Modeling biodegradation and kinetics of glyphosate by artificial neural network

Journal of Environmental Science and Health - Part B Pesticides, Food Contaminants, and Agricultural Wastes

Volumn 47, Issue 5, 2012, Pages 455-465

  Nourouzi, Mohsen M ^a   Chuah, Teong G ^a   Choong, Thomas S Y ^a   Rabiei, F ^a  

^a UNIVERSITY PUTRA MALAYSIA   (Malaysia)

Author keywords

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

Indexed keywords

ARTIFICIAL NEURAL NETWORK MODELS; BACTERIA GROWTH; GLYPHOSATE DEGRADATION; GLYPHOSATES; HALDANE EQUATIONS; HALDANE MODEL; HERBICIDE GLYPHOSATE; INHIBITORY EFFECT; INOCULUM SIZE; MAXIMUM VALUES; MONOD MODEL; OPTIMUM PH; PH VALUE; PREDICTIVE ABILITIES; SATURATION CONSTANT; SELF-INHIBITION; VARYING PARAMETERS;

ACETIC ACID; BIODEGRADATION; DEGRADATION; MICROBIOLOGY; NEURAL NETWORKS; PH;

HERBICIDES;

DRUG DERIVATIVE; GLYCINE; GLYPHOSATE; HERBICIDE;

ARTIFICIAL NEURAL NETWORK; BACTERIUM; BIODEGRADATION; DOSE-RESPONSE RELATIONSHIP; GLYPHOSATE; GROWTH RATE; HERBICIDE; INHIBITION; PH; REACTION KINETICS;

ARTICLE; ARTIFICIAL NEURAL NETWORK; BIOLOGICAL MODEL; BIOREMEDIATION; CHEMISTRY; KINETICS; PH;

BIODEGRADATION, ENVIRONMENTAL; GLYCINE; HERBICIDES; HYDROGEN-ION CONCENTRATION; KINETICS; MODELS, BIOLOGICAL; NEURAL NETWORKS (COMPUTER);

EID: 84859364388     PISSN: 03601234     EISSN: 15324109     Source Type: Journal    
DOI: 10.1080/03601234.2012.663603     Document Type: Article

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