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UDC 606:546.289:662.7 https://doi.org/10.15407/biotech10.04.044
VARIANCE ANALYSIS FOR OPTIMIZATION OF THE GERMANIUM BIOLEACHING PROCESS FROM COAL BENEFICIATION DUMPS
I. A. Blaydа
N. Yu. Vasylieva Odesa National Mechnykov University, Ukraine
T. V. Vasylieva L. I. Sliusarenko
E-mail: [email protected]
Received 17.05.2017
The aim of the work was to optimize the process of germanium bioleaching from the dumps after coal beneficiation, namely, to determine the optimal composition of the new nutrient medium for acidophilic chemolithotrophic bacteria ensuring the maximum recovery of valuable metal in minimum time. We optimized the method of mathematical planning adapted to the plan in Greek-Latin squares. The calculations in this approach are based on the analysis of variance. The formal design of experiments has been carried out with four operating factors at four levels. The calculations were performed in Excel. The significance of the factor levels were analyzed using the Duncan's multiple range test, the uniformity of the variances was examined the Cochran test, and the significance of the factors was tested by the Fisher criterion for each day of the experiment. The obtained results were interpreted mathematically and biologically. The following combination of factors and their levels was recommended as optimum nutrient medium, g/dm3: KH2PO4 — 1.0; (NH4)2SO4 — 2.0; KCl — 0.1; MgSO4 — 0.5; NH4Cl — 0.5; Na2S2O3 — 5.0. The proposed composition allows the more than 90% quick extraction of germanium into the solution (in four days), which was previously impossible.
Key words: bioleaching, acidophilic chemolithotrophic bacteria, germanium, coal beneficiation, Greek-Latin squares, variance analysis.
Previously [1-7], rock waste of coal enrichment in Ukraine proved to be promising as a source of the rare metal germanium. The tested current biotechnological methods exploit the native microbiota activity. A singular community of mostly the heterotrophic and acidophilic chemolithotrophic bacteria is formed during the processes of formation, storage and storage in the studied man-made ecosystems [5]. There, the most active group of microorganisms in the native microbiota of coal waste substrates at coal dumps is a group of acidophilic chemolithotrophic microorganisms, both mesophilic and moderately thermophilic, of the genera Acidithiobacillus and Sulfobacillus [6]. In our work, the optimal parameters of the bioleaching process were selected and determined according to the recommendations on the use of nutrient media to activate a certain group of microorganisms, and conditions for their maximum growth and activity [8, 9]. Under constant conditions (ratio of solid (substrate)
to a liquid (nutrient medium) S:L = 1:10, pH < 2.0, 30.0 ± 2 °C, 7 days, using a standard 9K nutrient medium with the addition of 44.5 g/dm3 FeSO4'7H2O as an energy source) the bioleaching process allows sufficiently high extraction of germanium and some of the heavy metals from the dumps into the solution [2]. The composition of nutrient medium is of utmost importance in the extraction of metals from the raw material. Specifically, phosphorus and nitrogen sources are necessary for the biomass growth of taxonomically different microorganisms, which also require energy sources to enhance their activity. Increasing the degree of germanium recovery into the solution in the shortest possible time is essential to intensify the developed biotechnological method. Mathematical methods of planning and analysis are widely used to optimize the studied biotechnological process with respect to this parameter, taking into account all possible factor effects with minimal number of experiments [10-15].
The aim of the work was to optimize the process of bioleaching germanium from the coal enrichment wastes, namely, to determine the optimal composition of the new nutrient medium, basing the experimental design on the variance analysis.
