Biosurfactant are Surfactants produced by certain microorganisms. These biosurfactants increase the biodegradability of insoluble pollutants. In this study, the fermentation products of Pseudomonas stutzeri Lh-42 (PS) and Rhodococcus sp. PR-1 (RD) were studied by Oil spreading method, emulsifying activity and infrared spectrum analysis. It was proved that these fermentation products were biosurfactant. And then the fermentation conditions of PS, RD were optimised by Placket-Burman (PB) design, hill-climbing experiment and response surface methodology (RSM). N source and liquid loading were significant factors in the fermentation of PS, while C source and speed were significant factors in the fermentation of RD. The surface tension was found to be as low as 39.53 ± 0.25 mN/m for the fermentation conditions of PS with an N source of 4.62 ± 0.41 g and a liquid loading of 28.4 ± 0.3%. The surface tension was 40.70 ± 0.47 mN/m for the incubation conditions of RD with a C source of 26.94 ± 0.62 g and a rotational speed of 210 r/min. Finally, the experimental results for the degradation of oily sludge showed that the degradation rate of oily sludge was improved when the fermentation conditions were optimised. The results of the infrared spectroscopy analysis showed that the organic matter content of the oily sludge treated with PS bacteria was significantly reduced after the optimised fermentation. This study provides a theoretical reference for further use of these bacteria to produce biosurfactants to treat organic matter.

  • Application of oil-degrading bacteria.

  • The kinds of fermentation products were identified by infrared spectrum analysis.

  • Plackett-Burman experiment and response surface methodology (RSM) were used to optimise the fermentation conditions.

  • It provides a theoretical reference for the treatment of organic pollution by bacteria.

Biosurfactants are surface active substances produced by various microbial metabolism. Biosurfactants are composed of macromolecules such as phospholipids, polysaccharides, and proteins, which contain various functional groups such as carboxyl and amino groups. Biosurfactants are classified according to their chemical organic composition (Molaei et al. 2021). These include glycolipids, lipopeptides, polysaccharides-protein complex, lipopolysaccharides, phospholipids, and fatty acids. The most common biosurfactants are glycolipids and lipopeptides. The structure of the biosurfactants includes hydrophilic and hydrophobic parts, making them amphiphilic (Diallo et al. 2020; Mukherjee et al. 2021). Hydrophobic chains typically consist of fatty acids with 8–18 carbon atoms, while hydrophilic chains may carry esters, hydroxyl, phosphoric or carboxyl groups or more complex parts (Singh et al. 2022).

Biosurfactant organisms can inhabit oceans, fresh water, soil, sediment and sludge, as well as extreme environments, and can grow at a wide range of temperatures, pH and salinity. Microbes produce biosurfactants that promote the dissolution of hydrophobic compounds in their environment, using them as substrates. The existence of biosurfactants increases the hydrophobicity of bacterial cells and enhances the viability of bacteria in the hydrophobic environment (Zhang et al. 2021). Biosurfactants have less environmental impact and toxicity than chemical surfactants because these natural ingredients can be produced from a renewable matrix. Some bacteria and yeasts produce biosurfactants (Akanji et al. 2021; Molaei et al. 2021).

Many microbial genera have been shown to produce biosurfactants, such as Bacillus, Pseudomonas and Corynebacterium. The use of biosurfactants is an effective and sustainable method for the treatment of oily pollutants (Carolin et al. 2021). Therefore, the use of biosurfactants is a promising alternative to the use of chemically synthesised surfactant. But biosurfactants are not widely used because they are expensive to produce (Decesaro et al. 2021). Fermentation processes to produce biosurfactants require optimisation and control of temperature, pH, oxygen and agitation rates, require the use of low-cost raw materials, and reduce the cost of dealing with related environmental problems (Al-Sakkaf & Onaizi 2022).

Biosurfactants can only function in the best environmental conditions for their growth and activity. Among the statistical methods, response surface methodology (RSM) has been widely used in the optimisation of fermentation media. RSM is a collection of statistical techniques used to design experiments, establish models, evaluate the effects of factors and find optimal conditions (Marangon et al. 2021). This is a statistically designed experiment in which several factors change simultaneously. In fact, the relationship between the response and the independent variable is usually unknown during the process, so the first step of the response model is to approximate the function by analysing the factor (the independent variable). In this study, this method was also used to optimise the environmental growth conditions.

In this study, we investigated the fermentation products of Pseudomonas stutzeri Lh-42 (PS) and Rhodococcus sp. PR-1 (RD) by spreading oil method, emulsification activity and infrared spectroscopy analysis. The results demonstrate that these fermentation products are biosurfactants. Finally, the fermentation conditions of PS and RD were optimised by Placket-Burman design, hill climbing experiments and RSM to further improve the yield of biosurfactants produced by the two strains. This study deepened our understanding of surfactant properties and provided a theoretical basis for the development of oil-based sludge treatment.

