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CROP BREEDING, GENETICS & CYTOLOGY

On-Farm Strip Trials vs. Replicated Performance Trials for Cultivar Evaluation

^a Dep. of Plant Agriculture, Univ. of Guelph, Guelph, ON, N1G 2W1, Canada
^b Cereal Lead, Ontario Ministry of Agriculture, Food, and Rural Affairs, Guelph, ON, N1G 5C9, Canada
^c Corn Lead, Ontario Ministry of Agriculture, Food, and Rural Affairs, Dep. of Plant Agriculture, Univ. of Guelph, Guelph, ON, N1G 2W1, Canada
^d Food Res. Program, Agriculture and Agri-Food Canada, Guelph, ON, N1G 5C9, Canada

* Corresponding author (wyan{at}uoguelph.ca)

A systematic comparison between two cultivar evaluation and recommendation systems, i.e., the balanced and replicated performance trials conducted in small plots at a small number of locations, and the unbalanced and non-replicated on-farm trials conducted in large strips on many farms, is lacking. This study was initiated to investigate the usefulness of the two contrasting systems in cultivar evaluation and the relationships between them. Yield data from Ontario winter wheat (Triticum aestivum L.) strip trials and performance trials for 1998 to 2000 were analyzed by mixed models. For all 3 yr, results from the two systems were highly correlated, both in terms of the best linear unbiased predictors (BLUP) and for the t-values of BLUP. Cultivars judged to be superior (or inferior) by one system were never judged to be inferior (or superior) by the other. Thus, both on-farm strip trials and replicated small-plot trials provide valid data for effective cultivar evaluation. On the basis of t-statistics, which measure cultivar reliability, cultivars can be classified into superior (t 2), inferior (t -2), and intermediate or inadequately tested (-2 < t < 2). Two cultivars can be regarded as different in reliability if their t-values differ by 3. The evaluation power of strip trials for a cultivar depends on the number of trials in which the cultivar is tested; a cultivar may not be adequately evaluated if it is tested in fewer than 20 trials.

Abbreviations: BLUP, best linear unbiased predictor

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