Materials and Methods
The study object was the rock waste of coal enrichment at the Chervonogradska coal preparation plant (CPP) of Lviv Coal Company by gravity separation and flotation methods. ROM coal was obtained in the mines of the Lviv-Volyn coal basin. The substrate is crystalline rock, comprised mostly of fairly large (5-7 mm) particles with a coal content up to 17.0%, sulfur up to 1.5% and organic weight up to 2.0%. Chemical composition,%: Fe — 4.46; Al — 1.39; Si — 15.90; Ti — 0.42; Ca — 1.72; Cu — 6.22.10-3; Zn — 1.13 .10-2; Mn — 3.18 . 10-2; Pb — 0.42 .10-2; Ni — 1.34 .10-2; Cd — 2.82.10-4; Sn — 3.52.10-2; Cr — 0.99.10-2; V — 1.50.10-2; Co — 1.16.10-2; Sr — 2.11.10-2; Ba — 5.19.10-2; Zr — 1.73.10-2; Rb — 1.41.10-2; Nb — 1.40.10-3; La — 4.80.10-3; Ce — 6.90.10-3; Ga — 1.2M0-3; Ge — 2.60.10-3. The substrate was stored in coal dumps for one year. The densities of aboriginal acidophilic chemolithotrophic microbiota are 6.4 ± 0.6 .104 cells/ml for mesophilic bacteria and 7.4 ± 0.3 .108 cells/ml for moderately thermophilic bacteria [5].
The fastest maximum extraction of germanium into the solution was selected as optimization parameter Y. The optimization was based on the method of mathematical experiment planning, adapted for the plan in Greco-Latin squares calculated using the variance analysis. The method itself consists in the determination and evaluation of individual factors and their combinations that cause the variability of the studied value [10-13]. The acting factors and their priority, the number of their levels and the size of the sample were
determined based on the requirements for planning the stages of the experiment and previous results. The formal planning of the experiment was carried out with four acting factors on four levels.
The value of the chosen variation interval should be greater than twice the quadratic error with which the level of this factor is fixed. The reason for this is that a small variation interval reduces the experimental area and hinders the search for the optimum. Thus the nutrient medium components serve as the factors of variation if there are sufficiently wide ranges of their concentration variations, known from the literature or established experimentally. The main requirement remains the importance of the factor for the growth of the microorganism.
Hence, four factors were chosen to determine the composition of the future nutrient medium. The factors were the nutrient medium components, standard sources of phosphorus and nitrogen for culturing the microorganisms of different taxonomic groups: A — KH2PO4, B — K2HPO4, C — (NH4)2SO4, and D — energy sources (FeSO4.7H2O, Fe2(SO4V7H2O or Na2S2O3) [8, 9, 16]. The levels of factors are given in Table 1. As additional components, the following salts were used in concentration as standard additives in cultivation of various microorganisms [9, 16], g/dm3: KCl 1.0; MgSO4 0.5; NH4Cl 0.9.
Based on the matrix of the four-factor experiment for four levels according to Greek-Latin squares, Table 2 was compiled reflecting the factor combinations for carrying out the experiments.
The calculations of the variance analysis according to the plan in Greco-Latin squares are presented in [13, 14]. The calculations were performed in Excel. The importance of the factor level was analyzed based on the multiple rank Duncan test for each day of the experiment, the uniformity of variances was verified with the Cochran test, and the
Table 1. Factor levels (g/dm3), used in the variance analysis adapted for the plan in the Greco-Latin squares
Factors Factor component concentration, g/dm3
Level 1 Level 2 Level 3 Level 4
A — KH2PO4 0.0 1.0 2.0 3.0
B — K2HPO4 0.0 0.5 1.0 1.5
C — (NH4)2SO4 0.0 2.0 3.0 5.0
D — energy sources FeSO4-7H2O 44.0 Fe2(SO4)3-7H2O 15.0 Na2S2O3 5.0 Fe2(SO4)3-7H2O 30.0
Table 2. Experimental conditions based at a four-factor four-level experiment matrix according
to the Greco-Latin squares method
№№ experiment Level A Level B Level C Level D Optimization parameter
1 A1 B1 C1 D1 Y1
2 A1 B2 C2 D2 Y2
3 A1 B3 C3 D3 Y3
4 A1 B4 C4 D4 Y4
5 A2 B1 C2 D3 Y5
6 A2 B2 C1 D4 Y6
7 A2 B3 C4 D1 Y7
8 A2 B4 C3 D2 Y8
9 A3 B1 C3 D4 Y9
10 A3 B2 C4 D3 Y10
11 A3 B3 C1 D2 Y11
12 A3 B4 C2 D1 Y12
13 A4 B1 C4 D2 Y13
14 A4 B2 C3 D1 Y14
15 A4 B3 C2 D4 Y15
16 A4 B4 C1 D3 Y16
importance of factors was tested using the Fisher criterion (F). The value of the Fisher criterion was assumed to be significant at 95.0% (P = 0.05).
