Statistical significance, selection accuracy, and experimental precision in plant breeding
Marcos Deon Vilela de Resende, Rodrigo Silva Alves
Abstract
We show there is a link between the two and both may be used. We derive equations for accuracy in multi-environment trials and determine numbers of repetitions and environments to reach accuracy. We propose a new methodology for accuracy classification based on p-values. This enables a better understanding of the level of accuracy being accepted when certain p-value is used. Accuracy of 90% is associated with p-value of 2%. Use of p-values up to 20% (accuracies above 50%) are acceptable to verify significance of genetic effects. Sample sizes for desired p-values are found via accuracy values.
Topics & Concepts
Selection (genetic algorithm)StatisticsVariance (accounting)Accuracy and precisionValue (mathematics)Sample size determinationComputer scienceBiologyMathematicsArtificial intelligenceBusinessAccountingGenetics and Plant BreedingGenetic and phenotypic traits in livestockGenetic Mapping and Diversity in Plants and Animals