203-2 Relationship Between Heritability, Progeny Size and Effectiveness of the Classification of Inbred Progenies by Simulation.

Poster Number 119

See more from this Division: ASA Section: Biometry and Statistical Computing
See more from this Session: General Biometry and Statistical Computing: II
Tuesday, October 23, 2012
Duke Energy Convention Center, Exhibit Hall AB, Level 1
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Fernando Henrique Toledo, PhD student, University of Sao Paulo, Piracicaba - SP, Brazil and Roland Vencovsky, Genetics Departament, Full Professor, University of São Paulo, Piracicaba - SP, Brazil
Poster Presentation
  • poster_FH.pdf (768.5 kB)
  • One of the advantages of simulation, as compared to conventional testing, is the large amount of results attainable in a short period of time and the possibility of circumventing the problem of sample size, overcoming the limitations due to large number of replications. The aim of this study was evaluating the relationship between the heritability of a trait , progeny size and the effectiveness in the ranking of progenies with selection of the 5% superior ones. A quantitative trait controlled by 100 independent loci with equal additive effects and two alleles, was considered. One hundred F6:7 progenies were simulated containing variable number of individuals per progenies (4; 16; 64 and 256). The correct identification of the 5% superior progenies was investigated considering heritability on a plant basis (h2) ranging from 0.01 to 0.99. Each scenario was repeated 500 times. For intermediate heritabilities larger progeny sizes increased the efectiveness of the classification process, and aproximately 30 individuals per progeny was found to be adequate for the ranking of progenies. For h2 = 0.25, the average of the 500 simulations indicated that the effectiveness of the classification was half of that obtained with 64 individuals; when h2 = 0.75, the effectiveness achieved with 4 plants was 80% of the precision obtained using 64 plants. Results suggested that evaluating progenies with much more than 30 individuals is inefficient when h2 is intermediate (0.25 <= h2 <= 0.75).
    See more from this Division: ASA Section: Biometry and Statistical Computing
    See more from this Session: General Biometry and Statistical Computing: II