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OJBTM

Online Journal of BioinformaticsTM

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 270 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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