Analysis of genotype x environment interaction for white sugar yield in new sugar beet hybrids

Document Type : Scientific - Research

Authors

1 Assistant Professor of Sugar Beet Seed Institute (SBSI) - Agricultural Research Education and Extension, Karaj,Iran

2 Agricultural and Natural Resources Research Center of Khorasan Razavi, Agricultural Research, Education and Extension Organization (AREEO), Iran

3 Assistant Professor of Sugar Beet Research Department, West Azarbayjan Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (ARREO). Urmia, Iran.

4 Assistant professor of Sugar Beet Research Department, Hamedan Agricultural and Natural Resources Research and Education Center (AREEO), Hamedan, Iran.

5 Instructor of Agricultural and Natural Resources Research Center Fars, Iran.

6 Associate professor of Sugar Beet Research Department, Kermanshah Agricultural and Natural Resources Research and Education Center (AREEO), Kermanshah, Iran.

7 Professor of Sugar Beet Seed Institute (SBSI) - Agricultural Research Education and Extension, Karaj,Iran

Abstract

The quality and productivity of sugar obtained from sugar beet is affected by genotype, environment and agronomic management. This study aimed to analyze the stability and adaptability of 15 new sugar beet genotypes for white sugar yield and adaptability. The hybrids were developed by crossing rhizomania resistant single-crosses with six rhizoctonia resistant pollinators including two national and three foreign checks using a randomized complete block design with four replications. Trials were performed at research stations of Agricultural Research Centers in four regions including Karaj, Mashhad, Miandoab, and Hamedan. To analyze the stability and the effect of genotype × environment interaction, GGE-biplot graphical method was applied. Evaluation of hybrids in Mashhad area indicating their response to resistance rhizomania disease. Results of the combined analysis of variance showed a significant differences among varieties for white sugar yield. The main effects of environment, genotype × environment interaction, and genotype defined 51.7, 9.5 and 9.0% of the total variations, respectively. The correlation between environments showed that the environments were different in terms of ranking and adaptability of genotypes. The highest white sugar yield was achieved in Miandoab, followed by Karaj, Mashhad and Hamedan, respectively. There was a positive correlation between Hamedan and Midandoab, while a negative correlation was observed between Mashhad and Karaj. Based on the GGE biplot model, genotypes G15, G7 and G10 are highly stable with high sugar yield production across the environments.

