Phenotypic evaluation of genetic variability and selection of yield contributing traits in chickpea recombinant inbred line population under high temperature stress
Abstract Heat is a major abiotic stress that drastically reduces chickpea yield. This study aimed to identify heat-responsive traits to sustain crop productivity by screening a recombinant inbred line (RILs) population at two locations in India (Ludhiana and Faridkot). The RIL population was derived...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Kushwah, Ashutosh [verfasserIn] Bhatia, Dharminder [verfasserIn] Singh, Gurpreet [verfasserIn] Singh, Inderjit [verfasserIn] Bindra, Shayla [verfasserIn] Vij, Suruchi [verfasserIn] Singh, Sarvjeet [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2021 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: Physiology and molecular biology of plants - Neu Delhi : Springer India, 2008, 27(2021), 4 vom: Apr., Seite 747-767 |
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| Übergeordnetes Werk: |
volume:27 ; year:2021 ; number:4 ; month:04 ; pages:747-767 |
| Links: |
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| DOI / URN: |
10.1007/s12298-021-00977-5 |
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| Katalog-ID: |
SPR043804888 |
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| 520 | |a Abstract Heat is a major abiotic stress that drastically reduces chickpea yield. This study aimed to identify heat-responsive traits to sustain crop productivity by screening a recombinant inbred line (RILs) population at two locations in India (Ludhiana and Faridkot). The RIL population was derived from an inter-specific cross between heat-tolerant genotype GPF 2 (C. arietinum L.) and heat sensitive accession ILWC 292 (C. reticulatum). The pooled analysis of variance showed highly significant differences for all the traits in RILs and most of the traits were significantly affected by heat stress at both locations. High values of genotypic coefficient of variation (19.52–38.53%), phenotypic coefficient of variation (20.29–39.85%), heritability (92.50–93.90%), and genetic advance as a percentage of mean (38.68–76.74%) have been observed for plant height, number of pods per plant, biomass, yield, and hundred seed weight across the heat stress environments. Association studies and principal component analysis showed a significant positive correlation of plant height, number of pods per plant, biomass, hundred seed weight, harvest index, relative leaf water content, and pollen viability with yield under both timely-sown and late-sown conditions. Path analysis revealed that biomass followed by harvest index was the major contributor to yield among the environments. Both step-wise and multiple regression analyses concluded that number of pods per plant, biomass and harvest index consistently showed high level of contribution to the total variation in yield under both timely-sown and late-sown conditions. Thus, the holistic approach of these analyses illustrated that the promising traits provide a framework for developing heat-tolerant cultivars in chickpea. | ||
| 650 | 4 | |a Heat stress tolerance |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Association analysis |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Path coefficient analysis |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Regression analysis |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Principal component analysis |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Bhatia, Dharminder |e verfasserin |4 aut | |
| 700 | 1 | |a Singh, Gurpreet |e verfasserin |4 aut | |
| 700 | 1 | |a Singh, Inderjit |e verfasserin |4 aut | |
| 700 | 1 | |a Bindra, Shayla |e verfasserin |4 aut | |
| 700 | 1 | |a Vij, Suruchi |e verfasserin |4 aut | |
| 700 | 1 | |a Singh, Sarvjeet |e verfasserin |4 aut | |
