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OJBTM
Online
Journal of Bioinformatics
Volume 19 (2):162-174, 2018.
Determining antioxidant stability in mixtures of heated
oils by neural networks.
Rubalya Valantina S (PhD)1 and
Neelamegham2 P (PhD).
1Department of Physics, 2Electrical
and Electronic Engineering, SASTRA University, Thanjavur,
Tamilnadu, India.
ABSTRACT
Rubalya Valantina S, Neelamegham P., Determining antioxidant stability in mixtures of heated
oils by neural networks, Onl J Bioinform.,
19 (2):162-174, 2018. Vegetable oils can undergo extensive oxidative deterioration during deep
fat-frying. An artificial neural network using a back
propagation algorithm was used to compute antioxidant activity of mixtures of
palm and rice bran oils heated to 270º C five times. The oils were first
(RP1) heated for in-vitro analysis of ABTS and DPPH free
radical scavenging peroxide ion radical. The radical scavenging activity IC50
value varies with the concentration of heated mixture of oils. Computation of
Inhibition was done by neural network analysis and correlated with experimental
value for the mixture of heated vegetable oils. Computed inhibition using ABTS in-vitro was 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). We find that the
method may mirror antioxidant status for frying oil.
Key words: Antioxidant, ABTS, DPPH,
Neural network.
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