Valorization of Using Agro-Wastes for Levan through Submerged Fermentation and Statistical Optimization of the Process Variables Applying Response Surface Methodology (RSM) Design
Abstract
:1. Introduction
2. Materials and Methods
2.1. Maintaining and Cultivating Microorganism
2.2. Collection of Substrates
2.3. Inoculum Preparation
2.4. Sucrose Content Determination by Polarimeter
2.5. Pretreatment of Substrates
2.6. Choosing the Optimal Substrate for the Manufacture of Levan
2.7. Process Optimization for Greatest Production of Levan
2.8. Precipitation and Quantification of Levan
2.9. Characterization of Levan
2.9.1. Fourier-Transform Infrared (FTIR) Spectroscopy
2.9.2. Analysis of Sugar Content with High-Performance Liquid Chromatography (HPLC)
2.9.3. Using High-Performance Size-Exclusion Chromatography (HPSEC) to Calculate the Molecular Weight of Levan
3. Results and Discussion
3.1. Analysis of Sucrose Content of Fruit Peels
3.2. Screening of Best Substrate for Levan Production
3.3. Levan Biosynthesis Optimization by RSM
3.4. Identification, Quantification, and Characterization of Levan
3.4.1. FTIR
3.4.2. HPLC Analysis
4. Discussion
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Codes | Independent Parameters | Unit | Low Level | High Level |
---|---|---|---|---|
A | Incubation time | h | 08 | 120 |
B | Temperature | °C | 20 | 50 |
C | pH | - | 05 | 10 |
D | Inoculum volume | mL | 01 | 5 |
E | Agitation speed | rpm | 100 | 200 |
Substrates | Sucrose Content (g/L) |
---|---|
Mangifera indica (mango) peels | 89.11 ± 0.54 |
Musa acuminate (banana) peels | 29.77 ± 0.32 |
Malus domestica (apple) peels | 14.02 ± 0.41 |
Saccharum officinarum (sugar cane) bagasse | 17.76 ± 0.18 |
Levan (g/L) | ||||||||
---|---|---|---|---|---|---|---|---|
Experiment | A | B | C | D | E | Observed | Predicted | Residuals |
1 | 48 | 30 | 7.5 | 1 | 150 | 0.401 | 0.442 | −0.041 |
2 | 64 | 25 | 7.5 | 2 | 130 | 0.336 | 0.341 | −0.005 |
3 | 120 | 30 | 5 | 1.5 | 150 | 0.336 | 0.388 | −0.021 |
4 | 48 | 30 | 8 | 3 | 130 | 0.315 | 0.319 | −0.003 |
5 | 48 | 35 | 7 | 5 | 200 | 0.635 | 0.660 | −0.024 |
6 | 48 | 30 | 5 | 2 | 150 | 0.476 | 0.483 | −0.007 |
7 | 120 | 30 | 7 | 5 | 180 | 0.464 | 0.487 | −0.022 |
8 | 48 | 40 | 7 | 4.5 | 100 | 0.128 | 0.117 | 0.010 |
9 | 24 | 25 | 10 | 3 | 180 | 0.578 | 0.602 | −0.023 |
10 | 72 | 50 | 7.5 | 2 | 100 | 0.013 | 0.030 | −0.016 |
11 | 24 | 30 | 7 | 1 | 130 | 0.374 | 0.381 | −0.006 |
12 | 24 | 35 | 7.5 | 2.5 | 150 | 0.424 | 0.438 | −0.013 |
13 | 12 | 40 | 8 | 3.5 | 130 | 0.303 | 0.308 | −0.004 |
14 | 24 | 50 | 5 | 4 | 100 | 0.141 | 0.132 | −0.009 |
15 | 64 | 35 | 7.5 | 2 | 180 | 0.717 | 0.541 | 0.175 |
16 | 64 | 50 | 6 | 2.5 | 110 | 0.106 | 0.118 | −0.012 |
17 | 64 | 30 | 5 | 4 | 150 | 0.451 | 0.451 | 0.0003 |
18 | 48 | 25 | 7 | 4 | 120 | 0.324 | 0.310 | 0.013 |
19 | 12 | 25 | 7.5 | 5 | 150 | 0.509 | 0.499 | 0.010 |
20 | 72 | 40 | 6 | 4.5 | 110 | 0.161 | 0.155 | 0.006 |
21 | 8 | 30 | 7.5 | 1.5 | 100 | 0.245 | 0.236 | 0.009 |
22 | 72 | 25 | 5 | 2 | 130 | 0.378 | 0.376 | 0.001 |
23 | 24 | 30 | 5 | 3 | 130 | 0.418 | 0.407 | 0.010 |
24 | 72 | 20 | 10 | 3.5 | 130 | 0.302 | 0.305 | −0.002 |
