Five different strains of Zygomycetes, namely, Absidia blakesleeana NCIM 889, Absidia butleri NCIM 977, Cunninghamella blakesleeana NCIM 687, Cunninghamella echinulata NCIM 691 and Rhizopus oryaze NCIM 1009 were purchased from National Collection of Industrial Microorganism (NCIM) Pune, India. For the screening, all the five strains were grown and maintained on potato dextrose agar (PDA) slants, grown at 30˚C for 10 days and stored at 4˚C and subcultured on a monthly basis. The chemicals and media components utilized in the present study were procured from Hi-Media (Mumbai, India). Concentrated NaOH solution was commercial grade and all chemicals were of analytical grade. Standards of chitosan were obtained from Sigma Chemical Co. (St. Louis, MO, USA).

The inoculum was prepared in Erlenmeyer flasks (250 ml) containing 100 ml of potato dextrose broth, inoculated with spore suspension (1.8 × 10⁸ spores/ml) and incubated at 30˚C for 16 h on a rotatory shaker (180 rpm). A 7.5% (v/v) of sixteen hr old inoculums was added aseptically to the 500 ml Erlenmeyer flasks, each containing 200 ml of the sterile production media of glucose 2%, peptone 1%, yeast extract 0.1%, (NH₄)₂SO₄ 0.5%, K₂HPO₄ 0.1%, NaCl 0.1%, CaCl₂ H₂O 0.01%, MgSO₄·7H₂O 0.05% [12] . The pH of production media was adjusted to 4.5 using hydrochloric acid. All inoculated flasks were kept on a rotary shaker at 30˚C ± 2˚C and 180 rpm. Various strains belonging to Zygomycetes species were screened for production of mycelial chitosan. The concentration of various carbon and nitrogen sources and culture conditions varied according to the experimental design described below. Unless otherwise stated, the cultivation was carried out using 500 ml Erlenmeyer flasks on a 180 rpm shaker at 30˚C ± 2˚C. All procedures were performed in triplicate.

To determine the optimum batch time for mycelial chitosan production, its production was carried out under the defined conditions, for different time periods ranging from 12 to 96 h. In order to investigate effect of initial pH of production media, fermentation runs were carried at initial pH varying from 3 to 6. The pH was adjusted using 0.1 N hydrochloric acid or 0.1 N sodium hydroxide. The effect of temperature on biomass and yield of mycelial chitosan was studied by incubating the production medium at varying temperature from 25˚C to 30˚C. In all three parameters after incubation, biomass was harvested, filtered through Whatman filter paper no. 1, washed with distilled water and dried them at 60˚C to a constant weight to determine the cell dry weight.

Several carbon sources were used to study the effect on mycelial chitosan production. To study the effect of various carbon sources on chitosan production, in the production medium, D (+) glucose was substituted with eight different carbon sources. All the carbon sources were used at 2% (w/v) concentration. Rests of the physicochemical parameters were constant.

To evaluate the effect of different nitrogen sources on mycelial chitosan production, combination of peptone (1% w/v), yeast extract (0.1% w/v) and ammonium sulphate (0.5% w/v) was replaced with different nitrogenous sources (both organic and inorganic) with concentration of 1.6% w/v. Mycelial chitosan yield and dry cell weight (DCW) were determined and rest of the physicochemical parameters were constant.

The most influential factors for mycelial chitosan production found by “one-factor-at-a-time” approach were further optimized with statistical approach. To describe the level of the significant parameters, interaction between variables, which influence the yield of mycelial chitosan and, the nature of the response surface in the optimum region, a Box-Behnken design [17] , and the response surface methodology was performed.

In this study, the experimental plan consisted of 17 trials and the independent variables are studied at three different levels, low (−1), medium (0) and high (+1). The variables and their coded levels used for the study are shown in Table 1. All the experiments were done in triplicate and the average of mycelial chitosan yield obtained was taken as the dependent variable or response (Y_CY). The second-order polynomial coefficients were calculated and analyzed using the Design Expert version 7.0.0 (STAT-EASE Inc., Minneapolis, MN, USA), statistical package.

The general form of the second degree polynomial Equation (1) is

where, Y_CY is the predicted response; β₀ a constant; β_i the linear coefficient; β_ii the squared coefficient; and β_ij the cross-product coefficient, k is number of factors, x_i and x_j the level of the independent variables, subscripts i and j takes values from 1 to the number of variables.

In the present study, three variables are involved and hence n takes the value 3. Thus, by substituting the value 3 for n, and the coded variables for natural ones, Equation (1) becomes the following form: The yield of mycelial chitosan was taken as dependent variable or response Y_CY, and a multiple regression analysis of the data was carried out for obtaining an empirical model that relates the response measured to the independent variables.

