Alim24400 Vol. 24 No. 1 (2025)

Vol. 24, No. 1 (2025), Alim24400 https://doi.org/10.24275/rmiq/Alim24400

Modeling of dehydration, polyphenol thermal degradation, and rehydration of instant germinated VD20 rice: Mathematical and artificial intelligence model

Authors

L.T.K. Loan, T.Q. Tat, P.D.T. Minh, V.T.T. Thao, P.T.M. Hoang, T.T.Y. Nhi, B.L. Giang, D.T. Phat, C. Mansamut, N.V. Tai

Abstract

VD20 rice, a local rice variety in Vietnam, is currently undergoing restoration and provides limited information about product development. In order to produce the instant germinated VD20 rice, the study on kinetics of dehydration, polyphenol thermal degradation, and rehydration of the instant product was carried out. Different temperatures were applied in this study, including 50oC, 55oC, 60oC, and 65oC. Various models were developed to describe these changes. The Page model provided the best fit for the sample's dehydration properties, with the moisture diffusivity (Deff) ranging from 7 x 10-12 to 1.19 x 10-11 m2/s and an activation energy of 31.70 kJ/mol. A zero-order model described the change in polyphenol during the drying process. The half-life values ranged from 3.737 h to 5.723 h. Also, the ANN model was used. This is an intelligent model made of an artificial neural network. It worked better and faster than earlier models like the Page model for dehydration behavior and the zero-order model for degradation property. The rehydration ratio of instant germinated rice also fitted well with the exponential model. These developed insights could facilitate further optimization and production on a larger scale, thereby enabling farmers to produce more products from this rice.

Keywords

rice, artificial neural network, drying, modeling, antioxidant.

