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Distinguishing edible oil using dielectric spectroscopy at microwave frequencies of 8.2–12.1 GHz


Citation

Amat Sairin, Masyitah and Abd Latiff, Nur Hamilia and Abd Aziz, Samsuzana and Rokhani, Fakhrul Zaman (2016) Distinguishing edible oil using dielectric spectroscopy at microwave frequencies of 8.2–12.1 GHz. In: 2016 10th International Conference on Sensing Technology (ICST), 11-13 Nov. 2016, Nanjing, China. .

Abstract / Synopsis

The study focused on application of spectral permittivity technique subjected to high frequency range of 8.2-12.1 GHz at the temperature of 25°C to identify animal fats from vegetable oils. Analysis of Variance (ANOVA) technique was used as a statistical data analysis to determine whether the samples are statistically distinctive. Principal Component Analysis (PCA) was used to classify animal fats and vegetable oils on their permittivity spectral. ANOVA analysis results showed that there is a significant difference between animal fats and vegetable oils with respect to their spectral permittivity at different frequencies. PCA classification plots showed that vegetable oil could be grouped into different clusters from the animal fats. From the results obtained in this study, spectral permittivity technique could be used to distinguish animal fats and vegetable oils.


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Additional Metadata

Item Type: Conference or Workshop Item (Paper)
Divisions: Faculty of Engineering
Halal Products Research Institute
DOI Number: https://doi.org/10.1109/ICSensT.2016.7796333
Publisher: IEEE
Keywords: Analysis of Variance (ANOVA); Edible oil discrimination; Principal component analysis (PCA); Spectral permittivity
Depositing User: Nabilah Mustapa
Date Deposited: 03 Jul 2017 09:38
Last Modified: 03 Jul 2017 09:38
Altmetrics: http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.1109/ICSensT.2016.7796333
URI: http://psasir.upm.edu.my/id/eprint/56121
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