The statistical and regression analyses of experimental data obtained from Box-Behnken design was done by using software Design Expert version 7.0.0 (STAT-EASE Inc., Minneapolis, MN, USA) to determine the significant differences (p ≤ 0.05) in response under different conditions. Three-dimensional surface plots were constructed for visualization of interaction between significant variables and their optimal values. The goodness of fit of the model was evaluated by the coefficient of determination (R²) and the analysis of variance (ANOVA) and its statistical significance was checked by an F test quadratic polynomial equations were attained by holding one of the independent variances at a constant value and changing the level of the other variables.

The dried fungal cell mass was finely homogenized and subjected to alkali treatments to extract alkali soluble material like glucan and protein, present in fungal biomass. Dried mycelia homogenized dry cell mass were treated with 1 N sodium hydroxide solution (1:40, w/v) carried out by autoclaving biomass at 121˚C for 20 min. The alkali insoluble materials (AIM) were centrifuged (10,000 rpm, 15 min), washed with distilled water, until it completely gets neutralized and further treated with 2% acetic acid (1:40, w/v) at 95˚C for 6 h, closely following the method of [18] . Through centrifugation, the supernatant, containing the chitosan, was isolated from the acid insoluble fraction. The mycelial chitosan was precipitated from supernatant by adjusting pH 10.0 with 2 M sodium hydroxide. The precipitate was centrifuged (10,000 rpm, 15 min) and washed with distilled water to pH 7, followed by 95% (v/v) ethanol (1:20, w/v) and acetone (1:20, w/v), and dried at 60˚C for 24 h and, weighed to calculate a mycelial chitosan yield. According to McGahren et al. [19] the alkali-insoluble precipitate obtained after suitable alkali and acid extraction contained virtually pure mycelial chitosan.

Isolated mycelial chitosan obtained by submerged fermentation by evaluating some of the physical properties including glucosamine content, Fourier-transform infrared (FTIR) spectroscopy, degree of deacetylation (DD), viscosity and molecular weight (MW).

Screening of fungal strains for mycelial chitosan producers are presented in Figure 1. Maintaining the fermentation parameters same, DCW of the strains ranges from 3.6 g/L (R. oryzae NCIM 1009) to 6.8 gm/L (A. butleri NCIM 977). In our screening among five fungal strains, we found that A. butleri NCIM 977 gave maximum production of mycelial chitosan (401 mg/L) followed by C. echinulata NCIM 691 (372 mg/L) and R. oryaze NCIM 1009 (274 mg/L). According to Bartnicki-Garcia [7] Zygomycetes species, contains chitosan as natural components of their cell wall. Nwe et al. [11] suggested that chitosan biosynthesis starts with production of chitin with the conversion of glucose into N-acetylglucosamine-1-phosphate, which reacts with UTP to form UDP- N-acetylglucosamine in a reaction catalyzed by glucosamine-6-phosphate synthase. Subsequently, the enzyme chitin synthase transfer the sugar dimer of N-acetylglucosamine moiety into the growing chitin polymer chain. Furthermore in Zygomycetes, deacetylation of the growing chitin chain occurs through the action of the enzyme chitin deacetylase which results in formation of mycelial chitosan. From the present experiment, it was found that A. butleri NCIM 977 was the most suitable fungal strain since it produced highest mycelial chitosan and therefore used for further optimization study.

In order to determine the optimum batch time for mycelial chitosan production, fermentation process was carried out in 200 ml of sterile production media at 30˚C ± 2˚C on a rotary shaker at 160 rpm for different time level ranging from 12 h to 96 h. It was observed that 72 h time period resulted into maximum mycelial chitosan production of 585.33 mg/L with DCW 7.6 g/L (Figure 2). Further increase in fermentation time observed low productivity and biomass concentration which may be due to physiological changes in the fungal cell wall [19] . Rane and Hoover [26] reported that decrease in mycelial chitosan yield is due to its degradation by chitosanase activity. Chitosan is produced in the fungal cell wall by deacetylating its precursor, nascent chitin [12] . During the exponential phase, the ratio of free chitosan molecules is relatively high, due to the active growth. Once the

culture enters the stationary growth phase, more of the chitosan is anchored to the cell wall of the Zygomycetes by binding to chitin and other polysaccharides and extraction becomes more difficult [7] . Therefore, although the fungal biomass was increased during the stationary growth phase, less chitosan is obtained while maximum mycelial chitosan yields at the late exponential phase [12] .

The pH of the medium always influences the physiology of a microorganism by affecting nutrient desirability, enzyme activity, oxidative-reductive reactions and most importantly cell membrane morphology. Among the various initial pH range studied (3 - 6), an initial pH 5.5 supported the maximum production of mycelial chitosan (669.16 mg/L) as well as biomass (Figure 3). The results were in agreement with the studies reported by Synowiecki and Ali-Khateeb [18] for Mucor rouxii while Yokoi et al. [27] for Gongronella species and Muzzarelli et al. [28] for Absidia coerulea for mycelail chitosan production. This may be due to the fact that the pH ranging from 4.5 to 5.5, favors the production of enzyme chitin deacetylase, which convert chitin to chitosan in fungal cell wall [13] .