References
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Chemical Engineering Journal, 86(1), 85-93. https://doi.org/10.1016/S1385-8947(01)00276-5 Demiray, E., & Tulek, Y. (2017). Effect of temperature on water diffusion during rehydration of sun-dried red pepper (Capsicum annuum L.). Heat and Mass Transfer, 53, 1829-1834. https://doi.org/10.1007/s00231-016-1940-0 Dias, C., Fonseca, A. M., Amaro, A. L., Vilas-Boas, A. A., Oliveira, A., Santos, S. A., Silvestre, A. J., Rocha, S. M., Isidoro, N., & Pintado, M. (2020). Natural-based antioxidant extracts as potential mitigators of fruit browning. Antioxidants, 9(8), 715. https://doi.org/10.3390/antiox9080715 Espinosa-Solares, T., & Domínguez-Puerto, R. (2023). Influence of power density and geometry of young cactus cladodes (Opuntia ficus-indica (L.) Mill.) on intermittent microwave drying kinetics. Revista Mexicana de Ingeniería Química, 22(1), Alim2965. https://doi.org/10.24275/rmiq/Alim2965 Finocchiaro, F., Ferrari, B., Gianinetti, A., Dall'Asta, C., Galaverna, G., Scazzina, F., & Pellegrini, N. (2007). Characterization of antioxidant compounds of red and white rice and changes in total antioxidant capacity during processing. Molecular nutrition & food research, 51(8), 1006-1019. Guido, L. F., & Moreira, M. M. (2017). Techniques for extraction of brewer’s spent grain polyphenols: A review. Food and Bioprocess Technology, 10, 1192-1209. https://doi.org/10.1007/s11947-017-1913-4 Gutiérrez-Martínez, S., Hernández-Varela, J., Chanona-Pérez, J., Méndez-Méndez, J., González-Martínez, H., Perea-Flores, M. d. J., Mendoza-Vázquez, S., & González-Victoriano, L. (2024). Study of drying, thermal, shrinkage, and color kinetics using digital and thermographic imaging of potato slices under real-time convective drying. Revista Mexicana de Ingeniería Química, 23(3), Alim24322. https://doi.org/10.24275/rmiq/Alim24322 Henríquez, C., Córdova, A., Almonacid, S., & Saavedra, J. (2014). Kinetic modeling of phenolic compound degradation during drum-drying of apple peel by-products. Journal of Food Engineering, 143, 146-153. https://doi.org/10.1016/j.jfoodeng.2014.06.037 Jebri, M., Tarrazó, J., Bon, J., Desmorieux, H., & Romdhane, M. (2018). Intensification of the convective drying process of Salvia officinalis: Modeling and optimization. Food Science and Technology International, 24(5), 382-393. https://doi.org/10.1177/1082013218759363 Jing, Y., CHEN, J.-f., ZHAO, Y.-y., & MAO, L.-c. (2010). Effects of drying processes on the antioxidant properties in sweet potatoes. Agricultural Sciences in China, 9(10), 1522-1529. https://doi.org/10.1016/S1671-2927(09)60246-7 Karaaslan, M., Yilmaz, F. M., Cesur, Ö., Vardin, H., Ikinci, A., & Dalgiç, A. C. (2014). Drying kinetics and thermal degradation of phenolic compounds and anthocyanins in pomegranate arils dried under vacuum conditions. International Journal of Food Science & Technology, 49(2), 595-605. https://doi.org/10.1111/ijfs.12342 Kaveh, M., Çetin, N., Khalife, E., Abbaspour-Gilandeh, Y., Sabouri, M., & Sharifian, F. (2023). Machine learning approaches for estimating apricot drying characteristics in various advanced and conventional dryers. Journal of Food Process Engineering, 46(12), e14475. https://doi.org/10.1111/jfpe.14475 Khan, M. I. H., Sablani, S. S., Joardder, M. U. H., & Karim, M. A. (2022). Application of machine learning-based approach in food drying: opportunities and challenges. Drying Technology, 40(6), 1051-1067. https://doi.org/10.1080/07373937.2020.1853152 Krokida, M., & Philippopoulos, C. (2005). Rehydration of dehydrated foods. Drying Technology, 23(4), 799-830. https://doi.org/10.1081/DRT-200054201 Krokida, M. K., & Maroulis, Z. B. (2001). Structural properties of dehydrated products during rehydration. International Journal of Food Science & Technology, 36(5), 529-538. https://doi.org/10.1046/j.1365-2621.2001.00483.x Li, C., Dhital, S., Gilbert, R. G., & Gidley, M. J. (2020). High-amylose wheat starch: Structural basis for water absorption and pasting properties. Carbohydrate polymers, 245, 116557. https://doi.org/10.1016/j.carbpol.2020.116557 Loan, L. T. K., Tat, T. Q., Minh, P. D. T., Thao, V. T. T., Hoang, P. T. M., Nhi, T. T. Y., Giang, B. L., Phat, D. T., & Tai, N. V. (2024). Prediction of the Germination Rate and Antioxidant Properties of VD20 Rice by Utilizing Artificial Neural Network-Coupled Response Surface Methodology and Product Characterization. Journal of Food Measurement and Characterization. https://doi.org/10.1007/s11694-024-02835-w Loan, L. T. K., Thuy, N. M., & Van