Capturing genetic variability and identification of promising drought-tolerant lines in exotic landrace derived population under reproductive drought stress in rice

Drought is one of the most predominant abiotic stresses in this century, leading to a drastic reduction in the yield of rainfed rice ecosystems. Breeding of drought-resilient rice varieties is very much in demand for sustainable rice production in drought-prone rainfed ecology. An experiment was des...

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Autores principales: Venkateshwarlu, Challa, Kole, Paresh Chandra, Paul, Pronob J., Singh, Arun Kumar, Singh, Vikas Kumar, Kumar, Arvind
Formato: Journal Article
Lenguaje:Inglés
Publicado: Frontiers Media 2022
Materias:
Acceso en línea:https://hdl.handle.net/10568/126341
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author Venkateshwarlu, Challa
Kole, Paresh Chandra
Paul, Pronob J.
Singh, Arun Kumar
Singh, Vikas Kumar
Kumar, Arvind
author_browse Kole, Paresh Chandra
Kumar, Arvind
Paul, Pronob J.
Singh, Arun Kumar
Singh, Vikas Kumar
Venkateshwarlu, Challa
author_facet Venkateshwarlu, Challa
Kole, Paresh Chandra
Paul, Pronob J.
Singh, Arun Kumar
Singh, Vikas Kumar
Kumar, Arvind
author_sort Venkateshwarlu, Challa
collection Repository of Agricultural Research Outputs (CGSpace)
description Drought is one of the most predominant abiotic stresses in this century, leading to a drastic reduction in the yield of rainfed rice ecosystems. Breeding of drought-resilient rice varieties is very much in demand for sustainable rice production in drought-prone rainfed ecology. An experiment was designed under irrigated non-stress and drought-stress situations involving an exotic drought-tolerant landrace (Chao Khaw) and a high-yielding aromatic rice cultivar (Kasturi), and an F2:4 derived population of 156 breeding lines was developed at IRRI South Asia Hub, Hyderabad. The objective of the study was to assess the genetic variability, drought tolerance behavior, and identify promising breeding lines for different rice ecologies and drought breeding programs. Restricted maximum likelihood (REML) analysis using the mixed model approach revealed a considerable genetic variation in the population for yield and yield contributing traits in non-stress and drought-stress conditions. We observed very high heritability for all the selected traits under stress 2015 WS (73.8% to 85.3%) and 2016 WS (72.4% to 93.5%) and non-stress 2015 WS (68.2% To 92.9%) and 2016 WS (61.4% to 92.6%) environments, indicating possible selection for grain yield under drought stress and non-stress with the same precision level. None of the secondary traits except harvest index and biomass included in our study showed a positive association with grain yield, indicating indirect selection’s ineffectiveness in improving yield under drought. A total of 48 promising breeding lines were found to have a better yield than donor Chao Khaw (up to 38% advantage) and popular drought-tolerant cultivars Shabhagidhan (up to 48% advantage) in stress conditions and recommended for rainfed upland ecology, 34 breeding lines under the well-watered condition suited for rainfed lowland ecology. Overall, the study found 21 common breeding lines that showed their superiority in non-stress and under drought stress situations, fitting best in rainfed lowland ecology with occasional drought occurrence. The large genetic variation found in this population can be exploited further to develop a few forward breeding high-yielding lines with better drought tolerance ability and used as drought donors in drought breeding programs.
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spelling CGSpace1263412025-12-08T10:29:22Z Capturing genetic variability and identification of promising drought-tolerant lines in exotic landrace derived population under reproductive drought stress in rice Venkateshwarlu, Challa Kole, Paresh Chandra Paul, Pronob J. Singh, Arun Kumar Singh, Vikas Kumar Kumar, Arvind drought tolerance abiotic stress varieties ecology rice Drought is one of the most predominant abiotic stresses in this century, leading to a drastic reduction in the yield of rainfed rice ecosystems. Breeding of drought-resilient rice varieties is very much in demand for sustainable rice production in drought-prone rainfed ecology. An experiment was designed under irrigated non-stress and drought-stress situations involving an exotic drought-tolerant landrace (Chao Khaw) and a high-yielding aromatic rice cultivar (Kasturi), and an F2:4 derived population of 156 breeding lines was developed at IRRI South Asia Hub, Hyderabad. The objective of the study was to assess the genetic variability, drought tolerance behavior, and identify promising breeding lines for different rice ecologies and drought breeding programs. Restricted maximum likelihood (REML) analysis using the mixed model approach revealed a considerable genetic variation in the population for yield and yield contributing traits in non-stress and drought-stress conditions. We observed very high heritability for all the selected traits under stress 2015 WS (73.8% to 85.3%) and 2016 WS (72.4% to 93.5%) and non-stress 2015 WS (68.2% To 92.9%) and 2016 WS (61.4% to 92.6%) environments, indicating possible selection for grain yield under drought stress and non-stress with the same precision level. None of the secondary traits except harvest index and biomass included in our study showed a positive association with grain yield, indicating indirect selection’s ineffectiveness in improving yield under drought. A total of 48 promising breeding lines were found to have a better yield than donor Chao Khaw (up to 38% advantage) and popular drought-tolerant cultivars Shabhagidhan (up to 48% advantage) in stress conditions and recommended for rainfed upland ecology, 34 breeding lines under the well-watered condition suited for rainfed lowland ecology. Overall, the study found 21 common breeding lines that showed their superiority in non-stress and under drought stress situations, fitting best in rainfed lowland ecology with occasional drought occurrence. The large genetic variation found in this population can be exploited further to develop a few forward breeding high-yielding lines with better drought tolerance ability and used as drought donors in drought breeding programs. 2022-02-14 2022-12-27T14:53:49Z 2022-12-27T14:53:49Z Journal Article https://hdl.handle.net/10568/126341 en Open Access application/pdf Frontiers Media Venkateshwarlu, Challa, Paresh Chandra Kole, Pronob J. Paul, Arun Kumar Singh, Vikas Kumar Singh, and Arvind Kumar. "Capturing Genetic Variability and Identification of Promising Drought-Tolerant Lines in Exotic Landrace Derived Population Under Reproductive Drought Stress in Rice." Frontiers in plant science 13 (2022): 814774-814774.
spellingShingle drought tolerance
abiotic stress
varieties
ecology
rice
Venkateshwarlu, Challa
Kole, Paresh Chandra
Paul, Pronob J.
Singh, Arun Kumar
Singh, Vikas Kumar
Kumar, Arvind
Capturing genetic variability and identification of promising drought-tolerant lines in exotic landrace derived population under reproductive drought stress in rice
title Capturing genetic variability and identification of promising drought-tolerant lines in exotic landrace derived population under reproductive drought stress in rice
title_full Capturing genetic variability and identification of promising drought-tolerant lines in exotic landrace derived population under reproductive drought stress in rice
title_fullStr Capturing genetic variability and identification of promising drought-tolerant lines in exotic landrace derived population under reproductive drought stress in rice
title_full_unstemmed Capturing genetic variability and identification of promising drought-tolerant lines in exotic landrace derived population under reproductive drought stress in rice
title_short Capturing genetic variability and identification of promising drought-tolerant lines in exotic landrace derived population under reproductive drought stress in rice
title_sort capturing genetic variability and identification of promising drought tolerant lines in exotic landrace derived population under reproductive drought stress in rice
topic drought tolerance
abiotic stress
varieties
ecology
rice
url https://hdl.handle.net/10568/126341
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