Combining Ability and Gene Action Studies for Grain Yield and Yield Contributing Traits in Wheat (Triticum aestivum L.)

Ingle, N.P.; Wadikar, P. B.; Salunke, P.M.

doi:10.20546/ijcmas.2018.708.279

Cited by 4 publications

(6 citation statements)

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“…For grain yield, the F2 populations i.e., IBWSN-131 × Pakhtunkhwa-15, IBWSN-131 × Shahkar-13, and PR107 × Shahkar-13, while for harvest index the F2 population IBWSN-131 × Pakhtunkhwa-15 and line PR-107 were identified as best specific and general combiners, respectively which performed better for grain yield and harvest index. In earlier studies, grain yield was primarily affected by tillers, spike traits, and seed index in wheat (Istipliler et al, 2015;Ingle et al, 2018). In previous studies, sizeable variations were exhibited by F1 and F2 populations and showed increased grain yield than parental genotypes in wheat (Abro et al, 2016;Afridi et al, 2019).…”

Section: Discussionmentioning

confidence: 91%

“…Past studies revealed that variations due to GCA and SCA and their ratio showed dominant gene action for the majority of the traits in wheat (Hei et al, 2015;Murugan and Kannan, 2017;Saeed and Khalil, 2017). The ratios of genetic differences owing to GCA to SCA indicated that the legacy of the majority of variables was managed by dominant gene action in wheat (Ingle et al, 2018;Younas et al, 2020). However, some studies revealed that earliness and production traits were controlled by additive gene action in wheat (Ljubicic et al, 2014;Mandal and Madhuri, 2016;Adhikari et al, 2020).…”

Section: Discussionmentioning

confidence: 99%

“…Past research enunciated that grain yield and its component traits were controlled by additive gene action in wheat (Ismail 2015;Khiabani et al, 2015;Kandil et al, 2016;Rahul, 2017;Adhikari et al, 2020). However, some investigations revealed that morphological, maturity, and yield variables were managed by dominant gene action in wheat (Ingle et al, 2018;Sattar et al, 2018;Sharma et al, 2019;Ayoob, 2020).…”

Section: Introductionmentioning

confidence: 99%

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Benthic Macroinvertebrates and Physicochemical Variables of Streams in the Guli River National Wetland Park, Greater Khingan Mountains, Northeast China

2020

THE JAPS

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In the current breeding program, the development of new wheat genotypes with greater genetic potential has become an enduring target to assist in food security. Wheat breeders are also trying to develop such genotypes that can fetch maximum return with limiting resources. Line-by-tester combining ability analysis was carried out during 2015-2018 to determine the genetic divergence, general and specific combining ability (GCA and SCA) among lines, testers, and line by tester interactions, and legacy of agronomic traits in wheat. Six wheat lines i.e., IBWSN-177, IBWSN-52, IBWSN-131, SRN-09111, PR-107, and NR-21, and three testers i.e., Pirsabak-15, Shahkar-13, and Pakhtunkhwa-15 were crossed in a line by tester mating fashion. After advancing the generation, eighteen F2 populations and nine parental genotypes were grown in a randomized complete block design with three replications and assessed through line by tester combining ability. Analysis of variance revealed significant (p≤0.01) variations among genotypes (parental cultivars and F2 populations) for the studied traits. According to combining ability analysis, lines revealed significant (p≤0.01) variances for days to heading and harvest index, while merely significant (p≤0.05) for plant height and flag leaf area. However, line by tester interactions revealed significant (p≤0.01) differences for all the variables. Parental genotypes IBWSN-131, Shahkar-13, and F2 populations IBWSN-131 × Pakhtunkhwa-15, IBWSN-131 × Shahkar-13, and PR107 × Shahkar-13 were identified as promising general and specific combiners which performed better for earliness and yield traits. High by high, high by low and low by high general combiners were involved in F2 populations with promising SCA and best mean performance. In comparative involvement to the total variance, the lines and L × T F2 populations had a maximum share for the majority of the traits. Ratios of GCA to SCA variances and degree of dominance revealed that all the traits were managed by dominant gene action. Non-additive gene action suggested that selection of promising populations should be postponed to later segregating generations for further improvement.