Tai, N. (2023). Mathematical and artificial neural network modeling of hot air drying kinetics of instant “Cẩm” brown rice. Food Science and Technology, 43, e27623. https://doi.org/10.5327/fst.27623 Martynenko, A., & Misra, N. N. (2020). Machine learning in drying. Drying Technology, 38(5-6), 596-609. https://doi.org/10.1080/07373937.2019.1690502 Meng, L., Sun, X., Zhang, Y., & Tang, X. (2024). Effects of high temperature and high relative humidity drying on moisture distribution, starch microstructure and cooking characteristics of extruded whole buckwheat noodles. Journal of Future Foods, 4(2), 159-166. https://doi.org/10.1016/j.jfutfo.2023.06.007 Multari, S., Marsol-Vall, A., Keskitalo, M., Yang, B., & Suomela, J.-P. (2018). Effects of different drying temperatures on the content of phenolic compounds and carotenoids in quinoa seeds (Chenopodium quinoa) from Finland. Journal of Food Composition and Analysis, 72, 75-82. https://doi.org/10.1016/j.jfca.2018.06.008 Önal, B., Adiletta, G., Crescitelli, A., Di Matteo, M., & Russo, P. (2019). Optimization of hot air drying temperature combined with pre-treatment to improve physico-chemical and nutritional quality of ‘Annurca’ apple. Food and Bioproducts Processing, 115, 87-99. https://doi.org/10.1016/j.fbp.2019.03.002 Pavkov, I., Radojčin, M., Stamenković, Z., Kešelj, K., Tylewicz, U., Sipos, P., Ponjičan, O., & Sedlar, A. (2021). Effects of osmotic dehydration on the hot air drying of apricot halves: Drying kinetics, mass transfer, and shrinkage. Processes, 9(2), 202. https://doi.org/10.3390/pr9020202 Randriamiarintsoa, N., Ryser, E. T., & Marks, B. P. (2024). Effect of Air Temperature and Velocity on Listeria monocytogenes Inactivation During Drying of Apple Slices. Journal of Food Protection, 87(4), 100253. https://doi.org/10.1016/j.jfp.2024.100253 Rasooli Sharabiani, V., Kaveh, M., Abdi, R., Szymanek, M., & Tanaś, W. (2021). Estimation of moisture ratio for apple drying by convective and microwave methods using artificial neural network modeling. Scientific Reports, 11(1), 9155. https://doi.org/10.1038/s41598-021-88270-z Rewthong, O., Soponronnarit, S., Taechapairoj, C., Tungtrakul, P., & Prachayawarakorn, S. (2011). Effects of cooking, drying and pretreatment methods on texture and starch digestibility of instant rice. Journal of Food Engineering, 103(3), 258-264. https://doi.org/10.1016/j.jfoodeng.2010.10.022 Rodríguez‐Arzuaga, M., Ríos, G., & Piagentini, A. M. (2019). Mild heat treatments before minimal processing reduce browning susceptibility and increase total phenolic content of low‐chill apple cultivars. Journal of Food Processing and Preservation, 43(11), e14209. https://doi.org/10.1111/jfpp.14209 Selvi, K. Ç., Alkhaled, A. Y., & Yıldız, T. (2022). Application of Artificial Neural Network for Predicting the Drying Kinetics and Chemical Attributes of Linden (Tilia platyphyllos Scop.) during the Infrared Drying Process. Processes, 10(10), 2069. https://doi.org/10.3390/pr10102069 Sharma, S., Semwal, A. D., Srihari, S. P., Govind Raj, T., & Wadikar, D. (2024). Effect of salt pretreatments on physico-chemical, cooking and rehydration kinetics of instant rice. Journal of Food Science and Technology, 61(4), 770-781. https://doi.org/10.1007/s13197-023-05877-y Shen, S., Wang, Y., Li, M., Xu, F., Chai, L., & Bao, J. (2015). The effect of anaerobic treatment on polyphenols, antioxidant properties, tocols and free amino acids in white, red, and black germinated rice (Oryza sativa L.). Journal of Functional Foods, 19, 641-648. https://doi.org/10.1016/j.jff.2015.09.057 Simal, S., Femenia, A., Garau, M., & Rosselló, C. (2005). Use of exponential, Page's and diffusional models to simulate the drying kinetics of kiwi fruit. Journal of Food Engineering, 66(3), 323-328. https://doi.org/10.1016/j.jfoodeng.2004.03.025 Vu, N. D., Tran, N. T. Y., Le, T. D., Phan, N. T. M., Doan, P. L. A., Huynh, L. B., & Dao, P. T. (2022). Kinetic Model of Moisture Loss and Polyphenol Degradation during Heat Pump Drying of Soursop Fruit (Annona muricata L.). Processes, 10(10), 2082. https://doi.org/10.3390/pr10102082 Yadav, G. P., Kumar, D., Dalbhagat, C. G., & Mishra, H. N. (2024). A Comprehensive Review on Instant rice: Preparation Methodology, Characterization, and Quality Attributes. Food Chemistry Advances, 4, 100581. Yu, L., Turner, M., Fitzgerald, M., Stokes, J., & Witt, T. (2017). Review of the effects of different processing technologies on cooked and convenience rice quality. Trends in food science & technology, 59, 124-138. https://doi.org/10.1016/j.tifs.2016.11.009

