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Full-Text Articles in Physical Sciences and Mathematics
Joint Modeling Of Additive And Non-Additive Genetic Line Effects In Single Field Trials, H Oakey, A Verbyla, Brian Cullis, W. Pitchford, H. Kuchel
Joint Modeling Of Additive And Non-Additive Genetic Line Effects In Single Field Trials, H Oakey, A Verbyla, Brian Cullis, W. Pitchford, H. Kuchel
Professor Brian Cullis
A statistical approach is presented for selection of best performing lines for commercial release and best parents for future breeding programs from standard agronomic trials. The method involves the partitioning of the genetic effect of a line into additive and non-additive effects using pedigree based inter-line relationships, in a similar manner to that used in animal breeding. A difference is the ability to estimate non-additive effects. Line performance can be assessed by an overall genetic line effect with greater accuracy than when ignoring pedigree information and the additive effects are predicted breeding values. A generalized definition of heritability is developed …
Joint Modeling Of Additive And Non-Additive (Genetic Line) Effects In Multi-Environment Trials, H Oakey, A Verbyla, Brian Cullis, X. Wei, W. Pitchford
Joint Modeling Of Additive And Non-Additive (Genetic Line) Effects In Multi-Environment Trials, H Oakey, A Verbyla, Brian Cullis, X. Wei, W. Pitchford
Professor Brian Cullis
A statistical approach for the analysis of multienvironment trials (METs) is presented, in which selection of best performing lines, best parents, and best combination of parents can be determined. The genetic effect of a line is partitioned into additive, dominance and residual nonadditive effects. The dominance effects are estimated through the incorporation of the dominance relationship matrix, which is presented under varying levels of inbreeding. A computationally efficient way of fitting dominance effects is presented which partitions dominance effects into between family dominance and within family dominance line effects. The overall approach is applicable to inbred lines, hybrid lines and …
Joint Modeling Of Spatial Variability And Within-Row Interplot Competition To Increase The Efficiency Of Plant Improvement, J. Stringer, Brian Cullis, R Thompson
Joint Modeling Of Spatial Variability And Within-Row Interplot Competition To Increase The Efficiency Of Plant Improvement, J. Stringer, Brian Cullis, R Thompson
Professor Brian Cullis
Trials in the early stages of selection are often subject to variation arising from spatial variability and interplot competition, which can seriously bias the assessment of varietal performance and reduce genetic progress. An approach to jointly model both sources of bias is presented. It models genotypic and residual competition and also global and extraneous spatial variation. Variety effects were considered random and residual maximum likelihood was used for parameter estimation. Competition at the residual level was examined using two special simultaneous autoregressive models. An equal-roots second-order autoregressive (EAR(2)) model is proposed for trials where competition is dominant. An equal-roots third-order …