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Section: Discussionmentioning

confidence: 91%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Benthic Macroinvertebrates and Physicochemical Variables of Streams in the Guli River National Wetland Park, Greater Khingan Mountains, Northeast China

2020

THE JAPS

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“…Enhancing these yield-contributing qualities will increase wheat's overall grain yield (Ingle et al, 2018). The resulting F 1 individuals displayed more grain than their progeny, which is noteworthy given the variations between the parental genotypes and their F 1 hybrids (Jatav et al, 2014).…”

Section: Discussionmentioning

confidence: 99%

“…However, other studies revealed that the additive gene effect governed traits linked to earliness and yield (Mandal and Madhuri, 2016). Selection should take time to a later generation because genetic changes caused by GCA and SCA showed that the dominance gene effect regulates the inheritance of numerous factors (Ingle et al, 2018).…”

Section: Discussionmentioning

confidence: 99%

Genetic Analysis for Production Traits in Wheat Using Line X Tester Combining Ability Analysis

RAUF¹,

KHAN²,

JAN³

et al. 2023

SABRAOJBG

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The knowledge of genetic variability, combining capability, and gene activity are vital in enhancing wheat productivity. Six diverse wheat genotypes, Anmol91, Fatehjung16, Khattakwal, Auqab2000, PR128, Abaseen 2021, and KT06, crossed with three strip rust-resistant wheat lines, i.e., YR5, YR10, and YR15, employed line × tester hybridization. The analysis determined that the general combining ability (GCA) and specific combining ability (SCA) variances were significantly different for examined parameters (p < 0.05). Parental lines Auqab2000 and Fatehjung16 emerged as better general combiners for earliness and yield-related attributes; however, Auqab2000 × YR5, KT06 × YR5, Khattakwal × YR10, PR128 × YR5, Khattakwal × Auqab, and KT06 × YR10, proved the top particular cross combinations for contributing features of grain yield per plant. Results also showed that lines import sufficient variety to manifest the traits under investigation. For almost all tested qualities, the value of σ2gca/ σ2sca demonstrated a non-additive gene effect, except for days to maturity, which the additive gene action influenced. The selection of superior plants should take time until later segregation generation when non-additive gene activities dominate. The genotypes chosen for the current study are crucial genetic resources for wheat’s continued gene development.

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Gene Effect Analysis for Grain Yield, Yield Components and Physiological Characters in Bread Wheat Under Water Limited Conditions of Bundelkhand Region

Saini,

Kumar,

Supriya

et al. 2023

IJBSM

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The present study was conducted during rabi, 2019-20 and 2020-21 with 08 bread wheat diverse parents and their 28 F1s (half diallel, excluding reciprocals) to study gene effects and heterosis for grain yield, yield attributes and physiological traits. Days to heading and days to maturity had general mean values of 89.8 days and 130.4 days, respectively. The parent GW 322 showed early heading in 88 days, while the genotype DBW 110 exhibited early maturity in 128 days. The hybrid NW 5054×PBW 723 (13.45 cm) had the highest spike length, followed by HD 3086×NW 5054 (13.40 cm) and PBW 723×NIAW 34 (13.25 cm). The grain yield per plant ranged from 17.37 g to 21.85 g in parents and 14.99 g to 23.41 g among hybrids. The cross HD 3086×K 1006 (23.41 g) and the parent HD 3086 (21.85 g) depicted the highest grain yield per plant. The parent NIAW 34 and the hybrid HD 3086×NIAW 34 showed the highest chlorophyll fluorescence. All three key physiological traits showed significant and positive associations with grain yield and harvest index. All the seventeen characters showed high GCA effects than SCA effects and indicated for preponderance of additive gene effects for yield, its components and physiological traits. An appraisal of GCA effects found that HD 3086 was a good general combiner for the majority of characters, while the crosses, HI 1544×NIAW 34, HI 1544×GW 322 and NW5054×PBW723 with significant SCA effects were found promising under water limited conditions of Bundelkhand region.

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Combining Ability and Gene Action Studies for Grain Yield and Yield Contributing Traits in Wheat (Triticum aestivum L.)

Cited by 4 publications

References 2 publications

Benthic Macroinvertebrates and Physicochemical Variables of Streams in the Guli River National Wetland Park, Greater Khingan Mountains, Northeast China

Benthic Macroinvertebrates and Physicochemical Variables of Streams in the Guli River National Wetland Park, Greater Khingan Mountains, Northeast China

Genetic Analysis for Production Traits in Wheat Using Line X Tester Combining Ability Analysis

Gene Effect Analysis for Grain Yield, Yield Components and Physiological Characters in Bread Wheat Under Water Limited Conditions of Bundelkhand Region

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