References

Ait Hmazi, F., Bagar, H., Madani, A., & Mrani, I. (2024). A novel approach for modelling and predicting the drying kinetics of couscous grains using artificial neural networks. Journal of Food Composition and Analysis, 132, 106301. https://doi.org/10.1016/j.jfca.2024.106301
Cai, J., Yang, Y., Cai, W., & Bridgwater, T. (2017). Drying Kinetic Analysis of Municipal Solid Waste Using Modified Page Model and Pattern Search Method. Waste and Biomass Valorization, 8(2), 301-312. https://doi.org/10.1007/s12649-016-9570-9
Chasiotis, V. K., Tzempelikos, D. A., Filios, A. E., & Moustris, K. P. (2020). Artificial neural network modelling of moisture content evolution for convective drying of cylindrical quince slices. Computers and Electronics in Agriculture, 172, 105074. https://doi.org/10.1016/j.compag.2019.105074
de Lima, A. G. B., Queiroz, M. R., & Nebra, S. A. (2002). Simultaneous moisture transport and shrinkage during drying of solids with ellipsoidal configuration. Chemical Engineering Journal, 86(1), 85-93. https://doi.org/10.1016/S1385-8947(01)00276-5
Demiray, E., & Tulek, Y. (2017). Effect of temperature on water diffusion during rehydration of sun-dried red pepper (Capsicum annuum L.). Heat and Mass Transfer, 53, 1829-1834. https://doi.org/10.1007/s00231-016-1940-0
Dias, C., Fonseca, A. M., Amaro, A. L., Vilas-Boas, A. A., Oliveira, A., Santos, S. A., Silvestre, A. J., Rocha, S. M., Isidoro, N., & Pintado, M. (2020). Natural-based antioxidant extracts as potential mitigators of fruit browning. Antioxidants, 9(8), 715. https://doi.org/10.3390/antiox9080715
Espinosa-Solares, T., & Domínguez-Puerto, R. (2023). Influence of power density and geometry of young cactus cladodes (Opuntia ficus-indica (L.) Mill.) on intermittent microwave drying kinetics. Revista Mexicana de Ingeniería Química, 22(1), Alim2965. https://doi.org/10.24275/rmiq/Alim2965
Finocchiaro, F., Ferrari, B., Gianinetti, A., Dall'Asta, C., Galaverna, G., Scazzina, F., & Pellegrini, N. (2007). Characterization of antioxidant compounds of red and white rice and changes in total antioxidant capacity during processing. Molecular nutrition & food research, 51(8), 1006-1019.
Guido, L. F., & Moreira, M. M. (2017). Techniques for extraction of brewer’s spent grain polyphenols: A review. Food and Bioprocess Technology, 10, 1192-1209. https://doi.org/10.1007/s11947-017-1913-4
Gutiérrez-Martínez, S., Hernández-Varela, J., Chanona-Pérez, J., Méndez-Méndez, J., González-Martínez, H., Perea-Flores, M. d. J., Mendoza-Vázquez, S., & González-Victoriano, L. (2024). Study of drying, thermal, shrinkage, and color kinetics using digital and thermographic imaging of potato slices under real-time convective drying. Revista Mexicana de Ingeniería Química, 23(3), Alim24322. https://doi.org/10.24275/rmiq/Alim24322
Henríquez, C., Córdova, A., Almonacid, S., & Saavedra, J. (2014). Kinetic modeling of phenolic compound degradation during drum-drying of apple peel by-products. Journal of Food Engineering, 143, 146-153. https://doi.org/10.1016/j.jfoodeng.2014.06.037
Jebri, M., Tarrazó, J., Bon, J., Desmorieux, H., & Romdhane, M. (2018). Intensification of the convective drying process of Salvia officinalis: Modeling and optimization. Food Science and Technology International, 24(5), 382-393. https://doi.org/10.1177/1082013218759363