25 | 24 | 25 | 7 | 4.5 | 150 | 0.502 | 0.495 | 0.007 |
26 | 72 | 35 | 5 | 4.5 | 180 | 0.548 | 0.564 | 0.015 |
27 | 24 | 50 | 6 | 5 | 100 | 0.119 | 0.108 | −0.012 |
28 | 120 | 20 | 6 | 5 | 120 | 0.270 | 0.254 | −0.009 |
29 | 48 | 50 | 7 | 2.5 | 110 | 0.108 | 0.121 | −0.029 |
30 | 12 | 35 | 7.5 | 3 | 150 | 0.442 | 0.452 | −0.008 |
31 | 48 | 35 | 6 | 3.5 | 200 | 0.657 | 0.686 | −0.06 |
32 | 8 | 25 | 10 | 1 | 100 | 0.213 | 0.221 | −0.14 |
Source | DF | Adj SS | Adj MS | F-Value | p-Value |
---|---|---|---|---|---|
Model | 20 | 0.955516 | 0.047776 | 50.53 | 0.001 |
Linear | 5 | 0.355740 | 0.071148 | 75.24 | 0.001 |
A | 1 | 0.000234 | 0.000234 | 0.25 | 0.629 |
B | 1 | 0.001084 | 0.001084 | 1.15 | 0.307 |
C | 1 | 0.000671 | 0.000671 | 0.71 | 0.418 |
D | 1 | 0.004332 | 0.004332 | 4.58 | 0.056 |
E | 1 | 0.129846 | 0.129846 | 137.32 | 0.000 |
Square | 5 | 0.004979 | 0.000996 | 1.05 | 0.435 |
A*A | 1 | 0.000055 | 0.000055 | 0.06 | 0.815 |
B*B | 1 | 0.001448 | 0.001448 | 1.53 | 0.242 |
C*C | 1 | 0.001383 | 0.001383 | 1.46 | 0.252 |
D*D | 1 | 0.000399 | 0.000399 | 0.42 | 0.530 |
E*E | 1 | 0.000369 | 0.000369 | 0.39 | 0.545 |
Two-Way Interaction | 10 | 0.026064 | 0.002606 | 2.76 | 0.056 |
A*B | 1 | 0.002037 | 0.002037 | 2.15 | 0.170 |
A*C | 1 | 0.000875 | 0.000875 | 0.93 | 0.357 |
A*D | 1 | 0.001883 | 0.001883 | 1.99 | 0.186 |
A*E | 1 | 0.008161 | 0.008161 | 8.63 | 0.014 |
B*C | 1 | 0.002803 | 0.002803 | 2.96 | 0.113 |
B*D | 1 | 0.001176 | 0.001176 | 1.24 | 0.289 |
B*E | 1 | 0.008845 | 0.008845 | 9.35 | 0.011 |
C*D | 1 | 0.001108 | 0.001108 | 1.17 | 0.302 |
C*E | 1 | 0.007263 | 0.007263 | 7.68 | 0.018 |
D*E | 1 | 0.009148 | 0.009148 | 9.68 | 0.010 |
Error | 11 | 0.010401 | 0.000946 | ||
Total | 31 | 0.965918 |
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Saeed, S.; Ahmed, S.; Naz, A.; Arooj, F.; Mehmood, T. Valorization of Using Agro-Wastes for Levan through Submerged Fermentation and Statistical Optimization of the Process Variables Applying Response Surface Methodology (RSM) Design. Microorganisms 2023, 11, 1559. https://doi.org/10.3390/microorganisms11061559
Saeed S, Ahmed S, Naz A, Arooj F, Mehmood T. Valorization of Using Agro-Wastes for Levan through Submerged Fermentation and Statistical Optimization of the Process Variables Applying Response Surface Methodology (RSM) Design. Microorganisms. 2023; 11(6):1559. https://doi.org/10.3390/microorganisms11061559
Chicago/Turabian StyleSaeed, Shagufta, Sibtain Ahmed, Alina Naz, Fariha Arooj, and Tahir Mehmood. 2023. "Valorization of Using Agro-Wastes for Levan through Submerged Fermentation and Statistical Optimization of the Process Variables Applying Response Surface Methodology (RSM) Design" Microorganisms 11, no. 6: 1559. https://doi.org/10.3390/microorganisms11061559
APA StyleSaeed, S., Ahmed, S., Naz, A., Arooj, F., & Mehmood, T. (2023). Valorization of Using Agro-Wastes for Levan through Submerged Fermentation and Statistical Optimization of the Process Variables Applying Response Surface Methodology (RSM) Design. Microorganisms, 11(6), 1559. https://doi.org/10.3390/microorganisms11061559