Optimization of the Tomato Drying Process through Artificial Neural Networks: A Focus on Food Sustainability
Abstract
Fruit dehydration is a widely used technique to extend shelf life, minimize waste, and preserve nutritional quality by reducing moisture content, which inhibits enzymatic activity and microbial growth. However, traditional dehydration methods are often inconsistent due to subjective assessments, environmental factors, and prolonged drying times. This study introduces an artificial intelligence (AI) approach to optimize tomato dehydration, employing a simple neural network model to predict relative humidity levels during drying. The goal is to enhance product quality, automate the process, and potentially reduce energy consumption. Experimental dehydration at different temperatures and thicknesses provided insights into organoleptic and nutritional effects, with sensory analysis identifying an optimal drying temperature of 50°C. The results support AI integration in food dehydration for enhanced control, quality, and sustainability. Future research may focus on integrating real-time energy consumption data and multidimensional variables into AI models to optimize this process further.
Downloads
References
Anaya, M. M. (2017). Estado actual de los desperdicios de frutas y verduras en Colombia. Memorias De Congresos UTP, 194-201. Recuperado a partir de https://revistas.utp.ac.pa/index.php/memoutp/article/view/1493
Benítez, R., Escudero, G., Kanaan, S., & Rodó, D.M. (2014). Inteligencia artificial avanzada. Editorial UOC. https://openaccess.uoc.edu/bitstream/10609/140427/8/Inteligencia%20artificial%20avanzada_M%C3%B3dulo%201_Inteligencia%20artificial%20avanzada.pdf
Doymaz, I. (2007). Air-drying characteristics of tomatoes. Journal of Food Engineering, 1291-1297. https://doi.org/10.1016/j.jfoodeng.2005.12.047
Degwale, A., Asrat, F., Eniyew, K., Asres, D., Tesfa, T., & Ayalew, A. (2022). Influence of Dehydration Temperature and Time on Physicochemical Properties of Tomato (Solanum lycopersicum L.) Powder. Frontiers in Sustainable Food Systems.
Espinosa, N. V.-C.-M.-B. (2023). Modelado dinámico y control del proceso de secado de productos agroindustriales. La Mecatrónica en México, 1-16. https://www.mecamex.net/revistas/LMEM/revistas/LMEM-V12-N02-01.pdf
Fuentes G., G. O. (2023). Aprovechando la inteligencia artificial como herramienta metodológica para la optimización del proceso de deshidratación de tomate. In Varios, Optimización, sustentabilidad y políticas públicas: un enfoque robusto (pp. 92-106). CENID. https://doi.org/10.23913/9786078830244
Gómez, M. (2019). Deshidratado de tomate saladette en un secador de charolas giratorias. [tesis Universidad tecnológica de la Mixteca ] Huajapan de León, Oaxaca, México. http://jupiter.utm.mx/~tesis_dig/10991.pdf
Gustavsson, J. C. (2011). J., Cederberg, C., Sonesson, U., Van Otterdijk, R., & Meybeck, A. (2011). Global food losses and food waste. Düsseldorf.
Khan, M. I. (2022). Application of machine learning-based approach in food drying: Opportunities and challenges. Drying Technology, 1051-1067. https://doi.org/10.1080/07373937.2020.1853152
Flórez, R., & Fernández, J. (2008). Las redes neuronales artificiales, fundamentos teoricos y aplicaciones practicas. España, Netbiblo.
Madhankumar, S., Viswanathan, K., Taipabu, M. I., & Wu, W. (2023). A review on the latest developments in solar dryer technologies for food drying process. Sustainable Energy Technologies and Assessments, 58, Article 103298. https://doi.org/10.1016/j.seta.2023.103298
Monsalve, J. &. (2007). Evaluación de dos métodos de deshidratación del tomate (Lycopersicom esculentum mill) variedad manzano. Multiciencias, 7(3), 256-265.
Mordor Intelligence. (n.d.). Dehydrated food market size. Retrieved October 28, 2024, from https://www.mordorintelligence.com/industry-reports/dehydrated-food-market/market-size
Secretaría de Agricultura y Desarrollo Rural. (s.f.). ¿A qué nos referimos con autosuficiencia alimentaria? Gobierno de México. Retrieved October 28, 2024, from https://www.gob.mx/agricultura/colima/articulos/a-que-nos-referimos-con-autosuficiencia-alimentaria-235470?idiom=es
Sengkhamparn, N. &. (2019). Phenolic compound extraction from industrial tomato waste by ultrasound-assisted extraction. Conference series: materials science and engineering (Vol. 639, No. 1), 012040. https://doi.org/10.1088/1757-899X/639/1/012040
Sullivan, V. K.-E. (2020). Dried fruit consumption and cardiometabolic health: a randomised crossover trial. . British Journal of Nutrition, 2020 Nov 14; 124(9), 912-921. https://doi.org/10.1017/S0007114520002007.
Yegrem, L., Mengestu, D., Legesse, O., Abebe, W., & Girma, N. (2022). Nutritional compositions and functional properties of New Ethiopian chickpea varieties: Effects of variety, grown environment and season. International Journal of Food Properties, 25(1), 1485–1497. https://doi.org/10.1080/10942912.2022.2087674
This work is licensed under a Creative Commons Attribution 4.0 International License.
In order to promote the development and dissemination of research in education in Latin America, the Ibero-American Journal for Educational Research and Development (RIDE) adhered to the Budapest Open Access Initiative, which is why it is identified as a Open access publication. This means that any user can read the complete text of the articles, print them, download them, copy them, link them, distribute them and use the contents for other purposes. Creative Cummons licenses allow users to specify the rights to use an open access journal available on the Internet in such a way that users know the rules of publication. Authors who publish in this journal accept the following conditions: Authors they keep the author's rights and give the magazine the right of the first publication, with the work registered with the attribution license of Creative Commons, which allows third parties to use the published material whenever they mention the authorship of the work and the first publication in this The authors can make other independent and additional contractual agreements for the non-exclusive distribution of the version of the article published in this journal (eg, include it in an institutional repository or publish it in a book) as long as they clearly indicate that The work was published for the first time in this magazine. Authors are allowed and recommended to publish their work. low on the Internet (for example on institutional or personal pages) before and during the review and publication process, as it can lead to productive exchanges and to a greater and faster dissemination of the published work
