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:: Volume 10, Issue 1 (2023) ::
pgr 2023, 10(1): 61-78 Back to browse issues page
Gene Actions Controlling of grain yield and its Contributing traits in Hybrid Maize under Water Deficiency
Mozhgan Shirinpour , Ehsan Atazadeh , Ahmad Bybordi , Saeid Aharizad , Ali Asghari * , Ashkboos Amini
Department of Production Engineering and Plant Genetics, University of Mohaghegh Ardabili, Ardabil, Iran , a_asghari@uma.ac.ir
Abstract:   (2428 Views)
Considering the importance of maize production and the impact of water deficit stress on reducing the yield of maize, estimating the genetic components and heritability of traits for determine the breeding method under water deficit stress is essential in breeding programs. The generations drived from a cross between two inbred lines of maize including B73 (maternal line) and MO17 (paternal line), SC704 (F1) as well as F2, BC1, BC2 and F3 generations in order to estimate the genetic effects and heritability of yield, yield components and morphological traits were studied. Seven maize generations using the generations mean analysis under the full irrigation, mild and severe water deficit conditions were evaluated. The experiment was conducted in the form of randomized complete block design with 20 replications per experimental unit during two cropping seasons (2018-2019) at the Agricultural Research Station of University of Tabriz. The results of two-year combined analysis of variance and mean comparisons under three different irrigation regimes showed that water deficit stress significantly reduced all of the studied traits (except root/shoot ratio). The generations mean analysis showed the high contribution of non-additive gene effects for the genetic control of grain yield, ear diameter, number of kernel row, ear weight (in full irrigation conditions), 100 grain weight, plant height, fresh shoot weight and biological yield traits. According to these results, selection in the advanced generations and the breeding method based on hybridization can be effective to improve these traits. Also, the significant contribution of additive gene effects in controlling the inheritance of ear length, ear weight (in both stress conditions) and root/shoot ratio traits indicated that selection in early segregating generations and inbred parents can be effective for breeding of these traits and taking advantage of additive variance. Hybrid SC704 and inbred MO17 compared with the inbred B73 showed the lowest variation percentage under the water deficit stress conditions, which indicated their high yield potential and stability in the stress conditions.
Keywords: Genetic analysis, Heritability, Maize generations, Water deficit stress
Full-Text [PDF 945 kb]   (889 Downloads)    
Type of Study: Research | Subject: Plant improvement
References
1. Ali, Q., Ahsan, M., Mustafa, H.S.B. and Hasan, E. (2013). Studies of genetic variability and correlation among morphological traits of maize (Zea mays L.) at seedling stage. Albanian Journal of Agricultural Sciences, 12(3): 405-410.
2. Almeida, V.C., Viana, J.M.S., Risso, L.A., Ribeiro, C. and DeLima, R.O. (2018). Generation mean analysis for nitrogen and phosphorus uptake, utilization, and translocation indexes at vegetative stage in tropical popcorn. Euphytica, 214(7): 103. [DOI:10.1007/s10681-018-2194-3]
3. Amegbor, I.K., van Biljon, A., Shargie, N., Tarekegne, A. and Labuschagne, M.T. (2022). Heritability and associations among grain yield and quality traits in quality protein maize (QPM) and non-QPM hybrids. Plants, 11(6): 713. [DOI:10.3390/plants11060713]
4. Amiri, R., Bahraminejad, S. and Cheghamirza, K. (2021). Estimation of genetic control model for agronomic traits in the progeny of Marvdasht and MV-17 wheat cross under normal and terminal drought stress conditions. Plant Genetic Researches, 8(1): pp.61-80 (In Persian). [DOI:10.52547/pgr.8.1.5]
5. Araus, J.L., Sánchez, C. and Cabrera‐Bosquet, L. (2010). Is heterosis in maize mediated through better water use? New Phytologist, 187(2): 392-406. [DOI:10.1111/j.1469-8137.2010.03276.x]
