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GGE Biplot Analysis of Multi-Environment Yield Trials in Barley (Hordeum vulgare L.) Cultivars

Year 2016, Volume: 2 Issue: 1, 90 - 99, 01.01.2016

Abstract

IdentiŞcation of the genetic stability and adaptation of released varieties are very important for breeding programs. Genotype x Environment Interaction (GEI) is extensively observed by breeders as differential ranking of variety yields among environments or years. Therefore, four spring barley varieties, registered in different years, were evaluated at eight environments in different years. The experiments were performed according to a complete randomized block design with four replications. Stability and genotypic superiority for yield was determined using ANOVA and GGE biplot analysis. Genotype x environment interaction was found to be highly signiŞcant (P < 0.01) for grain yield. The GGE biplot indicated that three mega-environment were occurred in terms of varieties. Kendal and Altikat, took place in same mega-environment, while Samyeli in the second, Sahin 91 in third. On the other hand, Kendal and Altikat showed general adaptability (E1, E2, E5, E7 and E8), while Samyeli and Sahin 91 exhibited speciŞc adaptation to E4 and E3 respectively. Considering both techniques, Samyeli and Sahin 91 came forward with low yielding, while Kendal and Altikat with high yielding and stability. Results indicated that GGE biplot is illuminant methods to discover stability and adaptation pattern of varieties in practical recommendations

References

  • Allard RW and Bradshaw AD (1964). Implication of genotype-environmental interaction in applied plant breeding. Crop Sci 5: 503-506
  • Brar KS, Singh P, Mittal VP, Singh P, Jakhar ML, Yadav Y, Sharma MM, Shekhawat US & Kumar C (2010). GGE biplot analysis for visualization of mean performance and stability for seed yield in taramira at diverse locations in India. Jo of Oilseed Brassica. 1(2): 66-74.
  • Ceccarelli S (1989). Wide adaptation: How wide. Euphytica. 40: 197-205
  • Comstock RE and Moll RH (1963). G x E interactions. Symposium on Statistical Genetics and Plant Breeding. National Academy Science National Research Council. Washington. D.C.. pp: 164-196
  • Dash SS and Pandey A (2009). Genetic variability and association of yield and its components in toria, Brassica rapa L. var toria germplasm. J. Oilseeds Res. (Special issue) 26: 53-55.
  • Eberhart SA and Russel WA (1966). Stability parameters for comparing varieties. Crop Sci., 6: 36-40.
  • Farshadfar E, Mohammadi M, Aghaee M, Vaisi Z (2012). GGE biplot analysis of genotype × environment interaction in wheat-barley disomic addition lines. Australian Journal of Crop Science, 6(6):1074–1079.
  • Gabriel KR (1971). The biplot graphic display of matrices with application to principal component analysis. Biometrika 58: 453-467
  • Gauch HG and Zobel RW (1997). Identifying megaenvironments and targeting genotypes. Crop., 37:311-326.
  • Kiliç H (2014). Additive main effects and multiplicative interactions (AMMI) analysis of grain yield in barley genotypes across environments, Journal of Agricultural Sciences, 20 (2014) 337-344.
  • (Letta et al. 2008: (Mizrak 1986). Mohammadi and Amri (2011). Singh et al. 2009). Kroonenberg PM (1995). Introduction to biplots for G×E tables. Department of Mathematics, Research Report #51, University of Queensland, 22.
  • Letta TM, Egidio GD and Abinasa M (2008). Analysis of multi-environment yield trials in durum wheat based on GGE-biplot Journal of Food, Agriculture and Environment Vol.6 (2): 217 -221
  • Mizrak G (1986). Climate zones in Turkey. The Center of Agricultural Research. Technical Publication. No. 2. Ankara.
  • Mohammadi R and Amri A (2011). Graphic analysis of trait Relations and genotype evaluation in durum wheat, Journal of Crop Improvement, 25:680–696.
  • Singh MM, Shekhar RR and Dixit RK (2009). Genetic variability and character association in Indian mustard, (Brassica juncea) .J. Oilseeds Res 26: 56-57.
  • Yan W L, Hunt A, Sheng Q and Szlavnics Z (2000). Cultivar evaluation and mega-environment investigation based on the GGE biplot. Crop Sci. 40: 597-605.
  • Yan W (2001). GGE biplot-a windows application for graphical analysis of multi-environment trial data and other types of two-way data. Agronomy J. 93. 1-11.
  • Yan W (2002). Singular value partition for biplot analysis of multi-environment trial data Agron. J., 94: 990-96.
  • Yan W and Kang MS (2003). GGE biplot analysis: A graphical tool for breeders, geneticists and agronomists. CRC Press, Boca.
  • Yan W S, Kang M, Baoluo M, Woods S & Cornelius PL (2007). GGE Biplot vs. AMMI Analysis of genotype-by-environment data. Crop Sci 47: 643-653.
  • Yan W and Rajcanw I (2002). Biplot analysis of test sites and trait relations of soybean in Ontario. Crop Science. 42. 11-20. doi:10.2135/cropsci2002.0011-17
  • Yan W and Tinker NA (2006). An Biplot analysis of multi-environment trial data; Principles and applications. Canadian Journal of Plant Science 86. 623-645.
Year 2016, Volume: 2 Issue: 1, 90 - 99, 01.01.2016

