Detection of fraud of palm, sunflower, and corn oil in butter using HPLC profile of tocopherols and tocotrienols by response surface method

In this research, mixing of palm oil, sunflower oil, and corn oil in the butter (as a fraud) was investigated by studying the HPLC profiles of the tocopherols and tocotrienols. The statistical D-Optimal mixture design (D-OMD) was used to design experiments. Based on D-OMD, 20 fraud butter samples with different percent of palm, sunflower, and corn oil (0, 10, and 20%) were prepared. Oil samples were dissolved in n-hexane, and tocopherols/tocotrienols profiles were analyzed by HPLC/fluorescence detector. The following compounds were detected in the samples: Alpha-tocopherol, Alpha-tocotrienol, Beta-tocopherol, Gamma-tocopherol, Beta-tocotrienol, Gamma-tocotrienol, Delta-tocopherol, and Delta-tocotrienol. The results were analyzed by response surface method, and the results showed that there is a significant relationship between the amount of tocopherols and tocotrienols and the fraudulent addition of palm, sunflower, and corn oils to butter oil. The mathematical models between percent of fraud agents (palm, sunflower, and corn oil) and amounts of tocopherols and tocotrienols were obtained. According to the results, the high amount of Alpha-tocopherol represents sunflower oil fraud, the high amount of Alpha-tocotrienol, Beta-tocotrienol, Gamma-tocotrienol, and Delta-tocotrienol represents palm oil fraud, and the high amount of Beta-tocopherol, Gamma-tocopherol, and Delta-tocopherol represents corn oil fraud. Therefore, the proposed method is a suitable method for identifying and quantifying butter oil authenticity.