Vol: 40 Page: 53

Authors:
Bogna Zawieja
Wiesław Pilarczyk
Bogna Kowalczyk

Title:
Comparison of uniformity decisions based on COYU and Bennett’s methods – simulated data

Language: English

Keywords:
Bennett's method
COYU method
DUS testing
oilseed rape
simulation
uniformity

Summary:
Uniformity decisions concerning new varieties of plants are based both on quantitative cha-racteristics and on qualitative characteristics. Decision rules for qualitative characteristics (usually “qualitative” is equivalent with “visually assessed”) are rather simple. Namely for every new variety the number of non-typical plants in a fixed sample size is counted and if it is larger than the threshold value (established by crop-experts), the variety is treated as non-uniform. More complicated procedure is applied for quantitative characteristics. Decisions are based on comparisons of standard deviation of candidate variety with average value of standard deviations of so called reference varieties. A special procedure called COYU (combined over years uniformity) was elaborated by member states of UPOV (International Union for Protection of New Varieties of Plants) for this purpose, Talbot (2000). The COYU method is – to some degree – an officially promoted method. But some other methods are still under consideration. One of such methods uses the Bennett test for coefficients of variation. The details of this new approach are given in paper by Zawieja and Pilarczyk (2005, 2006, 2007) and by Zawieja, Pilarczyk and Kowalczyk (2009). Some comparisons of uniformity decisions concerning winter wheat and oilseed rape varieties based on COYU and Bennett’s test are also included in mentioned papers. During the annual session of Technical Working Party on Automation and Computer Programs (held in Alexandria, Virginia in June 2009) it was suggested to compare decisions on uniformity of varieties using simulated data based on real measurements. So in the present paper this problem is reconsidered using real data for oilseed varieties (reference set) and simulated data (candidate varieties).

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