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Use of Statistics in Plant Biotechnology

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Part of the Methods in Molecular Biology™ book series (MIMB,volume 318)

Abstract

Statistics and experimental design are important tools for the plant biotechnologist and should be used when planning and conducting experiments as well as during the analysis and interpretation of results. This chapter provides some basic concepts important to the statistical analysis of data obtained from plant tissue culture or biotechnological experiments, and illustrates the application of common statistical procedures to analyze binomial, count, and continuous data for experiments with different treatment factors as well as identifying trends of dosage treatment factors.

Key Words

  • Analysis of variance
  • binomial data
  • continuous data
  • concentration treatment factors
  • count data
  • data analysis
  • logistic regression
  • mean separation tests
  • plant tissue culture
  • Poisson regression
  • regression analysis

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  • DOI: 10.1385/1-59259-959-1:145
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References

  1. Little, T. M. and Hills, F. J. (eds.) (1978) Agricultural Experimentation: Design and Analysis. John Wiley and Sons, Inc., New York.

    Google Scholar 

  2. Lentner, M. and Bishop, T. (eds.) (1986) Experimental Design and Analysis. Valley Book Company, Blacksburg, VA.

    Google Scholar 

  3. Kempthorne, O. (ed.) (1973) The Design and Analysis of Experiments. Robert E. Krieger Publishing Co., Malabar, FL.

    Google Scholar 

  4. Compton, M. E. (1994) Statistical methods suitable for the analysis of plant tissue culture data. Plant Cell Tiss. Org. Cult. 37, 217–242.

    Google Scholar 

  5. Compton, M.E. (2000) Statistical analysis of plant tissue culture data, in Plant Tissue Culture Concepts and Laboratory Exercises (Trigiano, R.N. and Gray, D.J., eds.), 2nd edition. CRC Press, Boca Raton, FL, pp. 61–74.

    Google Scholar 

  6. Compton, M. E. (2004) Elements of in vitro research, in Plant Development and Biotechnology (Trigiano, R. N. and Gray, D. J., eds.), CRC Press, Boca Raton, FL pp. 55–71.

    CrossRef  Google Scholar 

  7. Compton, M.E. and Mize, C.W. (1999) Statistical considerations for in vitro research: I—Birth of an idea to collecting data. In Vitro Cell. Dev. Biol., Plant 35, 115–121.

    CAS  Google Scholar 

  8. Anonymous (2004) SAS/STAT Software. SAS Institute. Accessed June 14, 2004; available at http://support.sas.com/rnd/app/da/stat.html.

  9. Anonymous (2004) SPSS. Accessed June 14 2004; available at http://www.spss.com/.

  10. Anonymous (2004) Systat Software, Inc. Software, Services, Solutions for the Statistics, Scientific Community. Accessed June 14 2004; available at http://www.systat.com/.

  11. Anonymous (2004) Minitab. Accessed June 14 2004; available at http://www.minitab.com.

  12. Anonymous (2004) STATISTIX. Accessed June 14 2004; available at http://www.statistix.com.

  13. Preece, J. E. (2000) Shoot organogenesis from petunia leaves, in Plant Tissue Culture Concepts and Laboratory Exercises, (Trigiano, R. N. and Gray, D. J., eds.), 2nd edition. CRC Press, Boca Raton, FL, pp. 167–173.

    Google Scholar 

  14. Mize, C. W., Koehler, K. J., and Compton, M. E. (1999) Statistical considerations for in vitro research: II data to presentation. In Vitro Cell. Dev. Biol., Plant 35, 122–126.

    CAS  CrossRef  Google Scholar 

  15. Zar, J. H. (ed.) (1984) Biostatistical Analysis, second edition. Prentice-Hall, Inc., Upper Saddle River, NJ.

    Google Scholar 

  16. Mize, C. W. and Chun, Y. W. (1988) Analysing treatment means in plant tissue culture research. Plant Cell Tissue Organ Cult. 13, 201–217.

    CrossRef  Google Scholar 

  17. Kleinbaum, D. G., Kupper, L. L., and Muller, K. E. (eds.) (1988) Applied Regression Analysis and Other Multivariable Methods. Second Edition. PWS-Kent Publishing Co., Boston.

    Google Scholar 

  18. Mize, C. W. and Winistorfer, P. M. (1982) Application of subsampling to improve precision. Wood Sci. 15, 14–18.

    Google Scholar 

  19. Kuklin, A. I., Trigiano, R. N., Sanders, W. L., and Conger, B. V. (1993) Incomplete block design in plant tissue culture research. J. Plant Tiss. Cult. Meth. 15, 204–209.

    CrossRef  Google Scholar 

  20. Carmer, S. G. and Seif, R. D. (1963) Calculation of orthogonal coefficients when treatments are unequally replicated and/or unequally spaced. Agronomy J. 55, 387–389.

    CrossRef  Google Scholar 

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© 2006 Humana Press Inc.

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Compton, M.E. (2006). Use of Statistics in Plant Biotechnology. In: Loyola-Vargas, V.M., Vázquez-Flota, F. (eds) Plant Cell Culture Protocols. Methods in Molecular Biology™, vol 318. Humana Press. https://doi.org/10.1385/1-59259-959-1:145

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  • DOI: https://doi.org/10.1385/1-59259-959-1:145

  • Publisher Name: Humana Press

  • Print ISBN: 978-1-58829-547-7

  • Online ISBN: 978-1-59259-959-2

  • eBook Packages: Springer Protocols