Insights from gene effects on agronomic, oleic acid and oil content using generation mean analysis in sunflower (Helianthus annuus L.)
DOI:
https://doi.org/10.14719/pst.6030Keywords:
additive interactions, gene actions, GMA, oil content, oleic acid contentAbstract
Plant hybridization produces hybrids with desirable traits such as high oil content, oleic acid and yield, enhancing the significance of crops. Understanding genetic dominance is essential for studying gene action in breeding programs. Using four parental lines, this study assessed gene action, genetic advance with heritability and heterosis for oleic acid, oil content, agronomic and yield traits in sunflowers. The IR6 × HO-5-29 (P1 × P2) cross I population demonstrated superior performance, while the CMSB825B × COSF6B (P3 × P4) cross II population also performed well based on mean performance. Generation mean analysis revealed that additive and dominance gene actions influenced trait inheritance, with dominance effects being more pronounced. Additive × additive interactions played a key role in traits like days to flowering and maturity, palmitic acid content and oleic acid content in cross I and head diameter in cross II. Additive × dominance interactions significantly influenced head diameter, 100-seed weight and oleic acid content in cross I and plant height in cross II. Dominance × dominance interactions strongly influenced seed and oil yield per plant, oil content and linoleic acid content in cross I and seed and oil yield per plant and volume weight in cross II. Duplicate gene action was observed for head diameter and 100-seed weight, whereas complementary gene action was observed for seed and oil yield per plant in both crosses. These findings offer valuable insights for plant breeders and farmers, supporting the development of sunflower varieties and hybrids with enhanced oleic content, oil content and yield.
Downloads
References
USDA. Production – Sunflowerseed [intenet]. United States Department of Agriculture; 2024 [cited 2024 Sept 18]. Available from: https://fas.usda.gov/data/production/commodity/2224000
UPAg. Unified Portal for Agricultural Statistics [internet]. New Delhi:Department of Agriculture and Farmer's Welfare. 2024 [cited 2024 Sept 18]. Available from: https://upag.gov.in/
Sampath L, Sasikala R, Kalaimagal T, Santhiya V, Antony B. Genetic diversity analysis in sunflower (Helianthus annuus L.) germplasms. J Oilseeds Res; 2023,38(3):244-50. https://doi.org/10.56739/jor.v40iSpecialissue.145374
Lavudya S, Thiyagarajan K, Ramasamy S, Sankarasubramanian H, Muniyandi S, Bellie A, Kumar S, Dhanapal S. Assessing population structure and morpho-molecular characterization of sunflower (Helianthus annuus L.) for elite germplasm identification. PeerJ. 2024;12:e18205.https://doi.org/10.7717/peerj.18205
Soldatov KI. Chemical mutagenesis in sunflower breeding. In: Proc. 7th Int. Sunflower Conf., Krasnodar, USSR ;1976 Jun 27 Vlaardingen, the Netherlands: Int. Sunflower Assoc; 1976 [cited 2024 Sep 18 ]. p. 352–7). Available from: https://www.scirp.org
Cveji? S, Miladinovi? D, Joci? S. Mutation breeding for changed oil quality in sunflower. In: Tomlekova NB, Kozgar NI, Wani MR, Editors. Mutagenesis: exploring genetic diversity of crops. Leiden, The Netherlands: Wageningen Academic 2014. p. 77-96. https://doi.org/10.3920/9789086867967_006
Premnath A, Narayana M, Ramakrishnan C, Kuppusamy S, Chockalingam V. Mapping quantitative trait loci controlling oil content, oleic acid and linoleic acid content in sunflower (Helianthus annuus L.). Mol Breed. 2016;36:1-7. https://doi.org/10.1007/s11032-016-0527-2
Vannozzi GP. The perspectives of use of high oleic sunflower for oleochemistry and energy raws/perspectivas en la utilización de girasol de alto contenido oleico en la industria de procesamiento y como materia prima para la producción de energía/perspectives de l’utilisation du tournesol à haute teneur oléique dans l’industrie de transformation et comme base de production d’énergie. Helia. 2006;29(44):1-24. https://doi.org/10.2298/hel0644001v
Regitano A, Miguel AM, Mourad AL, Henriques EA, Alves RM. Environmental effect on sunflower oil quality. Crop Breed Appl Biotechnol. 2016;16 (3):197-204. https://doi.org/10.1590/1984-70332016v16n3a30
Fick GN. Inheritance of high oleic acid in the seed oil of sunflower. In: Proceedings of Sunflower Research Workshop Bismarck, USA:Workshop. Natl. Sunflower Assooc., 1984 [cited 2024 18 Sept]. p. 1-8.
Urie AL. Inheritance of very high oleic acid content in sunflower. In: Proc. 6th Sunflower Res Bismarck, USA:Workshop. Natl. Sunflower Assooc., 1984 [cited 2024 18 Sept]. p. 9-10.
