Quality assessment and variability estimation in rice landraces

An experiment was conducted with 188 rice landraces to analyze the genetic variability and quality assessment using yield and quality attributing traits at seed breeding farm, JNKVV, Jabalpur,MP. A significant amount of genetic variability was observed for the traits like number of spikelets per panicle, fertile spikelet per panicle, thousand grain weight, days to 50% flowering and grain length with higher genotypic coefficient of variation (GCV) and phenotypic coefficient of variation (PCV) values. Higher values of heritability and genetic advance among these traits suggested prevalence of the additive gene action. The quality analysis of rice articulated that genotypes, such as Palhakilal tendina, Srikarhi, Veerbhan mangal, Kordhan-7, Bhaidanu, Jhullar, Vrai boota, Hanskanakhad, Kalajeera Shankar, Rajbhog, Assam Koti, Khardana 8, Vishnubhog- 1 were identified as good quality genotypes which can be utilized in formulating breeding programs for the development of new rice varieties with good quality traits.

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Publication Details

Journal
ORYZA- An International Journal on Rice
Published
2024-12-31
DOI
https://doi.org/10.35709/ory.2024.61.4.1
Primary Topic
Rice Cultivation and Yield Improvement
Type
article
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article

Quality assessment and variability estimation in rice landraces

Sharad Tiwari, Yogendra Singh, DR Pani, Sanjay K. Singh et al.
ORYZA- An International Journal on Rice
Rice Cultivation and Yield Improvement
article

Quality assessment and variability estimation in rice landraces

Sharad Tiwari, Yogendra Singh, DR Pani, Sanjay K. Singh, Ravi Gautam
article en

Abstract

An experiment was conducted with 188 rice landraces to analyze the genetic variability and quality assessment using yield and quality attributing traits at seed breeding farm, JNKVV, Jabalpur,MP. A significant amount of genetic variability was observed for the traits like number of spikelets per panicle, fertile spikelet per panicle, thousand grain weight, days to 50% flowering and grain length with higher genotypic coefficient of variation (GCV) and phenotypic coefficient of variation (PCV) values. Higher values of heritability and genetic advance among these traits suggested prevalence of the additive gene action. The quality analysis of rice articulated that genotypes, such as Palhakilal tendina, Srikarhi, Veerbhan mangal, Kordhan-7, Bhaidanu, Jhullar, Vrai boota, Hanskanakhad, Kalajeera Shankar, Rajbhog, Assam Koti, Khardana 8, Vishnubhog- 1 were identified as good quality genotypes which can be utilized in formulating breeding programs for the development of new rice varieties with good quality traits.

ORYZA- An International Journal on RiceVol. 61(4)
Jawaharlal Nehru Krishi Vishwa Vidyalaya (IN), ICAR-National Bureau Of Plant Genetic Resources (IN)
Openalex Percentile: Top 85%
Rice Cultivation and Yield Improvement
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Quality assessment and variability estimation in rice landraces — Sharad Tiwari, Yogendra Singh, et al. · ORYZA- An International Journal on Rice (2024) | TGRS Research Map | TGRS