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10.1007/s12298-021-00977-5 doi (DE-627)SPR043804888 (DE-599)SPRs12298-021-00977-5-e (SPR)s12298-021-00977-5-e DE-627 ger DE-627 rakwb eng 570 ASE Kushwah, Ashutosh verfasserin aut Phenotypic evaluation of genetic variability and selection of yield contributing traits in chickpea recombinant inbred line population under high temperature stress 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Heat is a major abiotic stress that drastically reduces chickpea yield. This study aimed to identify heat-responsive traits to sustain crop productivity by screening a recombinant inbred line (RILs) population at two locations in India (Ludhiana and Faridkot). The RIL population was derived from an inter-specific cross between heat-tolerant genotype GPF 2 (C. arietinum L.) and heat sensitive accession ILWC 292 (C. reticulatum). The pooled analysis of variance showed highly significant differences for all the traits in RILs and most of the traits were significantly affected by heat stress at both locations. High values of genotypic coefficient of variation (19.52–38.53%), phenotypic coefficient of variation (20.29–39.85%), heritability (92.50–93.90%), and genetic advance as a percentage of mean (38.68–76.74%) have been observed for plant height, number of pods per plant, biomass, yield, and hundred seed weight across the heat stress environments. Association studies and principal component analysis showed a significant positive correlation of plant height, number of pods per plant, biomass, hundred seed weight, harvest index, relative leaf water content, and pollen viability with yield under both timely-sown and late-sown conditions. Path analysis revealed that biomass followed by harvest index was the major contributor to yield among the environments. Both step-wise and multiple regression analyses concluded that number of pods per plant, biomass and harvest index consistently showed high level of contribution to the total variation in yield under both timely-sown and late-sown conditions. Thus, the holistic approach of these analyses illustrated that the promising traits provide a framework for developing heat-tolerant cultivars in chickpea. Heat stress tolerance (dpeaa)DE-He213 Association analysis (dpeaa)DE-He213 Path coefficient analysis (dpeaa)DE-He213 Regression analysis (dpeaa)DE-He213 Principal component analysis (dpeaa)DE-He213 Bhatia, Dharminder verfasserin aut Singh, Gurpreet verfasserin aut Singh, Inderjit verfasserin aut Bindra, Shayla verfasserin aut Vij, Suruchi verfasserin aut Singh, Sarvjeet verfasserin aut Enthalten in Physiology and molecular biology of plants Neu Delhi : Springer India, 2008 27(2021), 4 vom: Apr., Seite 747-767 (DE-627)595711707 (DE-600)2487126-6 0974-0430 nnns volume:27 year:2021 number:4 month:04 pages:747-767 https://dx.doi.org/10.1007/s12298-021-00977-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 27 2021 4 04 747-767 |
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10.1007/s12298-021-00977-5 doi (DE-627)SPR043804888 (DE-599)SPRs12298-021-00977-5-e (SPR)s12298-021-00977-5-e DE-627 ger DE-627 rakwb eng 570 ASE Kushwah, Ashutosh verfasserin aut Phenotypic evaluation of genetic variability and selection of yield contributing traits in chickpea recombinant inbred line population under high temperature stress 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Heat is a major abiotic stress that drastically reduces chickpea yield. This study aimed to identify heat-responsive traits to sustain crop productivity by screening a recombinant inbred line (RILs) population at two locations in India (Ludhiana and Faridkot). The RIL population was derived from an inter-specific cross between heat-tolerant genotype GPF 2 (C. arietinum L.) and heat sensitive accession ILWC 292 (C. reticulatum). The pooled analysis of variance showed highly significant differences for all the traits in RILs and most of the traits were significantly affected by heat stress at both locations. High values of genotypic coefficient of variation (19.52–38.53%), phenotypic coefficient of variation (20.29–39.85%), heritability (92.50–93.90%), and genetic advance as a percentage of mean (38.68–76.74%) have been observed for plant height, number of pods per plant, biomass, yield, and hundred seed weight across the heat stress environments. Association studies and principal component analysis showed a significant positive correlation of plant height, number of pods per plant, biomass, hundred seed weight, harvest index, relative leaf water content, and pollen viability with yield under both timely-sown and late-sown conditions. Path analysis revealed that biomass followed by harvest index was the major contributor to yield among the environments. Both step-wise and multiple regression analyses concluded that number of pods per plant, biomass and harvest index consistently showed high level of contribution to the total variation in yield under both timely-sown and late-sown conditions. Thus, the holistic approach of these analyses illustrated that the promising traits provide a framework for developing heat-tolerant cultivars in chickpea. Heat stress tolerance (dpeaa)DE-He213 Association analysis (dpeaa)DE-He213 Path coefficient analysis (dpeaa)DE-He213 Regression analysis (dpeaa)DE-He213 Principal component analysis (dpeaa)DE-He213 Bhatia, Dharminder verfasserin aut Singh, Gurpreet verfasserin aut Singh, Inderjit verfasserin aut Bindra, Shayla verfasserin aut Vij, Suruchi verfasserin aut Singh, Sarvjeet verfasserin aut Enthalten in Physiology and molecular biology of plants Neu Delhi : Springer India, 2008 27(2021), 4 vom: Apr., Seite 747-767 (DE-627)595711707 (DE-600)2487126-6 0974-0430 nnns volume:27 year:2021 number:4 month:04 pages:747-767 https://dx.doi.org/10.1007/s12298-021-00977-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 27 2021 4 04 747-767 |
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10.1007/s12298-021-00977-5 doi (DE-627)SPR043804888 (DE-599)SPRs12298-021-00977-5-e (SPR)s12298-021-00977-5-e DE-627 ger DE-627 rakwb eng 570 ASE Kushwah, Ashutosh verfasserin aut Phenotypic evaluation of genetic variability and selection of yield contributing traits in chickpea recombinant inbred line population under high temperature stress 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Heat is a major abiotic stress that drastically reduces chickpea yield. This study aimed to identify heat-responsive traits to sustain crop productivity by screening a recombinant inbred line (RILs) population at two locations in India (Ludhiana and Faridkot). The RIL population was derived from an inter-specific cross between heat-tolerant genotype GPF 2 (C. arietinum L.) and heat sensitive accession ILWC 292 (C. reticulatum). The pooled analysis of variance showed highly significant differences for all the traits in RILs and most of the traits were significantly affected by heat stress at both locations. High values of genotypic coefficient of variation (19.52–38.53%), phenotypic coefficient of variation (20.29–39.85%), heritability (92.50–93.90%), and genetic advance as a percentage of mean (38.68–76.74%) have been observed for plant height, number of pods per plant, biomass, yield, and hundred seed weight across the heat stress environments. Association studies and principal component analysis showed a significant positive correlation of plant height, number of pods per plant, biomass, hundred seed weight, harvest index, relative leaf water content, and pollen viability with yield under both timely-sown and late-sown conditions. Path analysis revealed that biomass followed by harvest index was the major contributor to yield among the environments. Both step-wise and multiple regression analyses concluded that number of pods per plant, biomass and harvest index consistently showed high level of contribution to the total variation in yield under both timely-sown and late-sown conditions. Thus, the holistic approach of these analyses illustrated that the promising traits provide a framework for developing heat-tolerant cultivars in chickpea. Heat stress tolerance (dpeaa)DE-He213 Association analysis (dpeaa)DE-He213 Path coefficient analysis (dpeaa)DE-He213 Regression analysis (dpeaa)DE-He213 Principal component analysis (dpeaa)DE-He213 Bhatia, Dharminder verfasserin aut Singh, Gurpreet verfasserin aut Singh, Inderjit verfasserin aut Bindra, Shayla verfasserin aut Vij, Suruchi verfasserin aut Singh, Sarvjeet verfasserin aut Enthalten in Physiology and molecular biology of plants Neu Delhi : Springer India, 2008 27(2021), 4 vom: Apr., Seite 747-767 (DE-627)595711707 (DE-600)2487126-6 0974-0430 nnns volume:27 year:2021 number:4 month:04 pages:747-767 https://dx.doi.org/10.1007/s12298-021-00977-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 27 2021 4 04 747-767 |
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10.1007/s12298-021-00977-5 doi (DE-627)SPR043804888 (DE-599)SPRs12298-021-00977-5-e (SPR)s12298-021-00977-5-e DE-627 ger DE-627 rakwb eng 570 ASE Kushwah, Ashutosh verfasserin aut Phenotypic evaluation of genetic variability and selection of yield contributing traits in chickpea recombinant inbred line population under high temperature stress 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Heat is a major abiotic stress that drastically reduces chickpea yield. This study aimed to identify heat-responsive traits to sustain crop productivity by screening a recombinant inbred line (RILs) population at two locations in India (Ludhiana and Faridkot). The RIL population was derived from an inter-specific cross between heat-tolerant genotype GPF 2 (C. arietinum L.) and heat sensitive