Materials

Shimadzu IRTracer-100 Fourier Transform Infrared Spectrometer. German KRUSS IL4201 tension tester. Bohui Jingke RE-101 Rotary Evaporator. Hitachi SU8010 electron microscope. Liquid paraffin. LB liquid medium contained 10.0 g peptone, 10.0 g NaCl and 5.0 g yeast powder. Beef extract peptone agar medium contained beef extract 3.0 g, peptone 10.0 g, NaCl 5.0 g, agar 20.0 g, water 1,000 mL, pH adjusted to 7. PS, RD were screened from soil in Liaohe oil field and oil-producing waters in Daqing Field.

Methods

Extraction of fermentation product of strain

The culture medium was centrifuged for 30 min at 5,000 × g and the cells were removed. The pH value of supernatant was adjusted to 2.0 with 6.0 M HCl, and then equal volume 2:1(v/v) CHCl3/CH3OH solution was added (Pitambri et al. 2021; Wei et al. 1998). After strongly shaking for 15 minutes, the solution was left to separate, the organic phase was removed, and this was repeated twice. The organic phases were grouped together, and the products were combined in a single rotary evaporator (Dutta et al. 2004). The resulting yellowish viscous material was dissolved in methanol and further concentrated by solvent evaporation at 45 °C. Finally, a scanning electron microscope was used to examine the powder of fermentation (Figure 1).
Figure 1

Scanning electron micrograph of fermentation powder of two kinds of bacteria. (a) PS, (b) RD.

Figure 1

Scanning electron micrograph of fermentation powder of two kinds of bacteria. (a) PS, (b) RD.

Close modal

Oil spreading method

At the same concentration point in the growth curve of two strains, 5 mL culture solution was centrifuged at 8,000 RPM for half an hour, and supernatant was collected carefully (Kalil et al. 2000). Then, 30 mL distilled water and 20 mL liquid paraffin were added to a clean petri dish and let stand for 3–10 minutes. When the wax was evenly spread over the distilled water, 1 mL of the culture drop was placed in the middle of the paraffin layer, the sample was added, and let stand for 1 minute to measure the diameter of the resulting oil drain ring. The average value of the three times repeated test was obtained, and the size of the oil drainage ring could indicate the size of the oil removal activity of the sample (Akta et al. 2006; Ciszczyk et al. 2016).

Determination of emulsifying activity

At the same concentration point in the growth curve of the two strains, 5 mL culture solution was taken, centrifuged at 8,000 RPM for half an hour, carefully collected and the supernatant preserved. The supernatant was added to the test tube of 2 cm in diameter, palm oil and liquid paraffin of the same volume were added into each test tube, and the liquid vortex shaken in each test tube for 1 minute to mix well, then the test tube mouth was sealed with a sealing film and the tube was placed vertically. The height of the emulsion layer in each test tube was measured at 2-hour intervals (Kapri et al. 2010). The emulsion efficiency was calculated by the height of the emulsion layer. Each sample was measured three times and the results were averaged. The formula was as follows:
formula
(1)
(h is the height of the emulsion layer, H0 the height of the organic material before the sample is added).

Fourier transform infrared spectra of the dried fermentation product

Fermentation products were identified by infrared spectroscopy. If the fermentation products contain water, the background peak in the result map would be too high if the fermentation products were analysed by infrared spectroscopy. In order to improve the accuracy of the infrared spectroscopy measurement results, the moisture in the products should be removed by freeze-drying the samples: first, the samples were frozen at −80 °C for 12 hours, the sample was then prefrozen in a lyophiliser for 3 hours, and then placed in a lyophiliser at 23 °C, which sublimated the water directly from the ice, thereby removing the water (Coleman & Bert 1989; Lievens et al. 2011). Finally, the samples of lyophilised fermentation products were determined by infrared spectroscopy, and the organic chemical groups in the samples were identified qualitatively; then the types of samples were analysed (Hilten & Das 2010).

Liquid surface tension

The dried bacterial fermentation products were dissolved in distilled water to prepare a series of surface active solutions of different concentrations. The surface tension of the solution was measured at (50.0 ± 0.05)°C by surface tension meter (German KRUSS IL4201 tension tester), to confirm the critical micelle concentration. Each sample was measured three times and the results were averaged.

Measurement of cell surface hydrophobicity

The optimal amount of fermentation broth was centrifuged at low temperature and high speed for 8 minutes, the supernatant was removed, the broth was washed twice with phosphoric acid buffer, and then suspended again. The OD400 of the control broth was about 1.0(T0); the OD400 value (T1) of 4 mL suspension and 1 mL hexane in 10 mL colorimetric tube was determined after 60 seconds of rapid oscillation and let stand for 30 min at room temperature. Each sample was measured three times and the results were averaged (Salas-Tovar et al. 2021). The formula for calculating surface hydrophobicity was as follows:
formula
(2)

Experimental design of RSM

The RSM design was based on the experimental results of selecting carbon and nitrogen sources. According to the significant factors determined by PB experiment and the steepest climb experiment (Mei et al. 2017), the central combination design experiment was carried out, and the best conditions were obtained by analysing the results with software, and experiments were done to prove it (Chen et al. 2019). PB experiment was designed to test seven factors: C source, N source, KH2PO4, MgSO4·7H2O, temperature, rotating speed and liquid loading. Each sample was measured three times and the results were averaged; the surface tension was the most responsive. The factors and levels of PB experiment are shown in Table 1.