6. Asadi, A.A., Valizadeh, M., Mohammadi, S.A. and Khodarahmi, M. (2019). Genetic analysis of response to water deficit stress in wheat yield traits with generation means and variance analysis. Journal of Crop Breeding, 11(32): 88-99 (In Persian). [DOI:10.29252/jcb.11.32.88]
7. Barutcular, C., Sabagh, A.E., Konuskan, O., Saneoka, H. and Yoldash, K.M. (2016). Evaluation of maize hybrids to terminal drought stress tolerance by defining drought indices. Journal of Experimental Biology and Agricultural Sciences, 4(6): 610-616. [DOI:10.18006/2016.4(Issue6).610.616]
8. Chohan, M.S.M., Muhammad, S., Muhammad, A. and Muhammad, A. (2012). Genetic analysis of water stress tolerance and various morpho-physiological traits in Zea mays L. using graphical approach. Pakistan Journal of Nutrition, 11(5): 489-500. [DOI:10.3923/pjn.2012.489.500]
9. Crusio, W.E. (2006). Neurobehavioral Genetics: An Introduction to Quantitative Genetics. CRC Press, Boca Raton, FL, USA. [DOI:10.1201/9781420003567.ch4]
10. Dos Reis, M.C., Pádua, J.M.V., Abreu, G.B., Guedes, F.L., Balbi, R.V. and de Souza, J.C. (2014). Estimates for genetic variance components in reciprocal recurrent selection in populations derived from maize single-cross hybrids. The Scientific World Journal, 2014: 1-7. [DOI:10.1155/2014/540152]
11. Edwards, C.E., Ewers, B.E. and Weinig, C. (2016). Genotypic variation in biomass allocation in response to field drought has a greater affect on yield than gas exchange or phenology. BMC Plant Biology, 16(1): 185. [DOI:10.1186/s12870-016-0876-3]
12. Erenstein, O., Jaleta, M., Sonder, K., Mottaleb, K. and Prasanna, B.M. (2022). Global maize production, consumption and trade: trends and R&D implications. Food Security, 14(5): 1295-1319. [DOI:10.1007/s12571-022-01288-7]
13. FAOSTAT. (2021). Food and Agricultural Organization Statistical Database. Rome, Italy: FAO. http://faostat.fao.org.
14. Farooq, M., Wahid, A., Kobayashi, N., Fujita, D. and Basra, S. (2009). Plant drought stress: effects, mechanisms and management. Agronomy for Sustainable Development, 29(1): 185-212. [DOI:10.1051/agro:2008021]
15. Ghanbari, F., Mousavi, S.S., Abdollahi, M.R., Kiani, A.R. and Mosavat, S.A. (2018). Estimation of gene action for grain yield and yield-related traits in grain maize (Zea mays L.) under moisture stress conditions. Seed and Plant Journal, 34 (1): 37-62 (In Persian).
16. Greaves, G.E. and Wang, Y.M. (2017). Yield response, water productivity, and seasonal water production functions for maize under deficit irrigation water management in southern Taiwan. Plant Production Science, 20(4): 353-365. [DOI:10.1080/1343943X.2017.1365613]
17. Hadini, H., Nasrullah, N., Taryono, T. and Basunanda, P. (2015). Estimates Of Genetic Variance Component Of An Equilibrium Population Of Corn. AGRIVITA, Journal of Agricultural Science, 37(1): 45-50. [DOI:10.17503/Agrivita-2015-37-1-p045-050]
18. Hallauer, A.R., Carena, M.J., Miranda Filho, J.d. (2010). Quantitative Genetics in Maize Breeding. Springer-Verlag New York, USA. [DOI:10.1007/978-1-4419-0766-0_12]
19. Haq, A., Tahir, M.H.N., Ahsan, M., Ahmad, R. and Akram, H.M. (2015). Screening and inheritance pattern studies of maize seedlings under normal and water stress conditions. Pakistan Journal of Life and Social Sciences, 13: 97-103.
20. Hassan, H.M., Hadifa, A.A., El-Leithy, S.A., Batool, M., Sherif, A., Al-Ashkar, I., Ueda, A., Rahman, M.A., Hossain, M.A. and Elsabagh, A. (2023). Variable level of genetic dominance controls important agronomic traits in Rice populations under water deficit condition. PeerJ, 11: e14833. [DOI:10.7717/peerj.14833]
21. Hayman, B. and Mather, K. (1955). The description of genic interactions in continuous variation. Biometrics, 11(1): 69-82. [DOI:10.2307/3001481]
22. Hütsch, B.W. and Schubert, S. (2021). Can nutrient‐utilization efficiency be improved by reduced fertilizer supply to maize plants treated with the plant growth regulator paclobutrazol?. Journal of Agronomy and Crop Science, 207(5): 884-900. [DOI:10.1111/jac.12521]
23. Jin, Z., Xue, Q.W., Jessup, K.E., Hou, X.B., Hao, B.Z., Marek, T.H., Xu, W.W., Evett, S.R., O'Shaughnessy, S.A. and Brauer, D.K. (2018). Shoot and root traits in drought tolerant maize (Zea mays L.) hybrids. Journal of Integrative Agriculture, 17(5): 1093-1105. [DOI:10.1016/S2095-3119(17)61869-0]
