A methodological approach to preprocessing FTIR spectra of adulterated sesame oil

Fourier transform infrared (FTIR) spectroscopy is established as an effective and fast method for the confirmation of the authenticity of food and among other, edible oils. However, no standard procedure is available for applying preprocessing as a vital step in obtaining accurate results from spectra. This study proposes a meth-odological approach to preprocessing FTIR spectra of sesame oil adulterated with vegetable oils (canola oil, corn oil, and sunflower oil). The primary preprocessing methods investigated are orthogonal signal correction (OSC), standard normal variate transformation (SNV), and extended multiplicative scatter correction (EMSC). Other preprocessing methods are used both as standalone methods and in combination with the primary preprocessing methods. The preprocessing results are compared using partial least squares regression (PLSR). OSC alone or with detrending were the most accurate in predicting the adulteration level of sesame oil, with a maximum coefficient of prediction (R2p) range of 0.910 to 0.971 for different adulterants.

Automated summary

Fourier transform infrared (FTIR) spectroscopy is an effective and fast method for confirming the authenticity of food and edible oils. However, there is no standard procedure for preprocessing FTIR spectra to obtain accurate results. This study proposes a methodological approach to preprocess FTIR spectra of adulterated sesame oil using different preprocessing methods. The results show that OSC alone or with detrending are the most accurate in predicting the adulteration level of sesame oil, with a maximum coefficient of prediction (R2p) range of 0.910 to 0.971 for different adulterants.