Jing, Y., CHEN, J.-f., ZHAO, Y.-y., & MAO, L.-c. (2010). Effects of drying processes on the antioxidant properties in sweet potatoes. Agricultural Sciences in China, 9(10), 1522-1529. https://doi.org/10.1016/S1671-2927(09)60246-7
Karaaslan, M., Yilmaz, F. M., Cesur, Ö., Vardin, H., Ikinci, A., & Dalgiç, A. C. (2014). Drying kinetics and thermal degradation of phenolic compounds and anthocyanins in pomegranate arils dried under vacuum conditions. International Journal of Food Science & Technology, 49(2), 595-605. https://doi.org/10.1111/ijfs.12342
Kaveh, M., Çetin, N., Khalife, E., Abbaspour-Gilandeh, Y., Sabouri, M., & Sharifian, F. (2023). Machine learning approaches for estimating apricot drying characteristics in various advanced and conventional dryers. Journal of Food Process Engineering, 46(12), e14475. https://doi.org/10.1111/jfpe.14475
Khan, M. I. H., Sablani, S. S., Joardder, M. U. H., & Karim, M. A. (2022). Application of machine learning-based approach in food drying: opportunities and challenges. Drying Technology, 40(6), 1051-1067. https://doi.org/10.1080/07373937.2020.1853152
Krokida, M., & Philippopoulos, C. (2005). Rehydration of dehydrated foods. Drying Technology, 23(4), 799-830. https://doi.org/10.1081/DRT-200054201
Krokida, M. K., & Maroulis, Z. B. (2001). Structural properties of dehydrated products during rehydration. International Journal of Food Science & Technology, 36(5), 529-538. https://doi.org/10.1046/j.1365-2621.2001.00483.x
Li, C., Dhital, S., Gilbert, R. G., & Gidley, M. J. (2020). High-amylose wheat starch: Structural basis for water absorption and pasting properties. Carbohydrate polymers, 245, 116557. https://doi.org/10.1016/j.carbpol.2020.116557
Loan, L. T. K., Tat, T. Q., Minh, P. D. T., Thao, V. T. T., Hoang, P. T. M., Nhi, T. T. Y., Giang, B. L., Phat, D. T., & Tai, N. V. (2024). Prediction of the Germination Rate and Antioxidant Properties of VD20 Rice by Utilizing Artificial Neural Network-Coupled Response Surface Methodology and Product Characterization. Journal of Food Measurement and Characterization. https://doi.org/10.1007/s11694-024-02835-w
Loan, L. T. K., Thuy, N. M., & Van Tai, N. (2023). Mathematical and artificial neural network modeling of hot air drying kinetics of instant “Cẩm” brown rice. Food Science and Technology, 43, e27623. https://doi.org/10.5327/fst.27623
Martynenko, A., & Misra, N. N. (2020). Machine learning in drying. Drying Technology, 38(5-6), 596-609. https://doi.org/10.1080/07373937.2019.1690502
Meng, L., Sun, X., Zhang, Y., & Tang, X. (2024). Effects of high temperature and high relative humidity drying on moisture distribution, starch microstructure and cooking characteristics of extruded whole buckwheat noodles. Journal of Future Foods, 4(2), 159-166. https://doi.org/10.1016/j.jfutfo.2023.06.007
Multari, S., Marsol-Vall, A., Keskitalo, M., Yang, B., & Suomela, J.-P. (2018). Effects of different drying temperatures on the content of phenolic compounds and carotenoids in quinoa seeds (Chenopodium quinoa) from Finland. Journal of Food Composition and Analysis, 72, 75-82. https://doi.org/10.1016/j.jfca.2018.06.008
Önal, B., Adiletta, G., Crescitelli, A., Di Matteo, M., & Russo, P. (2019). Optimization of hot air drying temperature combined with pre-treatment to improve physico-chemical and nutritional quality of ‘Annurca’ apple. Food and Bioproducts Processing, 115, 87-99. https://doi.org/10.1016/j.fbp.2019.03.002