Bacterial leaching of metals was carried out in the previously determined optimal conditions: S: L = 1:10; pH < 2.0; temperature 30.0 ± 2.0 °C, stationary cultivation for 7 days. The content germanium in solutions was analyzed using AAS-1 (Germany) and S-115PK Selmi (Ukraine) devices for atomic absorption spectroscopy. The reliability of the results was evaluated by the Student's test with a probability of P < 0.05. The "metal extraction ratio" is the ratio of the amount of metal passed into solution as a result of contact of the nutrient medium with the substrate in the presence of microorganisms (in%) to the original amount of this metal in the original solid substrate. The 100% corresponds to a complete transition of the metal from the substrate to the solution.
Results and Discussion
The results for determining the optimization parameter (the degree of germanium extraction in the solution for each day of the experiment) are given in Table 3 and in the Figure. The mean germanium recovery was determined in all of the 16 experiments in 1-7 days of
observations. The difference between the maximum and average indices of germanium extraction supports the advantage of a certain combination of factors with respect to the general variety: the greater the difference, the more effective the combination of factors. The obtained results were interpreted both from the mathematical and from the biological point of view [15].
The generalized table of calculated values was analyzed using the Fisher test (Fr) for all observation days (Table 4). The factor D is the most effective factor, and its maximum effect was recorded from the 4th to the 7th days of the study (Fr > Fst, where Fst is the table value of the Fisher test, equal to 3.49) [17]. Calculated with according to the Plokhinsky formula [18], the factor's influence on the optimization index (Table 5) was also the maximum for factor D. The tested indicator ranged from 58.9 to 73.2% for the 4th-6th days of the study. The maximum amount of germanium passed from the substrate to the leaching solution was also recorded on the 4th day of observation (Figure).
The daily calculation of the statistics according to the dispersion analysis adapted to the Greco-Latin square plan showed that in the 1st day of the experiment the Fisher criterion value was the maximum for almost all factors (Table 4). The only factor with the
Table 5. Indicators of factor influence (Plokhinsky's formula,%)
Table 3. Extraction rate of germanium (%) during optimization planned in the Greco-Latin squares
№№ experiment Day 1 Day 2 Day 3 Day 4 Day 5 Day 6 Day 7
1 0.52 15.63 18.34 25.05 17.88 31.68 36.95
2 8.54 12.44 17.61 23.78 14.34 29.68 29.14
3 4.54 7.72 6.23 39.94 16.88 17.43 16.34
4 7.51 2.72 9.35 1.15 0.40 8.17 7.26
5 5.08 4.81 7.26 82.60 62.18 86.87 76.34
6 8.26 5.54 10.35 2.36 9.99 0.36 2.25
7 3.36 12.70 11.98 0.00 10.44 7.26 1.45
8 11.80 13.25 15.79 48.38 42.94 60.46 68.45
9 9.98 6.98 11.35 4.36 8.26 8.62 1.49
10 13.40 11.44 10.35 93.50 93.50 80.25 70.00
11 9.26 14.34 11.98 45.66 68.89 60.55 47.75
12 4.54 11.17 7.89 0.00 5.08 6.35 3.00
13 6.54 8.71 12.53 42.39 43.94 39.40 37.85
14 9.98 7.81 14.43 4.36 9.35 9.08 7.00
15 5.81 12.35 10.44 0.00 4.18 1.45 0.90
16 10.89 9.80 16.52 36.58 52.11 57.37 65.05
Table 4. The values of the Fisher's exact test (P = 0.05)
Factor (dispersion source) Fisher's exact test (Fr)
Day 1 Day 2 Day 3 Day 4 Day 5 Day 6 Day 7
