INCOMPLETE BLOCK-DESIGNS FOR GENETIC TESTING - STATISTICAL EFFICIENCIES OF ESTIMATING FAMILY MEANS

A half-sib progeny trial with single-tree plots on one test site of va rious environmental Variations is simulated to examine the relative st atistical efficiencies of randomized incomplete block designs (ICBs) o ver their corresponding randomized complete block design (RCB) in esti mating family means. The TCBs with full constraint (FC), half constrai nt (HC), and no constraint (NC) over replicates and an alpha design (A lpha) are considered. A geostatistical spatial model is employed, whic h allows specifications of patchy and systematic environmental variati ons across the test site and estimations of block and error components with SAS PROC MIXED. The simulation shows that Alpha is the most effi cient ICB in the 21 scenarios of patchy and systematic site variations , followed by NC and HC, and these ICBs (except FC) are generally more efficient than RCB in terms of the average Variance of a family mean contrast. The gains in statistical efficiencies with implementations o f Alpha and NC (rather than RCB) in forest genetic testing can be high , depending largely on the nature (and level) of spatial environmental variation. Practical implications of these simulated results for fore st genetic trials are discussed.