accession ILWC 292 (C. reticulatum). The pooled analysis of variance showed highly significant differences for all the traits in RILs and most of the traits were significantly affected by heat stress at both locations. High values of genotypic coefficient of variation (19.52–38.53%), phenotypic coefficient of variation (20.29–39.85%), heritability (92.50–93.90%), and genetic advance as a percentage of mean (38.68–76.74%) have been observed for plant height, number of pods per plant, biomass, yield, and hundred seed weight across the heat stress environments. Association studies and principal component analysis showed a significant positive correlation of plant height, number of pods per plant, biomass, hundred seed weight, harvest index, relative leaf water content, and pollen viability with yield under both timely-sown and late-sown conditions. Path analysis revealed that biomass followed by harvest index was the major contributor to yield among the environments. Both step-wise and multiple regression analyses concluded that number of pods per plant, biomass and harvest index consistently showed high level of contribution to the total variation in yield under both timely-sown and late-sown conditions. Thus, the holistic approach of these analyses illustrated that the promising traits provide a framework for developing heat-tolerant cultivars in chickpea. Heat stress tolerance (dpeaa)DE-He213 Association analysis (dpeaa)DE-He213 Path coefficient analysis (dpeaa)DE-He213 Regression analysis (dpeaa)DE-He213 Principal component analysis (dpeaa)DE-He213 Bhatia, Dharminder verfasserin aut Singh, Gurpreet verfasserin aut Singh, Inderjit verfasserin aut Bindra, Shayla verfasserin aut Vij, Suruchi verfasserin aut Singh, Sarvjeet verfasserin aut Enthalten in Physiology and molecular biology of plants Neu Delhi : Springer India, 2008 27(2021), 4 vom: Apr., Seite 747-767 (DE-627)595711707 (DE-600)2487126-6 0974-0430 nnns volume:27 year:2021 number:4 month:04 pages:747-767 https://dx.doi.org/10.1007/s12298-021-00977-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 27 2021 4 04 747-767 |
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10.1007/s12298-021-00977-5 doi (DE-627)SPR043804888 (DE-599)SPRs12298-021-00977-5-e (SPR)s12298-021-00977-5-e DE-627 ger DE-627 rakwb eng 570 ASE Kushwah, Ashutosh verfasserin aut Phenotypic evaluation of genetic variability and selection of yield contributing traits in chickpea recombinant inbred line population under high temperature stress 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Heat is a major abiotic stress that drastically reduces chickpea yield. This study aimed to identify heat-responsive traits to sustain crop productivity by screening a recombinant inbred line (RILs) population at two locations in India (Ludhiana and Faridkot). The RIL population was derived from an inter-specific cross between heat-tolerant genotype GPF 2 (C. arietinum L.) and heat sensitive accession ILWC 292 (C. reticulatum). The pooled analysis of variance showed highly significant differences for all the traits in RILs and most of the traits were significantly affected by heat stress at both locations. High values of genotypic coefficient of variation (19.52–38.53%), phenotypic coefficient of variation (20.29–39.85%), heritability (92.50–93.90%), and genetic advance as a percentage of mean (38.68–76.74%) have been observed for plant height, number of pods per plant, biomass, yield, and hundred seed weight across the heat stress environments. Association studies and principal component analysis showed a significant positive correlation of plant height, number of pods per plant, biomass, hundred seed weight, harvest index, relative leaf water content, and pollen viability with yield under both timely-sown and late-sown conditions. Path analysis revealed that biomass followed by harvest index was the major contributor to yield among the environments. Both step-wise and multiple regression analyses concluded that number of pods per plant, biomass and harvest index consistently showed high level of contribution to the total variation in yield under both timely-sown and late-sown conditions. Thus, the holistic approach of these analyses illustrated that the promising traits provide a framework for developing heat-tolerant cultivars in chickpea. Heat stress tolerance (dpeaa)DE-He213 Association analysis (dpeaa)DE-He213 Path coefficient analysis (dpeaa)DE-He213 Regression analysis (dpeaa)DE-He213 Principal component analysis (dpeaa)DE-He213 Bhatia, Dharminder verfasserin aut Singh, Gurpreet verfasserin aut Singh, Inderjit verfasserin aut Bindra, Shayla verfasserin aut Vij, Suruchi verfasserin aut Singh, Sarvjeet verfasserin aut Enthalten in Physiology and molecular biology of plants Neu Delhi : Springer India, 2008 27(2021), 4 vom: Apr., Seite 747-767 (DE-627)595711707 (DE-600)2487126-6 0974-0430 nnns volume:27 year:2021 number:4 month:04 pages:747-767 https://dx.doi.org/10.1007/s12298-021-00977-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 27 2021 4 04 747-767 |
