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Assessment of genotype × environment interaction and yield stability of grain maize (Zea mays L.) hybrids | ||
| Crop Breeding Journal | ||
| دوره 15، شماره 2، آذر 2025، صفحه 1-19 اصل مقاله (686.52 K) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22092/cbj.2025.368964.1095 | ||
| نویسندگان | ||
| A. Estakhr* 1؛ Z. Dehghanpour2؛ M. R. Shiri3؛ H. Hassanzadeh Moghaddam4؛ H. Najafinejad5؛ A. Shirkhani6؛ P. Jafari7؛ M. Mohseni8؛ K. Anvari9 | ||
| 1Fars Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization, Shiraz, Iran. | ||
| 2Seed and Plant Improvement Institute, Agricultural Research, Education and Extension Organization, Karaj, Iran. | ||
| 3Seed and Plant Improvement Institute, Agricultural Research, Education and Extension Organization, Karaj, Iran | ||
| 4Khorasan Razavi Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization, Mashhad, Iran. | ||
| 5Kerman Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization, Kerman, Iran. | ||
| 6Kermanshah Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization, Kermanshah, Iran. | ||
| 7Isfahan Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization, Isfahan, Iran. | ||
| 8Mazandaran Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization, Sari, Iran. | ||
| 9West Azerbaijan Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization, Urmia, Iran. | ||
| چکیده | ||
| Understanding the genotype × environmental interaction in the maize (Zea mays) breeding programs is necessary for finding high yielding and stable yield genotypes for different environmental conditions, enhancing breeding efficiency and crop productivity. To identify early-maturing maize hybrids that possess both high yield and yield stability, 11 hybrids including four promising three-way crosses and seven promising single crosses along with three single-cross hybrids (cv. Dehghan, cv. Fajr, and cv. Koosha) as control were evaluated across nine locations over two consecutive growing seasons (18 environments). The experimental design was randomized complete blocks with four replications. Phenological traits including silking, anthesis and physiological maturity dates, as well as grain yield, and yield components were measured and recorded. Combined analysis revealed significant effects of hybrid, growing season, location and their interaction on grain yield, emphasizing on the necessity of multi-environment trials to identify superior and stable yield grain maize hybrids. Grain yield showed positive correlation with all traits, except for cob percentage and kernel moisture content. The yield stability analysis using different yield stability indices showed high variation among hybrids. The hybrids were ranked based on grain yield and eight stability indices. Hybrids H, H11, H2, H4 and H5 achieved higher rank and were grouped as stable yield hybrids. The GGE biplot divided nine experimental locations into two major sectors and identified H8, H11, H10, H5 and H4 as winning hybrids adapted to specific environments. The first sector included Karaj, Miandoab, Kerman, Moghan and Sari with H11 and H8 and H4 as the winning hybrids, and the second sector comprised Shiraz, Isfahan, Kermanshah and Mashhad where H5 and H10 were the best-performing hybrids. The visualization of the ideal genotype demonstrates that H4 followed by H11 were located in close proximity to the ideal genotype. The single cross hybrid H11 (KE 76009/312 × K 1264/5-1) and the three-way cross hybrid H4 (KE 77008/1 × KSC260) performed significantly different from the control hybrids, producing the highest grain yield of 11.447 and 11.238 t ha-1, respectively. The GGE biplot and complementary yield stability analyses consistently identified H11 and H4 (from the FAO group 400) as desirable hybrids with high stable grain yield, therefore suitable for being commercially released. | ||
| کلیدواژه‌ها | ||
| maize؛ early maturity؛ stable yield genotypes؛ specific adaptation؛ GGE biplot analysis | ||
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Adu, G. B., Badu-Apraku, B., Akromah, R., Haruna, A., Amegbor, I. K. and Amadu, M. K. 2019. Grain yield and stability of early-maturing single-cross hybrids of maize across contrasting environments. J. Crop Improv. 33(6): 776-796. DOI:10.1080/15427528.2019.1661055.
Allard, R.W. and Bradshaw, A. D. 1964. Implication of genotype environment interactions in applied plant breeding. Crop Sci. 4: 403-508. DOI: 10.2135/cropsci1964.0011183X000400050021x.
