Plant Genetic Research
Scientific Journal

Graphical Analysis of Grain Yield and Related Traits in Maize (Zea Mays L.) Under Normal and Water Deficit Stress Conditions

Document Type : Original Article

Authors

Somaye Zallaghi 1
Zahra Khodarahmpour 2
Aziz Afarinesh 3
Mohammad Motamedi 2
Seyed Keyvan Marashi 4

1 Department of Genetics and Plant Breeding, Ahv.C., Islamic Azad University, Ahvaz, Iran

2 Department of Production Engineering and Plant Genetics, Sho.C., Islamic Azad University, Shoushtar, Iran

3 Crop and Horticultural Science Research Department, Safiabad Dezfol, Agricultural and Natural Resources Research and Education Center, AREEO, Dezful, Iran

4 Department of Agronomy, Ahv.C., Islamic Azad University, Ahvaz, Iran

https://doi.org/10.22034/pgr.2025.2066879.1009
Abstract
Identifying and determining the genetic components of different traits facilitate the choice of appropriate breeding and selection strategies for genetic improvement of grain yield and stress tolerance. Fifteen maize hybrid genotypes were obtained from crossing among six lines including three drought tolerant lines (C4-95-2, C4-95-6 and C4-95-23) and three drought sensitive lines (C5-95-4, C5-95-12 and C6-95-5) and used in the initial experiments in a randomized complete block design with three replications. Grain yield and related traits, including number of grains per row, number of rows per ear, 1000-grain weight, leaf area index, ASI, harvest index, and tassel length were examined. Hayman’s genetic analysis showed that the parameters D, H1, and H2 were significant under normal conditions for grain yield, number of grains per row, tassel length, harvest index, and thousand-grain weight, highlighting the contribution of both additive and non-additive effects to the inheritance of these traits. Under water stress conditions, grain yield and number of numbers of grain rows per ear were significant for the H1 and H2 dominance variance, indicating the role of non-additive effects for these traits under water stress conditions. The estimates of broad-sense heritability (h²b) and narrow-sense heritability (h²n) indicated that grain yield, number of grain rows per ear, and harvest index exhibited values above 70% under both normal and water-stress conditions. The regression of Wr on Vr for grain yield in both environments showed the regression line intersecting below the origin on the Wr axis, suggesting the involvement of over dominant genes. In normal conditions, lines C4-95-2 and C4-95-6 and under water stress conditions, lines C4-95-2 and C4-95-23 were the closest lines to the Wr axis, indicating a greater role of dominant genes in controlling grain yield. Considering the greater contribution of non-additive effects in the genetic control of important traits, including grain yield, under water deficit stress conditions, this study suggests that selection should be carried out in the final generations in order to genetically improve these traits and identify lines tolerant to water deficit stress.