A — KH2PO4 6.23 0.16 0.93 0.87 3.31 0.85 0.43
B — K2HPO4 9.80 0.61 0.51 1.02 0.35 0.80 1.21
C — (NH4)2SO4 2.99 0.53 0.83 0.25 1.79 0.39 0.46
D — energy sources 7.59 2.24 1.67 12.4 11.66 8.95 8.47
Factor (dispersion source) Evaluation of the factor influence, %
Day 1 Day 2 Day 3 Day 4 Day 5 Day 6 Day 7
A — KH2PO4 24.6 5.49 12.4 5.12 17.19 6.98 73.1
B — K2HPO4 35.5 2.5 9.5 6.23 1.84 6.47 4.74
C — (NH4)2SO4 11.1 3.01 15.6 1.61 9.5 3.09 20.8
D — energy sources 29.18 7.21 22.1 73.2 58.9 64.2 4.71
Fisher criterion value below the tabulated one was factor C, (NH4)2SO4. Testing the factor influence using the Plokhinsky's formula, it was shown that factors B (K2HPO4) and D (energy sources) exhibited the maximum influence on the optimization index on the first day of observation (Table 5). In this case, the optimization parameter (the degree of germanium extraction to the leaching solution) was minimal. The mean
indicator of germanium recovery from the general set of all 16 experiments for the first day was only 7.5%, and the maximum was 13.4% (Figure).
The most significant levels were determined using the multiple Duncan criterion, also taking into account all the information obtained in the experiment [12]. The significant levels of the active factors determined with the Duncan rank test are given in Table 6.
Fig. The mean and maximum indicators of germanium extraction into solution in the bioleaching process, optimized using dispersion analysis adapted to the Greek-Latin square planning * — P < 0.05 compared to control (0)
Table 6. The generalized significant levels of active factors determined using the Duncan rank test
Time Factor level
Factor A Factor B Factor C Factor D
Day 1 A3 B2 C3 D2
Day 2 A1 B3 C1 D2
Day 3 A1 B2 C1 D2
Day 4 A2 B1 C2 D3
Day 5 A3 B1 C1 D3
Day 6 A3 B1 C1 D3
Day 7 A2 B1 C1 D3
Calculation of the Duncan rank test for the 1st day showed the significance of factor A (KH2PO4) at A3 level, factor B (K2HPO4) at B2 level, factor C ((NH4)2SO4) at C3 level and factor D (energy sources) at D2 level (level values are given in Table 1). In addition, the calculated effect of the factor influence on the optimization parameter (Table 7) coincided with the data obtained using the multiple Duncan criterion.
The statistical data of the first experimental day also has a biological meaning. Bioleaching of metals is the result of the ore oxidation, the effectiveness of which depends on the amount and activity of chemilithotrophic bacteria of the aboriginal consortium of the studied "substrate-solution" system. The exponents of the germanium extraction into the solution indicate their leaching activity. All the factors used in the experiment are nutrient components of media for the cultivation of
chemilithotrophic bacteria, therefore their action is considered to stimulate the bacterial growth.
Thus, the first day seems to be a phase of bacterial adaptation. Accordingly, at this moment their metabolic activity is quite low. The extraction of metals in the solution can be the result of oxidative processes. This explains the low degree of germanium recovery into the solution at high Fisher criterion and the factor influence calculated by Plokhinsky's formula. In other words, we observe to a lesser extent the process of metal bioleaching due to the microbiotic activity rather than the process of chemical oxidation under the influence of medium factors.
