Stability analysis and genotype×environment interaction study for grain yield of some barley genotypes

Document Type : Research paper

Authors

1 Department of Plant Production and Genetics, Faculty of Agriculture, University of Maragheh, P. O. Box: 55181-83111, Maragheh, Iran.

2 Kohgiluyeh and Boyerahmad Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Yasuj, Iran.

3 Ardabil Agricultural and Natural Resources Research Center, Agricultural Research, Education and Extension Organization (AREEO), Ardebil, Iran.

4 Golestan Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Golestan, Iran.

5 Lorestan Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Khorram-Abad, Iran.

6 Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Ilam, Iran.

Abstract

Analysis of the genotype×environment (GE) interaction of barley (Hordeum vulgare L.) can aid in detecting genotype performance better under diverse and harsh environments. Sixteen advanced breeding lines and two cultivars were tested across five locations at Gachsaran, Gonbad, Ilam, Lorestan and Mughan districts during three years of 2017 to 2019. Stability analysis was determined using 19 different variance and regression methods with 26 univariate statistics because each method explores stability from different aspects and all of them can reflect a comprehensive stability characteristic of genotypes. The result showed that environment, genotype and GE contributed 92, 2 and 8% of the total variation and there is no strongest genetic control. According to the GE sum squares-based parameters, genotypes G13, G12 and G15 were more stable. The coefficient of line slope and residual variance of common and adjusted linear regression, manifested G1, G2, G12 and G18 as the most stable and responsive genotypes. The selective value of genotype (SVG) identified G6, G10 and G11 as the most stable genotypes while G2, G5 and G13 were the most stable genotypes based on superiority measure (SM). According to H parameter, genotypes G2, G13 and G18 were identified as the most stable genotypes while the dynamic CV and dynamic regression introduced G3 and G15 as the most stable genotypes. The relative superiority (RS), proposed G1, G2 and G5 as the most stable genotypes. Finally, H statistic, RS and SM could be recommended for stability analysis in future breeding programs for the simultaneous selection of yield and stability.

