Data/hora: 10/06/2024 04:25:36

Provedor de dados: 	111	
País: 	China	
Título: 	Authentication of Virgin Olive Oil by Using Dielectric spectroscopy combined with Some Artificial Intelligence Methods	
Autores: 	Soltani, Mahmoud; Rashvand, Mahdi; Teimouri, Nima; Omid, Mahmoud.	
Data: 	2019-12-16	
Ano: 	2019	
Palavras-chave: 	Postharvest Engineering Olive oil; Authentication; Dielectric properties; Data mining.	
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%.	
Tipo: 	Info:eu-repo/semantics/article	
Idioma: 	Inglês	
Identificador: 	http://www.cigrjournal.org/index.php/Ejounral/article/view/5483	
Editor: 	International Commission of Agricultural and Biosystems Engineering	
Relação: 	http://www.cigrjournal.org/index.php/Ejounral/article/view/5483/3217

http://www.cigrjournal.org/index.php/Ejounral/article/downloadSuppFile/5483/2454	
Formato: 	application/pdf	
Fonte: 	Agricultural Engineering International: CIGR Journal; Vol 21, No 4 (2019): CIGR Journal; 224-230

1682-1130	
Fonte: 	Copyright (c) 2019 Agricultural Engineering International: CIGR Journal