Advertisement

Waste and Biomass Valorization

, Volume 10, Issue 5, pp 1277–1284 | Cite as

Optimization of Xylanase Production by Trichoderma orientalis Using Corn Cobs and Wheat Bran via Statistical Strategy

  • Chuannan Long
  • Jian Liu
  • Lihui Gan
  • Bin Zeng
  • Minnan LongEmail author
Original Paper
  • 146 Downloads

Abstract

In order to obtain the best conditions for xylanase production, statistical experimental designs were applied for improvement of xylanase yield by Trichoderma orientalis EU7-22 using corn cobs and wheat bran as raw materials. Plackett–Burman design was applied to evaluate the effects of eight variables (concentration of peptone, tween-80, CaCl2, MgSO4, FeSO4, as well as initial pH, fermentation temperature, fermentation time). The key factors influencing on xylanase production were identified as the fermentation time, concentration of MgSO4, and fermentation temperature. And then the path of steepest ascent was carried out to approach the optimal region of the three significant factors. These variables were subsequently further investigated by Box–Behnken design of response surface methodology. The optimum conditions for xylanase production were obtained as fermentation time 72 h, concentration of 0.08% for MgSO4, fermentation temperature 37.3 °C, and the xylanase activity increased from 107.6 to 269.4 IU/mL, which was a 150% increase. It was found that the higher temperature (37.3 °C) was more suitable for xylanase production than low temperature (30.0 °C) in T. orientalis EU7-22. The statistical experimental design was proven as an effective method to obtain optimum parameters for xylanase production. The mixture of corn cobs and wheat bran as substrates could greatly improve the xylanase yield, in comparison with corn cobs alone, wheat bran alone, and Avicel supplement with wheat bran as inducer substrates, respectively.

Keywords

Trichoderma orientalis Xylanase Plackett–Burman design Response surface methodology 

Notes

Acknowledgements

This work was supported by the National Natural Science Foundation of China (Grant Nos. 31170067, 21303142), Jiangxi Province Science Foundation for Youths (Grant No. 20161BAB214177).