Keywords

Additive effects
Dominance effects
Genetic parameters
Diallel
Heritability

Subjects

Afarinesh, A., Farshadfar, E.A. and Choukan, R. (2005). Genetic analysis of drought tolerance in maize (Zea mays L.) using diallel method. Seed and Plant, 20: 457-473 (In Persian). http://dx.doi.org/10.29252/abj.21.1.1
Afolabi, M.S., Salami, A.E. and Agbowuro, G.O. (2019). Genetic studies of grain yield and other agronomic traits of Low-N maize (Zea mays L.) using a diallel cross under nitrogen fertilizer levels. International Journal of Plant Breeding and Crop Science, 6(3): 569–574.
Ahmed, M., Saleem, M., Ahsan, M. and Ahmad, A. (2016). Genetic analysis of water-deficit response traits in maize. Genetics and Molecular Research, 15 (1): 1-10. https://doi.org/10.4238/gmr.15017459
Akhtar, N. and Chowdhry, M.A. (2006). Genetic analysis of yield and some other quantities traits in bread wheat. International. Journal of Agriculture and Biology, 4: 523-527.
Ali, F., Ahsan, M., Ali, Q. and Kanawal, N. (2017). Phenotypic stability of Zea mays grain yield and its attributing traits under drought stress. Frontiers in Plant Science, 8: 1-11. https://doi.org/10.3389/fpls.2017.01397
Al-Naggar, A.M., Atta, M., Ahmed, M.A. and Younis, S.M. (2016). Genetic variance, heritability and selection gain of maize (Zea mays L.) adaptive traits to high plant density combined with water stress. Journal of Applied Life Sciences International, 7(2): 1-17. https://doi.org/10.9734/JALSI/2016/28414
Atlin, G.N., Cairns, J.E. and Das, B. (2017). Rapid breeding and varietal replacement are critical to adaptation of cropping systems in the developing world to climate change. Global Food Security, 12: 31-37. https://doi.org/10.1016/j.gfs.2017.01.008
Baiumy, K.A. (2025). Genetic analysis of quantitative traits in maize: evaluation of diallel crosses for normal and delayed growth using various stress tolerance indices. Journal of Plant Production, 16 (4): 127–135. https://doi.org/10.21608/jpp.2025.373559.1445
Banaei, R., Baghizadeh, A. and Khavari-Khorasani, S. (2016). Estimates of genetic variance parameters and general and specific combining ability of morphological traits, yield and yield components of maize hybrids in normal and salt stress conditions. Plant Genetic Research, 3(1): 57-74 (In Persian). https://doi.org/10.29252/pgr.3.1.57
Dorri, P., Khavari-Khorasani, S., Valizadeh, M. and Taheri, P. (2015). Investigation the heritability and gene effects on yield and some agronomic traits of maize (Zea mays L.). Plant Genetic Research, 1(2): 33-42 (In Persian). https://doi.org/10.29252/pgr.1.2.33
Erfani Moghadam, Z., Fotovat, R., Mohseni Fard, E. and Rodriguez, V. (2023). Genetic analysis of grain yield and related traits in maize (Zea mays L.) using graphical diallel analysis. Cereal Research, 13(2): 129-143 (In Persian).
FAO. (2023). FAOSTAT. Food and Agricultural Organization of the United Nations. Available at http://www.fao.org/faostat/en/#data/QC (Accessed on 9 September 2023). FAO. Rome, Italy.
Gami, R.A., Chauhan, B.B. and Patel, R.N. (2020). Hayman’s diallel analysis for yield and attributing traits in sesame (Sesamum indicum L.). Electronic Journal of Plant Breeding, 11(2): 359-366. https://doi.org/10.37992/2020.1102.064
Girma, S., Gong, Y., Gorg, H. and Lancheros, S. (2015). Estimating direct and indirect effects of foreign direct investment on firm productivity in the presence of interactions between firms. Journal of International Economics, 95(1): 157-169. https://doi.org/10.1016/j.jinteco.2014.11.007
Hallauer, A.R., Carena, M.J. and Miranda Filho, J.D. (2010). Quantitative Genetics in Maize Breeding. Springer, New Yourk, USA. https://doi.org/10.1007/978-1-4419-0766-0_12
Hayman, B.I. (1954). The analysis of variance of diallel tables. Biometrics, 10(2): 235-244. https://doi.org/10.2307/3001877
Hayman, B.I. (1958). The theory and analysis of diallel crosses II. Genetics, 43(1): 63-85. https://doi.org/10.1093/genetics/43.1.63
Issa, Z., Nyadanu, D., Richard, A., Sangare, A., Adejumobi, I. and Ibrahim, D. (2018). Inheritance and combining ability study on drought tolerance and grain yield among early maturing inbred lines of maize (Zea mays L.). Journal of Plant Breeding and Crop Science, 10: 115-127. https://doi.org/10.5897/JPBCS2017.0703
Kumar, A., Vyas, R., Tomar, A. and Singh, M. (2017). Genetic components analysis in maize (Zea mays L.). The Pharma Innovation. 6: 315- 317.
