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Optimal Replication in Selection Experiments

Soil, Crop and Atmospheric Sciences, Cornell University, Ithaca, NY 14853-1901
USDA-ARS-NAA, 1017 Bradfield Hall, Ithaca, NY 14853-1901

^* Corresponding author (hgg1{at}cornell.edu).

The efficiency and selection gain of yield trial experiments is affected by experimental design. A larger number of genotypes, G, increases the chances of including markedly superior genotypes, and a larger number of replications, R, reduces errors and thereby increases the chances of correctly identifying truly superior material. But assuming that cost rises approximately as the number of plots GR, containing research cost imposes a tradeoff between G and R. This paper gives tables specifying the number of replications that optimizes selection of genotypes with the highest true yields. It also quantifies the impact of suboptimal choices. Even with an optimal level of replication, the value of a selection experiment rises logarithmically with the number of plots and hence the cost. Since benefits from more data follow this severe law of diminishing returns, statistical strategies for decreasing errors and improving selections are quite important.

Received for publication March 3, 1995.

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