Aman, J., Bantte, K., Alamerew, S. and Sbhatu, D. B. 2020. Correlation and path coefficient analysis of yield and yield components of quality protein maize (Zea mays L.) hybrids at Jimma, western Ethiopia. Int. J. of Agron. 2020(1): 1-7. DOI: 10.1155/2020/9651537.
Changizi, M., Choukan, R., Heravan, E. M., Bihamta, M. R. and Darvish, F. 2014. Evaluation of genotype-environment interaction and stability of corn hybrids and relationship among univariate parametric methods. Can. J. Plant Sci. 94: 1255-1267. DOI: 10.4141/CJPS2013-386.
Crossa, J. 1990. Statistical analyses of multi-location trials. Adv. Agron. 44: 55-85. DOI: 10. 1016 /S0065-2113(08)60818-4.
Dehghani, H., Sabaghpour, S. H. and Sabaghnia, N. 2008. Genotype × environment interaction for grain yield of some lentil genotypes and relationship among univariate stability statistics. Span. J.of Agric. Res. 6: 385-394.
Djurovic, D., Madic, M., Bokan, N., Stevovic, V., Tomic, D. and Tanaskovic, S. 2014. Stability parameters for grain yield and its component traits in maize hybrids of different FAO maturity groups. J. Cent. Europ. Agric. 15(4): 199-212. DOI: 10.5513/JCEA01/15.4.1530.
Eberhart, S. A. and Russell, W. A. 1966. Stability parameters for comparing varieties. Crop Sci 6: 36-40. DOI: 10.2135/cropsci1966.0011183X000600010011x.
Estakhr, A. and Choukan, R. 2011. Effect of planting date on grain yield and its components and reaction to important maize viruses in Fars Province in some exotic and Iranian maize hybrids. Seed Plant Prod. J. 27: 313-333. DOI: 10.22092/SPPJ.2017.110440.
Estakhr, A. and Dehghanpour, Z. 2011. Determination of the suitable planting date for new early maturity maize hybrids in second cropping in temperate regions in Fars province. Seed Plant Prod. J. 26: 169-191.
Estakhr, A. and Heidari, B. 2012. Combining ability and gene action for maturity and agronomic traits in different heterotic groups of maize inbred lines and their diallel crosses. J. Crop Sci. Biotechnol. 15: 219-223. DOI: 10.1007/s12892-012-0030-1.
Estakhr, A., Heidari, B. and Ahmadi, Z. 2015. Evaluation of kernel yield and agronomic traits of European maize hybrids in the temperate region of Iran. Arch. Agron. and Soil Sci. 61(4): 475-491. DOI: 10.1080/03650340.2014.941822.
Eze, C. E., Akinwale, R. O., Michel, S. and Bürstmayr, H. 2020. Grain yield and stability of tropical maize hybrids developed from elite cultivars in contrasting environments under a rainforest agro-ecology. Euphytica, 216:1-13. DOI: 10.1007/s10681-020-02620-y.
FAO. 2012. FAOSTAT. Food and Agriculture Organization of the United Nations. Food and Agriculture Data Network. Available from: http://faostat.fao.org.
Finlay, K. W. and Wilkinson, G. N. 1963. The analysis of adaptation in a plant breeding programe. Aust. J. Agric. Res. 14:742–754.
Francis, T. R. and Kanenberg, L. W. 1978. Yield stability studies in short season maize. A descriptive method for grouping genotypes. Can. J. Plant Sci. 58(4) 1026-1034. DOI: 10.4141/cjps78-157.
Gauch, H. G., Piepho, H. P. and Annicchiarico, P. 2008. Statistical analysis of yield trials by AMMI and GGE: Further considerations. Crop Sci. 4 8(3): 866-889. DOI: 10.2135/cropsci2007.09.0513.
Ghaed-Rahimi, L., Heidari, B. and Dadkhodaie, A. 2014. Genotype× environment interactions for wheat grain yield and antioxidant changes in association with drought stress. Arch. Agron. and Soil Sci. 61(2): 153-171. DOI: 10.1080/03650340.2014.926004.
Hassani, M., Heidari, B., Dadkhodaie, A. and Stevanato, P. 2018. Genotype by environment interaction components underlying variations in root, sugar and white sugar yield in sugar beet (Beta vulgaris L.). Euphytica 214: 1-21. DOI: 10.1007/s10681-018-2160-0.
