Statistical Performance Analysis of Complete and Incomplete Block Designs: a Comparison of Rcbd, Lattice and Alpha Lattice Designs Under a Sari Field Conditions

Statistical Performance Analysis of Complete and Incomplete Block Designs: a Comparison of RCBD, Lattice Design and Alpha-Lattice Designs under SARI Field Conditions

By
Ashenafi Abebe

A Thesis Submitted to the Department of Statistics, School of Graduate Studies, College of Natural Science, Jimma University In Partial Fulfillment for the Requirements of Masters of Science (MSc) Degree in Biostatistics

October, 2011 Jimma, Ethiopia
Statistical Performance Analysis of Complete and Incomplete Block Designs: a Comparison of RCBD, Lattice Design and Alpha-Lattice Designs under SARI Filed Conditions

M.Sc. Thesis

Ashenafi Abebe Gaenamo

October, 2011 Jimma, Ethiopia DEPARTMENT OF STATISTICS, SCHOOL OF GRADUATE STUDIES JIMMA UNIVERSITY As thesis advisors, we hereby certify that we had read and evaluated the thesis prepared by Ashenafi Abebe under our guidance, which was entitled statistical “Statistical Performance Analysis of Complete and Incomplete Block Designs: a Comparison of RCBD, Lattice Design and Alpha-Lattice Designs under SARI Field Conditions”. We recommend that the thesis be submitted as it fulfills the requirements for the degree of Master of Science in Biostatistics. Yehenew Getachew (Asst Prof, PhD Scholar) ________________ _______________ Major advisor Signature Date Legesse Negash (PhD Scholar) ________________ _______________ Co- advisor Signature Date As the members of the board of examiners of Msc thesis open defense examination of Ashenafi Abebe Gaenamo, we certify that we have read and evaluated the thesis and examined the candidate. We recommend that the thesis be accepted as it fulfills the requirements

