Research Article
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Year 2017, , 235 - 242, 15.12.2017
https://doi.org/10.17557/tjfc.357424

Abstract

References

  • Akcura, M., Taner, S. and Kaya, Y. 2011. Evaluation of bread wheat genotypes under irrigated multi-environment conditions using GGE biplot analyses. Agriculture, 98(1), 35-40.
  • Akcura, M., Y. Kaya, S. Taner and R. Ayranci. 2006. Parametric stability analyses for grain yield of durum wheat. Plant Soil Environ. 52:254-261.
  • Akcura, M., Y. Kaya and S. Taner. 2005. Genotype-environment ınteraction and phenotypic stability analysis for grain yield of durum wheat in Central Anatolian Region. Turkish J. Agric. For. 29:369-375.
  • Annicchiarico, P. 1997. Joint regression vs. AMMI analysis of genotype-environment interactions for cereals in Italy. Euphytica 94:53-62.
  • Dehghani, H., A. Ebadi and A. Yousefi. 2006. Biplot analysis of genotype x environment interaction for barley yield in Iran. Agron. J. 98: 388-393.
  • Eberhart, S.A. and W.A. Russell. 1966. Stability parameters for comparing varieties. Crop Sci. 6:36-40.
  • Flores, F., M.T. Moreno and J.I. Cubero. 1998. A comparison of univariate and multivariate methods to analyze environments. Field Crop Res. 56:271-286.
  • Francis, T.R. and L.W. Kannenberg. 1978. Yield stability studies in short season maize 1. A descriptive method for grouping genotypes. Can. J. Plant Sci. 58:1029-1034.
  • Gauch, G.H. and Zobel, R.W. 1988. Predictive and postdictive success of statistical analyses of yield trials. Theor. Appl. Genet. 76: 1-10. Jalata, Z. 2011. GGE-biplot analysis of multi-environment yield trials of barley (Hordeum vulgare L.) genotypes in Southeastern Ethiopia highlands Int. J. Plant Breed. Genet. 5(1):59-75.
  • Kandus, M., D. Almorza, R. Boggio Ronceros and J.C. Salerno. 2010. Statistical models for evaluating the genotype-environment interaction in maize (Zea mays L.). Phyton (Buenos Ares) 79:39-45.
  • Kaplan, M. 2005. Effects of different intra and inter row spacing on yield and yield components of second crop silage maize (Zea mays L.) under Kahramanmaras conditions. MSc Thesis, University of Kahramanmaras Sutcu Imam Kahramanmaras Turkey.
  • Kaplan, M., O. Baran, A. Unlukara, H. Kale, M. Arslan, K. Kara, S. Buyukkilic Beyzi, Y. Konca and A. Ulas. 2016. The effects of different nitrogen doses and irrigation levels on yield, nutritive value, fermentation and gas production of corn silage. Turk J. Field Crops 2(1):100-108.
  • Kaya, Y., M. Akcura and S. Taner. 2006. GGE-Biplot analysis of multi-environment yield trials in bread wheat. Turk J. Agric. 30:325-337.
  • McDonald, P. A.R. Henderson and S.J.E. Heron. 1991. The Biochemistry of Silage. Second Edition. 340 p. Chalcombe Publication.
  • Meeske. R., G. Ashbell, Z.G. Weinberg and T. Kipnis. 1993. Ensiling forage sorghum at two stages of maturity with the addition of lactic acid bacterial inoculants. Anim. Feed Sci. Technol. 43:165-175.
  • Nachit, M.M., M.E. Sorrells, R.W. Zobel, H.G. Gauch, R.A. Fischer and W.R. Coffman. 1992. Association of environmental variables with sites’ mean grain yield and components of genotype-environment interaction in durum wheat. J. Gene. Breed Org. 46:369-372.
  • Neylon, J.M. and L. Kung. 2003. Effects of cutting height and maturity on the nutritive value of corn silage for lactating cows. J. Dairy Sci. 86:2163-2169.
  • R Development Core Team. 2008. R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0. http://www.R-project.
  • Rakshit, S., K.N. Ganapathy, S.S. Gomashe, A. Rathore, R.B. Ghorade, M. Kumar, K. Kumar, S.K. Ganesmurthy, M.Y. Jain, J.S. Kamtar, S.S. Sachan, B.R. Ambekar, D.G. Ranwa, M. Kanawade, D. Balusamy, A. Kadam, V.A. Sarkar and J.V. Tonapi. 2012. GGE biplot analysis to evaluate genotype, environment and their interactions in sorghum multi-location data. Euphytica 185(3):465-479.
  • SAS. 2014. SAS: Business analytics and business intelligence software. SAS Inst. http://www.sas.com/en_us/home.html.
  • Shukla, G.K. 1972. Some statistical aspects of partitioning genotype environmental components of variability. Heredity 29:237-245.
  • Yan, W. 1999. Methodology of cultivar evaluation based on yield trial data-with special reference to winter wheat in Ontario. Ph.D Thesis, University of Guelph, Guelph, ON, Canada.
  • Yan, W. and L.A. Hunt. 1998. Genotype by environment interaction and crop yield. Plant Breed Rev. 16:35-178.
  • Yan, W., L.A. Hunt, Q. Sheng and Z. Szlavnics. 2000. Cultivar evaluation and mega-environment investigation based on GGE biplot. Crop Sci. 40:597-605.
  • Yan, W., P.L. Cornelius, J. Crossa and L.A. Hunt. 2001. Two types of GGE Biplots for analyzing multi-environment trial data. Crop Sci. 41:656-663.
  • Yan, W. and M.S. Kang. 2003. GGE Biplot Analysis: A Graphical Tool for Breeders, Geneticists and Agronomists. 1st Edn, CRC Press LLC, Boca Roton, Florida, pp: 271.
  • Yan, W. and N.A. Tinker. 2006. Biplot analysis of multi-environment trial data: Principles and applications. Can. J. Plant Sci. 86:623-645.
  • Yan, W. 2014. Crop variety trials: Data management and analysis. John Wiley and Sons. pp. 349.
  • Yan, W., Tinker, N.A., Molnar, S., Fregeau-Reid, J. and McElroy, A. 2007. Associations among oat traits and their responses to the environment in North America. Journal of Crop Improvement 20:1-29.
  • Yan, W. 1999. A study on the methodology of cultivar evaluation based on yield trial data — with special reference to winter wheat in Ontario, Ph.D. thesis, University of Guelph, Guleph, Ontario, Canada.
  • Zobel, R.W., M.J. Wright and H.G. Gauch, Jr. 1988. Statistical analysis of a yield trial. Agron. J. 80:388-393

