Genetic Diversity of Different Agronomic Traits in Rice Genotypes (Oryza sativa L.)

Subject Areas : Journal of Plant Ecophysiology

Nasim  Ranjkesh ¹ (Dept. of Agronomy & Crops Breeding,Faculty of Agriculture, Islamic Azad University, Chalous Branch,Chalous, Iran.)
Morteza  sam deliri ² (Dept. of Agronomy & Crops Breeding,Faculty of Agriculture, Islamic Azad University, Chalous Branch,Chalous, Iran.)
pouria  mazloum ³ (Associate prof., Islamic Azad University, Chalous Branch, Faculty of Agriculture, Dept. of Agronomy & Crops Breeding, Chalous, Iran.)
Amirabbas  mousavi ⁴ (Dept. of Agronomy & crops Breeding, Faculty of Agriculture,Islamic Azad University, Chalous Branch, Chalous, Iran)
valiollah  rameeh ⁵ (Association professor, Agronomic and Horticulture Crops Research Department, Mazandaran Agricultural and Natural Resources Research and Education Center, AREEO, Sari, Iran)

Received: 2018-11-12 Accepted : 2019-05-30 Published : 2020-09-22

Keywords: Grain yield, grouping, Quantitative traits, partial component analysis, baiplat,

Abstract :

Rice is one of the most important strategic products that is considered to be the main food of the world. In this regard, an experiment was conducted with 30 native and modified rice genotypes in a randomized complete block design at research farm of Sari University of Agricultural Sciences and Natural Resources with four replications in 2016-2017. The studied traits were plant height, length of panicles, number of effective tillers, total number of grains, number of unfilled grains, number of filled grains, 1000-grain weight, biological yield, grain yield, harvest index, chlorophyll index and growth period. The results of analysis of variance showed that genotypes have a significant difference in terms of traits, which indicates the existence of genetic variation among genotypes. The results of mean comparisons showed that the highest mean total number of grains and number of filled grains in the cluster belonged to the genotype of the Keshvari. The results of principal components analysis showed that the first five principal components accounted for 78.050% of the total variation. The cluster analysis by Unweighted Pair Group Method Arithmetic (UPGMA) method and with the euclidean distance criterion for studied traits, genotypes studied were divided into five groups.

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