Keywords

References

Allard R. W., and Bradshaw A. D. (1964). Implications of genotype-environmental interactions in applied plant breeding 1. Crop Science, 4: 503–508.
Becker H. C. (1981). Correlations among some statistical measures of phenotypic stability. Euphytica, 30: 835–840.
 Dehghani H. (1994). Yield stability analysis of moderate and early maturity of maize. M.S. Thesis. Faculty of Agriculture, Tarbiat Modares University, Tehran, Iran, pp. 121.
Eberhart S. A., and Russell W. A. (1966). Stability parameters for comparing varieties. Crop Science, 6: 36–40.
Emebiri L. C., Matassa V., and Moody D. B. (2005). GENSTAT programs for performing Muir’s alternative partitioning of genotype-by-environment interaction. Journal of Heredity, 96: 78–79.
Faostat (2018). Faostat Data. www.faostat.fao.org.
Faramoushi S., Hatami Maleki H., Vaezi B., and Sabaghnia N. (2018). Interpretation of genotype by environment interaction for barley genotypes via simultaneous selection for yield and stability. Philippine Agricultural Scientist, 101: 333–343.
Finlay K. W., and Wilkinson G. N. (1963). The analysis of adaptation in a plant breeding programme. Australian Journal of Agricultural Research, 14: 742–754.
Flores F., Moreno M. T., and Cubero, J. I. (1998). A comparison of univariate and multivariate methods to analyze environments. Field Crops Research, 56: 271–286.
Francis T. R., and Kanneberg L. W. (1978). Yield stability studies in short-season maize: I. A descriptive method for grouping genotypes. Canadian Journal of Plant Science, 58: 1029–1034.
Freeman G. H., and Perkins J. M. (1971). Environmental and genotype-environmental components of variability VIII. Relations between genotypes grown in different environments and measures of these environments. Heredity, 27: 15–23.
Hanson W. D. (1970). Genotypic stability. Theoretical Applied Genetics, 40: 226–231.
Hussein M. A., Bjornstad A., and Aastveit A. H. (2000). SASG×ESTAB, A SAS program for computing genotype x environment stability statistics. Agronomy Journal, 92: 454–459.
Janmohammadi M., Movahedi Z., and Sabaghnia, N. (2014). Multivariate statistical analysis of some traits of bread wheat for breeding under rainfed conditions. Journal of Agricultural Sciences, 59: 1–14.
Kamidi R. E. (2001). Relative stability, performance, and superiority of crop genotypes across environments. Journal of Agricultural, Biological, and Environmental Statistics, 6: 449–460.
Karimzadeh R., Mohammadi M., Sabaghnia N., and Shefazadeh M. K. (2012). Using Huehn’s nonparametric stability statistics to investigate genotype×environment interaction. Notulae Botanicae Horti Agrobotanici Cluj-Napoca, 40: 293–301.
Kilchevskii A. V., and Khotilova L. V. (1985). A method for assessing genotype adaptive capacity and stability, the environment differentiating ability. Report 1. Validation of the method. Genetika, 21: 1481–1490.
Kobus-Cisowska J., Szulc P., Szczepaniak O., Dziedziński M., Szymanowska D., Szymandera-Buszka K., Goryńska-Goldmann E., Gazdecki M., Telichowska A., and Ligaj M. (2020). Variability of Hordeum vulgare L. cultivars in yield, antioxidant potential, and cholinesterase inhibitory activity. Sustainability, 5: 1938.
Lidansky T., Naidenova N., Vassileva I., and Vassilevska-Ivanova R. (1997). A stability estimation method. Cereal Research Communications, 25: 163–168.
Lidansky T., Vassilevska-Ivanova R., Naidenova N., and Vassileva I. (1998). A regression method of stability estimation. Cereal Research Communications, 26: 337–341.
Lin C. S., and Binns M. R. (1988). A superiority measure of cultivar performance for cultivar×location data. Canadian Journal of Plant Science, 68: 193–198.
Lin C. S., Binns M. R., and Lefkovitch L. P. (1986). Stability analysis: where do we stand? Crop Science, 26: 894–900.
Maniruzzaman I., Begum M. Z., Khan F., Amiruzzaman M. A. A., and Hossain A. (2019). Evaluation of yield stability of seven barley (Hordeum vulgare L.) genotypes in multiple environments using GGE biplot and AMMI model. Open Agriculture, 4: 284–293.
Martynov S. P. (1990). A method for the estimation of crop varieties stability. Biometrical Journal, 32: 887–893.
Mohammadi M., Karimizadeh R., Sabaghnia N., and Shefazadeh M. K. (2013). Estimating genotypic ranks by several nonparametric stability statistics in Barley (Hordeum vulgare L.). Yüzüncü Yıl Üniversitesi Tarım Bilimleri Dergisi, 23: 57–65.
Muir W., Nyquist W. E., and XU S. (1992). Alternative partitioning of the genotype-by environment. Theoretical and Applied Genetics, 84: 193–200.
Paknejad F., Fatemi Rika Z., and Elkaee Dehno M. (2017). Investigation end season drought effect on yield and yield components of ten barley (Hordeum vulgare L.) cultivars in Karaj region. Environmental Stresses in Crop Sciences, 10: 391–401.
Perkins J. M., and Jinks J. L. (1968). Environmental and genotype-environmental components of variability. Heredity, 23: 339–356.
Pinthus J. M. (1973). Estimate of genotype value: a proposed method. Euphytica, 22: 121–123.
Plaisted R. I. (1960). A shorter method for evaluating the ability of selections to yield consistently over locations. American Potato Journal, 37: 166–172.
Plaisted R. I., and Peterson L. C. (1959). A technique for evaluating the ability of selection to yield consistently in different locations or seasons. American Potato Journal, 36: 381–385.
Pour-Aboughadareh A., Barati A., and Koohkan S. A. (2022). Dissection of genotype-by-environment interaction and yield stability analysis in barley using AMMI model and stability statistics. Bulletin of the National Research Centre, 46: 19.
 Ramla D., Yakhou M. S., Bilek N., Hamou M., Hannachi A., Aissat A., and Mekliche-Hanifi L. (2016). Grain yield stability analysis of barley doubled haploid lines in Algerian semi-arid zones. Asian Journal of Crop Science, 8: 43–51.
Sabaghnia N. (2010). Multivariate statistical analysis of genotype×environment interaction in multi-environment trials of breeding programs. Agriculture and Forestry, 56: 19–38.
Sabaghnia N., Dehghani H., Alizadeh B., and Moghaddam M. (2011). Yield analysis of rapeseed (Brassica napus L.) under water-stress conditions using GGE biplot methodology. Journal of Crop Improvement, 25: 26–45.
Sabaghnia N., Karimizadeh R., and Mohammadi M. (2012). Genotype by environment interaction and stability analysis for grain yield of lentil genotypes. Žemdirbystė, 99: 305–312.
Sabaghnia N., Mohammadi M., and Karimizadeh R. (2012). The evaluation of genotype×environment interactions of durum wheat’s yield using of the AMMI model. Agriculture & Forestry, 55: 5–21.
Sabaghnia N., Mohammadi M., and Karimizadeh R. (2013). Yield stability of performance in multi-environment trials of barley (Hordeum vulgare L.) genotypes. Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, 61: 787–793.
Shukla G. K. (1972). Some statistical aspects of partitioning genotype-environmental components of variability. Heredity, 29: 237–245.
SPSS Institute. (2004). SPSS 14. SPSS User’s guide. SPSS Institute, Chicago, IL, USA.
Tai G. C. C. (1971). Genotypic stability analysis and application to potato regional trials. Crop Science, 11: 184–190.
Wricke G. (1962). Über eine Methode zur Erfassung derökologischen Streubreite in Feldversuchen. Zeitschrift Für Pflanzenzüchtung, 47: 92–96.
Iranian Journal of Genetics and Plant Breeding
Volume 9, Issue 2 - Serial Number 18
October 2020
Pages 134-143

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History

  • Receive Date: 01 March 2021
  • Revise Date: 19 April 2022
  • Accept Date: 20 April 2022

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