ADJUSTMENT FOR COMPETITION BETWEEN GENOTYPES IN SINGLE-ROW-PLOT TRIALS OF WINTER-WHEAT (TRITICUM-AESTIVUM)

Several statistical methods were investigated for improving yield esti mation for 72 genotypes of winter wheat tested in a single-row-plot (S RP) trial. The different analytical models were compared using several criteria: the residual mean square fit; the standard error of differe nces of genotype means; the correlations of genotype means with means from six-row-plot (6RP) reference trial; the expected genetic gains re lative to 6RP trial from selecting the 10 top yielding genotypes. Ther e was no significant correlation between the unadjusted genotype means for SRP and 6RP. Genotype yields were positively correlated with heig ht in SRP, but this correlation was reversed in 6RP. Using the mean he ight difference of a plot with its two neighbours as a covariate to ad just for competition in SRP reduced the standard error of difference o f genotype means and substantially increased their correlation with th e 6RP means. The predicted selection efficiency in SRP trial increased from zero, before adjustment, to 83% of 6RP trial. Including the diff erence in heading date and the effect of guards at borders as covariat es in the SRP analysis improved the residual mean square fit but had n o effect on correlation with 6RP means or selection efficiency. A prod ucer-competitor model in which individual competitor effects were esti mated for each genotype gave a substantial improvement in fit over the covariate models but a much lower correlation with 6RP means and sele ction efficiency. Yield selection in early generation wheat trials bas ed on single-row plots could be considerably strengthened by use of a plot covariate derived from height difference between neighbours.