Investigation of Genotype × Environment Interaction in Some Sunflower (Helianthus annuus L.) Genotypes in Different Environmental Conditions
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https://doi.org/10.5281/zenodo.7642289Keywords:
Sunflower, hibrid, seed yield, oil ratio, interactionAbstract
Trials in different environmental conditions have a fundamental role in selecting genotypes that perform best in different environments. Adana and Muş locations can be considered as a new test environment for sunflower breeders in terms of performance evaluation of some sunflower genotypes. This study was carried out in Adana and Muş ecological conditions in 2022 with 14 hybrid lines and 5 standard varieties according to Randomized Complete Block Design. According to the results of analysis of variance, genotype, location and genotype×location interaction were found statistically significant at 1% and 5% levels in terms of many traits. According to the average results of both locations in the study, plant height of genotypes is 139.0-179.0 cm, diameter 18.0 -22.8 cm, 1000 seed weight 59.3-83.0 g, seed yield 2198 - 4144 kg ha-1, oil ratio 38.1-41.3 (%) and protein ratio ranged from 16.8 to 18.2 (%). In the GGE biplot technique, PC1 constituted 58.84% of the variation, PC2 constituted 41.16% and 100% of the variation in total. As a result, according to the findings obtained in the research; H1, H10 and H14 genotypes stand out in terms of oil ratio, H6, H18 and H3 genotypes in terms of seed yield and H9 and H11 genotypes in terms of both criteria. When the yield and quality traits of genotypes in Adana and Muş locations were evaluated together, it was concluded that H8 and H13 genotypes could be recommended for both locations.
References
Aarthi, S., Suresh, J., Leela, N. K., Prasath, D., 2020. Multi environment testing reveals genotype-environment interaction for curcuminoids in turmeric (Curcuma longa L.). Industrial Crops and Products, 145: 112090.
Alizadeh, B., Rezaizad, A., Hamedani, M.Y., Shiresmaeili, G., Nasserghadimi, F., Khademhamzeh, H.R., Gholizadeh, A., 2022. Genotype × environment interactions and simultaneous selection for high seed yield and stability in Winter Rapeseed (Brassica napus L.) multi-environment trials. Agricultural Research, 11(2): 185-196.
Andrianasolo, F.N., Casadebaig, P., Langlade, N., Debaeke, P., Maury, P., 2016. Effects of plant growth stage and leaf aging on the response of transpiration and photosynthesis to water deficit in sunflower. Functional Plant Biology, 43(8): 797-805.
Ansarifard, I., Mostafavi, K., Khosroshahli, M., Reza Bihamta, M., Ramshini, H., 2020. A study on genotype–environment interaction based on GGE biplot graphical method in sunflower genotypes (Helianthus annuus L.). Food Science & Nutrition, 8(7): 3327-3334.
Anonim, 2022. Turkey oil sunflower production statistics. Access link: https://biruni.tuik.gov.tr/medas/?kn=92&locale=tr (Accessed: 10.09.2022)
AOAC, 2005. Official methods of analysis of the AOAC, 18th ed. Methods 990.03 Association of Official Analytical Chemists. Arlington, VA, USA.
Atabey, S., Toprak, Z.F., 2018. Long-term temperature change comparison of Bitlis and Muş provinces within the framework of climate change. Dicle University Engineering Faculty Journal of Engineering, 9(1): 419-428.
Balalić, I., Branković, G., Zorić, M., Miklič, V., Jocić, S., Šurlan-Momirović, G., 2013. Sunflower mega-environments in Serbia revealed by GGE biplot analysis. Ratarstvo i povrtarstvo, 50(2): 20-27.
Çetin, K., Öztürk, Ö., 2018. Determination of yield and yield characteristics of some hybrid sunflower cultivars. Selcuk Journal of Agriculture and Food Sciences, 32(3): 282-288.
Dalló, S.C., Zdziarski, A.D., Woyann, L. G., Milioli, A.S., 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(6): 1-12.
da Cruz, D.P., de Amaral Gravina, G., Vivas, M., Entringer, G.C., Rocha, R. S., da Costa Jaeggi, M.E.P., Daher, R.F., 2020. Analysis of the phenotypic adaptability and stability of strains of cowpea through the GGE Biplot approach. Euphytica, 216(10): 1-11.
FAOSTAT, 2022. World oil sunflower production statistics. Access link: https://www.fao.org/faostat/en/#data/QCL/visualize (Accessed: 10.09.2022)
Gauch Jr, H.G., 2006. Statistical analysis of yield trials by AMMI and GGE. Crop Science, 46(4): 1488-1500.
Ghaffari, M., Gholizadeh, A., Andarkhor, S. A., Zareei Siahbidi, A., Kalantar Ahmadi, S. A., Shariati, F., Rezaeizad, A., 2021. Stability and genotype× environment analysis of oil yield of sunflower single cross hybrids in diverse environments of Iran. Euphytica, 217(10): 1-11.
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(2): 473-486.
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. Archives of Agronomy and Soil Science, 1-15.
Gholizadeh, A., Ghaffari, M., Jabbari, H., Cheshmehnoor, M., Nadali, F., Payghamzadeh, K., Kia, S., 2022. Evaluation of Genotype × environment interaction for seed yield of sunflower hybrids using GGE biplot method. Journal of Crop Breeding, 14(41): 194-204.