Lay, P. and Razdan, A. (2017). Genetic analysis of grain yield and its components of maize (Zea mays L.) inbred lines. International Journal of Current Microbiology and Applied Sciences, 6(7): 1366-1372. https://doi.org/10.20546/ijcmas.2017.607.163
Madadi, S., Rahimi, M., Ahmadi-Afzadi, M. and Mirzaei, S. (2020). Estimation of gene effect and combining ability of some maize traits under normal and low irrigation conditions by diallel method. Environmental Stresses in Crop Sciences, 13 (2): 331-340.
Moradi, M. and Choukan, R. (2017). Graphical Analysis for grain yields related traits in maize (Zea mays L.) using diallel crosses under normal and water stress conditions. Journal of Crop Breeding, 9(22): 149-157 (In Persian). https://doi.org/10.29252/jcb.9.22.149
Mosavat, S.A., Mazahery-Laghab, H., Soltanloo, H. and Choukan, R. (2019). Estimated combining ability and gene action in selected maize (Zea mays L.) lines. Iranian Journal of Crop Sciences, 21(1): 1-15 (In Persian). https://doi.org/10.29252/abj.21.1.1
Mostafavi, K.H., Golbashi, M. and Khavari-Khorasani, S. (2010). Study response of corn S.C hybrids to drought stress using multivariate statistical analysis. Journal of Agronomy and Plant Breeding, 7: 117- 132 (In Persian).
Ojo, G.O.S., Adedzwa, D.K. and Bello, L.L. (2007). Combining ability estimates and Heterosis for grain yield and yield component in maize (Zea mays L.). Journal of Sustainable Development in Agriculture and Environment, 3: 49-57.
Rahimi, M. (2019). Genetic analysis of grain yield and its components of maize in lines and F2 progenies using diallel analysis by Hayman’s graphical approach. Cereal Research, 9(2): 169-177 (In Persian).
Ramadan, A.A., Hussein, F. and Ftaikhan, M. (2021).  Genetic analysis of combining ability and gene action of yield and its components in maize (Zea mays L.) using full diallel cross. Annals of the Romanian Society for Cell Biology, 25(5): 1241–125
Riache, M., Revilla, P., Oula Maafi, O., Malvar, R.A. and Djemel, A. (2021). Combining Ability and heterosis of algerian saharan maize populations (Zea mays L.) for tolerance to no-nitrogen fertilization and drought. Agronomy, 11: 492-511. https://doi.org/10.3390/agronomy11030492
Rovaris, S.R.S., Oliveira, A.L.B., Sawazaki, E., Gallo, P.B. and Paterniani, M.E. (2017). Genetic parameter estimates and identification of superior white maize populations. Acta Scientiarum. Agronomy, 39(2): 157-174. https://doi.org/10.4025/actasciagron.v39i2.32517
Sedric, J., Pajhc, Z. and Mladenovic-Drinic S.S. (2007). Inheritance of maize grain yield components. Maydica, 52(3): 261-264.
Singh, P. and Narayanan, S.S. (2000). Biometrical Techniques in Plant Breeding. Kalayani Publishers, New Delhi, IND.
Umar, U. (2015). Genetics of drought tolerance in maize (Zea mays L.) under non-stress and water stress conditions. Ph.D. Thesis, Ahmadu Bello University, Zaria, Nigeria.
Vahed-Rezaei, A., Aharizad, S., Norouzi, M. and Mafakheri, K. (2020). Genetic analysis of agronomic traits in generations derived from the cross of MO17 and B73 maize inbred lines under water deficit stress. Journal of Crop Breeding, 12: 76-85 (In Persian). https://doi.org/10.29252/jcb.12.33.76
Wannows, A.K., Azam, H.A. and Al-Ahmad, S.A. (2010). Genetic variances, heritability, correlation and path coefficient analysis in yellow maize crosses. Agriculture and Biology Journal North American, 1(4): 630-637.
Zabet, M., Barazandeh, F. and Samadzadeh, A. (2023). Evaluation of genetic structure of yield and its components in sesame using Hayman's numerical and graphical analysis in Birjand’s climate conditions. Plant Genetic Research, 10(1): 123-144 (In Persian). http://doi.org/10.22034/pgr.10.1.8
Zamani Farsi, M., Rahimi, M., Abdoli-Nesab, M. and Baghizadeh, A. (2019). Graphical estimation of the genetic control of grain yield and its components in S7 corn lines under normal and water deficit conditions. Environmental Stresses in Crop Sciences, 12(4): 1049-1061 (In Persian).
Zare, M., Choukan, R., Bihamta, M.R., Majidi-Heravan, E. and Kamelmanesh, M.M. (2011). Gene action for some agronomic traits in maize (Zea mays L.). Journal of Crop Breeding, 1(2): 133-141 (In Persian).
Zeleke, K., Demissew, A. and Wosene, G. (2020). Heterosis and combining ability of highland adapted maize (Zea mays L.) DH lines for desirable agronomic traits. African Journal of Plant Science, 14: 121–133. https://doi.org/10.5897/AJPS2019.1880
Plant Genetic Research
Volume 12, Issue 1
June 2025
Pages 131-146

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