Agricultural Research Management Information System

Home
Research Summary
Search
About Us
- ARMIS
- Brochure
Contact Us
Report
User Request
Data Input
Help
- Operation Manual
  - PDF
  - Video
- Program Area & Commodity
We have reached 37600 number of research entries at this moment.

- Logout

Research Detail

Home
Research
Detail

Morpho-genetic Evaluation of Rice Genotypes (oryza Sativa L.) Including Some Varieties and Advanced Lines Based on Yield and Its Attributes

Afsana Hannan
Department of Genetics and Plant Breeding, Bangladesh Agricultural University, Mymensingh 2202, Bangladesh

Md. Mukidul Islam
Department of Genetics and Plant Breeding, Bangladesh Agricultural University, Mymensingh 2202, Bangladesh

Muhammad Saifur Rahman
Department of Genetics and Plant Breeding, Bangladesh Agricultural University, Mymensingh 2202, Bangladesh

Md. Najmol Hoque
Department of Biochemistry and Molecular Biology, Khulna Agricultural University, Khulna-9100, Bangladesh

G H M Sagor
Department of Biochemistry and Molecular Biology, Khulna Agricultural University, Khulna-9100, Bangladesh

Abstract/ Executive Summary:

In inbreeding programs, direct selection based on yield is very difficult due to its polygenic nature. Therefore, breeders need to consider the association of numerous yield-related attributes with yield and among themselves. In this study, 43 rice genotypes including some released varieties and advanced lines were evaluated based on morpho-genetic parameters. A field experiment was conducted at the field laboratory of Genetics and Plant Breeding Department, Bangladesh Agricultural University using a randomized complete block design with three replications. Analysis of variance revealed that all genotypes exhibited significant variations (P ≤ 0.001) for all considered traits except leaf length indicating a wider extent of variability for selection. Greater phenotypic coefficient of variation (PCV) compared to corresponding genotypic coefficient of variation (GCV) for all the traits representing environmental influence on the studied traits. High GCV and PCV values were observed for the most important yield-related traits like seedling height, leaf length, flag leaf area, flag leaf angle, number of effective tiller hil^l-1, 1000-grain weight and yield plant^-1. These results suggested that selecting genotypes with these traits could be a way for attaining enhancement in rice yield. The majority of the traits displayed high heritability (>60%) with high genetic advance (>20%) pointing towards non-additive gene action suggesting selection should be practiced carefully. The correlation study explored significant positive and negative associations among yield and related attributes. The principal component analysis revealed the most important traits contributing to the variations among the genotypes. According to cluster analysis, 43 genotypes were grouped into 4 clusters among which genotypes within-cluster I and cluster III might be selected for future rice breeding programs regarding yield potentiality and other related traits.

Keywords: Rice genotypes, Yield and related traits, Genetic parameters, Diversity analysis

Location: The “Genetics and Plant breeding Field Laboratory” of Department of Genetics and Plant Breeding, Bangladesh Agricultural University

Start Date:

End Date:

Program Area: Variety and Species

Commodity: Rice

Objectives:

To evaluate a set of 43 rice genotypes based on morpho-genetic parameters with an aim to characterize these different rice accessions for providing a solid basis for selection and ultimately for the improvement of rice yield.

Methodology:

Experimental site and materials: This field experiment was performed at the “Genetics and Plant breeding Field Laboratory” of the Department of Genetics and Plant Breeding, Bangladesh Agricultural University. The experimental site was located in the sub-tropical climate zone, characterized by heavy rainfall during the months from May to September and scanty rainfall in the rest of the year. The experimental materials consisted of forty-three rice genotypes including some varieties and advanced lines and all are collected from “Genetics and Plant breeding Field Laboratory” of the Department of Genetics and Plant Breeding, Bangladesh Agricultural University.
Experimental design and plant growth: A randomized complete block design along with three replications was used for this study. Seedlings of forty-three rice genotypes were sown in raised seedbed on 20 July 2018. Seedbeds were prepared by raising the soil from the field surface to 5-10 cm above and then puddling. Transplantation to the main plot was performed when seedlings were thirty days old. One seedling was transplanted per hill for all rice genotypes. Plot size was 1m × 1m. Row to row and plant to plant distances were maintained as 20 cm and 15 cm, respectively. Maturity time varies among the genotypes. Harvesting was done at the time of 90-95% of the plant population of each plot reached maturity.
Data collection: For each genotype of each replication, five plants were chosen randomly. From them, data were taken on the selected traits. The studied yield and related attributes were seedling height (SH), leaf length (LL), leaf width (LW) leaf angle (LAN), flag leaf area (FLA), flag leaf angle (FLAN), culm length (CL), culm diameter (CD), internode length (IL), number of tiller hill^-1 (NTH), number of effective tiller hill^-1 (ETH), panicle length (PL), secondary branch in a panicle (SB/P), filled grain panicle^-1 (FG), unfilled grain panicle^-1 (UFG), grain length (GL), grain breadth (GB), grain length-breadth ratio (GL/GB), ligule length (LIL), 1000-grain weight (TGW) and yield plant^-1 (Y/P).
Statistical analysis: The collected data from 43 rice genotypes for various morphological traits related to yield were statistically analyzed by MINITAB®17 statistical software packages (Minitab Inc., State College, Pennsylvania, USA) and MSTAT computer software. Two-way Analysis of Variance (ANOVA) was performed for studied traits following a general linear model (GLM) to find out the variation among genotypes. MSTAT computer software was used for posthoc analyses. Genotypic and phenotypic variances, heritability (%), genetic advance were estimated according to the formula given by Johnson et al. (1955); GCV and PCV values were estimated according to the formula given by Burton and Devane (1953) and Singh and Chaudhury (1985); GA (%) was calculated by the formula of Comstock and Robinson (1952). Diversity analysis, i.e. principal component analysis (PCA) and cluster analysis was executed using MINITAB®17 statistical software packages. Cluster analysis was accomplished by using the average values for each trait of each genotype following the Squared Euclidean Distance method.

Source of Information: J Bangladesh Agril Univ 18(4): 923–933, 2020 Journal home page: http://baures.bau.edu.bd/jbau

Article Link (Online Journal): https://doi.org/10.5455/JBAU.9328

Funding Source:

Budget:

Total Budget (Tk.) :

Achievement/Findings:

The present study revealed the existence of sufficient genetic variability in the tested genotypes. The extent of heritability and genetic advance were moderate to high for the traits, offering more chances for advancement. Yield plant-¹ exhibited a significant positive correlation with seedling height, flag leaf area, number of tiller hill^-1, number of effective tiller hill^-1, filled grain panicle^-1, grain breadth, internode length, leaf angle, 1000-grain weight, but showed a negative correlation with grain length-breadth ratio. This result indicated that the characters positively associated with yield had an influence on increasing grain yield. Thus selection based on these traits can improve the yield performance of rice. The first two principal components from the principal component analysis described 35.5% of the total variation. Among four clusters obtained from cluster analysis, cluster I and cluster III were the most feasible for selection based on yield potentiality. This study provided genetic differences among genotypes based on yield and its attributes which might be utilized for future varietal development programs.

Knowledge Management: Journal