GREEN HERBAGE YIELD ASSESSMENTS OF MAIZE CULTIVARS THROUGH GGE BIPLOT ANALYSIS METHOD

Year 2017, , 235 - 242, 15.12.2017
https://doi.org/10.17557/tjfc.357424

Abstract

The present study was conducted to assess green herbage yields of hybrid maize cultivars grown under different environments for two years. GGE biplot analysis method and regression coefficients were used to assess genotype x environment interaction and to identify the most stable cultivars for green herbage yield. Experiments were conducted in six different environments, green herbage yields in the environments varied between 6.0 t da-1 (E5) and 10.4 t da-1 (E1) and green herbage yield yields of the cultivars varied between 6.8 t da-1 (G14) and 10.9 t da-1 (G18). In GGE biplot analysis, the first two principle component (PC) axis explained about 82.45% of total variation. The genotypes with high PC1 and low PC2 values and regression coefficient of 1.0 were assessed as stable. The cultivar Safak (G18) with such values was identified as the most stable cultivar. The regression coefficient of 1.0 and the greatest green herbage yield proved the stability of that cultivar. The cultivars with higher PC1 and lower PC2 values [30B74 (G2), Seme Kukuruza 877 (G22), ADV 2898 (G24), Wayne (G17), and Safak (G18)] generally had higher green herbage yield than the general average. Safak (G18), 30B74 (G2), Seme Kukuruza 877 (G22), ADV 2898 (G24) and Wayne (G17) cultivars can be use green herbage yield production in south eastern Anatolia will allow the growers to have a profitable production.

