Correlation between spectral permittivity characteristics and fatty acid methyl ester composition for lard detection in edible oils

• Main Author: Amat Sairin, Masyitah
• Format: Thesis
• Language: English
• Published: 2017
• Subjects: Oils and fats - Analysis; Lard
• Online Access: http://psasir.upm.edu.my/id/eprint/77155/1/IPPH%202018%203%20-%20IR.pdf; http://psasir.upm.edu.my/id/eprint/77155/
• Institution: Universiti Putra Malaysia

Lard adulteration in processed food has been a major public concern as it tightly connected to religion and believes, other than concern on the danger of heart coronary diseases. A number of works have been applied on discriminating lard from other animal fats and plant oils. Most of them are based on non-electrical properties sensing and require meticulous lab steps and huge lab-based equipment. Hence, the requirement to develop rapid, low cost, non-destructive and portable Halal authentication and verification system. This study aims to provide basic information that would serve as the foundation for studies on the development of adulteration monitoring systems and Halal sensors by means of spectral permittivity data. In this research, we propose and experimentally demonstrate the use of spectral permittivity with correlation to fatty acid methyl ester composition as a technique to discriminate lard from other edible oils. The spectral permittivity profile for edible oil was investigated in a wide radio frequency range between 5 MHz to 30 MHz at different temperature of 45°C, 65°C and 85°C. Fatty acid composition of edible oil was investigated by fatty acid methyl ester (FAME) analysis using gas chromatography mass spectrometry (GCMS). From the spectral permittivity data and fatty acid methyl ester composition obtained, multiple data analysis techniques were implemented. Relative standard deviation (RSD) is used as a mean to characterize measurement variability and validate the precision of the technique. One-way analysis of variance (ANOVA) was implemented for statistical analysis to investigate the significant difference between different edible oils samples. Tukey’s range test was used to group the edible oils into different classes. Principal component analysis (PCA) was implemented to the data for statistical modeling to cluster different groups of edible oils, especially lard from other edible oils. The spectral permittivity profile of edible oil shows slight decrease as the frequency is increased, which could be explained by the movement limitation of the dipoles at high frequency electric field. Increase in temperature shows that the spectral permittivity profile of edible oils were decreasing, which is caused by increased kinetic energy and mechanical amplitudes of motion of the molecules. Other than that, when the temperature increased, the viscosity of the material is reduced, causing reduction of relaxation time and higher dipole moment which also result in decreasing spectral permittivity. The study on fatty acid composition shows edible oils that have higher long chain fatty acid composition have lower spectral permittivity; and spectral permittivity of edible oils increases with increasing degree of fatty acid unsaturation. The technique was proved to have high precision and small variability. One-way ANOVA shows that there is significant difference between different edible oils. Tukey’s range test and PCA shows good performance in separating different edible oils; especially in discriminating lard from other edible oils.