Hebert, Y., Plomion, C. and Harzic, N. 1995. Genotypic × environment interaction for root traits in maize, as analyzed with factorial regression models. Euphytica 81: 85-92.
Kang, M. S. 1988. A rank-sum method for selecting high-yielding, stable corn genotypes. Cereal Res. Commun. 16: 113–115.
Kovačević, A., Pavlov, J., Stevanović, M., Delić, N., Mutavdzic, D. and Živanović, T. 2024. Direct selection parameter estimates and path coefficient analysis for grain yield and quantitative traits in maize (Zea mays L.). Roman. Agric. Res. 41: p.4101.DOI: 10.59665/rar4101.
Kumar, B., Choudhary, M., Kumar, P., Kumar, S., Sravani, D., Vinodhana, N. K., Kumar, G. S., Gami, R., Vyas, M., Jat, B. S. and Dagla, M. C. 2024. GGE biplot analysis and selection indices for yield and stability assessment of maize (Zea mays L.) genotypes under drought and irrigated conditions. Indian Journal of Genet. Plant Breed. 84(02): 209-215. DOI: 10.31742/ISGPB.84.2.8 .
Li, L. L., Ming, B., Xue, J., Gao, S., Wang, K. R., Xie, R.Z., Hou, P. and Li, S. K. 2021. Difference in corn kernel moisture content between pre-and post-harvest. J. Integr. Agric. 20(7): 1775-1782. DOI: 10.1016/S2095-3119(20)63245-2.
Oyekunle, M., Haruna, A., Badu‐Apraku, B., Usman, I. S., Mani, H., Ado, S. G., Olaoye, G., Obeng‐Antwi, K., Abdulmalik, R. O. and Ahmed, H. O. 2017. Assessment of early‐maturing maize hybrids and testing sites using GGE biplot analysis. Crop Sci. 57(6): 2942-2950. DOI: 10.2135/cropsci2016.12.1014.
Payne, R. W., Murray, D. A., Harding. S, A., Baird. D, B, and Soutar, D. M. 2012. Genstat® for Windows™, 15th Edition, Introduction. VSN International, Oxford.
Plaisted, R. I. and Peterson, L. C. 1959. A technique for evaluating the ability of selection to yield consistently in different locations or seasons. Am. Potato Res. J. 36: 381–385. DOI: 10.1007/BF02852735.
Plaisted, R.L. 1960. A shorter method for evaluating the ability of selections to yield consistently over locations. Am. Potato Res. J. 37: 166–172. DOI: 10.1007/BF02855271.
Pour‐Aboughadareh, A., Yousefian, M., Moradkhani, H., Poczai, P. and Siddique, K.H. 2019. STABILITYSOFT: A new online program to calculate parametric and non‐parametric stability statistics for crop traits. Appl, in Plant Sci. 7(1). DOI: 10.1002/aps3.1211.
Rafiq, C. M., Rafique, M., Hussain, A. and Altaf, M. 2010. Studies on heritability, correlation and path analysis in maize (Zea mays L.). J. Agric. Res. 48(1): 35-38.
Rahimi Jahangirlou, M., Akbari, G. A., Alahdadi, I., Soufizadeh, S., Kumar, U. and Parsons, D. 2021. Phenotypic traits, grain yield and yield components of maize cultivars under combinations of management practices in semi-arid conditions of Iran. Int. J. Plant Produc. 15: 459-471. DOI: 10.1007/ s42106-021-00151-7.
Raut, S. K., Ghimire, S, K,, Kharel. R., Kuwar. C. B., Sapkota, M. and Kushwaha, U. K. S. 2017. Study of yield and yield attributing traits of maize. Amer. J. of Food Sci. Health 3(6): 123-129.
Ruswandi, D., Syafii, M., Wicaksana, N., Maulana, H., Ariyanti, M., Indriani, N.P., Suryadi, E., Supriatna, J. and Yuwariah, Y. 2022. Evaluation of high yielding maize hybrids based on combined stability analysis, sustainability index, and GGE biplot. BioMed. Res. Int. 2022:1-12. DOI: 10.1155/2022/3963850.