Table 1

PB experimental design factors and levels

FactorFactor coding+ 1 (High level)− 1 (Low level)
C source (g/L) 25 15 
N source (g/L) 15 
KH2PO4 (g/L) 1.5 0.5 
MgSO4•7H2O (g/L) 0.15 0.1 
Temperature (°C) 22 27 
Rotation rate (r/min) 130 170 
The volume of liquid (%) 50 100 
FactorFactor coding+ 1 (High level)− 1 (Low level)
C source (g/L) 25 15 
N source (g/L) 15 
KH2PO4 (g/L) 1.5 0.5 
MgSO4•7H2O (g/L) 0.15 0.1 
Temperature (°C) 22 27 
Rotation rate (r/min) 130 170 
The volume of liquid (%) 50 100 

The statistical model equation we used to analyse the experiment was the following equation.
formula
where Y is the predicted response, k is the number of factors, is the design factor of interest, and and are the coefficients. The significance of the model was statistically analysed using the f-test of analysis of variance (ANOVA). The coefficient of determination is used to measure the goodness of fit of the model.

Oil spreading method

Liquid paraffin was used to test the bioactivity of oil removal from the fermentation broth (100% concentration) of the two strains in the experimental group and the LB medium in the control group. Although the color contrast between the oil phase and the water phase was small, the bioactivity of oil removal from the LB medium of the two strains in the experimental group was measured by the liquid paraffin. However, in the real-time photo, the obvious oil drain ring could be observed (Figure 2). After the diameter of each sample was measured repeatedly, its average value was obtained. The results were as follows: the diameter of the oil drainage ring of PS was 5.20 ± 0.08 cm, the diameter of the oil drainage ring of RD was 4.97 ± 0.03 cm, the diameter of oil drainage ring in control group was 1.13 ± 0.02 cm. The results showed that the surface activity of PS and RD fermentation broth was better than that of the control, and the oil drainage effect was better.
Figure 2

Degreasing effects of fermentation broth on liquid paraffin. (a) PS, (b) RD, (c) Control group: LB Medium.

Figure 2

Degreasing effects of fermentation broth on liquid paraffin. (a) PS, (b) RD, (c) Control group: LB Medium.

Close modal

Determination of emulsifying activity

Emulsifying activity is an important index to evaluate the deoiling effect of surfactant oil. The emulsifying activity of PS and RD in palm oil is higher than that of the control group, as shown in Table 2; the emulsifying efficiency of the control group is very low. For palm oil, the emulsifying rates of PS, RD and Control group LB Medium are 65.3 ± 0.2%, 42.7 ± 0.1% and 2.2 ± 0.1%, respectively. For paraffin oil, the emulsifying rates of PS, RD and Control group LB Medium are 60.6 ± 0.3%, 57.1 ± 0.3% and 1.3 ± 0.1%, respectively. It can be seen that PS and RD had high emulsifying activity in paraffin oil, and the emulsifying efficiency of control group is very low.

Table 2

Determination of emulsifying activity of fermentation broth

Fermentation liquidPSRDControl group:LB Medium
Average emulsifying efficiency (%) Palm oil 65.3 42.7 2.2 
Paraffins 60.6 57.1 1.3 
Fermentation liquidPSRDControl group:LB Medium
Average emulsifying efficiency (%) Palm oil 65.3 42.7 2.2 
Paraffins 60.6 57.1 1.3 

Identification of fermentation product of strain

Figure 3 is the result of infrared spectrum analysis. It can be seen that the infrared waveforms of the two strains were similar in general shape, and the fermentative products of the two strains have a strong absorption peak at 3,400 cm−1; the strong absorption peak at this position is the hydroxyl group peak, which indicates that the fermentation products of the two strains are composed of several hydroxyl groups. The absorption peaks at 1,650–1,643 cm−1 of the two strains indicate the existence of carbon and oxygen double bonds of unsaturated fatty bonds in the fermentation products. The position of PS at 2,917–2,930 cm−1 is the result of the vibration of the hydrocarbon bonds contained in the carbohydrate molecules, but the peaks produced by RD are less pronounced. The dense peaks at the 1,342–1,100 cm−1 position of PS indicate the presence of a variety of ether bonds in different states and the vibration of amino groups, which are generally composed of various carboxylic ester groups and lipopeptide groups. The results of the previous oil drainage ring experiment, the emulsifying activity study and the final infrared spectrum analysis were sufficient to prove that the fermentation products of both strains are biosurfactants.
Figure 3

IR spectrum profile of dried biosurfactant produced. PS(a), RD(b).

Figure 3

IR spectrum profile of dried biosurfactant produced. PS(a), RD(b).

