Modeling biodegradation and kinetics of glyphosate by artificial neural network

作者：Nourouzi Mohsen M^*; Chuah Teong G; Choong Thomas S Y; Rabiei F

来源：Journal of Environmental Science and Health - Part B: Pesticides, Food Contaminants, and Agricultural Wastes , 2012, 47(5): 455-465.

DOI：10.1080/03601234.2012.663603

• Glyphosate
• biodegradation
• Monod model
• Haldane model
• artificial neural network (ANN)

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 (%26lt;8) exhibited the inhibitory effect of glyphosate on bacteria growth. The value of K-i/K-s increased when the mixed inoculum size was increased from 10(4) to 10(6) 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.

• 出版日期2012
• 单位中国林业科学研究院热带林业研究所