Fusion of dielectric technique and intelligence methods in order to predict acidity and peroxide of virgin olive oil Online publication date: Wed, 01-Apr-2020
by Mahdi Rashvand; Majid Javanmard; Abbas Akbarnia; Shahram Sarami
International Journal of Postharvest Technology and Innovation (IJPTI), Vol. 6, No. 3, 2019
Abstract: Olive oil is one of the strategic and rich in minerals and nutrients among different oils. Due to the high price of olive oil, the quality of this product has a very important factor for consumers. Generally, the quality of olive oil is measured by two indexes of acidity and peroxide value. In this research, dielectric technique, artificial neural network (ANN) and support vector machine (SVM) methods were used to predict the acidity and peroxide value of olive oil. To analysis of output data in the range of frequency 1 KHz10 MHz, the artificial neural network with a topology of 1861-15-10 for acidity value and topology 1861-23-10 for peroxide value were predicted. Also, the best result of vector support was obtained by Gaussian algorithm with accuracy of 0.99. The results showed that the device and the evaluation methods were appropriate for prediction of acidity and peroxide value of olive oil.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Postharvest Technology and Innovation (IJPTI):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com
Our Blog 
Follow us on Twitter 
Visit us on Facebook