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OJBTM
Online
Journal of Bioinformatics ©
Volume
11 (1):134-148, 2009
Determination of antioxidant
stability in heated mixture of oils through neural networks
Valantina
R1, Neelamegham P2
1Department of Physics, 2Department of
Electrical and Electronic Engineering,
ABSTRACT
Valantina
R, Neelamegham P., Determination
of antioxidant stability in heated mixture of oils by neural network, Online J
Bioinformatics (11) 134-148, 2009. Artificial Neural Networks using a back propagation
algorithm was used to compute the percentage of inhibition concentration and antioxidant activity of palm and rice bran oils
heated 5 times to 270º C. Rice bran oil and palm oil were blended and
anti-oxidative properties were determined by In Vitro ABTS
and DPPH free radical scavenging peroxide ion radical. The radical scavenging
activity IC 50 value varied with the concentration of heated mixture
of oils. Computation of Inhibition concentration at different concentration of
the sample using neural network analysis was performed and correlated with an
experimental value for the mixture of vegetable oils. The percentage of computed and measured (with ABTS in-vitro) were
correlated for RP1 (r = -0.935; p<0.01), RP2 (r = +0.333; p<0.01, RP3 (r
= -0.169; p< 0.001) and for DPPH in-vitro RP1 (r = -0.941;
p<0.01), RP2 (r = +0.091; p<0.001, RP3 (r = +0.032; p< 0.01). The oil
mixture exhibited antioxidant stability during deep-frying, which could reduce
the incidence of malignancy, colon cancer and coronary heart diseases.
Key words: Antioxidant, ABTS, DPPH, Neural network.