24. Kang, M. (1994). Applied Quantitative Genetics. Kang. MS Publisher, Baton Rouge, LA, USA.
25. Khan, N.H., Ahsan, M., Naveed, M., Sadaqat, H.A. and Javed, I. (2016). Genetics of drought tolerance at seedling and maturity stages in Zea mays L. Spanish Journal of Agricultural Research, 14(3): 13. [DOI:10.5424/sjar/2016143-8505]
26. Khavari Khorasani, S. and Mahdi Poor, A. (2018). Genetic improvement of grain yield by determination of selection index in single cross hybrids of maize (Zea mays L.). Plant Genetic Researches, 5(1): 1-18 (In Persian). [DOI:10.29252/pgr.5.1.1]
27. Khodarahmpour, Z. (2011). Genetic control of different traits in maize inbred lines (Zea mays L.) using graphical analysis. African Journal of Agricultural Research, 6(7): 1661-1666.
28. Lean, C.H., Doolittle, W.F. and Bielawski, J.P. (2022). Community-level evolutionary processes: Linking community genetics with replicator-interactor theory. Proceedings of the National Academy of Sciences, 119(46): e2202538119. [DOI:10.1073/pnas.2202538119]
29. Li, D., Zhou, Z., Lu, X., Jiang, Y., Li, G., Li, J., Wang, H., Chen, S., Li, X., Würschum, T. and Reif, J.C. (2021). Genetic dissection of hybrid performance and heterosis for yield-related traits in maize. Frontiers in Plant Science, 12: 774478. [DOI:10.3389/fpls.2021.774478]
30. Mather, K. (1973). The Genetical Structure of Populations. Chapman and Hall Press, London, UK.
31. Mather, K. and Jinks, J.L. (1982). Biometrical Genetics: The Study of Continuous Variation. Springer, Chapman and Hall, London, UK. [DOI:10.1007/978-1-4899-3406-2]
32. Mathew, I., Shimelis, H., Mwadzingeni, L., Zengeni, R., Mutema, M. and Chaplot, V. (2018). Variance components and heritability of traits related to root: shoot biomass allocation and drought tolerance in wheat. Euphytica, 214(12): 1-12. [DOI:10.1007/s10681-018-2302-4]
33. Mendes-Moreira, P., Alves, M.L., Satovic, Z., dos Santos, J.P., Santos, J.N., Souza, J.C., Pego, S.E., Hallauer, A.R. and Patto, M.C.V. (2015). Genetic architecture of ear fasciation in maize (Zea mays) under QTL scrutiny. PloS One, 10(4): e0124543. [DOI:10.1371/journal.pone.0124543]
34. Moosavi, S.G. (2012). The effect of water deficit stress and nitrogen fertilizer levels on morphology traits, yield and leaf area index in maize. Pakistan Journal of Botany, 44: 1351-1355.
35. Moosavi, S.S., Ghanbari, F., Abdollahi, M.R. and Kiani, A.R. (2018). Genetic analysis of yield, yield-components and related phenological traits of maize (Zea mays L.) to breed under moisture stress conditions. Desert, 23(2): 273-283.
36. Mounce, R.B., O'Shaughnessy, S.A., Blaser, B.C., Colaizzi, P.D. and Evett, S.R. (2016). Crop response of drought-tolerant and conventional maize hybrids in a semiarid environment. Irrigation Science, 34(3): 231-244. [DOI:10.1007/s00271-016-0497-5]
37. Muliadi, A., Effendi, R. and Azrai, M. (2021). Genetic variability, heritability and yield components of waterlogging-tolerant hybrid maize. Earth and Environmental Science, 648(1): 012084). [DOI:10.1088/1755-1315/648/1/012084]
38. Musvosvi, C., Setimela, P.S., Wali, M.C., Gasura, E., Channappagoudar, B.B. and Patil, S.S. (2018). Contribution of Secondary traits for high grain yield and stability of tropical maize germplasm across drought stress and non‐stress conditions. Agronomy Journal, 110(3): 819-832. [DOI:10.2134/agronj2017.04.0199]
39. Nasrollahzade Asl, V., Moharramnejad, S., Yusefi, M., Bandehhagh, A. and Ibrahimi, L. (2017). Evaluation of grain yield of maize (Zea mays L.) hybrides under water limitation. Journal of Agricultural Science and Sustainable Production, 27(2): 85-96 (In Persian).
