Mathematical Models Of The Growth And Degradation Of Pyrene-degrading Bacteria

With the intensification of human activities such as the exploration and exploitation of oil,the discharge of oily waste water and the leakage of oil,human living environment has been polluted and persecuted to varying degrees.Among various petroleum-polluted compounds,PAHs are widely distributed and exist in the environment for a long time.The most serious hazards are PAHs,which are also persistent organic pollutants that have been discovered by humans very early but are hardest to degrade.The mathematical model of the growth and degradation of Pyrene degradation was established for 5 strains of earthworms degraded and screened from petroleum contaminated soil.The first-order growth model and the first-order kinetics model of degrading limulus were fitted by Logistic equation and Gompertz equation,and the temperature,pH value,optimal condition of NaCl concentration,and influence of NaCl-degrading bacteria were preliminarily investigated by single factor experiment.Degradation bacteria degradation characteristics of the temperature,pH value,NaCl concentration,inoculum volume,the optimum concentration of germanium concentration.Box-Behnken experimental design and response surface analysis were used to determine the optimal conditions.The experimental results are as follows: A first-order growth model and a second-order growth model with good fitness are established.A multi-model mathematic model of five bacteria is established through the establishment of a first-order model simulation,among which three strains of pseudo-units The degree of fit of the first-order secondary growth model established by the same genus of bacteria is good,indicating that the established multi-bacterial first-class growth model can better reflect the growth process of the growth process.During the degradation process,a first-order degradation model and a second-level degradation model were established for the five strains.The three-level degradation model was based on the artificial neural network and response surface methodology to carry out the influencing factors of the deuterium degradation process.According to theexperimental data of degrading maggot decomposing bacteria,determine the factors affecting the experiment temperature,pH,initial hydrazine concentration,inoculum,NaCl,deuterium degradation rate is the response value.According to the experimental factors,the number of levels and the response of the optimal situation response surface method design.Based on the experimental data of the response surface design of the deuterium degradation process,an artificial neural network model was established to predict the degradability of the degrading response of the deuterium.Finally,based on the response surface methodology and the predictive value of deuterium degradation rate,a regression equation for deuterium degradation was established and optimized.The optimum design conditions for the degradation of indole were obtained.The RSM-BP and RSM-RBF modes were compared.The experimental results showed that the optimal experimental conditions for the degradation process of alfalfa were: pH 7.41,temperature 32.89?,inoculation When the amount was 4.48% and the deuterium concentration was 55.16 mg/L,the degradation rate was the highest.Under this condition,the simulation experiment showed that the deuterium degradation rate reached 60.9%.The RSM-RBF model optimized the original experiment depth.The combination of response surface method and artificial neural network optimizes the design and analysis of the deuterium degradation experiment,and provides new methods and ideas for the actual repair of deuterium degradation.It has certain practical application value and theoretical guidance significance.