Bhartiya Krishi Anusandhan Patrika, volume 38 issue 3 (september 2023) : 223-226

A Method of Constructing p-rep Designs

L.N. Vinaykumar1, Cini Varghese1, Seema Jaggi2, Eldho Varghese3, Mohd Harun1, Sayantani Karmakar1,*, Devendra Kumar1
1ICAR-Indian Agricultural Statistics Research Institute, Pusa-110 012, New Delhi, India.
2Human Resource Development, Krishi Anusandhan Bhavan II, ICAR, New Delhi, India.
3Division of Fishery Resources Assessment, ICAR-Central Marine Fisheries Research Institute, Kochi-682 018, Kerala, India.
  • Submitted13-07-2022|

  • Accepted02-06-2023|

  • First Online 04-10-2023|

  • doi 10.18805/BKAP561

Cite article:- Vinaykumar L.N., Varghese Cini, Jaggi Seema, Varghese Eldho, Harun Mohd, Karmakar Sayantani, Kumar Devendra (2023). A Method of Constructing p-rep Designs . Bhartiya Krishi Anusandhan Patrika. 38(3): 223-226. doi: 10.18805/BKAP561.
Background: Early generation breeding trials (EGBTs) are very important in plant breeding programmes. In most cases, a large number of breeding lines are to be tested, often with very few available resources and it is also required to repeat these trials in a number of environments. For such trials, an alternative is to use partially replicated designs, where a proportion of the test lines are replicated at each environment. 

Methods: Here, a general method of constructing a series of efficient partially replicated designs for EGBTs in equal block sizes, through initial blocks is developed. 

Result: Taking all environments together, the designs obtained are equi-replicate and are partially balanced. They are cost effective in terms of resources as they require lesser replications.

  1. Clarke, G.P.Y. and Stefanova, K.T. (2011). Optimal design for early generation plant breeding trials with unreplicated or partially replicated test lines. Australian and New Zealand Journal of Statistics. 53(4): 461-480.

  2. Cullis, B.R., Smith, A.B. and Coombes, N.E. (2006). On the design of early generation variety trials with correlated data. Journal of Agricultural, Biological and Environmental Statistics. 11(4): 381-393.

  3. Cullis, B.R., Smith, A.B., Cocks, N.A. and Butler, D.G. (2020). The design of early-stage plant breeding trials using genetic relatedness. Journal of Agricultural, Biological and Environmental Statistics. 25(4): 553-578.

  4. Harun, M., Varghese, C., Varghese, E. and Jaggi, S. (2016a). Three-way cross designs for test lines vs. control line comparisons. Electronic Journal of Plant Breeding.  7(1): 42-47.

  5. Harun, M., Varghese, C., Jaggi, S., Varghese, E., Bhowmik, A., Datta, A. and Kumar, N. (2016b). Designs for breeding trials involving triallel crosses. Bhartiya Krishi Anushandhan Patrika. 31(2): 158-160.  

  6. Kempton, R.A. (1982). The design and analysis of unreplicated feld trials. Vortrage fur Panzenzuchtung. 7: 219-242.

  7. Moehring, J., Williams, E.R. and Piepho, H.P. (2014). Efficiency of augmented p-rep designs in multi-environmental trials. Theoretical and Applied Genetics. 127(5): 1049-1060.

  8. Piepho, H.P., Williams, E.R. and Michel, V. (2016). Nonresolvable row-column designs with an even distribution of treatment replications. Journal of Agricultural, Biological and Environmental Statistics. 21(2): 227-242. 

  9. Smith, A.B., Thompson, R. and Cullis, B.R. (2009). Embedded partially replicated designs for grain quality testing. [Conference paper - 2073].

  10. Sermarini, R.A., Brien, C., Demétrio, C.G.B. and dos Santos, A. (2020). Impact on genetic gain from using misspecified statistical models in generating p rep designs for early generation plant breeding experiments. Crop Science. 60(6): 3083-3095.

  11. Williams, E., Piepho, H.P. and Whitaker, D. (2011). Augmented p rep designs. Biometrical Journal. 53(1): 19-27.

  12. Williams, E.R., John, J.A. and Whitaker, D. (2014). Construction of more flexible and efficient p-rep designs. Australian and New Zealand Journal of Statistics. 56(1): 89-96.

Editorial Board

View all (0)