Modeling the Moisture Content and Drying Rate of Zucchini (Cucurbita pepo L.) in a Solar Hybrid Dryer Using ANN and ANFIS Methods

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dc.contributor.authorBulu?, Halil Nusret
dc.contributor.authorMoralar, Aytaç
dc.contributor.authorÇelen, Soner
dc.date.accessioned2024-10-29T17:43:49Z
dc.date.available2024-10-29T17:43:49Z
dc.date.issued2023
dc.departmentTekirdağ Namık Kemal Üniversitesi
dc.description.abstractEstimating product drying kinetics is critical to obtain the best drying process without compromising product quality and necessitates the development of numerical drying models. This research aims to compare the prediction models developed using artificial neural network (ANN) and adaptive network-based fuzzy inference system (ANFIS), two popular machine learning approaches in the recent years. Zucchini slices were chosen as samples and dried in a solar-assisted microwave belt dryer at 0.245 m/min belt speed and microwave powers of 0.7, 1, and 1.4 kW. On the data set obtained by computing the moisture content and drying rate values, prediction models were developed using ANN and ANFIS approaches. These models were evaluated using the coefficient of determination, mean absolute percent error, and root mean square error data. The ANFIS-based prediction model outperformed the ANN model in terms of drying rate performance, but the ANN model outperformed the ANFIS model in terms of moisture content values. Results showed that both methods established can be utilized to estimate zucchini slices. © 2023, College of Agriculture and Food Science, University of the Philippines Los Banos. All rights reserved.
dc.identifier.endpage305
dc.identifier.issn0031-7454
dc.identifier.issue3en_US
dc.identifier.scopus2-s2.0-85175181890
dc.identifier.scopusqualityQ4
dc.identifier.startpage293
dc.identifier.urihttps://hdl.handle.net/20.500.11776/12636
dc.identifier.volume106
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherCollege of Agriculture and Food Science, University of the Philippines Los Banos
dc.relation.ispartofPhilippine Agricultural Scientist
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectANFIS
dc.subjectANN
dc.subjectconveyor
dc.subjectmicrowave drying
dc.subjectzucchini
dc.titleModeling the Moisture Content and Drying Rate of Zucchini (Cucurbita pepo L.) in a Solar Hybrid Dryer Using ANN and ANFIS Methods
dc.typeArticle

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