Sabaghnia, N., Sabaghpour, S. H. and Dehghani, H. 2008. The use of an AMMI model and its parameters to analysis yield stability in multi-environment trials. J. Agric. Sci. 146: 571-581.
Shahriari, Z., Heidari, B. and Dadkhodaie, A. 2018. Dissection of genotype × environment interactions for mucilage and seed yield in Plantago species: Application of AMMI and GGE biplot analyses. PloS One, 13(5). e0196095. DOI: 10.1371/journal.pone.0196095.
Shiri, M. 2013. Grain yield stability analysis of maize (Zea mays L.) hybrids in different drought stress conditions using GGE biplot analysis. Crop Breeding Journal 3(2): 107-112. DOI: 10.22092/cbj.2012.100456.
Shojaei, S. H., Mostafavi, K., Bihamta, M.R., Omrani, A., Mousavi, S, M. N., Illes. A., Bojtor, C. and Nagy, J. 2022. Stability on maize hybrids based on GGE biplot graphical technique. Agron. 12(2): 394: 1-10. DOI: 10.3390/ agronomy 12020394.
Shojaei, S. H., Mostafavi, K., Omrani, A., Omrani, S., Nasir Mousavi, S. M., Illés, Á., Bojtor, C. and Nagy, J. 2021. Yield stability analysis of maize (Zea mays L.) hybrids using parametric and AMMI methods. Scientifica 2021. 1-9. DOI: 10.1155/2021/5576691.
Shukla, G. K. 1972. Some statistical aspects of partitioning genotype-environmental components of variability. Heredity 29: 237-245. DOI: 10.1038/hdy.1972.87.
Tahmasebi, S., Esmaeilzadeh Moghaddam, M., Tabib Ghaffar, M., Sayyahfar, M., Lotfi Ayeneh, G. and Akbari Moghaddam, H. 2021. Dissection of genotype× environment interaction and assessment of adaptability and grain yield stability of spring bread wheat genotypes. Crop Breeding Journal, 11(2):.11-24. doi: 10.22092/CBJ.2022.357170.1072.
Tahmasebi, S., Heidari, B., Pakniyat, H. and Jalal Kamali, M. R. 2014. Independent and combined effects of heat and drought stress in the Seri M82 × Babax bread wheat population. Plant Breeding 133(6): 702-711. DOI: 10.1111/pbr.12214.
Wrick, E. 1962. Uber eine mehode zur Erfassung der Okologischen streubreite in feld versuchen. A. Pflanzenauecht 47: 92-95.
Yahaya, M. S., Bello, I. and Unguwanrimi, A. Y. 2021. Correlation and path-coefficient analysis for grain yield and agronomic traits of maize (Zea mays L.). Sci. World J. 16(1): 10-13.
Yan, W. 2001. GGE biplot- a windows application for graphical analysis of multi-environment trial data and other types of two-way data. Agron. J. 93: 1111-1118. DOI: 10.2134/agronj2001.9351111x.
Yan, W., Hunt, L. A., Sheng, Q. and Szlavnics, Z. 2000. Cultivar evaluation and mega-environment investigation based on the GGE biplot. Crop Sci. 40: 597-605. DOI: 10.2135/ cropsci2000 .403597x.
Yan, W. and Kang, M. S. 2002. GGE biplot analysis: A graphical tool for breeders, geneticists, and agronomists. CRC press. 286 pp.
Yan, W., Kang, M. S., Ma, B., Wood, S. and Cornelius, P. L. 2007. GGE biplot vs. AMMI analysis of genotype-by-environment data. Crop Sci. 47: 643-655.
Yan, W. and Tinker, N. A. 2005. An integrated biplot analysis system for displaying, interpreting and exploring genotype× environment interaction. Crop Science 45(3): 1004-1016. DOI:10.2135/cropsci2004.0076.
Zhang, H., Gou, X., Ma, L., Zhang, X., Qu, J., Wang, X., Huang, W., Yan, S., Zhang, X., Xue, J. and Xu, S. 2024. Reveal the kernel dehydration mechanisms in maize based on proteomic and metabolomic analysis. BMC Plant Biol. 24(1): 1-15. DOI: 10.1186/s12870-023-04692-z. | ||
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