Abstract

The purpose of this research was to formulate statistical models and assumptions to apply to the problem of comparing wheat varieties for yielding ability among locations within seasons and over seasons. The methodology could just as well be applied to field testing of other crops for yield or other characteristics of interest (test weight, protein level, etc.)

The methodology approaches the problem of comparing varieties by comparing how well each "measures up" when matched against some common checks. For each variety, the basic data are differences in yield between the variety and the average yield of the checks at different testing locations within a season and over seasons. The differences are assumed to be "nature-randomized" sample values from a population of differences created by different environments within seasons and over seasons.

The methodology is illustrated by application to hard red spring wheat varieties in the U. S. N orthem Plains. Results showing varieties in descending order by differential yielding ability, together with standard errors and probabilities when testing null hypotheses, provide a consolidated summary of elite varieties in testing programs.

Keywords

varietal testing, differential yielding ability

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Apr 26th, 8:30 AM

STATISTICAL ANALYSIS OF FIELD WHEAT VARIETAL PERFORMANCE TRIALS

The purpose of this research was to formulate statistical models and assumptions to apply to the problem of comparing wheat varieties for yielding ability among locations within seasons and over seasons. The methodology could just as well be applied to field testing of other crops for yield or other characteristics of interest (test weight, protein level, etc.)

The methodology approaches the problem of comparing varieties by comparing how well each "measures up" when matched against some common checks. For each variety, the basic data are differences in yield between the variety and the average yield of the checks at different testing locations within a season and over seasons. The differences are assumed to be "nature-randomized" sample values from a population of differences created by different environments within seasons and over seasons.

The methodology is illustrated by application to hard red spring wheat varieties in the U. S. N orthem Plains. Results showing varieties in descending order by differential yielding ability, together with standard errors and probabilities when testing null hypotheses, provide a consolidated summary of elite varieties in testing programs.