References

  • Akcura, M., Taner, S. and Kaya, Y. 2011. Evaluation of bread wheat genotypes under irrigated multi-environment conditions using GGE biplot analyses. Agriculture, 98(1), 35-40.
  • Akcura, M., Y. Kaya, S. Taner and R. Ayranci. 2006. Parametric stability analyses for grain yield of durum wheat. Plant Soil Environ. 52:254-261.
  • Akcura, M., Y. Kaya and S. Taner. 2005. Genotype-environment ınteraction and phenotypic stability analysis for grain yield of durum wheat in Central Anatolian Region. Turkish J. Agric. For. 29:369-375.
  • Annicchiarico, P. 1997. Joint regression vs. AMMI analysis of genotype-environment interactions for cereals in Italy. Euphytica 94:53-62.
  • Dehghani, H., A. Ebadi and A. Yousefi. 2006. Biplot analysis of genotype x environment interaction for barley yield in Iran. Agron. J. 98: 388-393.
  • Eberhart, S.A. and W.A. Russell. 1966. Stability parameters for comparing varieties. Crop Sci. 6:36-40.
  • Flores, F., M.T. Moreno and J.I. Cubero. 1998. A comparison of univariate and multivariate methods to analyze environments. Field Crop Res. 56:271-286.
  • Francis, T.R. and L.W. Kannenberg. 1978. Yield stability studies in short season maize 1. A descriptive method for grouping genotypes. Can. J. Plant Sci. 58:1029-1034.
  • Gauch, G.H. and Zobel, R.W. 1988. Predictive and postdictive success of statistical analyses of yield trials. Theor. Appl. Genet. 76: 1-10. Jalata, Z. 2011. GGE-biplot analysis of multi-environment yield trials of barley (Hordeum vulgare L.) genotypes in Southeastern Ethiopia highlands Int. J. Plant Breed. Genet. 5(1):59-75.
  • Kandus, M., D. Almorza, R. Boggio Ronceros and J.C. Salerno. 2010. Statistical models for evaluating the genotype-environment interaction in maize (Zea mays L.). Phyton (Buenos Ares) 79:39-45.
  • Kaplan, M. 2005. Effects of different intra and inter row spacing on yield and yield components of second crop silage maize (Zea mays L.) under Kahramanmaras conditions. MSc Thesis, University of Kahramanmaras Sutcu Imam Kahramanmaras Turkey.
  • Kaplan, M., O. Baran, A. Unlukara, H. Kale, M. Arslan, K. Kara, S. Buyukkilic Beyzi, Y. Konca and A. Ulas. 2016. The effects of different nitrogen doses and irrigation levels on yield, nutritive value, fermentation and gas production of corn silage. Turk J. Field Crops 2(1):100-108.
  • Kaya, Y., M. Akcura and S. Taner. 2006. GGE-Biplot analysis of multi-environment yield trials in bread wheat. Turk J. Agric. 30:325-337.
  • McDonald, P. A.R. Henderson and S.J.E. Heron. 1991. The Biochemistry of Silage. Second Edition. 340 p. Chalcombe Publication.
  • Meeske. R., G. Ashbell, Z.G. Weinberg and T. Kipnis. 1993. Ensiling forage sorghum at two stages of maturity with the addition of lactic acid bacterial inoculants. Anim. Feed Sci. Technol. 43:165-175.
  • Nachit, M.M., M.E. Sorrells, R.W. Zobel, H.G. Gauch, R.A. Fischer and W.R. Coffman. 1992. Association of environmental variables with sites’ mean grain yield and components of genotype-environment interaction in durum wheat. J. Gene. Breed Org. 46:369-372.
  • Neylon, J.M. and L. Kung. 2003. Effects of cutting height and maturity on the nutritive value of corn silage for lactating cows. J. Dairy Sci. 86:2163-2169.
  • R Development Core Team. 2008. R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0. http://www.R-project.
  • Rakshit, S., K.N. Ganapathy, S.S. Gomashe, A. Rathore, R.B. Ghorade, M. Kumar, K. Kumar, S.K. Ganesmurthy, M.Y. Jain, J.S. Kamtar, S.S. Sachan, B.R. Ambekar, D.G. Ranwa, M. Kanawade, D. Balusamy, A. Kadam, V.A. Sarkar and J.V. Tonapi. 2012. GGE biplot analysis to evaluate genotype, environment and their interactions in sorghum multi-location data. Euphytica 185(3):465-479.
  • SAS. 2014. SAS: Business analytics and business intelligence software. SAS Inst. http://www.sas.com/en_us/home.html.
  • Shukla, G.K. 1972. Some statistical aspects of partitioning genotype environmental components of variability. Heredity 29:237-245.
  • Yan, W. 1999. Methodology of cultivar evaluation based on yield trial data-with special reference to winter wheat in Ontario. Ph.D Thesis, University of Guelph, Guelph, ON, Canada.
  • Yan, W. and L.A. Hunt. 1998. Genotype by environment interaction and crop yield. Plant Breed Rev. 16:35-178.
  • Yan, W., L.A. Hunt, Q. Sheng and Z. Szlavnics. 2000. Cultivar evaluation and mega-environment investigation based on GGE biplot. Crop Sci. 40:597-605.
  • Yan, W., P.L. Cornelius, J. Crossa and L.A. Hunt. 2001. Two types of GGE Biplots for analyzing multi-environment trial data. Crop Sci. 41:656-663.
  • Yan, W. and M.S. Kang. 2003. GGE Biplot Analysis: A Graphical Tool for Breeders, Geneticists and Agronomists. 1st Edn, CRC Press LLC, Boca Roton, Florida, pp: 271.
  • Yan, W. and N.A. Tinker. 2006. Biplot analysis of multi-environment trial data: Principles and applications. Can. J. Plant Sci. 86:623-645.
  • Yan, W. 2014. Crop variety trials: Data management and analysis. John Wiley and Sons. pp. 349.
  • Yan, W., Tinker, N.A., Molnar, S., Fregeau-Reid, J. and McElroy, A. 2007. Associations among oat traits and their responses to the environment in North America. Journal of Crop Improvement 20:1-29.
  • Yan, W. 1999. A study on the methodology of cultivar evaluation based on yield trial data — with special reference to winter wheat in Ontario, Ph.D. thesis, University of Guelph, Guleph, Ontario, Canada.
  • Zobel, R.W., M.J. Wright and H.G. Gauch, Jr. 1988. Statistical analysis of a yield trial. Agron. J. 80:388-393
There are 31 citations in total.