A significant decrease in the Fisher criterion and the factor effect on the 2nd and 3rd days of the experiment (Tables 4 and 5) shows that the components of the leaching solution have a specific effect on the biomass growth
Table 7. The effects of the factor influences and levels in the biologically interpreted data on the process of germanium leaching from rock dumps
Time Optimization factor
Factor A Factor B Factor C Factor D
factor level influence effect factor level influence effect factor level influence effect factor level influence effect
1 2 3 4 5 6 7 8 9
Day 1 A1 -0.025 B1 -0.0214 C1 -0.0037 D1 -0.0316
A2 -0.0043 B2 0.0296 C2 -0.016 D2 0.016
A3 0.0213 B3 -0.019 C3 0.017 D3 0.011
A4 0.0079 B4 0.011 C4 0.003 D4 0.0039
Day 2 A1 -0.0025 B1 -0.0087 C1 0.0162 D1 0.021
A2 -0.0082 B2 -0.006 C2 0.0038 D2 0.025
A3 0.0125 B3 0.0215 C3 -0.01 D3 -0.015
A4 -0.0018 B4 -0.0067 C4 -0.009 D4 -0.032
Day 3 A1 0.0157 B1 0.0034 C1 0.0249 D1 0.0123
A2 -0.0077 B2 0.0124 C2 -0.0138 D2 0.0267
A3 -0.0181 B3 -0.0197 C3 0.0 D3 -0.0205
A4 0.0101 B4 0.0039 C4 -0.011 D4 -0.0185
Day 4 A1 -0.0617 B1 0.1158 C1 -0.0073 D1 -0.2285
A2 0.0577 B2 0.0301 C2 -0.0166 D2 0.1320
A3 0.0838 B3 -0.0737 C3 -0.0420 D3 0.3844
A4 -0.0798 B4 -0.0722 C4 0.0660 D4 -0.2880
Day 5 A1 -0.18 B1 0.0475 C1 0.0928 D1 -0.199
A2 0.0287 B2 0.033 C2 -0.0805 D2 0.1516
A3 0.167 B3 -0.0405 C3 -0.1035 D3 0.3017
A4 -0.015 B4 -0.0401 C4 0.0912 D4 -0.2543
Day 6 A1 -0.1077 B1 -3.9586 C1 0.0652 D1 -0.1989
A2 0.0787 B2 0.1117 C2 -0.0048 D2 0.1769
A3 0.0809 B3 -0.0183 C3 -0.0843 D3 0.3188
A4 -0.0518 B4 -0.1094 C4 0.0239 D4 -0.2968
Day 7 A1 -0.078 B1 0.0958 C1 0.0941 D1 -0.1911
A2 0.0846 B2 -0.0259 C2 -0.0228 D2 0.1801
A3 0.00123 B3 -0.1412 C3 -0.0673 D3 0.3029
A4 -0.0190 B4 0.0713 C4 -0.004 D4 -0.2918
and are less involved in chemical oxidation of the substrate. This time period corresponds to the initial stage of bacterial growth. The amount of germanium that passed into the solution is insignificant and corresponds to 15.63-18.34% (Figure). Analyzing the values of the Duncan test for the influence of the factors and their levels (Tables 6, 7), we can say that at the stage of bacterial growth, factor B is more important than factors A and C. The influence of the energy source factor at the D2 level does not change.
The maximum recovery of germanium (93.5%) was recorded on the 4th and 5th days of the experiment (Figure, Table 3). The obtained results correspond to the literature data. According to [19], the bacterial participants of the bioleaching process reach their maximum metabolic activity on the 4th-5th days. The factor D of all the factors, the source of energy, had the greatest influence on the process (Table 7), which is confirmed by a high Fisher test value significantly higher than Fst for the 4th and 5th days of observation (Table 4). Calculation of the Duncan rank test for the 4th and 5th days of the experiment showed a change in the levels of the acting factors (Table 6). Thus, the need for factor A then increased to the level of A2-A3 corresponding to 2.0-3.0 g/ dm3. The need for factor B, on the contrary, decreased to the level of B1 (0.0 g/dm3); the need for factor C was at the minimum level of C1-C2, which corresponds to 0.0-2.0 g/dm3 (Table 2). Also in this time period, a change in the level of factor D was recorded. In the earlier stages of the experiment, trivalent iron was the most significant source of energy, and from the 4th day of observation the demand for thiosulphate prevailed. Such a change in the required energy source can be explained from a biological point of view considering the discovery of extracellular polymer compounds (EPC) released by microorganisms attached to the surface of a solid particle [20] and the hypothesis of an indirect bioleaching mechanism through the formation of thiosulphate [21].
