Publication Cover
Journal of Environmental Science and Health, Part B
Pesticides, Food Contaminants, and Agricultural Wastes
Volume 47, 2012 - Issue 5
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ARTICLES

Modeling biodegradation and kinetics of glyphosate by artificial neural network

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Pages 455-465 | Received 10 Jun 2011, Published online: 16 Mar 2012
 

Abstract

An artificial neural network (ANN) model was developed to simulate the biodegradation of herbicide glyphosate [2-(Phosphonomethylamino) acetic acid] in a solution with varying parameters pH, inoculum size and initial glyphosate concentration. The predictive ability of ANN model was also compared with Monod model. The result showed that ANN model was able to accurately predict the experimental results. A low ratio of self-inhibition and half saturation constants of Haldane equations (< 8) exhibited the inhibitory effect of glyphosate on bacteria growth. The value of Ki/Ks increased when the mixed inoculum size was increased from 104 to 106 bacteria/mL. It was found that the percentage of glyphosate degradation reached a maximum value of 99% at an optimum pH 6-7 while for pH values higher than 9 or lower than 4, no degradation was observed.

Acknowledgment

The authors gratefully acknowledge Crop Protection (M) Sdn. Bhd for providing the glyphosate throughout this research study.

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