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Estimation of antioxidant activity of foods using artificial neural networks

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dc.contributor.authors Cerit, I; Yildirim, A; Ucar, MK; Demirkol, A; Cosansu, S; Demirkol, O;
dc.date.accessioned 2020-03-06T08:32:53Z
dc.date.available 2020-03-06T08:32:53Z
dc.date.issued 2017
dc.identifier.citation Cerit, I; Yildirim, A; Ucar, MK; Demirkol, A; Cosansu, S; Demirkol, O; (2017). Estimation of antioxidant activity of foods using artificial neural networks. JOURNAL OF FOOD AND NUTRITION RESEARCH, 56, 148-138
dc.identifier.issn 1336-8672
dc.identifier.uri https://hdl.handle.net/20.500.12619/67421
dc.description.abstract The aim of this study was to demonstrate that artificial neural networks (ANN) is an economical and rapid method to estimate antioxidant activity of foods. Phenolic content of different food varieties (red pepper and grape seeds) was used as two input variables, and ferric ion reducing antioxidant power (FRAP) values were estimated as output. The number of total experimental data was 150 (70 % for train, 30 % for test). The developed ANN was able to reveal the relationship between phenolic compounds and antioxidant activity of food with the feed-forward model. The estimated FRAP values calculated by ANN correlated with experimental FRAP values with high correlation coefficients. In addition, error rate was found to be approximately 10 %, which corresponds to approximately 90 % of success. The relationship between antioxidant substances and antioxidant activity demonstrated that ANN can be used to determine the antioxidant properties of foods and results of this study showed that this was possible. By this way, it was demonstrated that ANN is a reliable software-based method to estimate antioxidant capacities of foods with savings of time, labour and experimental costs.
dc.language English
dc.publisher VUP FOOD RESEARCH INST, BRATISLAVA
dc.subject Food Science & Technology
dc.title Estimation of antioxidant activity of foods using artificial neural networks
dc.type Article
dc.identifier.volume 56
dc.identifier.startpage 138
dc.identifier.endpage 148
dc.contributor.department Sakarya Üniversitesi/Mühendislik Fakültesi/Gıda Mühendisliği Bölümü
dc.contributor.saüauthor Cerit, İnci
dc.contributor.saüauthor Uçar, Muhammed Kürşad
dc.contributor.saüauthor Demirkol, Aşkın
dc.contributor.saüauthor Coşansu Akdemir, Serap
dc.contributor.saüauthor Demirkol, Omca
dc.relation.journal JOURNAL OF FOOD AND NUTRITION RESEARCH
dc.identifier.wos WOS:000403928300005
dc.identifier.eissn 1338-4260
dc.contributor.author Cerit, İnci
dc.contributor.author Ayse Yildirim
dc.contributor.author Uçar, Muhammed Kürşad
dc.contributor.author Demirkol, Aşkın
dc.contributor.author Coşansu Akdemir, Serap
dc.contributor.author Demirkol, Omca


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