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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, SASTRA University, Tamilnadu, India.

 

ABSTRACT

 

Valantina R, Neelamegham P., Determination of antioxidant stability in heated mixture of oils by neural network, Onl J Bioinform., (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 270 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.


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