Abstract

References

  • Allard RW and Bradshaw AD (1964). Implication of genotype-environmental interaction in applied plant breeding. Crop Sci 5: 503-506
  • Brar KS, Singh P, Mittal VP, Singh P, Jakhar ML, Yadav Y, Sharma MM, Shekhawat US & Kumar C (2010). GGE biplot analysis for visualization of mean performance and stability for seed yield in taramira at diverse locations in India. Jo of Oilseed Brassica. 1(2): 66-74.
  • Ceccarelli S (1989). Wide adaptation: How wide. Euphytica. 40: 197-205
  • Comstock RE and Moll RH (1963). G x E interactions. Symposium on Statistical Genetics and Plant Breeding. National Academy Science National Research Council. Washington. D.C.. pp: 164-196
  • Dash SS and Pandey A (2009). Genetic variability and association of yield and its components in toria, Brassica rapa L. var toria germplasm. J. Oilseeds Res. (Special issue) 26: 53-55.
  • Eberhart SA and Russel WA (1966). Stability parameters for comparing varieties. Crop Sci., 6: 36-40.
  • Farshadfar E, Mohammadi M, Aghaee M, Vaisi Z (2012). GGE biplot analysis of genotype × environment interaction in wheat-barley disomic addition lines. Australian Journal of Crop Science, 6(6):1074–1079.
  • Gabriel KR (1971). The biplot graphic display of matrices with application to principal component analysis. Biometrika 58: 453-467
  • Gauch HG and Zobel RW (1997). Identifying megaenvironments and targeting genotypes. Crop., 37:311-326.
  • Kiliç H (2014). Additive main effects and multiplicative interactions (AMMI) analysis of grain yield in barley genotypes across environments, Journal of Agricultural Sciences, 20 (2014) 337-344.
  • (Letta et al. 2008: (Mizrak 1986). Mohammadi and Amri (2011). Singh et al. 2009). Kroonenberg PM (1995). Introduction to biplots for G×E tables. Department of Mathematics, Research Report #51, University of Queensland, 22.
  • Letta TM, Egidio GD and Abinasa M (2008). Analysis of multi-environment yield trials in durum wheat based on GGE-biplot Journal of Food, Agriculture and Environment Vol.6 (2): 217 -221
  • Mizrak G (1986). Climate zones in Turkey. The Center of Agricultural Research. Technical Publication. No. 2. Ankara.
  • Mohammadi R and Amri A (2011). Graphic analysis of trait Relations and genotype evaluation in durum wheat, Journal of Crop Improvement, 25:680–696.
  • Singh MM, Shekhar RR and Dixit RK (2009). Genetic variability and character association in Indian mustard, (Brassica juncea) .J. Oilseeds Res 26: 56-57.
  • Yan W L, Hunt A, Sheng Q and Szlavnics Z (2000). Cultivar evaluation and mega-environment investigation based on the GGE biplot. Crop Sci. 40: 597-605.
  • Yan W (2001). GGE biplot-a windows application for graphical analysis of multi-environment trial data and other types of two-way data. Agronomy J. 93. 1-11.
  • Yan W (2002). Singular value partition for biplot analysis of multi-environment trial data Agron. J., 94: 990-96.
  • Yan W and Kang MS (2003). GGE biplot analysis: A graphical tool for breeders, geneticists and agronomists. CRC Press, Boca.
  • Yan W S, Kang M, Baoluo M, Woods S & Cornelius PL (2007). GGE Biplot vs. AMMI Analysis of genotype-by-environment data. Crop Sci 47: 643-653.
  • Yan W and Rajcanw I (2002). Biplot analysis of test sites and trait relations of soybean in Ontario. Crop Science. 42. 11-20. doi:10.2135/cropsci2002.0011-17
  • Yan W and Tinker NA (2006). An Biplot analysis of multi-environment trial data; Principles and applications. Canadian Journal of Plant Science 86. 623-645.
There are 22 citations in total.

Details

Other ID JA35ZK93PT
Journal Section Articles
Authors

Enver Kendal This is me

Publication Date January 1, 2016
Published in Issue Year 2016 Volume: 2 Issue: 1

Cite

APA Kendal, E. (2016). GGE Biplot Analysis of Multi-Environment Yield Trials in Barley (Hordeum vulgare L.) Cultivars. Ekin Journal of Crop Breeding and Genetics, 2(1), 90-99.
AMA Kendal E. GGE Biplot Analysis of Multi-Environment Yield Trials in Barley (Hordeum vulgare L.) Cultivars. Ekin Journal. January 2016;2(1):90-99.
Chicago Kendal, Enver. “GGE Biplot Analysis of Multi-Environment Yield Trials in Barley (Hordeum Vulgare L.) Cultivars”. Ekin Journal of Crop Breeding and Genetics 2, no. 1 (January 2016): 90-99.
EndNote Kendal E (January 1, 2016) GGE Biplot Analysis of Multi-Environment Yield Trials in Barley (Hordeum vulgare L.) Cultivars. Ekin Journal of Crop Breeding and Genetics 2 1 90–99.
IEEE E. Kendal, “GGE Biplot Analysis of Multi-Environment Yield Trials in Barley (Hordeum vulgare L.) Cultivars”, Ekin Journal, vol. 2, no. 1, pp. 90–99, 2016.
ISNAD Kendal, Enver. “GGE Biplot Analysis of Multi-Environment Yield Trials in Barley (Hordeum Vulgare L.) Cultivars”. Ekin Journal of Crop Breeding and Genetics 2/1 (January 2016), 90-99.
JAMA Kendal E. GGE Biplot Analysis of Multi-Environment Yield Trials in Barley (Hordeum vulgare L.) Cultivars. Ekin Journal. 2016;2:90–99.
MLA Kendal, Enver. “GGE Biplot Analysis of Multi-Environment Yield Trials in Barley (Hordeum Vulgare L.) Cultivars”. Ekin Journal of Crop Breeding and Genetics, vol. 2, no. 1, 2016, pp. 90-99.
Vancouver Kendal E. GGE Biplot Analysis of Multi-Environment Yield Trials in Barley (Hordeum vulgare L.) Cultivars. Ekin Journal. 2016;2(1):90-9.