Joksimovi? J, Atlagi? J, Marinkovi? R, Jovanovi? D. Genetic control of oleic and linoleic acid contents in sunflower/control genético del contenido de aceite oleico y linólico en girasol/contrôle génétique des contenus d’acide oléique et linoléique chez le tournesol. Helia. 2006;29(44):33-40. https://doi.org/10.2298/hel0644033j
Lacombe S, Kaan F, Griveau Y, Bervillé A. The pervenets high oleic mutation: methodological studies/mutación altamente oleica pervenets: investigaciones metodológicas/mutation d’acides oléiques gras pervenets: recherches méthodologiques. Helia. 2004;27(40):41-54. https://doi.org/10.2298/hel0440041l
Berville A. Oil composition variations. In: Jinguo Hu, Gerald S, Kole C, editors. Genetics, genomics and breeding of sunflower. Boca Raton: Routledge; 2010. p. 253-77. https://doi.org/10.1201/b10192
Ferfuia C, Vannozzi GP. Maternal effect on seed fatty acid composition in a reciprocal cross of high oleic sunflower (Helianthus annuus L.). Euphytica. 2015;205:325–36. https://doi.org/10.1007/s10681-015-1378-3
Ganapati RK, Rasul MG, Sarker U, Singha A, Faruquee M. Gene action of yield and yield contributing traits of submergence tolerant rice (Oryza sativa L.) in Bangladesh. Bull Nat Res Centre. 2020;44:1-7. https://doi.org/10.1186/s42269-019-0261-0
Patel DK, Patel A, Patel CJ, Jat AL. Generation Mean Analysis for Seed Yield and Wilt Resistance in Castor (Ricinus communis L.). Ind J Agric Res. 2024;58(2). https://doi.org/10.18805/IJARe.A-5685
Sandhu R, Singh B, Delvadiya IR, Pandey MK, Rai SK, Attri M. Genetic analysis of grain yield and its contributing traits in four bread wheat (Triticum aestivum L.) crosses using six parameter model. Elect J Pl Breed. 2023;14(1):154-9. https://doi.org/10.37992/2023.1401.032
Chandra D, Islam MA, Barma NC. Variability and interrelationship of nine quantitative characters in F5 bulks of five wheat crosses. Pak J Biol Sci. 2004;7(6):1040-5. https://doi.org/10.3923/pjbs.2004.1040.1045
Khaled M. Estimation of genetic variance for yield and yield components in two bread wheat (Triticum aestivum L.) crosses. J Plant Prod. 2007;32(10):8043-53. https://doi.org/10.21608/jpp.2007.220889
Singh CM, Singh AK, Mishra SB, Pandey A. Generation mean analysis to estimate the genetic parameters for yield improvement and inheritance of seed colour and lusture in mungbean [Vigna radiata (L.) Wilczek]. Legume Res. 2016;39(4):494-501. https://doi.org/10.18805/lr.v0iOF.10762
Pathak S, Pant U, Yadav VN, Mishra A. Analysis of genetic architecture through generation mean analysis for yield and yield contributing traits in crosses of Indian Mustard (Brassica juncea). J Adv Biol Biotech. 2024;27(8):462-70. https://doi.org/10.9734/jabb/2024/v27i81158
Anuradha B, Manivannan N, Sasikala R, Harish S, Senthivelu M. Genetic variability and association studies in BC 3 F 1 population of sunflower (Helianthus annuus L.). Electronic Journal of Plant Breeding. 2023;14(3):923-7. https://doi.org/10.37992/2023.1403.104
Mather K, Jinks JL, Mather K, Jinks JL. Components of means: additive and dominance effects. In: Kenneth M, John LJ, editors. Biometrical genetics: The study of continuous variation. Boston, MA:Springer; 1971. p. 65-82. https://doi.org/10.1007/978-1-4899-3404-8_4
Singh RK, Chaudhary BD. Biometrical methods in quantitative genetic analysis. Lucknow: Kalyani Publisher; 1981
Hayman BI. The separation of epistatic from additive and dominance variation in generation means. Heredity;1958:371-90
Manivannan N. TNAUSTAT-Statistical package [internet].Coimbatore:TNAU; 2018 [cited 2024 Sept 18] Available from: https: //sites.google.com/site/tnaustat
Fonseca S, Patterson FL. Hybrid vigor in a seven?parent diallel cross in common winter wheat (Triticum aestivum L.). Crop Sci. 1968;8(1):85-8. https://doi.org/10.2135/cropsci1968.0011183X000800010025x
Rao, N. Statistics for Agricultural Sciences. New Delhi: Oxford and IBH Publishing; 1980.
Robinson HF, Comstock RE, Harvey PH. Estimates of heritability and the degree of dominance in corn. Agron J; 1949:353-9.
Kempthorne O. An introduction to genetic statistics. New York: John Wiley and Sons, Inc.; 1957.
Warner JN. A method for estimating heritability. Agron J. 1952;44:427-30.
Johnson HW, Robinson HF, Comstock RE. Estimates of genetic and environmental variability in soybeans. Agron J. 1955;314-8.