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Enthalten in Physiology and molecular biology of plants 27(2021), 4 vom: Apr., Seite 747-767 volume:27 year:2021 number:4 month:04 pages:747-767 |
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Enthalten in Physiology and molecular biology of plants 27(2021), 4 vom: Apr., Seite 747-767 volume:27 year:2021 number:4 month:04 pages:747-767 |
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Heat stress tolerance Association analysis Path coefficient analysis Regression analysis Principal component analysis |
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Physiology and molecular biology of plants |
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Kushwah, Ashutosh @@aut@@ Bhatia, Dharminder @@aut@@ Singh, Gurpreet @@aut@@ Singh, Inderjit @@aut@@ Bindra, Shayla @@aut@@ Vij, Suruchi @@aut@@ Singh, Sarvjeet @@aut@@ |
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Kushwah, Ashutosh |
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Kushwah, Ashutosh ddc 570 misc Heat stress tolerance misc Association analysis misc Path coefficient analysis misc Regression analysis misc Principal component analysis Phenotypic evaluation of genetic variability and selection of yield contributing traits in chickpea recombinant inbred line population under high temperature stress |
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570 ASE Phenotypic evaluation of genetic variability and selection of yield contributing traits in chickpea recombinant inbred line population under high temperature stress Heat stress tolerance (dpeaa)DE-He213 Association analysis (dpeaa)DE-He213 Path coefficient analysis (dpeaa)DE-He213 Regression analysis (dpeaa)DE-He213 Principal component analysis (dpeaa)DE-He213 |
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Phenotypic evaluation of genetic variability and selection of yield contributing traits in chickpea recombinant inbred line population under high temperature stress |
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Kushwah, Ashutosh Bhatia, Dharminder Singh, Gurpreet Singh, Inderjit Bindra, Shayla Vij, Suruchi Singh, Sarvjeet |
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phenotypic evaluation of genetic variability and selection of yield contributing traits in chickpea recombinant inbred line population under high temperature stress |
| title_auth |
Phenotypic evaluation of genetic variability and selection of yield contributing traits in chickpea recombinant inbred line population under high temperature stress |
| abstract |
Abstract Heat is a major abiotic stress that drastically reduces chickpea yield. This study aimed to identify heat-responsive traits to sustain crop productivity by screening a recombinant inbred line (RILs) population at two locations in India (Ludhiana and Faridkot). The RIL population was derived from an inter-specific cross between heat-tolerant genotype GPF 2 (C. arietinum L.) and heat sensitive accession ILWC 292 (C. reticulatum). The pooled analysis of variance showed highly significant differences for all the traits in RILs and most of the traits were significantly affected by heat stress at both locations. High values of genotypic coefficient of variation (19.52–38.53%), phenotypic coefficient of variation (20.29–39.85%), heritability (92.50–93.90%), and genetic advance as a percentage of mean (38.68–76.74%) have been observed for plant height, number of pods per plant, biomass, yield, and hundred seed weight across the heat stress environments. Association studies and principal component analysis showed a significant positive correlation of plant height, number of pods per plant, biomass, hundred seed weight, harvest index, relative leaf water content, and pollen viability with yield under both timely-sown and late-sown conditions. Path analysis revealed that biomass followed by harvest index was the major contributor to yield among the environments. Both step-wise and multiple regression analyses concluded that number of pods per plant, biomass and harvest index consistently showed high level of contribution to the total variation in yield under both timely-sown and late-sown conditions. Thus, the holistic approach of these analyses illustrated that the promising traits provide a framework for developing heat-tolerant cultivars in chickpea. |
