Garlic (Allium sativum) is used daily in a variety of cooking methods worldwide however, it is under threat from economic adulteration. Garlic and possible adulterants such as talc, maltodextrin, corn starch, cornflour, peanut butter powder, sodium caseinate, potato starch, rice flour, cassava and white maize meal were obtained for the development of an adulteration detection method. Near infrared (NIR) and Fourier transform infrared (FTIR) along with chemometrics were used for adulteration detection method development. Principal component analysis (PCA) models were created to establish if there was separation of garlic from the adulterants. Orthogonal partial least squares – discriminant analysis (OPLS-DA) models were then developed resulting in R2 and Q2 values of 0.985 and 0.914 respectively for NIR. The FTIR values were 0.994 (R2) and 0.964 (Q2). Following validation, the receiver operating curve (ROC) indicated highly accurate models with an area under the curve (AUC) of 0.997 for NIR and 1 for FTIR. The Youden index was calculated at 0.984 and 1 for NIR and FTIR respectively and used to determine the test cut-off value. These results indicate that the NIR and FTIR methods are capable of detecting adulteration in unknown garlic samples and can be used to help protect spice industry from fraud.