Journal of food science and technology(Iran)

Journal of food science and technology(Iran)

Using Magnetic Levitation to Identify Types of Iranian Cooking Oils Based on Density

Document Type : Original Article

Authors
Mojgan Moradi Doureh
Kamal Alizadeh
Ali Daneshfar
Faculty of Chemistry, Lorestan University, Khorramabad, Iran
10.48311/fsct.2026.119859.83109
Abstract
Public health is significantly affected by the consumption of impure edible oils and the repeated reuse of cooking oils. Although traditional analytical techniques, such as gas chromatography and high-performance liquid chromatography, offer high precision, their reliance on complex and costly instrumentation limits their application outside laboratory settings. This study introduces an accessible and cost-effective analytical approach based on magnetic levitation (Maglev) for evaluating oil quality and detecting impurity in Iranian edible oils, including Kermanshahi animal fat and olive oil. The technique exploits density variations among oil samples to establish their levitation equilibrium in a paramagnetic fluid, enabling simple visual differentiation. To validate the performance of the Maglev method, controlled adulteration of Kermanshahi animal fat was carried out using graded concentrations of bovine fat, industrial hard fats, and semi-solid oils. In addition, the capability of the system to distinguish pure olive oil from industrial liquid oils was investigated. The experimental results demonstrate that the Maglev technique reliably detects impurities and provides semi-quantitative estimates of oil purity. The system is characterized by its simplicity and portability, requires no electrical power, and uses minimal components—specifically two permanent magnets and a paramagnetic solution. These features make Maglev a promising tool for on-site quality control, food safety monitoring, rapid contamination screening, and prevention of adulteration in regions with limited technical infrastructure.
Keywords
Paramagnetic medium
Levitation
Edible oils
purity
Density based detection
Subjects
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