<![CDATA[Abstract High-value products such as honey, oils, meat, and spices are primary targets of adulteration. To meet the need for fast, accurate, and non-destructive analytical methods for detecting adulteration, this study reviews the application of Fourier Transform Infrared spectroscopy combined with chemometric techniques. Fourier Transform Infrared spectroscopy offers advantages such as minimal sample preparation, rapid analysis, and high sensitivity, while chemometrics enables the interpretation of complex spectral data through techniques like Principal Component Analysis, Discriminant Analysis, and Partial Least Squares. The findings indicate that Fourier Transform Infrared, especially when using Attenuated Total Reflectance accessories, is effective in detecting adulteration in various food products such as sesame oil, honey, butter, and meat. Spectral pre-processing methods such as Standard Normal Variate, Multiplicative Scatter Correction, and Savitzky-Golay derivatives are crucial in improving model accuracy. Chemometric analyses such as Principal Component Analysis (unsupervised) and Discriminant Analysis or Partial Least Squares (supervised) have proven effective in classifying and predicting the level of adulteration. Therefore, the combination of Fourier Transform Infrared and chemometrics has strong potential as a reliable tool for food product authentication and quality monitoring throughout the supply chain. ]]>
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