SPATIAL-ANALYSIS IMPROVES PRECISION OF SEED LOT COMPARISONS

Spatial analysis, by least squares smoothing, was compared with random ized block analysis of data from held trials of 50 seed lots of spring wheat (Triticum aestivum L, cv. Katepwa) and of 40 seed lots of sprin g barley (Hordeum vulgare L. cv, Harrington). Spatial analysis reduced standard errors (SED) of differences for grain yield, but not for sta nd density. For grain yield, least squares smoothing reduced the SED b y 11 to 53% in four spring wheat trials and by 24 to 34% in three spri ng barley trials. Improved precision is expected to affect correlation s between trials. For spring wheat, the inter-trial correlation increa sed from 0.40 to 0.60 in one trial, from 0.03 to 0.41 in another, and had little effect in the remaining four of six pairs of wheat trials. For barley yield, the inter-trial correlation increased from 0.25 to 0 .36 in one of three pairs of trials, and decreased from 0.28 to - 0.06 or from 0.22 to -0.05 in the other two. In the spring wheat trial wit h largest spatial variability, least squares smoothing, first-order au toregressive residuals, and the iterated Papadakis' methods gave simil ar reductions in SED (53-63%) and adjusted means that were highly corr elated (r > 0.94). Row-column analysis gave little reduction in the SE D, A multiplicative model reduced the SED, but adjusted means were poo rly correlated with those of other methods (r < 0.78). Simulation show ed that an incomplete block analysis could have provided nearly the sa me improvement in precision as spatial analysis, Our results confirm t hat spatial or incomplete block analyses can improve the efficiency of field trials.