Spanish 
Chinese 
Russian 
German 
French 
Japanese 
Portuguese 
Hindi Determining the Level of Genotypic Variability of Different Upland Rice Genotypes via Cluster Analysis
*Corresponding Author: Gedifew Gebrie, Department of Crop Science and Technology, Pawe Agricultural Research Center, Pawe, Ethiopia Exn.946454437, Email: gebriegedifew1976@gmail.comReceived Date: Apr 14, 2022 / Published Date: Jun 20, 2022
Citation: Gebrie G, Abebe D (2022) Determining the Level of Genotypic Variability of Different Upland Rice Genotypes via Cluster Analysis, 10:527.
Copyright: 2022 Gebrie G, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Abstract
Determining the level of germplasm diversity and genetic relationships among breeding materials is an invaluable aid in crop improvement strategies with an understanding that genetic variability is the base for crop improvement providing opportunity for plant breeders to develop new and improved cultivars with desirable characteristics and it is a key to reliable and sustainable production of the food crops through breeding. It has been also confirmed that measuring the available diversity of crops is important for effective evaluation and utilization of germplasms to explore their variability so as to identify desirable agronomic attributes. For eradicating the problem of national rice production, the national rice breeding and genetics research program of the country is introducing and evaluating different rice germplasms for their environmental adaptability and agronomic performance with increasing the crops’ genetic diversity. With the same approach, 100 upland rice genotypes were introduced and evaluated using Augmented-RCBD experimental design so as to assess and determine the extent and pattern of their genetic and phenotypic variability using cluster analysis bringing them into similarity groups based on important agronomic traits. Each genotype was planted on a plot area of 2.5 m2 involving 4 rows per plot with 0.25 m spacing between each row. The seeds were drilled in rows with a seed rate of 60 kgha-1. Nitrogen Phosphorus Sulfur (NPS) and Urea fertilizers were applied in the amount of 124 kg ha-1 and 100 kgha-1 respectively. The quantitative traits such as days to 50% heading, days to 85% maturity, plant height, panicle length, number of filled grains per a panicle and number of unfilled grains per a panicle, grain yield and 1000 seed weight were measured and subjected to clustering analysis using XLSTAT 5.03 statistical software so as to determine the extent and pattern of the genetic and phenotypic variability of 97 upland rice genotypes. During clustering analysis, the genotypes were grouped into five clusters with different Euclidian distances confirming the presence of genetic and phenotypic variability among the evaluated upland rice genotypes. The genotype with the highest grain (6298 kgha-1) yield was obtained under cluster-III.
