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Optimization of culture conditions for tannase production by Aspergillus sp. gm4 in solid state fermentation/ Otimizacao das condicoes de cultivo para producao de tanase por Aspergillus sp. gm4 em fermentacao em estado solido.


Tannase or tannin acyl hydrolase (EC is an inducible enzyme produced by different microorganisms, such as bacteria (OSAWA et al., 2000; MONDAL et al., 2001) and fungi (BANERJEE et al., 2001; SAXENA; SAXENA, 2003; MUKHERJEE; BANERJEE, 2006). It catalyzes the breakdown of hydrolysable tannins, as for example tannic acid, as well as gallic acid esters (LEKHA; LONSANE, 1997). In addition, tannase is applied commercially in the food industry where it is used as clarifying agent in some wines and fruit juices, and in the production of instant tea (LEKHA et al., 1993). In the pharmaceutical industry, it is used in the production of gallic acid, a substrate applied in the chemical or enzymatic synthesis of the propyl gallate, a potent antioxidant and in the manufacture of Trimethoprim. Tannase is also used to treat tannery effluents and to reduce the non nutritional effects of tannins in animal feed (AGUILAR; GUTIERREZ-SANCHEZ, 2001).

Studies on tannase production have been done in liquid surface, submerged or solid-state fermentation (SSF) (SABU et al., 2005; MUKHERJEE; BANERJEE, 2006; BANERJEE et al., 2007; BATTESTIN; MACEDO, 2007; RODRIGUES et al., 2007; MANJIT et al., 2008; SELWAL et al., 2011). SSF is a bioprocess in which microorganisms are grown on solid substrates in the absence or near absence of free water (RODRIGUES et al., 2008). Tannase production by SSF shows advantages over submerged or liquid surface fermentation (AGUILAR; GUTIERREZSANCHEZ, 2001; LEKHA; LONSANE, 1994). In this system of enzyme production by fungal sources, the obtaining of tannase is cheaper and less technology oriented. In this respect, tannin-rich plant residues could be a cost-effective substrate in SSF and are advantageous for countries where these materials are generated in abundance (JANA et al., 2012). In addition, this system produces only a negligible amount of liquid effluents and thereby creates less pollution (MANJIT et al., 2008).

Among the microorganisms, the genus Aspergillus has been widely used for the production of tannase (LEKHA; LONSANE, 1997). Species have been studied to produce tannase by fermentation, such as Aspergillus niger (LEKHA; LONSANE, 1994; AGUILAR; GUTIERREZ-SANCHEZ, 2001; SABU et al., 2005), Aspergillus foetidus (MUKHERJEE; BANERJEE, 2006), Aspergillus aculeatus (BANERJEE et al., 2007), Aspergillus ruber (KUMAR et al., 2007), Aspergillus fumigatus MA (MANJIT et al., 2008) and Aspergillus oryzae (RODRIGUES et al., 2007, 2008).

Fermentation processes for the production of tannase are influenced by several parameters, besides the microorganism used, that should be optimized to achieve greater enzyme yield. The main parameters that influence the production of tannase are tannic acid concentration, humidity, type of substrate used, temperature, pH, incubation time and addition of different sources of carbon and nitrogen (LEKHA; LONSANE, 1997). Few studies use experimental designs to optimize the production of tannase, with the majority of optimization experiments evaluating the effect of each variable separately (KAR; BANERJEE, 2000; SABU et al., 2005; MANJIT et al., 2008; RODRIGUES et al., 2008). However, as in fermentation processes each variable can interact with and influence the effect of other, it is essential that an optimization method capable of detecting possible interactions be developed, so that an optimal point is chosen to obtain high yields of enzyme (JANA et al., 2012).

Thus, in the present study the best substrate and optimized the medium conditions were selected for tannase production by Aspergillus sp. GM4 under SSF using experimental design associated to the response surface methodology.

Material and methods

Microorganism and inoculum preparation

The strain Aspergillus sp. GM4, from the collection of the Bioprospecting and Fungal Genetics Laboratory of the Federal University of Lavras, was used. The initial inoculum of Aspergillus sp. GM4 was prepared from 7 day-old cultures grown at 30[degrees]C on potato dextrose agar (PDA) medium. The spores were then scraped and transferred to distilled water and counted in a Neubauer chamber until the desired concentration for each experiment was reached.

