A Novel Statistical Approach to Analyze Genetic Resource Evaluations Using Capsicum as an Example

A novel statistical method is presented that allows quantitative and qualitative data to be combined for statistical analysis. Developing core subsets to increase the utilization and accessibility of germplasm resources is an important application of the method. Our objective was to determine if the normed binary scale statistical method would assist in identifying dissimilar accessions. Morphological characters that would be taken in field evaluations of Capsicum germplasm are used to illustrate the method. By combining both qualitative and quantitative data, one data set can be analyzed for dissimilarities among accessions. In addition, this method of analysis allows for the bounds of the limits to be reestablished if new trait limits are discovered. This method is applicable to any crop where quantitative and qualitative data has been collected.