Close modal

Liquid surface tension

The surface tension of fermentation broth of two kinds of bacteria under different concentrations (%) was measured by surface tension meter. The experimental results are shown in Figure 4. The results show that the surface tension of the fermentation broth decreases with increasing concentration, and when the concentration reached critical micelle concentration(CMC), the surface tension was basically no longer increasing. The CMC of PS fermentation broth was larger than that of RD fermentation broth, which might be due to the small volume of hydrophobic base in the surface active component structure of PS fermentation broth; this caused more molecules to line up on the surface of the solution.
Figure 4

Curves of surface tension with concentration for two bacterial fermentates.

Figure 4

Curves of surface tension with concentration for two bacterial fermentates.

Close modal

Experimental design of response surface analysis method

Experimental results of selecting carbon and nitrogen sources

Glucose, sucrose, starch, yeast extract and lactose were used as C source,, and peptone as N source was added into the fermentation medium. The oil drainage activity, emulsifying properties and cell surface hydrophobicity of PS and RD strains were investigated under various conditions, and the suitable carbon sources were screened out. After the C source was determined, the suitable N sources for the strain were screened by using peptone, urea, ammonium sulfate, ammonium dihydrogen phosphate and ammonium chloride as N sources. The results are shown in Tables 3 and 4 below. During the culture of PS, the oil drainage activity, emulsifying property and cell surface hydrophobicity were better when sucrose was used as C source and urea was used as N source; in the culture of RD, glucose as C source, peptone as N source, oil drainage activity, emulsifying property and cell surface hydrophobicity were better.

Table 3

C source selection experimental results

Medium compositionOil drainage activity/cm
Emulsifying property/%
Cell surface hydrophobicity/%
PSRDPSRDPSRD
Dextrose 6.4 8.4 53 65 14.62 24.95 
Sucrose 8.1 6.3 63 45 28.63 15.49 
Starch 7.4 6.8 55 51 13.55 17.93 
Yeast extract 5.4 7.8 36 59 10.38 22.33 
Lactose 7.7 7.4 61 58 21.34 19.71 
Medium compositionOil drainage activity/cm
Emulsifying property/%
Cell surface hydrophobicity/%
PSRDPSRDPSRD
Dextrose 6.4 8.4 53 65 14.62 24.95 
Sucrose 8.1 6.3 63 45 28.63 15.49 
Starch 7.4 6.8 55 51 13.55 17.93 
Yeast extract 5.4 7.8 36 59 10.38 22.33 
Lactose 7.7 7.4 61 58 21.34 19.71 
Table 4

N source selection experimental results

Medium compositionOil drainage activity/cm
Emulsifying property/%
Cell surface hydrophobicity/%
PSRDPSRDPSRD
Dextrose 7.9 8.5 65 63 13.74 24.36 
Sucrose 8.5 8.3 72 56 28.16 24.13 
Starch 8.3 8.5 66 53 2.82 14.98 
Yeast extract 8.2 7.6 68 54 18.27 3.88 
Lactose 7.5 8.2 59 58 3.56 6.99 
Medium compositionOil drainage activity/cm
Emulsifying property/%
Cell surface hydrophobicity/%
PSRDPSRDPSRD
Dextrose 7.9 8.5 65 63 13.74 24.36 
Sucrose 8.5 8.3 72 56 28.16 24.13 
Starch 8.3 8.5 66 53 2.82 14.98 
Yeast extract 8.2 7.6 68 54 18.27 3.88 
Lactose 7.5 8.2 59 58 3.56 6.99 

Scheme and results of PB experiment

The PB experimental design and results for PS are shown in Table 5. The PB experimental design and results for RD are shown in Table 6. The data in Tables 5 and 6 were analysed by response surface software; the regression coefficients of each factor and their significance are given in Table 7.

Table 5

Optimisation of PS fermentation test scheme and results by RSM

Serial numberABCDEFGSurface tension (mN/m)
−1 −1 −1 −1 40.70 
−1 −1 −1 −1 47.35 
−1 −1 60.93 
−1 −1 −1 59.50 
−1 −1 −1 −1 45.91 
−1 −1 46.60 
−1 −1 −1 46.99 
−1 −1 −1 −1 44.65 
−1 −1 −1 −1 51.76 
10 −1 −1 −1 −1 −1 −1 −1 41.90 
11 −1 −1 −1 59.64 
12 −1 −1 42.69 
Serial numberABCDEFGSurface tension (mN/m)
−1 −1 −1 −1 40.70 
−1 −1 −1 −1 47.35 
−1 −1 60.93 
−1 −1 −1 59.50 
−1 −1 −1 −1 45.91 
−1 −1 46.60 
−1 −1 −1 46.99 
−1 −1 −1 −1 44.65 
−1 −1 −1 −1 51.76 
10 −1 −1 −1 −1 −1 −1 −1 41.90 
11 −1 −1 −1 59.64 
12 −1 −1 42.69 
Table 6