Selection of substrates for tannase production under SSF

Leafy vegetables, such as mango (Mangifera indicaL.), jamun (Syzygium cumini) and coffee (Coffea arabica L.), and agro industrial residues like coffee husks, rice husks and wheat bran, were used as substrates for tannase production by Aspergillus sp. GM4 under SSF. The mature leaves of each substrate and the agro industrial wastes were dried at 60[degrees]C, finely powdered and used in SSF. Ten grams of each substrate were added to 250 mL Erlenmeyer flasks, moistened with 10 mL of mineral salt solution at pH 5.0 containing (g [L.sup.-1]): NaN[O.sub.3], 3; KCl, 0.5; K[H.sub.2]P[O.sub.4], 1; MgS[O.sub.4].7[H.sub.2]O, 0.5; FeS[O.sub.4], 7; [H.sub.2]O, 0.01. The obtained contents were autoclaved at 121[degrees]C for 20 min., cooled to room temperature and inoculated with 107 spores [g.sup.-1] to each substrate. After that, all contents were incubated at 30[degrees]C for 96 hours for growth and tannase production by Aspergillus sp. GM4. Each substrate was investigated in duplicate and average values were reported. The Sisvar 5.3 program was used to compare the data by the Tukey test (p [less than or equal to] 0.05). The substrate that presented higher enzyme production was selected for optimization of tannase production in SSF.

Estimation of tannin and centesimal composition of the substrates

The tannin content of substrates was estimated by using the Folin and Denis method (FOLIN; DENIS, 1912).

Moisture content was determined by drying them at 105[degrees]C until constant weight. The ethereal extract, which corresponds to every fraction of the soluble substrate in ether primarily comprising fats, was determined using the continuous type Soxhlet extractor, according to AO AC (1990). The remainder of analyzes were determined in dried and degreased samples: crude protein and amino acid polymers were determined by total nitrogen, according to the method of Kjeldahl, and multiplied by a factor 6.25 for conversion into protein. The ash content, which corresponds to inorganic fraction of the substrate, was determined by burning in a muffle at 550[degrees]C for 3 hours.

Crude fiber (CF) is the residue of acid digestion of the substrate and was determined by the Weende method, based on the difference of weight of a funnel pore before and after receiving the sample digested in acid. In addition, the carbohydrate portion of the substrate was determined by subtraction:

Carbohydrate = 100 - (moisture + protein + ether extract + ash + fiber) (AOAC, 1990).

Effect of tap water as moisturizing agents of jamun leaves in SSF

Tap water was evaluated as moisturizing agent of jamun leaves (substrate selected for next experiments) to replace mineral salt solution. Ten grams of jamun leaves were added to 250 mL Erlenmeyer flasks, moistened with 10 mL of tap water (pH = 5.0). The contents were autoclaved at 121[degrees]C for 20 min., cooled to room temperature and inoculated with 107 spores [g.sup.-1] of substrate. The contents were incubated at 30[degrees]C for 96 h (KUMAR et al., 2007).

Plackett-Burman design

For identifying the influence of the different variables for tannase production, 12 factors were evaluated using the PB experimental design of Plackett and Burman (1946) with 16 trials. The total number of trials to be carried out according to PB is k + 4 where k is the number of variables (RODRIGUES; IEMMA, 2005). Each variable is represented at two levels, high and low, which are denoted by " + 1" and " -1", respectively; and by one central point denoted by "0". Table 1 illustrates the 12 factors investigated, as well as the levels of each factor used in the experimental design. The software Statistica[R] 5.0 was used to analyze the PB design. The independent variables with p value < 0.1, at confidence level of 90%, were considered statistically significant.

Central composite design (CCD), response surface methodology, experimental design and statistical analysis

The response surface methodology was used to optimize the screened components for tannase production using the CCD (MONTGOMERY, 1997). The complete experimental design was performed with [2.sup.2] experiments plus four axial points and three central points to estimate the experimental error. Each factor in the design was studied at five different levels (-1.41, -1, 0, +1, +1.41). A set of 13 experiments was performed.

Upon completion of the experiment, tannase production was taken as the dependent or response variable (Y). The independent variables are coded for statistical calculation according to the following equation: Xi = xi - x0/[DELTA]xi, where Xi is the dimensionless coded value (-1.41 or 1.41) of the independent variable xi; xi is the real value of that independent variable; x0 is the real value of that independent variable xi at the center point; [DELTA]xi is defined by ([Xi.sub.(+1)] - [Xi.sub.(-1)] /2).