At the beginning of the process, contact bioleaching takes place, and oxidation is supported by the microorganisms attached to the solid surface of the substrate [22]. Here, an important role is played by the Fe3+ ion, which is part of both the extracellular exopolymer layer and the culture medium. As soon as the microorganism is attached to the surface of the metal sulfide insoluble in the acid (in the test substrate of the piles it is pyrite FeS2), the Fe3+*on begins an indirect
attack on the metal sulfide in the reaction [21]:
FeS2 + 6Fe3++3H2O^ ^ 7Fe2+ + S2O32- + 6H+ (1)
The attack mechanism lies in the fact that microorganisms oxidize the sulfur in pyrite, which leads to the formation of soluble compounds containing Fe2+, H+ and S2O32- ions. The EPC and the Fe3+ion play an important role in the attachment of cells to the mineral and its further dissolution. EPC provide a strong contact between microbial cells and insoluble pyrite FeS2, which is an electron donor in reaction (1). In addition, Fe3+ participates in the first stage of pyrite destruction, which requires the presence of a certain amount of Fe3+ in the nutrient medium at the beginning of the bioleaching process. This explains the significance of factor D at the level of D2 in the 1st-3rd days of the experiment (Table 6).
Starting from the 4th day, thiosulfate begins to play a more significant role as a source of energy. It is either formed by the reaction (1) or is introduced into the nutrient medium initially. Either the initial or intermediate product, thiosulfate eventually turns into sulfate under the influence of microorganisms and components of the medium through the formation of tetrathionate and trithionate in the reaction:
S2O32- + 8Fe3+ + 5H2O ^
8Fe2+ + 2SO42- + 10H+. (2)
The resulting Fe2+ can be converted again to Fe3+ by such iron-oxidizing bacteria as Acidithiobacillus ferrooxidans:
2Fe2+ + 2H+ + 0.5O2 ^ ^ (microorganisms) ^ ^ 2Fe3+ + H20. (3)
Thus, the role of microorganisms at this stage is reduced to the formation of an oxidizer in the form of Fe3+ ions, which promotes a more complete leaching of the substrate components into the solution.
On the 6th and 7th days of observation, the germanium recovery into the solution decreased by 70%. At the same time, the current levels of factors remained unchanged (Table 6). The Fisher criterion (Table 4) unequivocally indicates the significance of the factor D:Fr (8.95) > Fst (3.49) and Fr (8.47) > Fst (3.49).
From the obtained results it follows that:
1. The biotechnological process of leaching germanium from rock dumps of Chervono-gradska CPP of the Lviv Coal Company was optimized using the method of Greco-Latin
squares mathematical planning based on the variance analysis.
2. These research, calculations and the analysis allowed to recommend a new composition of the optimal nutrient medium (ONM) for the fastest maximum extraction of germanium. The recommended combination of factors and their levels A2B1C2D3 corresponds
to the ONM composition, g/dm3: KH2PO4 — 1.0; (NH4)2SO4 — 2.0; KCl — 0.1; MgSO4 — 0.5; NH4Cl — 0.5; Na2S2O3 — 5.0.
3. The new ONM composition allows to achieve the 93.5% recovery of germanium from the coal dumps of Chervonogradska CPP in solution in for 4 days, which was impossible to obtain earlier.
