Turmeric powder is a widely consumed spice, making it an attractive target for adulteration, which is not easily detected. The study examined the simultaneous use of IR spectroscopy in combination with controlled (PCA) and uncontrolled (PLS-DA and CMCA) pattern recognition techniques to detect and classify Sudan Red, starch and metanil yellow fraud in turmeric powder nondestructively.The results showed that the two major peaks in turmeric powder at 1625 cm−1 and 1600 cm-1 are not present in Sudan Red, starch and metanil yellow because these materials lack this functional group. Data distribution at the two PC locations showed clearlyscattered clusters according to the four mixing studied models (turmeric powder, turmeric powder—Sudan Red mixture, turmeric powder—starch mixture and turmeric powder—metanil yellow mixture), but there was a clear overlap between turmeric powder and turmeric powder - Sudan red mixture.Both PLS-DA and SIMCA supervised methods showed satisfactory discrimination. The results also showed that in all the sample groups, when the samples were classified by PLS-DA, the values were higher compared to the SIMCA model. The overall precision of the SIMCA and PLS-DA classifier were 82% and 92%, respectively. However, when considering only two main categories adulterated (the samples at the groups 2, 3 and 4) and pure (the samples at the group 1), an acceptable degree of separation between the resulting classes was obtained. Consequently, IR spectroscopy with pattern recognition methods was found to be a promising tool for nondestructive grouping of turmeric powder samples with different types of adulteration in turmeric powder.

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