References

  1. 1.
    Kumar, R., Singh, S., Singh, O.V.: Bioconversion of lignocellulosic biomass: biochemical and molecular perspectives. J. Ind. Microbiol. Biotechnol. 35, 377–391 (2008)CrossRefGoogle Scholar
  2. 2.
    Minic, Z., Christophe, R., Do, C.T., Lerounge, P., Jouanin, L.: Purification and characterization of enzymes exhibiting β-d-xylosidase activities in stem tissues of Arabidopsis. Plant Physiol. 135, 867–878 (2004)CrossRefGoogle Scholar
  3. 3.
    Collins, T., Gerday, C., Feller, G.: Xylanases, xylanase families and extremophilic xylanases. FEMS Microbiol. Rev. 29, 3–23 (2005)CrossRefGoogle Scholar
  4. 4.
    Knob, A., Terrasan, C.R.F., Carmona, E.C.: β-Xylosidases from filamentous fungi: an overview. World J. Microbiol. Biotechnol. 26, 389–407 (2010)CrossRefGoogle Scholar
  5. 5.
    Katahira, S., Fujita, Y., Mizuike, H., Fukuda, H., Kondo, A.: Construction of a xylan-fermenting yeast strain through codisplay of xylanolytic enzymes of the surface of xylose utilizing Saccharomyces cerevisie cells. Appl. Environ. Microbiol. 70, 5407–5414 (2004)CrossRefGoogle Scholar
  6. 6.
    Sánchez, C.: Lignocellulosic residues: biodegradation and bioconversion by fungi. Biotechnol. Adv. 27, 185–194 (2009)CrossRefGoogle Scholar
  7. 7.
    Subramanyan, S., Prema, P.: Biotechnology of microbial xylanases: enzymology, molecular biology and application. Crit. Rev. Biotechnol. 22(1), 33–64 (2002)CrossRefGoogle Scholar
  8. 8.
    Li, Y., Cui, F.J., Liu, Z.Q., Xu, Y.Y., Zhao, H.: Improvement of xylanase production by Penicillium oxalicum ZH-30 using response surface methodology. Enzyme Microb. Technol. 40, 1381–1388 (2007)CrossRefGoogle Scholar
  9. 9.
    Desai, D.I., Iye, B.D.: Utilization of corn cob waste for cellulase-free xylanase production by Aspergillus niger DX-23: medium optimization and strain improvement. Waste Biomass Valor. (2016).  https://doi.org/10.1007/s12649-016-9567-4 Google Scholar
  10. 10.
    Irfan, M., Asghar, U., Nadeem, M., Nelofer, R., Syed, Q., Shakir, H.A., Qazi, J.I.: Statistical optimization of saccharification of alkali pretreated wheat straw for bioethanol production. Waste Biomass Valor. (2016).  https://doi.org/10.1007/s12649-016-9540-2 Google Scholar
  11. 11.
    Walia, A., Mehta, P., Chauhan, A., Shirkot, C.K.: Optimization of cellulase-free xylanase production by alkalophilic Cellulosimicrobium sp CKMX1 in solid-state fermentation of apple pomace using central composite design and response surface methodology. Ann. Microbiol. 63(1), 187–198 (2013)CrossRefGoogle Scholar
  12. 12.
    Qing, Q., Wyman, C.E.: Supplementation with xylanase and β-xylosidase to reduce xylo-oligomer and xylan inhibition of enzymatic hydrolysis of cellulose and pretreated corn stover. Biotechnol. Biofuels 4, 1–18 (2011)CrossRefGoogle Scholar
  13. 13.
    Xu, C., Long, M.N., Wu, X.B., Xu, H.J., Zhang, F.Z., Xu, L.S.: Screening and characterization of the high-cellulose-producing strain. Front. Biol. 1(1), 35–40 (2006)CrossRefGoogle Scholar
  14. 14.
    Bailey, M.J., Biely, P., Poutanen, K.: Interlaboratory testing of methods for assay of xylanase activity. J. Biotechnol. 23, 257–270 (1992)CrossRefGoogle Scholar
  15. 15.
    Ghose, T.K.: Measurement of cellulase activities. Pure. Appl. Chem. 59, 257–268 (1987)CrossRefGoogle Scholar
  16. 16.
    Khosravi-Darani, K., Zoghi, A.: Comparison of pretreatment strategies of sugarcane baggase: experimental design for citric acid production. Bioresour. Technol. 99, 6986–6993 (2008)CrossRefGoogle Scholar
  17. 17.
    Plackett, R.L., Burman, J.P.: The design of optimum multifactorial experiments. Biometrika 37, 305–325 (1946)MathSciNetCrossRefzbMATHGoogle Scholar
  18. 18.
    Nath, A., Chattopadhyay, P.K.: Optimization of oven toasting for improving crispness and other quality attributes of ready to eat potato-soy snack using response surface methodology. J. Food. Eng. 80, 1282–1292 (2007)CrossRefGoogle Scholar
  19. 19.
    Sin, H.N., Yusof, S., Hamid, N.S.A., Rahman, R.A.: Optimization of enzymatic clarification of sapodilla juice using response surface methodology. J. Food. Eng. 73, 313–319 (2006)CrossRefGoogle Scholar
  20. 20.
    Tanyildizi, M.S., Ozer, D., Elibol, M.: Optimization of α–amylase production by Bacillus sp. using response surface methodology. Process. Biochem. 40(7), 2291–2296 (2005)CrossRefGoogle Scholar
  21. 21.
    Xu, H., Sun, L.P., Shi, Y.Z., Wu, Y.H., Zhang, B., Zhao, D.Q.: Optimization of cultivation conditions for extracellular polysaccharide and mycelium biomass by Morchella esculenta As51620. Biochem. Eng. J. 39, 66–73 (2008)CrossRefGoogle Scholar
  22. 22.
    Khurana, S., Kapoor, M., Gupta, S., Kuhad, R.C.: Statistical optimization of alkaline xylanase production from Streptomyces violaceoruber under submerged fermentation using response surface methodology. Indian J. Microbiol. 47, 144–152 (2007)CrossRefGoogle Scholar
  23. 23.
    Sun, X.Y., Liu, Z.Y., Qu, Y.B., Li, X.Z.: The effects of wheat bran composition on the production of biomass-hydrolyzing enzymes by Penicillium decumbens. Appl. Biochem. Biotechnol. 146(1–3), 119–128 (2008)CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V., part of Springer Nature 2017

Authors and Affiliations

  • Chuannan Long
    • 1
    • 2
    • 3
  • Jian Liu
    • 3
  • Lihui Gan
    • 3
  • Bin Zeng
    • 1
    • 2
  • Minnan Long
    • 3
    Email author
  1. 1.Jiangxi Key Laboratory of Bioprocess EngineeringJiangxi Science & Technology Normal UniversityNanchangChina
  2. 2.School of Life ScienceJiangxi Science & Technology Normal UniversityNanchangChina
  3. 3.College of EnergyXiamen UniversityXiamenChina

Personalised recommendations