| Registro completo |
| Provedor de dados: |
CIGR Journal
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| País: |
China
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| Título: |
Authentication of Virgin Olive Oil by Using Dielectric spectroscopy combined with Some Artificial Intelligence Methods
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| Autores: |
Soltani, Mahmoud
Rashvand, Mahdi
Teimouri, Nima
Omid, Mahmoud
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| Data: |
2019-12-16
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| Ano: |
2019
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| Palavras-chave: |
Postharvest Engineering Olive oil
Authentication
Dielectric properties
Data mining
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| Resumo: |
Adulteration is a serious problem in the food industry. Olive oil is widely adulterated with other cheap edible oils such as sunflower and canola oils. Therefore, developing a low-cost, practical and rapid analytical method for detecting such adulteration in olive oil would be useful and needed. In this research, we aimed to develop a dielectric measurement based system combined with complementary analytical intelligent techniques to recognize authentication of virgin olive oil from adulterated with vegetable oils (canola and sunflower). 192 sinusoidal signals in the range of 20 kHz and 20 MHz were feed into the cylindrical dielectric sensor filled with oil sample. Correlation based feature selection (CFS) was applied to select the most appropriate dielectric features and eliminate irrelevant data. Support vector machines (SVMs), artificial neural networks (ANNs) and decision trees (DTs) were developed to classify virgin olive oil samples from adulterated ones. The obtained results indicated that ANN with topology of 2-5-3 has the best performance with accuracy of 100%.
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| Tipo: |
Info:eu-repo/semantics/article
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| Idioma: |
Inglês
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| Identificador: |
http://www.cigrjournal.org/index.php/Ejounral/article/view/5483
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| Editor: |
International Commission of Agricultural and Biosystems Engineering
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| Relação: |
http://www.cigrjournal.org/index.php/Ejounral/article/view/5483/3217
http://www.cigrjournal.org/index.php/Ejounral/article/downloadSuppFile/5483/2454
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| Formato: |
application/pdf
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| Fonte: |
Agricultural Engineering International: CIGR Journal; Vol 21, No 4 (2019): CIGR Journal; 224-230
1682-1130
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| Direitos: |
Copyright (c) 2019 Agricultural Engineering International: CIGR Journal
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