PAPER TITLE :PREDICTION OF GEOGRAPHICAL ORIGIN OF PALM OILS (ELAEISGUINEENSIS) USING QUALITY PARAMETERS AND CHEMOMETRICS

APPLIED TROPICAL AGRICULTURE | VOLUME 24 NUMBER 1 2019

Paper Details

  • Author(s) : Olusola Samuel Jolayemi
  • Abstract:

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.
Key words: Palm oils, quality parameters, regional prediction PCA, OPLS-DA