Pavkov, I., Radojčin, M., Stamenković, Z., Kešelj, K., Tylewicz, U., Sipos, P., Ponjičan, O., & Sedlar, A. (2021). Effects of osmotic dehydration on the hot air drying of apricot halves: Drying kinetics, mass transfer, and shrinkage. Processes, 9(2), 202. https://doi.org/10.3390/pr9020202
Randriamiarintsoa, N., Ryser, E. T., & Marks, B. P. (2024). Effect of Air Temperature and Velocity on Listeria monocytogenes Inactivation During Drying of Apple Slices. Journal of Food Protection, 87(4), 100253. https://doi.org/10.1016/j.jfp.2024.100253
Rasooli Sharabiani, V., Kaveh, M., Abdi, R., Szymanek, M., & Tanaś, W. (2021). Estimation of moisture ratio for apple drying by convective and microwave methods using artificial neural network modeling. Scientific Reports, 11(1), 9155. https://doi.org/10.1038/s41598-021-88270-z
Rewthong, O., Soponronnarit, S., Taechapairoj, C., Tungtrakul, P., & Prachayawarakorn, S. (2011). Effects of cooking, drying and pretreatment methods on texture and starch digestibility of instant rice. Journal of Food Engineering, 103(3), 258-264. https://doi.org/10.1016/j.jfoodeng.2010.10.022
Rodríguez‐Arzuaga, M., Ríos, G., & Piagentini, A. M. (2019). Mild heat treatments before minimal processing reduce browning susceptibility and increase total phenolic content of low‐chill apple cultivars. Journal of Food Processing and Preservation, 43(11), e14209. https://doi.org/10.1111/jfpp.14209
Selvi, K. Ç., Alkhaled, A. Y., & Yıldız, T. (2022). Application of Artificial Neural Network for Predicting the Drying Kinetics and Chemical Attributes of Linden (Tilia platyphyllos Scop.) during the Infrared Drying Process. Processes, 10(10), 2069. https://doi.org/10.3390/pr10102069
Sharma, S., Semwal, A. D., Srihari, S. P., Govind Raj, T., & Wadikar, D. (2024). Effect of salt pretreatments on physico-chemical, cooking and rehydration kinetics of instant rice. Journal of Food Science and Technology, 61(4), 770-781. https://doi.org/10.1007/s13197-023-05877-y
Shen, S., Wang, Y., Li, M., Xu, F., Chai, L., & Bao, J. (2015). The effect of anaerobic treatment on polyphenols, antioxidant properties, tocols and free amino acids in white, red, and black germinated rice (Oryza sativa L.). Journal of Functional Foods, 19, 641-648. https://doi.org/10.1016/j.jff.2015.09.057
Simal, S., Femenia, A., Garau, M., & Rosselló, C. (2005). Use of exponential, Page's and diffusional models to simulate the drying kinetics of kiwi fruit. Journal of Food Engineering, 66(3), 323-328. https://doi.org/10.1016/j.jfoodeng.2004.03.025
Vu, N. D., Tran, N. T. Y., Le, T. D., Phan, N. T. M., Doan, P. L. A., Huynh, L. B., & Dao, P. T. (2022). Kinetic Model of Moisture Loss and Polyphenol Degradation during Heat Pump Drying of Soursop Fruit (Annona muricata L.). Processes, 10(10), 2082. https://doi.org/10.3390/pr10102082
Yadav, G. P., Kumar, D., Dalbhagat, C. G., & Mishra, H. N. (2024). A Comprehensive Review on Instant rice: Preparation Methodology, Characterization, and Quality Attributes. Food Chemistry Advances, 4, 100581.
Yu, L., Turner, M., Fitzgerald, M., Stokes, J., & Witt, T. (2017). Review of the effects of different processing technologies on cooked and convenience rice quality. Trends in food science & technology, 59, 124-138. https://doi.org/10.1016/j.tifs.2016.11.009