Temperature influences the metabolic activities and microbial growth which affects the production. In order to find out the effect of temperature on mycelial chitosan production, fermentation was carried out at different temperatures ranging from 20˚C to 35˚C. The yield increases from 20˚C till 30˚C and further decreased at 35˚C (Figure 4). A maximum mycelial chitosan production of 667.16 mg/L with highest biomass production (8.4 g/L) was observed at 30˚C.

During microbial fermentations, the carbon source not only acts as a major constituent for building of cellular material, but also as an important energy source. All carbon sources with 2% (w/v) concentration showed different effects on mycelial chitosan production (Figure 5). The fungal strain A. butleri NCIM 977 grown on the medium supplemented with fructose, sucrose, galactose resulted in increase biomass production however glucose as a sole carbon source supported the highest biomass as well as mycelial chitosan production as compared to other carbon sources. Among all carbon sources glucose employed showed maximum mycelial chitosan production (683.16 mg/L) with DCW of 8.3 g/L, followed by galactose (383 mg/L), fructose (343.33 mg/L), and sucrose (291.5 mg/L). It may be due to the fact that glucose can be easily assimilated in the metabolic pathway for biosynthesis.

The nitrogen source is a critical factor which needs to be optimized for mycelial chitosan production. Chitosan is a nitrogen containing biopolymer, which is deacetylated form chitin. Fungi require an inorganic or organic nitrogen source as nutrient to synthesize the chitin and chitosan for their cell wall. Hence the nitrogen source is one of the important factors for the production of chitosan by fungi [29] . Among the organic and inorganic nitrogen sources, organic nitrogen source exhibited a prominent effect on mycelial chitosan production (Figure 6 and Figure 7). Among the organic nitrogen sources studied soyabean meal produced the highest DCW of 11.13 g/L followed by beef extract (7.44 g/L) and yeast extract (7.06 g/L). However, tryptone supported the maximum production of mycelial chitosan (570.33 mg/L) with DCW of 6.78 g/L. In the absence of nitrogen source, chitosan yield was found to be drastically decreased, hence it can be concluded that that nitrogen source is significant parameter in the fermentative production of mycelial chitosan.

In this study, according to Box-Behnken design, all 17 designed experiments were conducted with different combinations of three independent parameters (glucose, tryptone and yeast extract) at three different levels, low (−1), medium (0) and, high (+1) to study the combined effects of these factors towards yield of mycelial chitosan. The variables and their coded levels used for the study are shown in Table 1. Box-Behnken design matrix of independent variables in coded units along with experimental and predicted values for mycelial chitosan production is shown in Table 2. The results were analyzed by multiple regression analysis. Maximum yield of mycelial chitosan (1 g per litre of fermentation media) was recorded under the experimental conditions having media

^aValues are mean ± SD of three determinations.

concentrations of glucose 1.5% (w/v), tryptone 1.6% (w/v), and yeast extract 1.1% (w/v). Consequently, the following second order polynomial equation for mycelial chitosan production was regressed and expressed in term of coded factors. It represents yield of mycelial chitosan (Y_CY) as a function of concentration of glucose (A), tryptone (B) and yeast extract (C).

In order to determine whether or not the quadratic model is significant, it is necessary to conduct analysis of variance (ANOVA). ANOVA for response surface quadratic model is presented in Table 3. The p-values were used as a tool to check the significance of each coefficient, which, in turn are necessary to understand the pattern of the mutual interactions between the test variables. The lower p-values are the more significant and effective in process parameters [30] . Here, the p-value of the model was smaller than 0.0001, which indicated that the model was suitable for use in this experiment. The lack of fit test, measures the failure of the model to represent experimental data in the experimental domain at point which are not included in regression analysis [31] . The p-value of “lack of fit” was 0.6031 (p > 0.01), indicated that “lack of fit” was insignificant relative to the pure error and the model equation was adequate to predict yield of mycelial chitosan under any sets of combination of variables. The regression coefficients and the corresponding p-values were presented in Table 4. From the p-values of each model term, it could be concluded that two linear coefficients (A, C), two quadratic coefficients (A², B²) and one cross-product coefficients (AC) were significant. It implies that three parameters are very critical for the production of mycelial chitosan and there was strong interaction between concentrations of glucose and yeast extract. The statistical significance of the polynomial equation was carried by F-test. The model F-

^aDegree of freedom; ^*Significant; ^**Not significant.

