Genetic diversity of wheat grain quality and determination the best clustering technique and data type for diversity assessment
Wheat is an important staple in human nutrition and improvement of its grain quality characters will have high impact on population's health. The objectives of this study were assessing variation of some grain quality characteristics in the Iranian wheat genotypes and identify the best type of data and clustering method for grouping genotypes. In this study 30 spring wheat genotypes were cultivated through randomized complete block design with three replications in 2009 and 2010 years. High significant difference among genotypes for all traits except for Sulfate, K, Br and Cl content, also deference among two years mean for all traits were no significant. Meanwhile there were significant interaction between year and genotype for all traits except Sulfate and F content. Mean values for crude protein, Zn, Fe and Ca in Mahdavi, Falat, Star, Sistan genotypes were the highest. The Ca and Br content showed the highest and the lowest broadcast heritability respectively. In this study indicated that the Root Mean Square Standard Deviation is efficient than R Squared and R Squared efficient than Semi Partial R Squared criteria for determining the best clustering technique. Also Ward method and canonical scores identified as the best clustering method and data type for grouping genotypes, respectively. Genotypes were grouped into six completely separate clusters and Roshan, Niknejad and Star genotypes from the fourth, fifth and sixth clusters had high grain quality characters in overall.