The role of each variable, their interactions, and statistical analysis to obtain predicted yields is explained by applying the quadratic equation: Y = [beta]0 + [beta]iXi + [beta]ii[Xi.sup.2] + [beta]jXj + [beta]jj[Xj.sup.2] + [beta]ijXiXj, where Y is the predicted response, [beta]0 is the offset term, [beta]i and [beta]j are the linear effects, [beta]ii and [beta]jj are the squared effects, [beta]ij is the interaction effect, [X.sub.i] and [X.sub.j] are the levels of the independent variables. Statistical analysis of the model was performed to evaluate the analysis of variance (ANOVA).

Statistical significance of the model equation was determined by Fisher's test value, and the proportion of variance explained by the model was given by the multiple coefficient of determination, R squared ([R.sup.2]) value. The quadratic models were represented as contour plots (3D) and response surface curves were generated. The software Statistica[R] 5.0 was used in this investigation.

Obtainment of tannase and enzymatic assay

After incubation, the fermented substrates were mixed properly by adding 0.1 M phosphate buffer (pH 6.0) to the flasks (MANJIT et al., 2008). Then, the flasks were kept on the rotary shaker at 200 rpm for one hour. The crude enzyme was extracted by passing the extract through muslin cloth and later through Whatman no. 1 filter paper. Then it was centrifuged at 10,000 g for 5 min. The filtrate was collected in test tubes and used for determination of tannase activity.

Tannase activity was estimated by a modified protein precipitation method (DESCHAMPS et al., 1983). The reaction mixture (1 mL) contained 250 [micro]L of 1% tannic acid (in phosphate buffer, pH 6.0), 500 [micro]L of phosphate buffer (pH 6.0) and 250 [micro]L of the culture filtrate. The mixture was incubated at 40[degrees]C for 30 min. in water bath. The reaction was stopped by adding 1 mL of 2% bovine serum albumin (BSA) solution. In the control, BSA was added to the incubation mixture prior to incubation. All tubes were left for 20 min. at room temperature to precipitate residual tannins and they were centrifuged at 3000 g for 20 min. The tannase activity in the supernatant was estimated after appropriate dilution and the absorbance directly read at 260 nm (this wavelength corresponds to the optimal absorption of gallic acid) against the control (as blank) in a UV spectrophotometer. One unit of enzyme activity was defined as the amount of enzyme that liberates 1 imol gallic acid per min under assay conditions.

Protein determination

Total soluble protein was determined by the method of Bradford (1976), using bovine serum albumin (BSA) as standard.

Results and discussion

Production of tannase by Aspergillus sp. GM4 under SSF

Different agricultural residues and leaves of different vegetables were studied for production of tannase by Aspergillus sp. GM4 in SSF, as shown in Table 2. Among the different substrates used, the high yield of tannase was obtained using in jamun leaves (1.44 U [mg.sup.-1]) as substrate, followed by mango leaves (0.99 U [mg.sup.-1]), after 4 days of incubation. There was no significant difference in the production of this enzyme between the jamun leaves and mango leaves (p < 0.05). On the other hand, jamun and mango leaves presented higher maximum tannin content at 98.58 and 92.43 mg [g.sup.-1], respectively, compared to the other surveyed substrates. Hence, tannase activity was related to tannin content on the respective substrates. This observation suggested that these substrates could act as an inducer for tannase production (MACEDO et al., 2005). In addition, the high enzyme activity with these substrates may be due to the presence of nutrients required by the fungus (KUMAR et al., 2007).

In respect to the centesimal composition, it was observed that both jamun and mango leaves had high levels of carbohydrates (54.33 and 41.35 %, respectively), fats (5.9 and 4.4 %, respectively) and fiber (21.20 and 30.60%, respectively) compared with others studied substrates. Based on our findings, it was suggested a stimulatory effect on fungus growth (Aspergillus sp. GM4) and, consequently, in its enzyme production (KUMAR et al., 2007).

From these previous results, our study was directed to the jamun leaves, which were selected as a substrate more appropriated for optimization of tannase production on SSF by Aspergillus sp. GM4.

Effect of tap water as moistening agent

The tannase production by Aspergillus sp. GM4 was higher in jamun leaves using tap water as moistening agent (3.07 U [mg.sup.-1]) than using mineral salt solution (1.44 U [mg.sup.-1]). The ability of the microorganism to produce a higher enzyme yield with tap water without addition of mineral salt in SSF could lead to reduction in enzyme production costs (KUMAR et al., 2007). Thus, tap water was used as moistening agent of jamun leaves in optimization experiments.

