Study of genetic variation and determination of effective traits on forage yield in Poa prathensis populations collected from Zanjan province / IRAN

Document Type : Research Paper

Authors

1 Agriculture and Natural Resources Research Center of Zanjan province

2 University of Zanjan.

3 Research Institute of Forests and Rangelands, Tehran, Iran.

Abstract

In order to study the genetic variation among Poa prathensis populations collected from Zanjan province, an experiment was conducted in Agricultural and Natural Resources Research Center of Zanjan during years 1382 and 1383. Seedlings of 10 genotypes were transplanted in the field using a completely randomized design with four replications. Each row plot was consisted of four spaced plants. Forage dry matter yield, ear emergence date, stem height, leaf length, leaf width, basal cover and etc. were recorded. Data was analysed using analysis of variance, combined and seperately for each year, principal components analysis and cluster analyses.
Analysis of variance showed significant differences among populations for all of the characters, indicating genetic variation in Poa prathensis populations collected from the Zanjan province. Using principal components analysis, the first three components determined 88.3% of the total variation. Ear emergence date, pollination date, seed maturity date and seed weight with positive sign and stem number with negative sign were the most important traits in first components. Flag leaf length, leaf weight and spike length were the important traits in second component and in third component, leaf width, canopy and flag leaf distance were the important traits. The 10 populations were grouped into 4 clusters based on multivariate analysis of 19 classification variables. Population in cluster 1 averaged well above the plant height and leaf ength. In cluster 2 that had high ratio of leaf to stem and the most canopy populations.The populations in cluster 3 had average forage yield. Finally, principal component analysis was in agreement with cluster analysis.

Keywords


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