References: 1. Alves E. G., St. Aubyn, A. and Martins, A. (2009): Experimental designs for evaluation of genetic variability and selection of ancient grapevine varieties: a simulation study. Heredity Journals, 104(6):552‐562. 2. Atkinson A.C. and Bailey, R.A. (2001): One Hundred Years of the Design of Experiments on and off the Pages of “Biometrika”. Biometrica, 88(1): 53-97. 3. Bartley, M.S. 1936. Square-root transformation in analysis of variance. J.R. Stat. Soc. Suppl. 3:68-78 4 5. Campbell B.T. and Bauer, P.J. (2007): Improving the precision of cotton performance trials conducted on highly variable soils of the South-Eastern USA coastal plain. Blackwell synergy-plant breeding, 126, 622-627. 6. Cochran W.G. and Cox, G.M. (1957): Experimental Designs. John Wiley & Sons, Inc. New York. 7. Cox V.G. (1950): Experimental Design. Biometrics 6, 301-302. 8. Cullis B.R. and Gleeson A.C. (1991): Spatial Analysis of Field Experiments. An Extension to Two Dimensions. Biometrics 47, 1449-1460. 9. Das M.N. and Giri N.C. (1986). Design and analysis of experiments. New Age international Limited. 10. Day B.B. and Austin L. (1939): A Three-dimensional Lattice Design for Studies in Forest Genetics. J. Agr. Res., 59, 101-119. 11. Drane J.W. (1989): Compromises and Statistical Designs for Grazing Experiments in Grazing Research. Crop Science Society of America and American Society of Agronomy: 16, 69-83. 12. Edme S.J., Tai and J.D. Miller (2007): Relative Efficiency of Spatial Analysis for Non-replicated Early-stage Sugarcane Field Experiments. Journal of the American Society of Sugar Cane Technologists, 27: 89-104. 13. Eskridge K.M. (2008): Field Trial Designs in Plant Breeding. University of Nebraska, Lincoln, NE. 14. Gharde Y. (2000): Analysis of Covariance. I.A.S.R.I., Library Avenue, New Delhi. 15. Girma T. A. (2002): Design and Analysis of Field Experiments in Agriculture. Ethiopian Agriculture Research Organization. Technical Manual No. 15, Addis Ababa. 16. Girma T. A. (2005): Using Spatial Modeling Techniques to Improve Data Analysis from Agricultural Field Trial. PhD Thesis of University of KwaZulu-Natal, Pietermaritzburg. 17. Gomez K.A. and Gomez, A.A. (1984): Statistical Procedures for Agricultural Research, 2nd ed. John Wiley and Sons, Inc.; New York 18 19. Gwowen Shieh, Show-Li Jan (2004): The effectiveness of randomized complete block design. Statistica Neerlandica: 58(1): 111–124. 20 21. Hatfield J.L. (2000): Precision Agriculture and Environmental Quality: Challenges for Research and Education. U.S. Department of Agriculture, in Ames, Iowa. 22. Idrees N. and Khan M.I. (2009): Design improvement Using Uniformity Trials Experimental data. Pakistan Journal Agricultural Science. 46, Faisalabad 23 24. Karcher D.E., Richardson M.D., and Secks M.E (2003): Does Blocking Affect Experimental Efficiency on Sand-Based Putting Greens? Crop Science Society of America, 43: 2295-2297. 25. Kempton R.A., Seraphin J.C. and Sword A.M. (1994): Statistical Analysis of Two Dimensional Variations in Variety Yield Trials. Journal of Agricultural Science, Cambridge, 122, 335-342. 26. Kuehl R.O (1994): Statistical Principles of Research Design and Analysis. Duxbury Press, Belmont, CA. 27. Leonardo Journal of sciences (2009), Issue 15 p. 71-8: Statistical Approaches in Analysis of Variance, Romania. 28. Little T. M. and Hills, F. J. (1978): Agricultural Experimentation, Design and Analysis. John Wiley and Sons, Inc. New York. 29. Mandefro N. (2005): Statistical procedures for Designed Experiments. Ethiopian Agriculture Research Organization, Addis Ababa. 30. Masoon A. A., Mujahid Y., Khan M.I., and Abid S. (2006): Improving precisions of Agricultural field Experiments. Journal of Sustainable Development, 3: 11-13. 31. Masood M. A., Farooq K., Mujahid Y. and Anwar M. Z. (2008): Improvement in Precision of Agricultural Field Experiments through Design and Analysis. Pak. J. Life Soc. Sci., 6(2): 89-91. 32. Montgomery D. C. (1991): Design and Analysis of Experiments. 3rd ed. John Wiley and Sons, Inc. New York. 33. M. Kashifa M. I. , Khanb M. , Arifb M. Anwerc and M. Ijazc(2001): Journal of Scientific Research: 3 (1), 91-95: www.banglajol.info/index.php/JSR 34 35. Panse V.G. (1958): Status of Agricultural Experiments. F.A.O., Rome. 36. Patterson H.D. and Hunter E.A. (1983): The efficiency of incomplete block designs in National List and Recommended cereal variety trials. J. Agric. Sci., 101, 427-433. 37. Patterson H.D. and Williams E.R. (1976): A New Class of Resolvable Incomplete Block Designs. Biometrika, 63:83-92. 38. Pearce S.C. (1983): The Agricultural Field Experiments. A Statistical Examination of Theory and Practice. John Wiley and Sons, Inc., New York. 39. Raza I. and Masood M.A (2009): Efficiency of Lattice Design in Relation to Randomized Complete Block Design in Agricultural Field Experiments. Pakistan J. Agric. Res. 22: 150-153. 40. Reza Hoshmand, A. (2006): Design of Experiments for Agriculture and the Natural Science, 2nd Edition: Daniel Webster College Nashua, New Hampshire, U.S.A. 41. Sharma V.K. (2000): Balanced Incomplete Block Designs. I.A.S.R.I., Library Avenue, New Delhi-110012. 42. Snedecor, G. and Cochran, W.G. 1980. Statistical Methods. 7th ed. Ames, IA: Iowa State University press. 43. Snyder E.B. (1962): Lattice and Compact Family Block Designs in Forest Genetics.U.S. Department of Agriculture, Gulfport, Mississippi. 44. Vas Es C.P. G. and Sellman M. (2007): Spatially-Balanced Complete Block Designs for field experiments. Cornell University, Ithaca, United States. Geoderma 140, 346-352. 45. Wu T. and Dutilleul P. (1999): Validity and Efficiency of Neighbor Analysis in Comparison with Classical Complete and Incomplete Block Analysis of Field Experiments. Agron. J. 91: 721-731. 46. Yates F. (1936): A New Method of Arranging Variety Trials Involving a Large Number of varieties. J. Agric. Sci. 26, 424-455. 47. Yates F. (1939): The Recovery of Inter-block Information in Variety Trials Arranged in Three-dimensional Lattices. Ann. Eugen. 9, 136-156. 48. Yau S.K. (1997): Efficiency of alpha-lattice designs in international variety yield trials of barley and wheat. The Journal of Agricultural Science, 128, 5-9.