Details

Primary Language English
Journal Section Articles
Authors

Kagan Kokten This is me

Mahmut Kaplan

Mevlut Akcura This is me

Publication Date December 15, 2017
Published in Issue Year 2017

Cite

APA Kokten, K., Kaplan, M., & Akcura, M. (2017). GREEN HERBAGE YIELD ASSESSMENTS OF MAIZE CULTIVARS THROUGH GGE BIPLOT ANALYSIS METHOD. Turkish Journal Of Field Crops, 22(2), 235-242. https://doi.org/10.17557/tjfc.357424
AMA Kokten K, Kaplan M, Akcura M. GREEN HERBAGE YIELD ASSESSMENTS OF MAIZE CULTIVARS THROUGH GGE BIPLOT ANALYSIS METHOD. TJFC. December 2017;22(2):235-242. doi:10.17557/tjfc.357424
Chicago Kokten, Kagan, Mahmut Kaplan, and Mevlut Akcura. “GREEN HERBAGE YIELD ASSESSMENTS OF MAIZE CULTIVARS THROUGH GGE BIPLOT ANALYSIS METHOD”. Turkish Journal Of Field Crops 22, no. 2 (December 2017): 235-42. https://doi.org/10.17557/tjfc.357424.
EndNote Kokten K, Kaplan M, Akcura M (December 1, 2017) GREEN HERBAGE YIELD ASSESSMENTS OF MAIZE CULTIVARS THROUGH GGE BIPLOT ANALYSIS METHOD. Turkish Journal Of Field Crops 22 2 235–242.
IEEE K. Kokten, M. Kaplan, and M. Akcura, “GREEN HERBAGE YIELD ASSESSMENTS OF MAIZE CULTIVARS THROUGH GGE BIPLOT ANALYSIS METHOD”, TJFC, vol. 22, no. 2, pp. 235–242, 2017, doi: 10.17557/tjfc.357424.
ISNAD Kokten, Kagan et al. “GREEN HERBAGE YIELD ASSESSMENTS OF MAIZE CULTIVARS THROUGH GGE BIPLOT ANALYSIS METHOD”. Turkish Journal Of Field Crops 22/2 (December 2017), 235-242. https://doi.org/10.17557/tjfc.357424.
JAMA Kokten K, Kaplan M, Akcura M. GREEN HERBAGE YIELD ASSESSMENTS OF MAIZE CULTIVARS THROUGH GGE BIPLOT ANALYSIS METHOD. TJFC. 2017;22:235–242.
MLA Kokten, Kagan et al. “GREEN HERBAGE YIELD ASSESSMENTS OF MAIZE CULTIVARS THROUGH GGE BIPLOT ANALYSIS METHOD”. Turkish Journal Of Field Crops, vol. 22, no. 2, 2017, pp. 235-42, doi:10.17557/tjfc.357424.
Vancouver Kokten K, Kaplan M, Akcura M. GREEN HERBAGE YIELD ASSESSMENTS OF MAIZE CULTIVARS THROUGH GGE BIPLOT ANALYSIS METHOD. TJFC. 2017;22(2):235-42.

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