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(4): 1-21.
Jocković, M., Cvejić, S., Jocić, S., Marjanović-Jeromela, A., Miladinović, D., Jocković, B., Radić, V., 2019. Evaluation of sunflower hybrids in multi-environment trial (MET). Turkish Journal of Field Crops, 24(2): 202-210.
Kaya, Y., Atakişi, İ.K. 2002. Stability analysis in different yield characters in sunflower (Helianthus annuus L.). ANADOLU Journal of Aegean Agricultural Research Institute, 12(2): 1-20.
Kaya, Y., Evci, G., Pekcan, V., Gücer, T., Yılmaz, M.İ., 2009. The determination relationships between oil yield and some yield traits in sunflower. Journal of Agricultural Sciences, 15(04): 310-318.
Kendal, E., 2022. Using Biplot Analysis Technique to Selection in Tritikale Breeding Studies. Yuzuncu Yıl University Journal of Agricultural Sciences, 32(1): 186-198.
Kendal, E., Sayar, M.S., 2016. The stability of some spring triticale genotypes using biplot analysis. JAPS: Journal of Animal & Plant Sciences, 26(3):10-22.
Khomari, A., Mohammadi, A., 2017. Stability study of yield in sunflower (Helianthus annuus L.) cultivars using AMMI method. Journal of Crop Breeding, 9(23): 117-124.
Lu´ quez, J.E., Aguirrezabal, L.A.N., Agüero, M.E., Pereyra, V.R. 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. Journal of Agronomy and Crop Science, 188(4): 225-234.
Malla, S., Ibrahim, A.M., Little, R., Kalsbeck, S., Glover, K.D., Ren, C., 2010. Comparison of shifted multiplicative model, rank correlation, and biplot analysis for clustering winter wheat production environments. Euphytica, 174(3): 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(2): 227-249.
Movahedi, H., Mostafavi, K., Shams, M., Golparvar, A.R. 2020. AMMI analysis of genotype× environment interaction on grain yield of sesame (Sesamum indicum L.) genotypes in Iran. Biotechnology & Biotechnological Equipment, 34(1): 1013-1018.
Mousavi, S.M.N., Hejazi, P., Khalkhali, S.K.Z., 2016. Study on stability of grain yield sunflower cultivars by AMMI and GGE biplot in Iran. Molecular Plant Breeding, 7(2): 1-6.
Olanrewaju, O.S., Oyatomi, O., Babalola, O.O., Abberton, M., 2021. GGE Biplot analysis of genotype× environment interaction and yield stability in bambara groundnut. Agronomy, 11(9): 1839.
Omoigui, L.O., Ajeigbe, H.A., Akinwale, R.O., Timko, M.P., Oyekunle, M., Bello, L.L., 2017. Performance of cowpea varieties under striga gesnerioides (Willd.) vatke infestation using biplot analysis. Euphytica, 213(11): 1-16.
Rakshit, S., Ganapathy, K.N., Gomashe, S.S., Rathore, A., Ghorade, R.B., Kumar, M.V., Patil, J.V., 2012. GGE biplot analysis to evaluate genotype, environment and their interactions in sorghum multi-location data. Euphytica, 185(3): 465-479.
Saremi-Rad, A., Mostafavi, K., Mohammadi, A., 2020. Genotype-environment interaction study base GGE biplot method for kernel yield in sunflower (Helianthus annuus L.) cultivars. Journal of Crop Breeding, 12(34): 43-53.
Sefaoğlu, F., Kaya, C., 2018. The adaptation and yield components of oil sunflower (Helianthus annuus L.) genotypes under Erzurum ecological conditions. Turkish Journal of Agricultural and Natural Sciences, 5(3): 222-230.
Seiler, G.J., Qi, L.L., Marek, L.F. 2017. Utilization of sunflower crop wild relatives for cultivated sunflower improvement. Crop Science, 57(3): 1083-1101.
Sserumaga, J.P., Oikeh, S.O., Mugo, S., Asea, G., Otim, M., Beyene, Y., Kikafunda, J., 2016. Genotype by environment interactions and agronomic performance of doubled haploids testcross maize (Zea mays L.) hybrids. Euphytica, 207(2): 353-365.
TTSM, 2001. Sunflower technical instruction. Ankara, 2001.
Yan, W., 2015. Mega‐environment analysis and test location evaluation based on unbalanced multiyear data. Crop Science, 55(1): 113-122.
Yan, W., Hunt, L.A. 2001. Interpretation of genotype× environment interaction for winter wheat yield in Ontario. Crop Science, 41(1): 19-25.
Yan, W., Hunt, L. A., Sheng, Q., Szlavnics, Z., 2000. Cultivar evaluation and mega‐environment investigation based on the GGE biplot. Crop science, 40(3): 597-605.
Yan, W., Rajcan, I., 2002. Biplot analysis of test sites and trait relations of soybean in Ontario. Crop science, 42(1): 11-20.
Yan, W., Tinker, N.A., 2006. Biplot analysis of multi-environment trial data: Principles and applications. Canadian journal of plant science, 86(3): 623-645.
Xu, N.Y., Fok, M., Zhang, G.W., Jian, L.I., Zhou, Z.G., 2014. The application of GGE biplot analysis for evaluat ng test locations and mega-environment investigation of cotton regional trials. Journal of Integrative Agriculture, 13(9): 1921-1933.
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