Plackett-Burman (PB) design

With the purpose of increasing tannase production by Aspergillus sp. GM4 using jamun leaves as substrate under SSF, 12 independent variables were studied (Table 1). Based on Table 3, it may be observed the PB experimental design for 16 trials with two levels of each variable, three trials on central points of each variable and the corresponding tannase production in the course of the experiments.

Among the variables tested, the statistically significant variables (p < 0.1) were tannic acid, potassium nitrate and incubation time. Tannic acid and incubation time had negative effects on tannase production and potassium nitrate had a positive effect (Figure 1).

Tannic acid has been used as inducer for tannase production; however, a great increase in its concentration do not promote an equivalent increase in enzyme synthesis (BATTESTIN; MACEDO, 2007). Actually, tannic acid at a high concentration may produce complexes with membrane protein of the organism, thereby both growth and enzyme production may be inhibited (BANERJEE et al., 2007). Considering the influence of potassium nitrate, similar results were observed for tannase production by A. niger ATCC 16620 (SABU et al., 2005).

This probably occurred due to the distinct assimilation of inorganic ions and the possibility of formation of complexes between tannins and protein structures of the yeast extract (RODRIGUES et al., 2007). Therefore, significant variables were subsequently evaluated.

The other variables studied in PB design such as temperature, amount of substrate, pH, inoculum concentration, glucose, gallic acid, ammonium sulfate, water: substrate ratio and yeast extract had no significant effect over tannase production (p < 0.1) (Figure 1).

Thus, the non-significant variables in the PB design were fixed on following levels: temperature (30[degrees]C); water:substrate ratio (v [w.sup.-1]) (1:1); pH (4.0); inoculum concentration ([10.sup.5] spores [g.sup.-1] of substrate); amount of substrate (5g). As the incubation time had negative and significant effects (Figure 1) on tannase production, this variable was fixed at the lowest level (2 days) (RODRIGUES; IEMMA, 2005).The variables glucose, gallic acid, ammonium sulfate and yeast extract were removed from the CCD experiments.

Central composite design (CCD), RSM, experimental design and statistical analysis

The final medium optimization and interaction amongst the selected factors on PB design was studied. The variables tannic acid (%) and potassium nitrate (KN[O.sub.3]) (%) were optimized using CCD. The levels of the factors chosen were based on the previous PB analysis. Each variable was studied at five coded levels (-1.41, -1, 0, 1, 1.41).

The design matrix of CCD is a [2.sup.2] design combined with three central points and four axial points. The matrix for this design along with the experimental and predicted results is shown in Table 4.

An empirical relationship between the response and the selected variables was expressed by the following fitted second-order polynomial equation: Y= 6.1545 + 0.2366 X1-1.60438 [X.sub.1.sup.2]+ 0.20377[X.sub.2] -1.826 [X.sub.2.sup.2] + 1.5044 XX2, where Y is the predicted response of tannase production (U [mg.sup.-1]), and [X.sub.1] and [X.sub.2] are the coded values of tannic acid and KN[O.sub.3], respectively. This polynomial equation was tested for adequacy by ANOVA. The results of the ANOVA showed that the F value of 4.44 was significant. The [R.sup.2] value indicated that 82% of the total variation was explained by the model. Table 4 shows that all the predicted values of the model are located nearby the experimental values. This supports the hypothesis that the model equation is sufficient to describe the response of the experimental observations (RODRIGUES; IEMMA, 2005). Thus, one response surface curve was plotted to determine the optimum concentration of each factor for maximum tannase specific activity (Figure 2).

The location of the optimum (Figure 2) was determined to be 0.12 (tannic acid) and 0.11 potassium nitrate (coded values) or 1.55% (w [w.sup.-1]) tannic acid and 2.71% potassium nitrate (w [w.sup.-1]) (real values), obtained by the software Design Experts 7.0. Although tannic acid presented negative effect on tannase production by Aspergillus sp. GM4 as observed in PB design, this compound was not removed from the medium since it induces tannase production under SSF as reported in other investigations (LEKHA; LONSANE, 1994; RANA; BHAT, 2005; SABU et al., 2005; BATTESTIN; MACEDO, 2007; RODRIGUES et al., 2008).

These results indicate that although jamun leaves present high tannin content, substrate supplementation with tannic acid was necessary for increasing tannase production. In addition, the presence of nitrogen sources has a positive effect on microbial growth and, consequently, on enzyme production. Tannase production depends on the availability of carbon and nitrogen sources in the medium and both have regulatory effects on enzyme synthesis (BATTESTIN; MACEDO, 2007). Thus, under these conditions, the enzyme production was increased 4.65-fold.

