PREDICTION OF GEOGRAPHICAL ORIGIN OF PALM OILS (ElaeisGuineensis) USING QUALITY PARAMETERS AND CHEMOMETRICS Olusola Samuel Jolayemi The Federal University of Technology, Department of Food Science and Technology, PMB 704 Akure Ondo State Nigeria Corresponding Author: osjolayemi@futa.edu.ng.

• Olusola Samuel Jolayemi

  The Federal University of Technology, Department of Food Science and Technology, PMB 704 Akure Ondo State Nigeria

  Author

This study presents a footprint for geographical discrimination of palm oil using its quality characteristics. A total of 60 oil samples; 20 from each region (North N, South S and Central C) of Ondo State Nigeria, were analyzed for their quality characteristics. Principal Component Analysis (PCA) and Orthogonal Projection to Latent Structure Discriminant Analysis (OPLS-DA) regression multivariate data analytical techniques were used to elaborate the data. The models were validated by independent prediction sets and cross validation. The results of chemical data were satisfactory with PCA creating distinctive clusters of samples based on their regional differences. Significantly high carotene content, free fatty acids (FFA), acid value (AV) and peroxide (PV) helped distinguish Central palm oils. K extinction values, color density and chlorophyll content were quality parameters peculiar to North oil samples. Discriminant class modeling of all the measured variables generated >85% correct regional prediction with K270nm ,ÄK, AV and FFAhaving the highest coefficients of determination. The results cannot be considered exhaustive owing to the limited sample size. But it serves as a preliminary study showing the potential of this method.

1. Olusola Samuel Jolayemi, The Federal University of Technology, Department of Food Science and Technology, PMB 704 Akure Ondo State Nigeria

   The Federal University of Technology, Department of Food Science and Technology, PMB 704 Akure Ondo State Nigeria

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