The non-destructive characterization of ultrasonic properties in mixtures of vegetable oils with similar dominant chemical compositions is becoming increasingly important for various applications. The combination of ultrasonic wave reflection as an experimental method and the partial least squares statistical method has been employed to establish reference graphs and models for detecting adulterated oils. This experimental study focuses precisely on measuring the attenuation and ultrasonic velocity of mixtures of organic argan oil with volumetric fractions of sesame oil, peanut oil or argan oil extracted from kernels depulped by goats. The measurements exhibit distinct behaviors manifested by electrical signals for the mixture obtained after the addition of each volumetric fraction, reflecting the capability of the adopted method to detect this difference. A notable decrease in ultrasonic velocity is observed in the mixtures as the quantity of added oil increases, with a maximum variation of 11 m/s for the argan/peanut oil mixture. Conversely, The attenuation of ultrasonic waves increases proportionally with the added volumetric fractions, with the argan/peanut oil mixture exhibiting an attenuation variation range of 3.57 Np/m. Prediction models for the added volumetric fractions to organic argan oil based on attenuation and ultrasonic velocity, showed a weak correlation between the predicted quantity of added oil and the actual quantity added to organic argan oil, with determination coefficients (r2) not exceeding 65%. The weak correlation is due to the similar chemical compositions of the oils. These results underscore the value of ultrasonic-statistical analysis for authenticating and ensuring the quality of vegetable oils. However, the limitations highlight the need to refine models for better accuracy. This method can verify oil authenticity in the food industry, ensuring consumer protection and quality standards. Additionally, it offers a quick and simple alternative to traditional methods, reducing costs and improving efficiency in quality control processes.
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