A—Glucose; B—Tryptone; C—Yeast extract; ^aDegree of freedom; ^*Significant; ^**Not significant.

value of 64.20 (p < 0.0001) implies the model is significant and is calculated as ratio of mean square regression and mean square residual. The goodness of fit of the model was checked by coefficient of determination (R²) and adjusted coefficient of determination (adjusted R²). The R² value varies from 0 to 1.0 and close to 1.0 implies better accuracy of the model. But in certain cases higher R² value may be resulted in presence of large number of insignificant variables in the model and thereby predicts poor response. So the term adjusted R² was introduced which corrects R² value accordingly to the sample size and number of terms in model. Ideally adjusted R² should be close to R² value. Larger difference between R² and adjusted R² gives warning that model content too many insignificant terms [32] . The high R² value (0.9880) indicates, good correlation between experimental and predicted values and 98.80% of the variability in the response could be explained by the model. The R² of 0.9880 is in reasonable agreement with the adjusted R² of 0.9726 confirming the validity of the model. “Adequate Precision” measures the signal to noise ratio and its value can be predicted by statistical analysis. A ratio greater than 4 is desirable [32] . In the present study, a ratio of 27.907 indicates an adequate signal. This explains that the model can be used to navigate the design space. The coefficient of variation (CV) is the ratio of the standard error of estimate to the mean value of the observed response, expressed as a percentage. Usually, the higher the value of CV, the lower is the reliability of experiment while low CV value predicts accuracy and reliability of the experiments conducted [33] . Here CV value was found to be 6.13 indicates a greater degree of precision. This is also evident from the parity plot (Figure 8), obtained by plotting observed and predicted yield of mycelial chitosan and it suggests satisfactory correlation between experimental and predicted value, as the data points were confined close to the digonal line, showing that the prediction of experimental data is quite satisfactory.

Perturbation graph shows the effect of each of the independent variables on response while keeping other variables at their respective zero level. From Figure 9 it is revealed that tryptone concentration (B) was most critical factor followed by glucose concentration (A) whereas yeast concentration (C) is least influential factor for the production of mycelial chitosan.

Accordingly, 3-D response surface plot were generated for the pairwise combination of two independent variables where remaining variables are fixed at their respective zero level and described by the regression model which illustrate the interactive effect of this independent variables on the response variable and also determine optimum level of each variable [34] .

Figure 10(a) represents the effects of glucose concentration, tryptone concentration and their reciprocal interactions on yield of mycelial chitosan at constant yeast extract concentration of 1.6% (w/v). At the designed

range of glucose concentration from 1.5% (w/v) to 2.5% (w/v), the amplification of mycelial chitosan yield resulted in a linear increase in tryptone concentration, and then reduced. It can be inferred that yield of mycelial chitosan was markedly affected by the combination of glucose concentration and tryptone concentration. An increase of tryptone concentration increased the mycelial chitosan yield at a constant glucose concentration within a tryptone concentration of 1.6% (w/v). The appropriate maximal mycelial chitosan yield was determined at a glucose concentration of 1.5% (w/v). Figure 10(b) shows the effects of glucose concentration, yeast extract concentration and their reciprocal interactions on mycelial chitosan yield at a tryptone concentration of 1.6% (w/v). At the designed range of glucose concentration from 1.5% (w/v) to 2.5% (w/v), the yield of mycelial chitosan increased with decreasing concentration of yeast extract. At low concentration of yeast extract, the yield of mycelial chitosan was found to be maximum. It could be seen from Figure 10(b) that at high concentrations of both glucose and yeast extract the yield of mycelial chitosan was minimum while the optimum concentrations of glucose and yeast extract for maximum mycelial chitosan production was around 1.5% (w/v) and 1.1% (w/v) respectively. The effect of concentrations of tryptone and yeast extract on the yield of mycelial chitosan at a glucose concentration of 2% (w/v) is provided in Figure 10(c). At first, an increase in mycelial chitosan yield was observed with the increasing of yeast extract and tryptone concentration. But the trend was reversed when the concentrations of glucose and tryptone reached a certain value. It could be seen from Figure 10(c) that yield of mycelial chitosan was affected significantly by tryptone concentration.

In order to verify the predicted results, an experiment was performed using the optimized nutrient levels. The optimum conditions for these selected parameters were predicted using desirability function criteria available in design expert software. The maximum predicted mycelial chitosan production could be achieved with glucose concentration of 1.58% w/v (A), Tryptone concentration of 1.61% w/v (B), and yeast concentration of 1.11% w/v (C). Under these conditions experiments were carried out in triplicate. The mean value of the yield of mycelial chitosan was 1.002 mg/L, which agreed with the predicted value (1.0012 mg/L) well. As a result, the models developed were considered to be accurate and reliable for predicting the production of mycelial chitosan from A. butleri NCIM 977.