Gaoh BS, Gangashetty PI, Mohammed R, Dzidzienyo DK, Tongoona P. Generation mean analysis of pearl millet [Pennisetum glaucum (L.) R. Br.] grain iron and zinc contents and agronomic traits in West Africa. J Cereal Sci. 2020;96:103066. https://doi.org/10.1016/j.jcs.2020.103066
Yadav S, Singh SP, Singhal T, Anju-Mahendru S, Bhargavi HA, Aavula N, Goswami S, Satyavathi CT. Genetic elucidations of grain iron, zinc and agronomic traits by generation mean analysis in pearl millet [Pennisetum glaucum (L.) R. Br.]. J Cereal Sci. 2023;113:103751 https://doi.org/10.1016/j.jcs.2023.103751
Labroo MR, Studer AJ, Rutkoski JE. Heterosis and hybrid crop breeding: a multidisciplinary review. Front Gene. 2021;12:643761. https://doi.org/10.3389/fgene.2021.643761
Hassan HM, Hadifa AA, El-Leithy SA, Batool M, Sherif A, Al-Ashkar I, Ueda A, Rahman MA, Hossain MA, Elsabagh A. Variable level of genetic dominance controls important agronomic traits in rice populations under water deficit condition. PeerJ. 2023;11:e14833. https://doi.org/10.7717/peerj.14833
Pujar M, Govindaraj M, Gangaprasad S, Kanatti A, Gowda TH, Dushyantha Kumar BM, Satish KM. Generation mean analysis reveals the predominant gene effects for grain iron and zinc contents in pearl millet. Front Pl Sci. 2022;12:693680. https://doi.org/10.3389/fpls.2021.693680
Joci? S, Škori? D. Inheritance of some yield components in sunflower. ). In: Proceedings, 16th International Sunflower Conference; 2004 29 Aug-2 Sept; 2004, Fargo, North Dakota, USA. Paris: International Sunflower Association. 2004 [cited 2024 18 Sept]. p. 503-10 Available from: https://www.isasunflower.org/
Cukadar?Olmedo B, Miller JF. Inheritance of the stay-green trait in sunflower. Crop Sci. 1997;37(1):150. https://doi.org/10.2135/cropsci1997.0011183X003700010026x
Marinkovi? R, Vasi? D, Joksimovi? J, Jovanovi? D, Atlagi? J. Gene actions for seed yield in sunflower (Helianthus annuus). In: Proceedings, 16th International Sunflower Conference; 2004 29 Aug-2 Sept; 2004, Fargo, North Dakota, USA. Paris: International Sunflower Association. 2004 [cited 2024 18 Sept]. p. 511–6 Available from: https://www.isasunflower.org/
Gangappa E, Channakrishnaiah KM, Thakur S, Ramesh S. Genetic architecture of yield and its attributes in sunflower (Helianthus annuus L.). Helia. 1997,85-93.
Lagiso TM, Singh BC, Weyessa B. Evaluation of sunflower (Helianthus annuus L.) genotypes for quantitative traits and character association of seed yield and yield components at Oromia region, Ethiopia. Euphytica. 2021;217(2):27. https://doi.org/10.1007/s10681-020-02743-2
Delen Y, Palali-Delen S, Xu G, Neji M, Yang J, Dweikat I. Dissecting the genetic architecture of morphological traits in sunflower (Helianthus annuus L.). Genes. 2024;15(7). https://doi.org/10.3390/genes15070950
Vivek M, Sasikala R, Thangaraj K, Harish S, Sudha M. Exploring the genetic variability and association for yield and its integrant traits in sunflower (Helianthus annuus L.). Elec J Pl Breed. 2023;14(3):1090-6. https://doi.org/10.37992/2023.1403.123
Dudhe MY, Mulpuri S, Meena HP, Ajjanavara RR, Kodeboyina VS, Adala VR. Genetic variability, diversity and identification of trait-specific accessions from the conserved sunflower germplasm for exploitation in the breeding programme. Agric Res. 2020;9:9-22. https://doi.org/10.1007/s40003-019-00406-w
Izquierdo N, Aguirrezábal L, Andrade F, Pereyra V. Night temperature affects fatty acid composition in sunflower oil depending on the hybrid and the phenological stage. Field Crops Res. 2002;77(2-3):115-26. https://doi.org/10.1016/S0378-4290(02)00060-6
Downloads
Published
Versions
- 13-02-2025 (2)
- 07-02-2025 (1)
How to Cite
Issue
Section
License
Copyright (c) 2025 Sampath Lavudya, Kalaimagal Thiyagarajan, Sasikala Ramasamy, Harish Sankarasubramanian, Senthivelu Muniyandi, Anita Bellie, Gopi Venkatesh, Anvesh Ellandula
This work is licensed under a Creative Commons Attribution 4.0 International License.
Copyright and Licence details of published articles
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
Open Access Policy
Plant Science Today is an open access journal. There is no registration required to read any article. All published articles are distributed under the terms of the Creative Commons Attribution License (CC Attribution 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited (https://creativecommons.org/licenses/by/4.0/). Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
