g dry matter/min and 392.8 μg/g, respectively. Validation optimal condition was performed and showed that the experimental values obtained were greatly close to the predicted values. From the 4 designed soup formulas, the macronutrient content in formula F2 met the range for AMDR with the percentage of calories from protein, lipid, and carbohydrate being 21.28 %, 20.28 %, and 58.44 %, respectively. It was proven that ANN-GA is a more reliable and robust predictive modelling tool for foam-mat tomato powder production optimization compared to RSM model. Also, the promising application of tomato powder in nutritious soup production also was shown in this study, which could further research in larger scale. |
| format | Article |
| id | doaj-art-5a888fe95f204266805087d76a50a5e0 |
| institution | OA Journals |
| issn | 2666-0164 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Case Studies in Chemical and Environmental Engineering |
| spelling | doaj-art-5a888fe95f204266805087d76a50a5e02025-08-20T02:17:59ZengElsevierCase Studies in Chemical and Environmental Engineering2666-01642024-12-011010100510.1016/j.cscee.2024.101005Artificial intelligence optimization for producing high quality foam-mat dried tomato powder and its application in nutritional soupNguyen Minh Thuy0Tran Ngoc Giau1Hong Van Hao2Vo Quang Minh3Ngo Van Tai4Institute of Food and Biotechnology, Can Tho University, 900000, Can Tho, Viet NamInstitute of Food and Biotechnology, Can Tho University, 900000, Can Tho, Viet NamInstitute of Food and Biotechnology, Can Tho University, 900000, Can Tho, Viet NamCollege of Environment and Natural Resources, Can Tho University, 900000, Can Tho, Viet NamSchool of Food Industry, King Mongkut's Institute of Technology Ladkrabang, 10520, Bangkok, Thailand; Corresponding author.The present work aims to investigate the effect of foam-mat drying on drying rate and lycopene content of tomato powder using a three-level Box-Behnken experimental design of Response Surface Methodology (RSM). Three process parameters included egg albumin (EA) ranging from 3 to 9 % as a foaming agent, carboxymethyl cellulose (CMC) from 0.2 to 0.6 % as a foam stabilizer and drying temperatures (60, 70, and 80oC). The responses measured drying rate (DR) and lycopene content, which are the indication of drying process and product quality. Optimization of drying process using RSM and artificial neural network coupled genetic algorithm (ANN-GA) models has been also investigated. Foam mat dried tomato powder produced under optimal conditions was then used to prepare a nutritious soup powder with 4 designed recipes with other nutritious ingredients. The results showed that the ANN-GA model (network structure of 3-10-2) could predict and optimize better than the RSM model. The optimal conditions for foam-mat drying process were EA of 6.67 %, CMC of 0.381 %, and drying temperature of 70.6oC. These gave the DR and lycopene to be 3.004 g water/g dry matter/min and 392.8 μg/g, respectively. Validation optimal condition was performed and showed that the experimental values obtained were greatly close to the predicted values. From the 4 designed soup formulas, the macronutrient content in formula F2 met the range for AMDR with the percentage of calories from protein, lipid, and carbohydrate being 21.28 %, 20.28 %, and 58.44 %, respectively. It was proven that ANN-GA is a more reliable and robust predictive modelling tool for foam-mat tomato powder production optimization compared to RSM model. Also, the promising application of tomato powder in nutritious soup production also was shown in this study, which could further research in larger scale.http://www.sciencedirect.com/science/article/pii/S2666016424003992TomatoFoam-mat dryingSoupOptimizationArtificial neural networkGenetic algorithm |
| spellingShingle | Nguyen Minh Thuy Tran Ngoc Giau Hong Van Hao Vo Quang Minh Ngo Van Tai Artificial intelligence optimization for producing high quality foam-mat dried tomato powder and its application in nutritional soup Case Studies in Chemical and Environmental Engineering Tomato Foam-mat drying Soup Optimization Artificial neural network Genetic algorithm |
| title | Artificial intelligence optimization for producing high quality foam-mat dried tomato powder and its application in nutritional soup |
| title_full | Artificial intelligence optimization for producing high quality foam-mat dried tomato powder and its application in nutritional soup |
| title_fullStr | Artificial intelligence optimization for producing high quality foam-mat dried tomato powder and its application in nutritional soup |
| title_full_unstemmed | Artificial intelligence optimization for producing high quality foam-mat dried tomato powder and its application in nutritional soup |
| title_short | Artificial intelligence optimization for producing high quality foam-mat dried tomato powder and its application in nutritional soup |
| title_sort | artificial intelligence optimization for producing high quality foam mat dried tomato powder and its application in nutritional soup |
| topic | Tomato Foam-mat drying Soup Optimization Artificial neural network Genetic algorithm |
| url | http://www.sciencedirect.com/science/article/pii/S2666016424003992 |
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