Keywords

Main Subjects


Bishwas KC, Poudel MR, Regmi D. AMMI and GGE biplot analysis of yield of different elite wheat lines under terminal heat stress and irrigated environments. Heliyon. 2021; 7(6): 07206. doi:10.1016/j.heliyon.2021.e07206.
FAO. http://www.fao.org/faostat/en/#data/FBS [last visited on 23/12/2022]. 2022.
Fasahat P, Hosseinpour M, Kakueinezhad M, Townson P. Physiological and Molecular Aspects of Sucrose Accumulation in Sugar Beet. In: Sugar Beet Cultivation, Management and Processing, Singapore: Springer Nature Singapore, 2022; pp. 27-48. doi:10.1007/978-981-19-2730-0_3.
Fasahat P, Muhammad K, Abdullah A, Rahman BMA, Siing NM, Gauch JHG, Ratnam W. Genotype× environment assessment for grain quality traits in rice. Communications in Biometry and Crop Science. 2014; 9(2): 71-82.
Fasahat P, Rajabi A, Mahmoudi SB, Noghabi MA and Rad JM. An Overview on the Use of Stability Parameters in Plant Breeding. Biometrics & Biostatistics International Journal. 2015; 2(5): 1-11. doi:10.15406/bbij.2015.02.00043.
Fasahat P, Rajabi A, Rad JM and Derera J. Principles and utilization of combining ability in plant breeding. Biometrics & Biostatistics International Journal. 2016; 4(1): 1-24. doi:10.15406/bbij.2016.04.00085.
Fasahat P, Rezaei J, Sharifi M, Azizi H, Fotouhi K, Mahdikhani P, Pedram A, Jalilian A, Babaei B. Assessment of Root and White Sugar Yield Stability of Sugar Beet Genotypes. Seed and Plant Journal. 2022; 38(2): 223-237. doi:10.22092/spj.2023.361320.1297.
Hassani M, Heidari B, Dadkhodaie A and Stevanato P. Genotype by environment interaction components underlying variations in root, sugar and white sugar yield in sugar beet (Beta vulgaris L.). Euphytica. 2018; 214: 1-21. doi:10.1007/s10681-018-2160-0.
Hoffmann CM, Huijbregts T, van Swaaij N, Jansen R. Impact of different environments in Europe on yield and quality of sugar beet genotypes. European Journal of Agronomy. 2009; 30(1): 17-26. doi:10.1016/j.eja.2008.06.004.
Javidfar F, Alizadeh B, Amiri OH, Sabaghnia N. Study on genotype×environment interaction in rapeseed genotypes by GGE biplot method. Iranian Journal of Crop Science. 2011; 41(4): 771-779. [In Persian]
Luterbacher MC, Asher MJC, Beyer W, Mandolino G, Scholten OE, Frese L, Biancardi E, Stevanato P, Mechelke W, Slyvchenko O. Sources of resistance to diseases of sugar beet in related Beta germplasm: II. Soil-borne diseases. Euphytica. 2005; 141: 49-63. doi:10.1007/s10681-005-5231-y.
Meng Y, Ren P, Ma X, Li B, Bao Q, Zhang H, Wang J, Bai J, Wang H. GGE biplot-based evaluation of yield performance of barley genotypes across different environments in China. 2016; 533-543.
Mohammadi R, Armion N, Zadhassan E, Eskandari, M. Analysis of genotype × environment interaction for grain yield in rainfed durum wheat. Dryland Agriculture. 2014; 2(2): 1-14. [In Persian]
Mostafavi K, Orazizadeh M, Rajabi A. Stability Analysis for Root Yield in Sugar Beet Varieties (Beta Vulgaris) Using Biplot Graphical Method. Journal of Agronomy and Plant Breeding. 2017; 12: 1-13. [In Persian]
Niazian M, Amiri R, Mortazavian SM, Rajabi A and Orazizadeh MR. Genetical analysis for yield traits in tropical beet using of GGE-biplot analysis of diallel cross data. Journal of Crop Breeding. 2009; 1(4): 77-94. doi:10.13140/2.1.1753.0560.
Pourdad SS, Jamshid Moghaddam, M. Study on genotype×environment interaction through gge biplot for seed yield in spring rapeseed (Brassica napus L.) in rain-fed condition. Journal of Crop Breeding, 2013; 5(12): 1-14. [In Persian]
Shojaei SH, Mostafavi K, Bihamta MR, Omrani A, Mousavi SMN, Illés Á, Bojtor C, Nagy J. Stability on Maize Hybrids Based on GGE Biplot Graphical Technique. Agronomy. 2022; 12(2), 394. doi: 10.3390/agronomy12020394.
Yan W. A study on the methodology of cultivar evaluation based on yield trial data- with special reference to winter wheat in Ontario (PhD thesis). University of Guelph, Guelph, Ontario, Canada, 1999.
Yan W. GGE biplot–A windows application for graphical analysis of multi-environment trial data and other types of two-way data. Agronomy Journal. 2001; 93: 1111–1118. doi:10.2134/agronj2001.9351111x.
Yan W, Kang MS, Ma B, Woods S, Cornelius PL. GGE biplot vs. AMMI analysis of genotype-by-environment data. Crop Science. 2007; 47: 643-655. doi:10.2135/cropsci2006.06.0374.
Yan W, Tinker NA. An integrated biplot analysis system for displaying, interpreting and exploring genotype × environment interaction. Crop Science. 2005; 45: 1004-1016. doi:10.2135/cropsci2004.0076.