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ДИСПЕРС1ЙНИЙ АНАЛ1З ДЛЯ ОПТИМ1ЗАЦП ПРОЦЕСУ Б1ОВИЛУГОВУВАННЯ ГЕРМАН1Ю З В1ДВАЛ1В ВУГЛЕЗБАГАЧЕННЯ
I. А. Блайда, Н. Ю. Васильева, Т. В. Васильева, Л. I. Слюсаренко
Одеський нащональний ушверситет iMern I. I. Мечникова, Укра1на
E-mail: [email protected]
Метою роботи була оптимiзацiя процесу бiовилуговування гермашю з вiдвалiв вуг-лезбагачення, а саме визначення оптимального складу нового живильного середовища для ацидоф^ьних хемол^отрофних бакте-рiй, що забезпечуе максимальне вилучення цiнного металу за мшмальний термiн. Для оптимiзацп використовували метод матема-тичного планування експерименту, адапто-ваний до плану греко-латинських квадраив, розрахунки в якому Грунтуються на дис-персiйному аналiзi. Формальне планування експерименту проводили з чотирма дтчими факторами (компонентами живильного середовища) на чотирьох рiвнях (концентрацш). Розрахунки було виконано в програмi Excel. Проведено аналiз значущостi рiвня фактора на пiдставi множинного рангового критер^ Дункана для кожного дня експерименту, пе-ревiрки однорiдностi дисперсiй за допомо-гою критерiю Кохрена, а також значущост факторiв за критерieм Фiшера. 1нтерпрета-цiю одержаних результаив проводили як ia математично1, так i з б^лопчно1 точок зору. В результат для оптимального живильного середовища рекомендували комбшащю чиннишв i 1хшх рiвнiв, що вщповщае складу цього середовища, г/дм3: KH2PO4 — 1,0; (NH4)2SO4 — 2,0; KCl — 0,1; MgSO4 — 0,5; NH4Cl — 0,5; Na2S2O3 — 5,0. Це дае змогу до-сягти вилучення гермашю в розчин бшьш нiж на 90% за короткий термш (чотири доби), що було неможливо рашше.
Ключовi слова: бмвилуговування, ацидоф^ьш хемолiтотрофнi бактери, германiй, вiдвали вуглезбагачення, план греко-римських квад-ратiв, дисперсшний аналiз.
ДИСПЕРСИОННЫЙ АНАЛИЗ ДЛЯ ОПТИМИЗАЦИИ ПРОЦЕССА БИОВЫЩЕЛАЧИВАНИЯ ГЕРМАНИЯ ИЗ ОТВАЛОВ УГЛЕОБОГАЩЕНИЯ
И. А. Блайда, Н. Ю. Васильева, Т. В. Васильева, Л. И. Слюсаренко
Одесский национальный университет имени И. И. Мечникова, Украина
E-mail: [email protected]
Целью работы была оптимизация процесса биовыщелачивания германия из отвалов углеобогащения, а именно определение оптимального состава новой питательной среды для ацидофильных хемолитотрофных бактерий, обеспечивающей максимальное извлечение ценного металла за минимальный срок. Для оптимизации использовали метод математического планирования эксперимента, адаптированный к плану греко-латинских квадратов, расчеты в котором основываются на дисперсионном анализе. Формальное планирование эксперимента проводили с четырьмя действующими факторами (компонентами питательной среды) на четырех уровнях (концентраций). Расчеты были выполнены в программе Excel. Проведен анализ значимости уровня фактора на основании множественного рангового критерия Дункана для каждого дня эксперимента, проверки однородности дисперсий с помощью критерия Кохрена, а также значимости факторов по критерию Фишера. Интерпретацию полученных результатов проводили как с математической, так и с биологической точек зрения. В результате для оптимальной питательной среды рекомендовали комбинацию факторов и их уровней, что соответствует составу этой среды, г/дм3: KH2PO4 — 1,0; (NH4)2SO4 — 2,0; KCl — 0,1; MgSO4 — 0,5; NH4Cl — 0,5; Na2S2O3 — 5,0. Это позволяет достичь извлечения германия в раствор более чем на 90% за короткий срок (четверо суток), что было невозможно ранее.
Ключевые слова: биовыщелачивание, ацидофильные хемолитотрофные бактерии, германий, отвалы углеобогащения, план греко-римских квадратов, дисперсионный анализ.
