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Genetic Divergence in T. Aman Rice

J K Nath
Department of Genetics and Plant Breeding, Bangabandhu Sheikh Mujibur Rahman Agricultural University (BSMRAU). Gazipur

U Sarker
Department of Genetics and Plant Breeding, Bangabandhu Sheikh Mujibur Rahman Agricultural University (BSMRAU). Gazipur

M A K Mian
Department of Genetics and Plant Breeding, Bangabandhu Sheikh Mujibur Rahman Agricultural University (BSMRAU). Gazipur

T Hlossain
Department of Crop Botany. BSMRAU. Gazipur

Abstract/ Executive Summary:

Genetic divergence analysis through principal component analysis ( PCA ), principal coordinate analysis (PCO), and canonical variate analysis (CVA) were clone on 32 T. A man rice genotype. As per PCA. D²and cluster analysis the genotypes grouped into five different clusters. PCA showed 90.64% variation against first three eigen value. The highest number of genotype were observed in cluster II. Cluster I and Ill each contained five genotype while IV and V contained six and seven genotypes respectively. Genotypes belonging to cluster I was far diverged from those of cluster II due to high inter-cluster distance. Plant height, days to flowering, days to maturity. tillers per hill, panicles per hill, primary branches per panicle, filled grain per plant and 1000-grain weight contributed maximum towards genetic divergence. Considering genetic diversity Doirgura, Hatisail, BRRI dhan38 and BRRI dhan34 might be selected as promising genotypes for future hybridization program.

Keywords: T. Aman rice, Genetic divergence, Statistics, Cluster

Location: Gazipur

Start Date: 12-06-2003

End Date: 23-12-2003

Program Area: Variety and Species

Commodity: Rice

Objectives:

To search suitable diverse genotype for the utilization in hybrid program and to find out selection criteria for high yielding and local rice varieties to assess the contribution of the different traits towards divergence.

Methodology:

The study was conducted at the experimental farm of Bangabandhu Sheikh Mujibur Rahman Agricultural University (BSMRAU), Gazipur, during June 2003 to December 2003. Thirty-two genotypes collected from Genetic Resource and Seed Di vision (GRS) of Bangladesh Rice Research Institute (BRRI)and the Department of Agronomy, BSMRAU were grown in randomized complete block design (RCBD) with three replications. . Data were collected from 10 randomly selected hills of each genotype on plant height, tillers/hill, panicles/ hill , primary branches/panicle, filled grains/plant , panicle length, panicle weight, spikelet sterility percentage, 1000 grain weight, harvest index and grain yield/plant. Protein content of grain were measured in the laboratory by measuring nitrogen through microkjeldahl method and then multiplied by factor (6.25) to convert it into protein. Mean data for each character was subjected to multivariate analysis. Viz., principal component analysis (PCA), principal coordinate analysis ( PCO), canonical variate analysis (CYA) and cluster analysis using GENSTAT 5.13 software program

Source of Information: Ann. Ballgladesh agric. (2008) 12( 1 ): 51-60

Article Link (Online Journal):

Funding Source:

Total Budget (Tk.) :

Achievement/Findings:

In the principal component analysis the eigen values were found as 90.64% in first three components and it was 75% in the first two components of the total variance. The genotypes of cluster T could be selected for earliest maturity, higher number of primary branches per panicle and high protein content and the lowest spikelet sterility percentage. The genotype cluster II could be selected for the highest number of filled grains per panicle and grain yield per plant. The genotypes of cluster III could be selected for the lowest plant height and days to flowering and the highest 1000-grain weight. The genotypes of cluster IV could be selected for the highest number of tillers per panicle, panicles per hill and panicle length. The genotypes of cluster V could be selected for the highest panicle weight, moderate protein content, and the highest harvest index. Therefore, these genotypes belonging to different clusters with high or moderate genetic distance might be recommended for use in future hybridization program.

Knowledge Management: Journal