Higher the grey relational grade, better the quality of the product is and vice versa. The factor effect and the optimal level for a controllable factor could be determined on the basis of grey relational grade. For each level of j of each factor i, we calculated the average of grade values (AGV)ij, then the effect of Ei is defined as: equation(9) Ei=max⁡(AGV)ij−min⁡(AGV)ijEi=max⁡(AGV)ij−min⁡(AGV)ijFor the controllable factor i, the optimum level, j*, is taken by: equation(10) j*=max⁡(AGV)ijj*=max⁡(AGV)ij Step 7: Finally, examined the validity of grey relational analysis.

The ANOVA was performed to find out the statistical significance of the rhamnolipid FK228 cell line production parameters. The results were examined to determine the main effects of all the factors. With the grey relational analysis and ANOVA, the optimum combination of the process parameters could be predicted. Finally, a confirmation experiment was conducted to verify the optimal process parameters obtained from the production process design. The Taguchi method is a systematic approach for design and analyzes the experiments to improve the product quality. This method could simplify the optimization of process parameters for multiple performance characteristics. Rashedi and Assadi [23] used

the Taguchi method to optimize rhamnolipid production. Wei et Ruxolitinib mw al. [32] used Taguchi method to optimize the trace elemental composition of minimal media for surfactin production by a Bacillus subtilis strain. Salehizadeh and Mohammadizad [29] used the Taguchi method to optimize the biosurfactants production by using Alcaligenes faecalis strain. Khalifeh et al. [13] used this method to optimize the application of biosurfactants for oily polluted waters clearance recovery. Mnif et al. [17] also investigated the soil washing potency by using Taguchi method in order to enhance the bioavailability of hydrophobic contaminants for bioremediation. The possible factors and sub-factors which could

affect the production process and the yield of rhamnolipid surfactants are shown in Fig. 1. The rhamnolipid yield obtained through a fermentation process generally depends on the microbiology and growth requirements of native or recombinant microbes. In addition, environmental and process factors also contribute to affect the net outcome of Mannose-binding protein-associated serine protease rhamnolipid yield. Some of the key factors have been under taken in the present study. At the first glance, by changing three factors (i.e., TS concentration, C/N ratio and incubation time), the rate of rhamnolipid produced in 3-level experiments was determined by the orcinol method. The experiments were conducted using L9 OA and the response values hence obtained are given in Table 2. The results show that the highest rhamnolipid yield of 1.45 g/L, when the TS, C/N ratio and incubation time were 2% (w/v), 20 and 7 days, respectively, under run 5; while the lowest value (corresponding to 0.