## 3 Results and Discussion
### Evaluation of Impact of Process Parameters on BNC Biosynthesis Yield  
The Plackett-Burman design was used to identify the most important factors in terms of the BNC production. This statistical method is a useful tool for the identification of factors which significantly influence the process without a detailed analysis of correlation between them. Based on literature, nine factors were typed to this research, namely bioreactor area, surface to volume ratio, air flow ratio, humidity of air, glucose concentration, pH, age and volume of inoculum, and cultivation time. The effects of examined input variables were calculated based on results presented in Table 2 and visualized in Figure 2 as Pareto charts and in Figure 3 as a main effect plots. The analysis performed for the yield calculated as the dry weight per surface unit is presented in Appendix A. From the Pareto charts and main effect plots it can be seen that almost all the studied variables have significant effects on BNC biosynthesis. In case of the dry weight of cellulose, only the s/v ratio and pH were not significantly effective (\(p\) value at 0.465 and 0.063, respectively), while for glucose conversion the s/v ratio was insignificant (\(p\) value at 0.232). The most important factor to maximize the dry weight of cellulose was bioreactor area (Figure 2a) with a contribution of 94.6% (Table 3) followed by the age of inoculum and incubation time. For glucose conversion the highest impact of glucose concentration was noted, with a contribution of 87.1%. The high impact of cultivation time and inoculum volume was also observed. Various studies based on PBD approaches were done to determine the most significant factors that increase BNC yield for different strains. [PERSON], [PERSON], and [PERSON] reported that the highest influencers of BNC yield were the temperature, pH, sucrose, and MgSO\({}_{4}\) concentration in case of agitated culture of _K. hansenii_ NCIM 2529 [23]. [PERSON] et al. observed that the most effective variables for high BNC biosynthesis by _G. persimmonis_ were the nitrogen source and glucose concentration [11]. In case of _G. xyliuns_ cultured in the caro-haricot bean medium, the highest impact of incubation time and nitrogen source, followed by inoculum ratio, was observed [12]. On the other hand, [PERSON] et al. Figure 2: Pareto charts of the standardized effects of process parameters on (**a**) dry weight of cellulose and (**b**) glucose conversion into cellulose. The \(X\) symbols correspond to factors, where \(X_{I}\) is bioreactor area, \(X_{2}\)-cultivation time, \(X_{3}\)-age of inoculum, \(X_{4}\)-s/v ratio, \(X_{5}\)-glucose concentration, \(X_{7}\)-air-flow ratio, \(X_{9}\)-volume of inoculum, \(X_{10}\)-pH, and \(X_{II}\)-humidity of air. The red line is a reference line at 2.056.  
reported significant positive effects of MgSO4, pH, ethanol, and yeast extract on BNC production by _K. hansenii_ AS.5 in Yamanaka medium [24]. It seems that the influence of factors varies for different bacterial strains, culture media, and culture conditions. Moreover, statistical significance of individual variables is dependent on the rational settings of low and high levels of studied factors. In our studies, there were four parameters (\(X_{1}\), \(X_{2}\), \(X_{7}\), and \(X_{8}\)) with positive effects on both studied responses, and two factors which negatively affected both the dry weight of cellulose and glucose conversion (\(X_{3}\) and \(X_{11}\)). Namely, higher bioreactor area, longer incubation time, higher air-flow ratio, and higher concentration of inoculum lead to more efficient BNC production (Figure 3). On the other hand, age of inoculum and moist air instead of dry have a contrary trend. The six factors which had a significant effect on at least one response will be taken into consideration in the second stage of this study which involves detailed analysis of the impact of culture conditions on the yield and mechanical properties.