Abstract
Multi-environment trials have a fundamental role in the selection of the best genotypes across different environments before its commercial release. This study was carried out to identify high-yielding stable sunflower hybrids using the graphical method of the GGE biplot. For this purpose, 11 new hybrids along with four hybrid cultivars were evaluated in a randomized complete block design with four replications across 8 environments (combination of years and locations) during the 2018–2020 growing seasons. The mean oil yield of the environments varied from 833 kg ha−1 in E4 to 1565 kg ha−1 in E5 and the oil yield of hybrids ranged from 1085 kg ha−1 in hybrid H9 to 1565 kg ha−1 in hybrid H8. The results indicated that genotype (G), environment (E) and genotype × environment (G × E) effects were significant for oil yield. The G, E, and G × E interaction effects accounted for 64.83, 11.86, and 23.31% of the total variation, respectively. Results of biplot analysis showed that the first and second principal components accounted for 45.9% and 20.4%, respectively, and in total 66.3% of oil yield variance. GGE biplot analysis indicated two major mega-environments of sunflower testing locations in Iran. Based on the hypothetical ideal genotype biplot, the hybrids H3 and H5 were better than the other hybrids in terms of oil yield and stability, which had the highest general adaptation to all of the environments. Based on the ideal genotype from the most desirable to the most undesirable the hybrids were ranked as follows: H5 > H3 > H8 > H14 > H6 > H2 > H13 > H12 > H10 > H11 > H1 > H7 > H4 > H15 > H9. Furthermore, ranking of the environments based on the ideal environment introduced Sari as the best environment. Therefore, Sari can be used as a suitable test location for selecting superior sunflower hybrids in Iran.
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References
Aarthi S, Suresh J, Leela N, Prasath D (2020) Multi environment testing reveals genotype-environment interaction for curcuminoids in turmeric (Curcuma longa L.). Ind Crops Prod 145:112090
Alizadeh B, Rezaizad A, Hamedani MY, Shiresmaeili G, Nasserghadimi F, Khademhamzeh HR, Gholizadeh A (2021) Genotype × environment interactions and simultaneous selection for high seed yield and stability in winter rapeseed (Brassica napus) multi-environment trials. Agric Res 10:1–12
Balalić I, Zorić M, Branković G, Terzić S, Crnobarac J (2012) Interpretation of hybrid × sowing date interaction for oil content and oil yield in sunflower. Field Crops Res 137:70–77
Da Cruz DP, de Amaral GG, Vivas M, Entringer GC, Rocha RS, da Costa Jaeggi MEP, Gravina LM, Pereira IM, do Amaral Junior AT, de Moraes R, (2020) Analysis of the phenotypic adaptability and stability of strains of cowpea through the GGE Biplot approach. Euphytica 216:1–11
Dallo SC, Zdziarski AD, Woyann LG, Milioli AS, Zanella R, Conte J, Benin G (2019) Across year and year-by-year GGE biplot analysis to evaluate soybean performance and stability in multi-environment trials. Euphytica 215:1–12
Darvishzadeh R, Maleki HH, Sarrafi A (2011) Path analysis of the relationships between yield and some related traits in diallel population of sunflower (Helianthus annuus L.) under well-watered and water-stressed conditions. Aust J Crop Sci 5:674–680
Dehghani MR, Majidi MM, Mirlohi A, Saeidi G (2016) Integrating parametric and non-parametric measures to investigate genotype× environment interactions in tall fescue. Euphytica 208:583–596
Dia M, Wehner TC, Arellano C (2016) Analysis of genotype × environment interaction (G×E) using SAS programming. Agron J 108:1838–1852
Ebdon J, Gauch JH (2002) Additive main effect and multiplicative interaction analysis of national turfgrass performance trials: II. Cultivar Recommendations Crop Sci 42:497–506
Eberhart ST, Russell W (1966) Stability parameters for comparing varieties 1. Crop Sci 6:36–40
FAO (2019) Agricultural production year book. Rome. Italy. Available at: http://faostat3.fao.org
Gauch JH (2006) Statistical analysis of yield trials by AMMI and GGE. Crop Sci 46:1488–1500
Gauch JH, Zobel RW (1997) Identifying mega-environments and targeting genotypes. Crop Sci 37:311–326
Gerrish BJ, Ibrahim AM, Rudd JC, Neely C, Subramanian NK (2019) Identifying mega-environments for hard red winter wheat (Triticum aestivum L.) production in Texas. Euphytica 215:1–9
Ghaffari M, Andarkhor SA, Homayonifar M, Ahmadi SAK, Shariati F, Jamali H, Rahmanpour S (2020) Agronomic attributes and stability of exotic sunflower hybrids in Iran. Helia 43:67–81
Gholizadeh A, Dehghani H (2016) Graphic analysis of trait relations of Iranian bread wheat germplasm under non-saline and saline conditions using the biplot method. Genetika 48:473–486
Gholizadeh A, Dehghani H, Khodadadi M (2019) Quantitative genetic analysis of water deficit tolerance in coriander through physiological traits. Plant Genet Resour 17:255–264
