Determination of Growth Parameters of Butyric Acid-Degrading Bacterium, Achromobacter xylosoxidans, as a Function of Constant Temperatures in Batch System
Determination of Growth Parameters of Butyric Acid-Degrading Bacterium, Achromobacter xylosoxidans, as a Function of Constant Temperatures in Batch System
Njalam’mano J.B., Chirwa E.M.N., 2019, Determination of Growth Parameters of Butyric Acid-Degrading Bacterium, Achromobacter xylosoxidans, as a Function of Constant Temperatures in Batch System, Chemical Engineering Transactions, 76, 1321-1326.
Achromobacter xylosoxidans is one of the bacterial strains that have the capability to degrade butyric acid which significantly contribute to malodours from pit latrines emissions. There is an increasing interest in being able to predict the consequences of its growth on butyric acid degradation for remediation of malodour emissions from pit latrines. The objective of this work was to elucidate the effect of temperature on butyric acid degradation by A.xylosoxidans and to estimate microbiologically relevant parameters at dissimilar isothermal conditions under batch conditions. The experiments were carried out by inoculating 1 mL of bacterial culture into 150 mL each of MSM supplemented with 1,000 mgL-1 of butyric acid as a sole carbon source in a sterile 250 mL Erlenmeyer volumetric flask in triplicates. The temperatures were set at 25, 30, 35 and 40 oC with initial medium pH of 7 and at agitation rate of 110 rpm. The values of microbiological parameters were obtained by the application of modified Gompertz and modified Logistic sigmoidal models. It was found that the bacterial strain was able to utilise butyric acid as a sole source of carbon at a wide range of temperatures. Both models fitted described most of the experimental data sufficiently to each individual growth curve. The values of the maximum growth rate ( µ ?????? ) and lag time (??) obtained using the modified logistic model were higher than the modified Gompertz model. In the cases investigated, the modified logistic model was statistically sufficient to describe the growth data of A. xylosoxidans and its application was easy.