Artículo
Producing non-traditional flour from watermelon rind pomace: Artificial neural network (ANN) modeling of the drying process
Fabani, Maria Paula
; Capossio, Juan Pablo
; Román Barón, María Celia
; Zhu, Wenlei; Rodriguez, Rosa Ana
; Mazza, German Delfor
Fecha de publicación:
03/2021
Editorial:
Academic Press Ltd - Elsevier Science Ltd
Revista:
Journal of Environmental Management
ISSN:
0301-4797
Idioma:
Inglés
Tipo de recurso:
Artículo publicado
Clasificación temática:
Resumen
An artificial neural network (ANN) model was developed to simulate the convective drying process of watermelon rind pomace used in the fabrication of non-traditional flour. Also, the drying curves obtained experimentally were fitted with eleven different empirical models to compare both modeling approaches. Lastly, to reduce the required fossil fuel in the convective drying process, two types of solar air heaters (SAH) were presented and experimentally evaluated. The optimization of the ANN by a genetic algorithm (GA) resulted in an optimal number of neurons of nine (9) for the first hidden layer and ten (10) for the second hidden layer. Also, the ANN performed better than the best fitted empirical model. Simulations with the trained ANN showed very promising generalization capabilities. The type II SAH showed the best performance and the highest air temperature it reached was 45 °C. The specific energy consumption (SEC) needed to dry the watermelon rind at this temperature and the CO2 emissions were 609 kWh.kg−1 and 318 kg CO2.kWh−1, respectively. Using the type II SAH, this energy amount would be saved without CO2 emissions. To reach higher drying temperatures the combination of the SAH and the electrical convective dryer is possible.
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Articulos(CCT - SAN JUAN)
Articulos de CENTRO CIENTIFICO TECNOLOGICO CONICET - SAN JUAN
Articulos de CENTRO CIENTIFICO TECNOLOGICO CONICET - SAN JUAN
Articulos(PROBIEN)
Articulos de INST. DE INVESTIGACION Y DES. EN ING. DE PROCESOS, BIOTECNOLOGIA Y ENERGIAS ALTERNATIVAS
Articulos de INST. DE INVESTIGACION Y DES. EN ING. DE PROCESOS, BIOTECNOLOGIA Y ENERGIAS ALTERNATIVAS
Citación
Fabani, Maria Paula; Capossio, Juan Pablo; Román Barón, María Celia; Zhu, Wenlei; Rodriguez, Rosa Ana; et al.; Producing non-traditional flour from watermelon rind pomace: Artificial neural network (ANN) modeling of the drying process; Academic Press Ltd - Elsevier Science Ltd; Journal of Environmental Management; 281; 3-2021; 1-14
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