Optimisation of RD fermentation test scheme and results by RSM

Serial numberABCDEFGSurface tension (mN/m)
−1 −1 −1 −1 50.48 
−1 −1 −1 −1 49.17 
−1 −1 51.34 
−1 −1 −1 60.75 
−1 −1 −1 −1 59.34 
−1 −1 46.29 
−1 −1 −1 56.09 
−1 −1 −1 −1 40.30 
−1 −1 −1 −1 48.42 
10 −1 −1 −1 −1 −1 −1 −1 61.85 
11 −1 −1 −1 54.35 
12 −1 −1 42.29 
Serial numberABCDEFGSurface tension (mN/m)
−1 −1 −1 −1 50.48 
−1 −1 −1 −1 49.17 
−1 −1 51.34 
−1 −1 −1 60.75 
−1 −1 −1 −1 59.34 
−1 −1 46.29 
−1 −1 −1 56.09 
−1 −1 −1 −1 40.30 
−1 −1 −1 −1 48.42 
10 −1 −1 −1 −1 −1 −1 −1 61.85 
11 −1 −1 −1 54.35 
12 −1 −1 42.29 
Table 7

Results analysis of Plackett-Burman experiment

Quadratic sum
Degrees of freedom
Mean square
F value
Pr > F
PSRDPSRDPSRDPSRDPSRD
Model 514.11 497.94 73.44 71.13 11.96 7.45 0.0152 0.0354 
2.96 171.01 2.96 171.01 0.48 17.91 0.5257 0.0134 
107.28 1.48 107.28 1.48 17.47 0.16 0.0139 0.7135 
19.00 4.30 19.00 4.30 3.09 0.45 0.1534 0.5391 
0.02 4.18 0.02 4.18 0.00 0.44 0.9529 0.5445 
17.33 3.14 17.33 3.14 2.82 0.33 0.1683 0.5970 
13.70 308.66 13.70 308.66 2.23 32.32 0.2096 0.0047 
353.82 5.17 353.82 5.17 57.61 0.54 0.0016 0.5025 
Surplus 24.56 38.20 6.14 9.55     
Sum 538.67 536.14 11 11       
Quadratic sum
Degrees of freedom
Mean square
F value
Pr > F
PSRDPSRDPSRDPSRDPSRD
Model 514.11 497.94 73.44 71.13 11.96 7.45 0.0152 0.0354 
2.96 171.01 2.96 171.01 0.48 17.91 0.5257 0.0134 
107.28 1.48 107.28 1.48 17.47 0.16 0.0139 0.7135 
19.00 4.30 19.00 4.30 3.09 0.45 0.1534 0.5391 
0.02 4.18 0.02 4.18 0.00 0.44 0.9529 0.5445 
17.33 3.14 17.33 3.14 2.82 0.33 0.1683 0.5970 
13.70 308.66 13.70 308.66 2.23 32.32 0.2096 0.0047 
353.82 5.17 353.82 5.17 57.61 0.54 0.0016 0.5025 
Surplus 24.56 38.20 6.14 9.55     
Sum 538.67 536.14 11 11       

As can be seen from Table 7, the p value of PS fermentation optimisation experimental regression model is 0.0152 (p < 0.05), which shows that the model is significant and fits well. The lower the p value, the higher the significance. The effects of various factors on the surface tension in the medium were as follows: MgSO4·7H2O < C source < rotation speed < KH2PO4 < N source < liquid loading, in which liquid loading (p = 0.0016) and N source (p = 0.0139) were the main influencing factors (p < 0.05); other factors had little effect on the fermentation experiment, so the PS fermentation optimisation experiment chose N source and liquid loading for further research.

The p value of the regression model for optimisation of RD fermentation was 0.0354 (p< 0.05), which showed that the model was significant and fitted well in the range of experimental data. The influence of various factors in medium on surface tension was as follows: N source < temperature < MgSO4·7H2O < KH2PO4 < liquid loading < C source < rotational speed. C source (p = 0.0134) and rotational speed (p = 0.0047) were the main influencing factors (p < 0.05); other factors had little effect on the fermentation, so the optimisation experiment of RD was carried out by selecting C source and rotational speed.

The steepest climbing experiment

The results of Plackett-Burman experiment for optimising the fermentation of PS showed that the main influencing factors were the amount of N source and liquid loading. The less liquid loading, the lower the surface tension. Details of the experiment are listed in Table 8.

Table 8

Experimental design and results of the steepest ascent of PS fermentation conditions

Order numberB:N source (g/L)G:The volume of liquid (%)Surface tension (mN/m)
15 100 59.5 
13.5 90 57.65 
12 80 56.98 
10.5 70 56.9 
60 53.1 
7.5 50 46.03 
40 41.97 
4.5 30 39.52 
20 55.71 
10 25 10 57.79 
Order numberB:N source (g/L)G:The volume of liquid (%)Surface tension (mN/m)
15 100 59.5 
13.5 90 57.65 
12 80 56.98 
10.5 70 56.9 
60 53.1 
7.5 50 46.03 
40 41.97 
4.5 30 39.52 
20 55.71 
10 25 10 57.79 

From Table 8, it can be seen that the surface tension of the bacterial solution reaches the lowest when the N source is 4.5 g/L and the liquid loading is 30%, so group 8 is chosen as the central point of the central experiment.