The model was validated by three experiments using 5g of jamun leaves, 1.55% tannic acid and 2.71% KN[O.sub.3]. The predicted response for tannase production was 6.18 U [mg.sup.-1],while an experimental response of 6.69 [+ or -] 0.29 U [mg.sup.-1] was found, confirming the validity of the model (Figure 2) (RODRIGUES; IEMMA, 2005). The good agreement between the predicted and the experimental data indicated that RSM was a powerful tool for optimization of tannase production by Aspergillus sp. GM4.

We are reporting that the fungus Aspergillus sp. GM4 was able to produce high yields of tannase under SSF conditions with jamun leaves. After the optimization process, the tannase production for Aspergillus sp. GM4 using this substrate increased 4.65-fold, which indicates that the statistical experimental design offers a practicable approach to the implementation of medium optimization. Our optimized medium for tannase production is mainly composed of a cheap and accessible substrate (jamun leaves), an inexpensive inorganic salt (potassium nitrate) and low supplementation of tannic acid (1.55%).

Doi: 10.4025/actascibiolsci.v37i1.22731


We acknowledge the financial support of Fundacao de Amparo a Pesquisa do Estado de Minas Gerais (FAPEMIG), Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior (CAPES) and Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq).


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Received on January 6, 2014.

Accepted on October 29, 2014.

License information: This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Patricia Nirlane da Costa Souza (1), Natalia da Costa Maia (1), Luis Henrique Souza Guimaraes (2), Mario Lucio Vilela de Resende (3) and Patricia Gomes Cardoso (1) *

(1) Departamento de Biologia, Setor de Microbiologia, Universidade Federal de Lavras, Cx. Postal 3037, 37200-000, Lavras, Minas Gerais, Brazil.

(2) Departamento de Biologia, Faculdade de Filosofia, Ciencias e Letras de Ribeirao Preto, Universidade de Sao Paulo, Sao Paulo, Brazil.

(3) Departamento de Agronomia, Setor de Fitopatologia, Universidade Federal de Lavras, Lavras, Minas Gerais, Brazil. * Author for correspondence. E-mail:

Table 1. Range of different variables studied in the
Plackett-Burman design.


                    Variables                        -1

1            Temperature ([degrees]C)                25
2      Tap water : Substrate (v [w.sup.-1])        0.5:1
3                       pH                          4.0
4                    Inoculum                  1 x [10.sup.5]
5           Tanic acid% (w [w.sup.-1])               0
6            Glucose% (w [w.sup.-1])                 0
7       Potassium nitrate% (w [w.sup.-1])            0
8             Substrate quantity (g)                 2
9             Incubation time (days)                 2
10         Gallic acid% (w [w.sup.-1])               0
11        Yeast extract% (w [w.sup.-1])              0
12       Ammonium sulfate% (w [w.sup.-1])            0


            0               + 1

1           30               35
2          1:1              2:1
3          5.0              6.0
4     1 x [10.sup.6]   1 x [10.sup.7]
5          2.5               5
6          2.5               5
7          0.6              1.2
8           6                10
9           4                6
10         2.5               5
11         0.6              1.2
12         0.6              1.2

Table 2. Tannin content, centesimal composition and tannase activity
in different substrates used for SSF.

Substrate          Tannin content    Moisture    Protein
                  (mg [g.sup.-1])       (%)        (%)

Jamun leaves           98.58           5.14        8.49
Mango leaves           92.43           4.89        8.49
Coffee husks           31.17           10.37      11.46
Coffee leaves          30.70           14.17      18.73
Wheat bran              5.92           13.27      16.63
Rice husks              2.75           5.54        2.98

Substrate          Fat    Fiber     Ash
                   (%)     (%)      (%)

Jamun leaves      5.90    21.20     6.94
Mango leaves      4.40    30.60    10.27
Coffee husks      2.50    23.60     6.68
Coffee leaves     3.30    21.00    11.24
Wheat bran        1.90    12.20     4.10
Rice husks        0.00    51.00    16.08

Substrate         Carbohydrate       Tannase activity
                       (%)           (U [mg.sup.-1]) *

Jamun leaves          52.33       1.44 [+ or -] 0.43 (a)
Mango leaves          41.35       0.99 [+ or -] 0.16 (ab)
Coffee husks          45.39       0.36 [+ or -] 0.09 (b)
Coffee leaves         31.57       0.34 [+ or -] 0.03 (bc)
Wheat bran            51.90       0.23 [+ or -] 0.04 (c)
Rice husks            24.41       0.13 [+ or -] 0.04 (c)

* Values are means of duplicates and those with different letters
are significantly different at p < 0.05.

