Abstract

Quantification and classification of diversity in germplasm collections is important for both plant breeders and germplasm curators. Distance measures between collection entries can be based on morphological or biochemical marker traits, pedigree information, or quantitative morphological traits. The objectives of this study were to group spring wheat (Triticum aestivum L.) cultivars into clusters according to their distance as measured by quantitative morphological traits, and to assess the relationship between distance based on quantitative morphological traits and distance based on coefficients of parentage. A broad collection of 289 spring wheat cultivars from the USA, Canada, and Mexico was grown in Minnesota during 1990 and 1991 and evaluated in three environments (two field and one greenhouse). A total of 35 different quantitative morphological traits were scored in one, two, or all three environments, resulting in a data set of 56 variables. This data set was reduced to 16 significant principle components (PCs) that cumulatively explained 80% of the variance. Squared Euclidean Distances based on PC‐scores were used as input for cluster analysis. All but six cultivars could be grouped into 17 major clusters. Major clusters grouped cultivars of common origin, parentage, and/or era of release. Partial agreement with the pedigree data was evident. Many clusters were recognizable across both methods from their most similar subgroups. Regression of the morphological distance on pedigree distance gave an R2 = 0.46 (P < 0.01) when the entire range of pedigree distances was sampled systematically. Quantitative morphological data provided valuable distance measures, and the quality of such measures increased with the number of traits evaluated regardless of whether selected or unselected traits were used. Combinations of distance measures based on pedigree and morphology can provide useful measures of genetic distance, but measurement of morphological traits requires considerable resources.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call