The results of Plackett-Burman experiment for RD fermentation optimisation showed that C source and rotation speed are the main influencing factors, and C source and rotation speed had positive effect. That is, the higher the content of C source, the lower the surface tension, and the higher the rotation speed, the lower the surface tension. Based on this result, the experimental schedule is detailed in Table 9.

Table 9

Experimental design and results of the steepest climb under RD fermentation conditions

Order numberA:C source (g/L)F:revolution (r/min)Surface tension (mN/m)
15 130 60.22 
16.5 140 59.82 
18 150 57.75 
19.5 160 54.04 
21 170 51.87 
22.5 180 47.63 
24 190 43.66 
25.5 200 40.84 
27 210 49.14 
10 28.5 220 55.73 
Order numberA:C source (g/L)F:revolution (r/min)Surface tension (mN/m)
15 130 60.22 
16.5 140 59.82 
18 150 57.75 
19.5 160 54.04 
21 170 51.87 
22.5 180 47.63 
24 190 43.66 
25.5 200 40.84 
27 210 49.14 
10 28.5 220 55.73 

It can be seen from Table 9 that C source is 25.5 g/L and rotating speed is 200 r/min, the surface tension of bacteria liquid reaches the lowest, so Group 8 experiment was chosen as the central point of the central experiment.

Optimisation of culture conditions by RSM

RSM is a combination of mathematical and statistical techniques that is useful for analysing the effects of several independent variables on the system response without the need of a predetermined relationship between the objective function and the variables. According to the results of PB experiment and steepest ascent experiment, two significant factors, N source and liquid loading, were studied in the optimisation experiment of PS fermentation conditions by composite centre design and RSM, and the optimum fermentation conditions were determined. The design level of the experimental factors is shown in Table 10. The C source was 20 g, MgSO4·7H2O was 0.125 g, KH2PO4 was 1 g, the speed of rotation was 160 r/min and the temperature was 25 °C.

Table 10

Experimental design and results of PS fermentation centre composite design

Order numberB:N source (g/L)G:the volume of liquid (%)Surface tension (mN/m)
1.5 30 47.74 
4.5 30 38.62 
40 56.99 
4.5 30 39.44 
4.5 30 39.01 
4.5 30 38.44 
4.5 50 57.35 
20 50.68 
7.5 30 48.54 
10 4.5 10 51.62 
11 40 45.71 
12 20 44.18 
13 4.5 30 40.69 
Order numberB:N source (g/L)G:the volume of liquid (%)Surface tension (mN/m)
1.5 30 47.74 
4.5 30 38.62 
40 56.99 
4.5 30 39.44 
4.5 30 39.01 
4.5 30 38.44 
4.5 50 57.35 
20 50.68 
7.5 30 48.54 
10 4.5 10 51.62 
11 40 45.71 
12 20 44.18 
13 4.5 30 40.69 

In the RD fermentation condition optimisation experiment, two significant factors, C source and rotation speed, were used in the centre group of composite centre design. Combined with RSM, the optimum fermentation conditions were determined. The design level of the experimental factors is shown in Table 11. The N source was 10 g, MgSO4·7H2O was 0.125 g, KH2PO4 was 1 g, the liquid loading rate was 50% and the temperature was 25 °C.

Table 11

Experimental design and results of RD fermentation centre composite design

Order numberA:C source (g/L)F:revolution (r/min)Surface tension (mN/m)
27 210 47.30 
24 210 43.02 
27 190 45.63 
28.5 200 55.49 
25.5 200 40.71 
25.5 180 54.86 
24 190 50.38 
25.5 200 41.86 
22.5 200 53.72 
10 25.5 200 39.68 
11 25.5 220 55.67 
12 25.5 200 44.37 
13 25.5 200 38.95 
Order numberA:C source (g/L)F:revolution (r/min)Surface tension (mN/m)
27 210 47.30 
24 210 43.02 
27 190 45.63 
28.5 200 55.49 
25.5 200 40.71 
25.5 180 54.86 
24 190 50.38 
25.5 200 41.86 
22.5 200 53.72 
10 25.5 200 39.68 
11 25.5 220 55.67 
12 25.5 200 44.37 
13 25.5 200 38.95 

Taking the surface tension as the response, the experimental data were analysed by Design-Expert 8.0.6 software. The results are shown in Tables 12 and 13.

