Abstract:
This study was carried out to produce quantitative
models for prediction of palm olein (PO) adulterations in coconut
testa oil (CTO) by using fatty acid compositional analysis and differential scanning calorimetric (DSC) analysis. Samples of authentic
CTO were prepared using mature coconuts collected out of three
local cultivars while a pure sample of PO was obtained from a
reliable supplier. In this experiment, samples of CTO were blended
with PO in the range of 20 to 80% (w/w) and subjected to fatty
acid and thermal analysis using the relevant instruments. Fatty acid
data and DSC data of thermal transitions namely, peak temperature,
peak area, peak onset and peak endset temperatures were employed
to perform statistical analysis. Results showed that all fatty acids
were suitable as parameters to develop quantitative models for
prediction of adulteration in CTO. The highest positive correlation
was displayed by linoleic acid (+0.977; p<0.0001) followed by
oleic (+0.973; p<0.0001), palmitic (+0.972; p<0.0001) and stearic
(+0.959; p<0.0001) acids. Out of all, the two models formed using
palmitic and oleic acids were the best for prediction. According
to DSC analysis, the highest correlations were found for peak
maxima (-0.965; p<0.0001) and peak area (-0.951; p<0.0001). Out
of these two, the model formed using peak maxima was the best
for prediction.