40. Noor, M., Fahad, S., Shahwar, D., Alam, M., Ullah, H., Adnan, M., Jamal, Y., Wahid, F., Rahman, H. and Yasir, M. (2018). Generation mean analysis for grain yield and its components in popcorn. Open Agriculture, 3(1): 437-458. [DOI:10.1515/opag-2018-0050]
41. Oury, V., Tardieu, F. and Turc, O. (2016). Ovary apical abortion under water deficit is caused by changes in sequential development of ovaries and in silk growth rate in maize. Plant Physiology, 171(2): 986-996.
42. Paredes, P., de Melo-Abreu, J., Alves, I. and Pereira, L. (2014). Assessing the performance of the FAO AquaCrop model to estimate maize yields and water use under full and deficit irrigation with focus on model parameterization. Agricultural Water Management, 144: 81-97. [DOI:10.1016/j.agwat.2014.06.002]
43. Pavan, R., Gangappa, E., Ramesh, S., Rao, A.M. and Shailaja, H. (2017). Detection of epistasis through triple test cross (TTC) analysis in maize (Zea mays L.). Journal of Applied and Natural Science, 9(4): 2496-2501. [DOI:10.31018/jans.v9i4.1560]
44. Sah, R., Chakraborty, M., Prasad, K., Pandit, M., Tudu, V., Chakravarty, M., Narayan, S., Rana, M. and Moharana, D. (2020). Impact of water deficit stress in maize: Phenology and yield components. Scientific Reports, 10(1): 1-15. [DOI:10.1038/s41598-020-59689-7]
45. Sah, S.K., Reddy, K.R., Li, J. (2016). Abscisic acid and abiotic stress tolerance in crop plants. Frontiers in Plant Science, 7: 571. [DOI:10.3389/fpls.2016.00571]
46. Shao, H.B., Chu, L.Y., Jaleel, C.A. and Zhao, C.X. (2008). Water-deficit stress-induced anatomical changes in higher plants. Comptes Rendus Biologies, 331(3): 215-225. [DOI:10.1016/j.crvi.2008.01.002]
47. Su, Y., Wu, F., Ao, Z., Jin, S., Qin, F., Liu, B., Pang, S., Liu, L. and Guo, Q. (2019). Evaluating maize phenotype dynamics under drought stress using terrestrial lidar. Plant Methods, 15(1): 11. [DOI:10.1186/s13007-019-0396-x]
48. Tabatabaei, S.A. and Shakeri, E. ( 2015) Short communication: effect of drought stress on maize hybrids yield and determination of the best hybrid using drought tolerance indices. Environmental Stresses in Crop Sciences, 8(1): 121-125 (In Persian).
49. Ul-Allah, S., Ijaz, M., Nawaz, A., Sattar, A., Sher, A., Naeem, M., Shahzad, U., Farooq, U., Nawaz, F. and Mahmood, K. (2020). Potassium application improves grain yield and alleviates drought susceptibility in diverse maize hybrids. Plants, 9(1): 75. [DOI:10.3390/plants9010075]
50. Wang, B., Liu, C., Zhang, D., He, C., Zhang, J. and Li, Z. (2019). Effects of maize organ-specific drought stress response on yields from transcriptome analysis. BMC Pant Biology, 19(1): 335. [DOI:10.1186/s12870-019-1941-5]
51. Wannows, A., Sabbouh, M. and Al-Ahmad, S. (2015). Generation mean analysis technique for determining genetic parameters for some quantitative traits in two maize hybrids (Zea mays L.). Jordan Journal of Agricultural Sciences, 11: 59-72. [DOI:10.12816/0030075]
52. Yan, W., Zhong, Y. and Shangguan, Z. (2016). Evaluation of physiological traits of summer maize under drought stress. Acta Agriculturae Scandinavica, Section B-Soil & Plant Science, 66(2): 133-140. [DOI:10.1080/09064710.2015.1083610]
53. Yi, Q., Liu, Y., Hou, X., Zhang, X., Li, H., Zhang, J., Liu, H., Hu, Y., Yu, G. and Li, Y. (2019). Genetic dissection of yield-related traits and mid-parent heterosis for those traits in maize (Zea mays L.). BMC Plant Biology, 19(1): 392. [DOI:10.1186/s12870-019-2009-2]
54. Zubairi, Z., Saeed, Z., Nazir, A., Saddique, S., Chaudhary, F. and Saeed, S. (2012). Water Logging a serious problem for the growth of maize (Zea mays L.). International Journal of Water Resources and Environmental Sciences, 1(4): 109-112.
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Shirinpour M, Atazadeh E, Bybordi A, Aharizad S, Asghari A, Amini A. Gene Actions Controlling of grain yield and its Contributing traits in Hybrid Maize under Water Deficiency. pgr 2023; 10 (1) :61-78
URL: http://pgr.lu.ac.ir/article-1-284-en.html


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