(untitled) (Asian Journal of Plant Biology, 2022)
Synthetic dyes are abundantly used in recent years and mainly consumed in the textile, pharmaceutical, plastic and cosmetic industries. The release of toxic constituents from dyes give adverse effect on human health and marine life. In textile industries, large amount of dye discharged into the wastewater and eventually to the aquatic system are mainly came from the critical step of dyeing and finishing processes in textile. The be able to precisely forecast the rate of bioremediation, depends on the gathering of precise rate of decolourisation, and this can be inaccurately acquired by natural logarithm transformation of the decolourisation process over time. In cases like this, a nonlinear regression of the curve must be performed making use of accessible rate models. Consequently, numerous primary models for example modified Logistic, modified Gompertz, modified logistics, modified Richards, modified Schnute, Baranyi-Roberts, Buchanan-3-phase, von Bertalanffy and the Huang models were utilized to fit the specific decolourisation rate. Several models did not converge and was disregarded and only Huang, Baranyi-Roberts, modified Gompertz, modified Richards and modified Logistics could actually model the data. The very best model according to statistical analysis was Baranyi Roberts with the highest value for Adjusted Coefficient of Determination and the lowest values for RMSE, AICc, HQC and BIC and the closest value to 1.0 for accuracy and bias factors. The Baranyi-Roberts fitted curve was discovered to conform to normality tests and is satisfactory to be used to fit the experimental data. The parameters extracted from this exercise may be used for additional secondary modelling training to gleam information about how substrate (dye) impact the rate of decolourisation of the substrate