Gholizadeh A, Dehghani H, Khodadadi M, Gulick PJ (2018) Genetic combining ability of coriander genotypes for agronomic and phytochemical traits in response to contrasting irrigation regimes. Plos one 13:e0199630
Gholizadeh A, Khodadadi M, Sharifi-Zagheh A (2021) Modeling the final fruit yield of coriander (Coriandrum sativum L.) using multiple linear regression and artificial neural network models. Arch Agron Soil Sci. 1–15
Hamidou M, Souleymane O, Ba MN, Danquah EY, Kapran I, Gracen V, Ofori K (2019) Identification of stable genotypes and genotype by environment interaction for grain yield in sorghum (Sorghum bicolor L. Moench). Plant Genet Resour 17:81–86
Hassani M, Heidari B, Dadkhodaie A, 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
Jamshidmoghaddam M, Pourdad SS (2013) Genotype× environment interactions for seed yield in rainfed winter safflower (Carthamus tinctorius L.) multi-environment trials in Iran. Euphytica 190:357–369
Jia C, Wang F, Yuan J, Zhang Y, Zhao Z, Abulizi B, Wen X, Kang M, Tang F (2020) Screening and comprehensive evaluation of rice (Oryza sativa L. subsp. japonica Kato) germplasm resources for nitrogen efficiency in Xinjiang. China Plant Genet Resour 18:179–189
Jockovic M, Cvejic S, Jocic S, Marjanovic-Jeromela A, Miladinovic D, Jockovic B, Miklic V, Radic V (2019) Evaluation of sunflower hybrids in multi-environment trial (MET). Turkish J Field Crop 24:202–210
Luquez J, Aguirrezabal L, Agüero M, Pereyra V (2002) Stability and adaptability of cultivars in non-balanced yield trials. Comparison of methods for selecting ‘high oleic’sunflower hybrids for grain yield and quality. J Agron Crop Sci 188:225–234
Malla S, Ibrahim AM, Little R, Kalsbeck S, Glover KD, Ren C (2010) Comparison of shifted multiplicative model, rank correlation, and biplot analysis for clustering winter wheat production environments. Euphytica 174:357–370
Mohammadi R, Amri A (2013) Genotype× environment interaction and genetic improvement for yield and yield stability of rainfed durum wheat in Iran. Euphytica 192:227–249
Omoigui LO, Ajeigbe HA, Akinwale RO, Timko MP, Oyekunle M, Bello LL (2017) Performance of cowpea varieties under Striga gesnerioides (Willd.) Vatke infestation using biplot analysis. Euphytica 213:1–16
Rakshit S, Ganapathy K, Gomashe S, Rathore A, Ghorade R, Kumar MN, Ganesmurthy K, Jain S, Kamtar M, Sachan J (2012) GGE biplot analysis to evaluate genotype, environment and their interactions in sorghum multi-location data. Euphytica 185:465–479
SAS (2003) SAS 9.1 (version SAS 9 1. 3, Service Pack 3). Cary (NC): SAS Institute Inc
Sserumaga JP, Oikeh SO, Mugo S, Asea G, Otim M, Beyene Y, Abalo G, Kikafunda J (2016) Genotype by environment interactions and agronomic performance of doubled haploids testcross maize (Zea mays L.) hybrids. Euphytica 207:353–365
Tai GC (1971) Genotypic stability analysis and its application to potato regional trials. Crop Sci 11:184–190
Ullah I, Ayub M, Khan MR, Ashraf M, Mirza M, Yousaf M (2007) Graphical analysis of multi-environment trial (MET) data in sunflower (Helianthus annuus L.) through clustering and GGE biplot technique. Pak J Bot 39:1639–1646
Vaezi B, Pour-Aboughadareh A, Mohammadi R, Mehraban A, Hossein-Pour T, Koohkan E, Ghasemi S, Moradkhani H, Siddique KH (2019) Integrating different stability models to investigate genotype× environment interactions and identify stable and high-yielding barley genotypes. Euphytica 215:1–18
Yan W (2001) GGEbiplot—A Windows application for graphical analysis of multi-environment trial data and other types of two-way data. Agron J 93:1111–1118
Yan W (2015) Mega-environment analysis and test location evaluation based on unbalanced multiyear data. Crop Sci 55:113–122
Yan W, Hunt L (2001) Interpretation of genotype× environment interaction for winter wheat yield in Ontario. Crop Sci 41:19–25
Yan W, Kang MS (2003) GGE biplot analysis: A graphical tool for breeders, geneticists, and agronomists. CRC Press, Boca Raton
Yan W, Tinker NA (2006) Biplot analysis of multi-environment trial data: principles and applications. Can J Plant Sci 86:623–645
Yan W, Hunt LA, Sheng Q, Szlavnics Z (2000) Cultivar evaluation and mega-environment investigation based on the GGE biplot. Crop Sci 40:597–605
Yan W, Kang MS, Ma B, Woods S, Cornelius PL (2007) GGE biplot vs. AMMI analysis of genotype-by-environment data. Crop Sci 47:643–653
Acknowledgements
This study was supported by grant and genetic material provision from the Seed and Plant Improvement Institute (SPII), Karaj, Iran. We would like to thank all members of the project who contributed to the implementation of the field work.
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Ghaffari, M., Gholizadeh, A., Andarkhor, S. et al. Stability and genotype × environment analysis of oil yield of sunflower single cross hybrids in diverse environments of Iran. Euphytica 217, 187 (2021). https://doi.org/10.1007/s10681-021-02921-w
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DOI: https://doi.org/10.1007/s10681-021-02921-w