| abstractGer |
Abstract Heat is a major abiotic stress that drastically reduces chickpea yield. This study aimed to identify heat-responsive traits to sustain crop productivity by screening a recombinant inbred line (RILs) population at two locations in India (Ludhiana and Faridkot). The RIL population was derived from an inter-specific cross between heat-tolerant genotype GPF 2 (C. arietinum L.) and heat sensitive accession ILWC 292 (C. reticulatum). The pooled analysis of variance showed highly significant differences for all the traits in RILs and most of the traits were significantly affected by heat stress at both locations. High values of genotypic coefficient of variation (19.52–38.53%), phenotypic coefficient of variation (20.29–39.85%), heritability (92.50–93.90%), and genetic advance as a percentage of mean (38.68–76.74%) have been observed for plant height, number of pods per plant, biomass, yield, and hundred seed weight across the heat stress environments. Association studies and principal component analysis showed a significant positive correlation of plant height, number of pods per plant, biomass, hundred seed weight, harvest index, relative leaf water content, and pollen viability with yield under both timely-sown and late-sown conditions. Path analysis revealed that biomass followed by harvest index was the major contributor to yield among the environments. Both step-wise and multiple regression analyses concluded that number of pods per plant, biomass and harvest index consistently showed high level of contribution to the total variation in yield under both timely-sown and late-sown conditions. Thus, the holistic approach of these analyses illustrated that the promising traits provide a framework for developing heat-tolerant cultivars in chickpea. |
| abstract_unstemmed |
Abstract Heat is a major abiotic stress that drastically reduces chickpea yield. This study aimed to identify heat-responsive traits to sustain crop productivity by screening a recombinant inbred line (RILs) population at two locations in India (Ludhiana and Faridkot). The RIL population was derived from an inter-specific cross between heat-tolerant genotype GPF 2 (C. arietinum L.) and heat sensitive accession ILWC 292 (C. reticulatum). The pooled analysis of variance showed highly significant differences for all the traits in RILs and most of the traits were significantly affected by heat stress at both locations. High values of genotypic coefficient of variation (19.52–38.53%), phenotypic coefficient of variation (20.29–39.85%), heritability (92.50–93.90%), and genetic advance as a percentage of mean (38.68–76.74%) have been observed for plant height, number of pods per plant, biomass, yield, and hundred seed weight across the heat stress environments. Association studies and principal component analysis showed a significant positive correlation of plant height, number of pods per plant, biomass, hundred seed weight, harvest index, relative leaf water content, and pollen viability with yield under both timely-sown and late-sown conditions. Path analysis revealed that biomass followed by harvest index was the major contributor to yield among the environments. Both step-wise and multiple regression analyses concluded that number of pods per plant, biomass and harvest index consistently showed high level of contribution to the total variation in yield under both timely-sown and late-sown conditions. Thus, the holistic approach of these analyses illustrated that the promising traits provide a framework for developing heat-tolerant cultivars in chickpea. |
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Phenotypic evaluation of genetic variability and selection of yield contributing traits in chickpea recombinant inbred line population under high temperature stress |
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https://dx.doi.org/10.1007/s12298-021-00977-5 |
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Bhatia, Dharminder Singh, Gurpreet Singh, Inderjit Bindra, Shayla Vij, Suruchi Singh, Sarvjeet |
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| score |
7.4016485 |