Abstract

Ghee, the most valuable fat is sold at a premium price over other fats and oils. Unscrupulous sellers take this advantage by mixing it with less expensive fats or oils. The addition of coconut oil (2, 4, 6, 8, 10 and 15%) in ghee was detected using ATR-FTIR and chemometrics. The spectra of pure ghee, coconut oil and adulterated samples (total 240 samples) were analyzed in the wavenumber region of 4000–500 cm−1. Principal component analysis (PCA) showed the distinct grouping of pure ghee and adulterated samples in the selected wavenumber range (1170-1141 and 1117–1100 cm−1). Soft independent modelling by class analogy (SIMCA) was able to categorize the pure ghee and coconut oil samples of the validation set with a classification efficiency of 100% using both Partial Least Squares Regression (PLS) and Principal components regression (PCR) models constructed on the training set. R2 values of greater than 0.99 between the actual and predicted values of adulterated ghee with coconut oil were observed in both the calibration and validation sets for the developed PLS and PCR models. The study revealed that coconut oil adulterated samples can be detected even at a lower concentration of 2% in ghee.

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