Table 12

Results analysis of of PS fermentation centre composite design experiment

Quadratic sumDegrees of freedomMean squareF valuePr > F
Model 550.07 110.01 48.51 <0.0001 
A-N source 1.96 1.96 0.86 0.3839 
B-the volume of liquid 20.24 20.24 8.92 0.0203 
AB 1.16 1.16 0.51 0.4983 
A2 178.77 178.77 78.83 <0.0001 
B2 444.34 444.34 195.93 <0.0001 
Surplus 15.87 2.27     
Lack of fit 12.66 4.22 5.24 0.0717 
Pure error 3.22 0.80     
Sum 565.94 12       
Quadratic sumDegrees of freedomMean squareF valuePr > F
Model 550.07 110.01 48.51 <0.0001 
A-N source 1.96 1.96 0.86 0.3839 
B-the volume of liquid 20.24 20.24 8.92 0.0203 
AB 1.16 1.16 0.51 0.4983 
A2 178.77 178.77 78.83 <0.0001 
B2 444.34 444.34 195.93 <0.0001 
Surplus 15.87 2.27     
Lack of fit 12.66 4.22 5.24 0.0717 
Pure error 3.22 0.80     
Sum 565.94 12       
Table 13

Results analysis of of RD fermentation centre composite design experiment

Quadratic sumDegrees of freedomMean squareF valuePr > F
Model 443.00 88.60 19.58 0.0005 
A-N source 0.79 0.79 0.17 0.6894 
B-the volume of liquid 1.38 1.38 0.31 0.5979 
AB 20.39 20.39 4.51 0.0715 
A2 256.82 256.82 56.76 0.0001 
B2 282.76 282.76 62.49 <0.0001 
Surplus 31.67 4.52     
Lack of fit 13.61 4.54 1.01 0.4772 
Pure error 18.06 4.52     
Sum 474.67 12       
Quadratic sumDegrees of freedomMean squareF valuePr > F
Model 443.00 88.60 19.58 0.0005 
A-N source 0.79 0.79 0.17 0.6894 
B-the volume of liquid 1.38 1.38 0.31 0.5979 
AB 20.39 20.39 4.51 0.0715 
A2 256.82 256.82 56.76 0.0001 
B2 282.76 282.76 62.49 <0.0001 
Surplus 31.67 4.52     
Lack of fit 13.61 4.54 1.01 0.4772 
Pure error 18.06 4.52     
Sum 474.67 12       

The mathematical model of PS fermentation centre composite design (CCD) experiment was: The equation R2 = 0.9719 (R2 > 0.90) and Radj2 = 0.9519 showed that this model could simulate the experiment well. The model p value was less than 0.0001 and the mimetic p value was 0.0717. In the regression equation, B, A2, B2 were significant. See Table 12 for details.

The mathematical model of RD fermentation CCD experiment was: The equation R2 = 0.9333(R2 > 0.90) and Radj2 = 0.8856 showed that this model could simulate the experiment well. From the analysis of the experimental results, we could see that the p value of the model was 0.0005 and the p value of the misfit term was 0.4772. In the regression equation, A2 and B2 were significant. See Table 13 for details.

Figure 5 shows the results of the effects of N source and liquid loading on PS fermentation. The best values in the regression model lie at the lowest point of the response surface, the centre of the contour plot. The small ball at the sharp corner of the response surface in Figure 5 is indicating the optimum value. The lowest point indicates the lowest surface tension under this condition, while the lowest surface tension of the solution corresponds to the best treatment of the organic matter by the surfactant indicating that the fermentation conditions of the bacteria are optimal under this condition, so the lowest point on the response surface indicates the optimum value. Through software calculations, the results showed that the optimum culture condition was as follows: C source was 20 ± 1 g, N source was 4.62 ± 0.41 g, MgSO4·7H2O was 0.125 ± 0.002 g, KH2PO4 was 1 ± 0.1 g, rotation speed was 160 r/min, temperature was 25 ± 1 °C, the loading rate was 28.4 ± 0.3%, and the surface tension was 39.53 ± 0.25 mN/m.
Figure 5

Three-dimensional curved surface diagram of interaction between N source and liquid loading in PS fermentation experiment.

Figure 5

Three-dimensional curved surface diagram of interaction between N source and liquid loading in PS fermentation experiment.

Close modal
Figure 6 shows the results of the effects of C source and liquid loading on RD fermentation. The best values in the regression model lie at the lowest point of the response surface, the centre of the contour plot. Through software calculations, the results showed that the optimum culture condition was as follows: C source was 26.94 ± 0.62 g, N source was 10 ± 0.4 g, MgSO4·7H2O was 0.125 ± 0.002 g, KH2PO4 was 1 ± 0.1 g, rotation speed was 210 r/min, temperature was 25 ± 1 °C, liquid loading was 50 ± 0.2%, and the surface tension was 40.70 ± 0.47 mN/m.
Figure 6

Three-dimensional curved surface diagram of interaction between C source and liquid loading in RD fermentation experiment.

Figure 6

Three-dimensional curved surface diagram of interaction between C source and liquid loading in RD fermentation experiment.

Close modal

Shake the bottle of fermentation verification results

In order to verify whether the theoretical value from the response surface experiment is consistent with the actual value, the strain PS and RD are cultured to verify the experimental results according to the optimised final fermentation conditions; the average surface tension of PS is 40.09 ± 0.12 mN/m, and that of RD is 42.36 ± 0.05 mN/m. The experimental results are almost the same as the predicted values, which shows that the model accords with the experimental situation.

