Genetic Variability Assessment in Lowland Rice Cultivars of Bihar, India

Kushwaha, Nitesh and Kant, Ravi and Kumar, Rajesh and ., Nilanjaya and Singh, Digvijay and Chhaya, Ruchika and Sinha, Naincy and Mohanty, Tushar Arun (2020) Genetic Variability Assessment in Lowland Rice Cultivars of Bihar, India. Current Journal of Applied Science and Technology, 39 (26). pp. 39-46. ISSN 2457-1024

[thumbnail of Kushwaha39262020CJAST60095.pdf] Text
Kushwaha39262020CJAST60095.pdf - Published Version

Download (228kB)

Abstract

The present investigation for various genetic parameters was done for twenty-two lowland rice genotypes in R.C.B.D. with three replications at Rice Breeding Section, Pusa Farm, Dr. Rajendra Prasad Central Agricultural University, Pusa, Samastipur, Bihar. Analysis of variance revealed significant differences (P-value =0.01) among genotypes for all the characters. Brasali was the highest yielder suggesting that it can be used for crossing programme for improvement in yield. The phenotypic variance was higher than corresponding genotypic variances for all the characters studied. Genotypic coefficient of variation (GCV) and phenotypic coefficient of variation (PCV) were highest for grain yield per plant followed by1000 grain weight, plant height, number of panicles, root volume, leaf length and days to 50 % flowering revealing that sufficient variability was present in the gene pool for these characters. Thus, there is ample scope for genetic improvement of these traits through selection. The broad sense heritability ranged from 23 % (panicle length of main axis) to 97% (1000 grain weight). High heritability was obtained for most of the characters except for panicle length of main axis and kernel width. High heritability accompanied with high genetic advance as percent of mean was recorded for days to 50% flowering, plant height, root volume, number of panicles, 1000 grain weight, leaf length and grain yield per plant. High values of GCV, PCV, heritability and genetic advance as percent of mean observed for various characters indicate that these traits can be used as selection indices for yield improvement.

Item Type: Article
Subjects: Research Scholar Guardian > Multidisciplinary
Depositing User: Unnamed user with email support@scholarguardian.com
Date Deposited: 12 Apr 2023 07:35
Last Modified: 23 Feb 2024 03:44
URI: http://science.sdpublishers.org/id/eprint/315

Actions (login required)

View Item
View Item