Work

Detection of the adulteration in pure cow ghee by electronic nose method (case study: sunflower oil and cow body fat)

Year: 2018

Type: article

Abstract: Cow ghee is very used in some regions of Iran, such as Kermanshah province. Cow ghee is a natural source that contains high-quality nutrients which are needed for the human body. Adulteration in dairy products is not only a serious threat to human health but also it causes economic losses. Diagnosis of foodstuff cheating and its estimation is one of the key concerns in recent years. The aim of this study was the detection of the adulteration in cow ghee by olfactory machine system. Therefore, an electronic nose system was used for the different levels of sunflower oil and cow body fat mixed with pure cow ghee (10%, 20%, 30%, 40%, and 50%). The principal components analysis (PCA) and artificial neural networks (ANNs) methods were used to achieve this goal. Based on the results, the accuracy of the principal components analysis of sunflower oil and cow body fat were 96% and 97% of the data variance, respectively. According to the results, artificial neural networks identified the adulteration with sunflower oil and cow body fat with an accuracy of 91.3% and 82.5%, respectively.

Source: International Journal of Food Properties

DOI: 10.1080/10942912.2018.1505755

Authors: Fardin Ayari, Esmaeil Mirzaee- Ghaleh, Hekmat Rabbani, Kobra Heidarbeigi

Institutions: Razi University, Ilam University

Language: English

Topic: Advanced Chemical Sensor Technologies

Subfield: Biomedical Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Zero hunger

Open Access status: gold

Estimated APC paid: $2,306