Experiment on degradation of oily sludge

The strains PS and RD were cultured under the conditions before and after fermentation optimisation, and the oily sludge was added to the strains from 18 h to the initial stable stage. Figure 7 shows the comparison of the degradation rate of oily sludge between the strains PS and RD without optimised fermentation and after optimised fermentation. On day 3 there is an increase in the slope; the reason for this is firstly that both bacteria have a process of adapting to their environment in the oily sludge and secondly that the concentration of the bacteria in the oily sludge reaches its maximum on day 3, which results in a faster increase in the concentration of the fermentation products and a faster treatment of the oily sludge, resulting in an increase in the slope on day 3. The inflection point on day 5 is probably due to the fact that as time passes, less and less of the oiled sludge can be processed by both bacteria, leaving the more stubborn organic molecules, which leads to the inflection point on day 5. The experimental results of oily sludge degradation show that, when the fermentation conditions were optimised, the degradation rate of oily sludge was increased; especially for PS, the degradation rate was increased by 9.20 ± 0.72%, and the degradation rate of RD solution was increased by 3.34 ± 0.26%. The degradation rate of PS increased sharply on the fourth day and lasted to the seventh day. The rate of oil degradation increases rapidly from day 3 to day 5, when the amount of surfactant produced reaches a concentration that breaks the oil-water interface, allowing microbes to come into direct contact with more oil. In the process of proliferation and metabolism, more petroleum is consumed as the C source for survival, thus increasing the rate of petroleum degradation.
Figure 7

The effect of fermentation optimisation on the degradation rate of oily sludge.

Figure 7

The effect of fermentation optimisation on the degradation rate of oily sludge.

Close modal

Infrared spectra of oily sludge before and after degradation

Fourier transform infrared (FTIR) analysis of oily sludge treated by PS bacteria and RD bacteria before and after optimisation is shown in Figure 8. The IR spectra showed that the C-H bond vibrated at 609.15 cm−1, the C-O-C bond vibrated at 1,082.20 cm−1, the O-H bond vibrated at 1,458.89 cm−1, the C = C vibrated at 1,637.08 cm−1, and the saturated C-H vibrated at 2,700–3,000 cm−1. The adsorption peak at 3,451.05 cm−1 is the stretching vibration of the hydroxyl group, which indicates the existence of amides, organic aromaticity and aromatic amino acid in oily sludge. By comparing the IR spectra of oily sludge treated by PS bacteria before and after optimisation, it was found that the intensity of IR spectra of oily sludge treated by PS bacteria after optimisation was weakened, and there were no other impurity peaks, indicating reduced availability of amides, organic aromaticity, and aromatic amino acids. However, the IR spectra of RD bacteria treating oily sludge before and after fermentation optimisation were similar. The results showed that RD strain had little effect on the content of organic matter in oily sludge before and after fermentation. The results showed that RSM had better effect on the optimisation of PS fermentation.
Figure 8

IR spectra of oily sludge treated by PS bacteria before optimisation (CG) and PS bacteria after optimisation (EG) (a: PS bacteria; b: RD bacteria).

Figure 8

IR spectra of oily sludge treated by PS bacteria before optimisation (CG) and PS bacteria after optimisation (EG) (a: PS bacteria; b: RD bacteria).

Close modal

In this study, the fermentation broth composition of the two strains was first demonstrated to be biosurfactant. The fermentation processes of both bacteria were optimised using RSM, and the experimental results showed that sucrose as a C source and urea as an N source during the PS fermentation process had better oil-draining activity, emulsification properties and cell surface hydrophobicity. During RD fermentation, glucose as C source and peptide as N source had better oil-draining activity, emulsification performance and cell surface hydrophobicity. N source and liquid loading were significant factors for PS fermentation, and C source and rotational speed were significant factors for RD fermentation. Through the steepest climbing experiment and response surface methodology, the optimum conditions for PS fermentation were found to be as follows: surface tension of 39.53 ± 0.25 mN/m minimum at 4.62 ± 0.41 g N source and 28.4 ± 0.3% liquid content. The optimum conditions for RD fermentation were as follows: surface tension of 40.70 ± 0.47 mN/M at 26.94 ± 0.62 g C source and 210 r/min rotational speed. Finally, the degradation of the oil sludge by the two bacteria was carried out, and the oily sludge before and after treatment was analysed by IR spectroscopy. The experimental results showed that the degradation rate of the oil-bearing sludge was significantly increased by the two bacterial strains, with the degradation rate of the PS-treated oil-bearing sludge increased by 9.20 ± 0.72%. The infrared spectroscopy results showed that the organic matter content in the oiled sludge treated by the optimised fermentation of PS bacteria was significantly reduced. This study will provide a theoretical basis for the biological treatment of oily sludge.

This work was supported by the Fundamental Research Funds for the Central Universities of Central South University.

All relevant data are included in the paper or its Supplementary Information.

The authors declare there is no conflict.

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