Table 3. Placket-Burman design variables (in coded levels)
with tannase production as response.


Trials      1      2      3      4      5      6      7

1           1      1      1      1      1      1      1
2           1      1      1      -1     1      1      -1
3           1      1      -1     1      1      -1     1
4           1      1      -1     -1     1      -1     -1
5           1      -1     1      1      -1     1      1
6           1      -1     1      -1     -1     1      -1
7           1      -1     -1     1      -1     -1     1
8           1      -1     -1     -1     -1     -1     -1
9           -1     1      1      1      -1     -1     -1
10          -1     1      1      -1     -1     -1     1
11          -1     1      -1     1      -1     1      -1
12          -1     1      -1     -1     -1     1      1
13          -1     -1     1      1      1      -1     -1
14          -1     -1     1      -1     1      -1     1
15          -1     -1     -1     1      1      1      -1
16          -1     -1     -1     -1     1      1      1
17 (C)      0      0      0      0      0      0      0
18 (C)      0      0      0      0      0      0      0
19 (C)      0      0      0      0      0      0      0

Trials      7      8      9      10     11     12    (U [mg.sup.-1])

1           1      1      1      1      1      1           0.80
2           -1     1      -1     -1     1      -1          1.04
3           1      -1     1      -1     -1     1           1.24
4           -1     -1     -1     1      -1     -1          3.08
5           1      -1     -1     1      -1     -1          6.12
6           -1     -1     1      -1     -1     1           0.47
7           1      1      -1     -1     1      -1          8.94
8           -1     1      1      1      1      1           1.58
9           -1     1      1      1      -1     -1          0.68
10          1      1      -1     -1     -1     1           3.52
11          -1     -1     1      -1     1      -1          2.49
12          1      -1     -1     1      1      1           7.29
13          -1     -1     -1     1      1      1           3.86
14          1      -1     1      -1     1      -1          1.34
15          -1     1      -1     -1     -1     1           1.08
16          1      1      1      1      -1     -1          4.81
17 (C)      0      0      0      0      0      0           0.59
18 (C)      0      0      0      0      0      0           0.95
19 (C)      0      0      0      0      0      0           1.45

(C) Central Points.

Table 4. CCD matrix of two variables with experimental and
predicted values of tannase production.

           Tannic Acid     KN[O.sub.3]
Trials         (%)             (%)

1            (-1) 0.4       (-1) 1.6
2            (+1) 2.4       (-1) 1.6
3            (-1) 0.4       (+1) 3.6
4            (+1) 2.4       (+1) 3.6
5           (-1.41) 0        (0) 2.6
6          (1.41) 2.82       (0) 2.6
7            (0) 1.41     (-1.41) 1.19
8            (0) 1.41       (1.41) 4
9 (C)        (0) 1.41        (0) 2.6
10 (C)       (0) 1.41        (0) 2.6
11 (C)       (0) 1.41        (0)2.6

               Tannase           Predicted
               Activity           Activity
Trials     (U [mg.sup.-1])    (U [mg.sup.-1])

1                4.75               3.79
2                1.97               1.25
3                1.83               1.19
4                5.06               4.67
5                1.78               2.63
6                2.79               3.30
7                1.33               2.24
8                2.36               2.81
9 (C)            5.03               6.15
10 (C)           7.74               6.15
11 (C)           5.70               6.15

(C) Central points.

Figure 1. Pareto Chart of standardized effects of variables in PB
design on tannase production by Aspergillus sp. ([R.sup.2] = 0.83).

                            Effect Estimate
                            (Absolute Value)

(9)Time                      -3.04635
(7)Potassium nitrate          2.801677
(5)Tannic acid               -1.95639
(3)pH                        -1.79418
(12)Ammonium sulfate         -1.22445
(10)Gallic acid               1.144238
(2)Water:Substrate           -1.14115
(11)Yeast Extract              .8955109
(8)Substrate                  -.484887
(4)Inoculum                    .2956184
(1)Temperature                -.253338
(6)Glucose                    -.019671


Note: Table made from bar graph.
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Title Annotation:texto en ingles
Author:Souza, Patricia Nirlane da Costa; Maia, Natalia da Costa; Guimaraes, Luis Henrique Souza; de Resende
Publication:Acta Scientiarum. Biological Sciences (UEM)
Date:Jan 1, 2015
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