MPB-2016v7n2 - page 9

Molecular Plant Breeding 2016, Vol.7, No.02, 1
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The Azargol and Almanzor cultivars showed besides
low performance, the largest fluctuations in
performance (most volatile), because vertical intervals
with the longest line on the horizontal axis. While the
Brocar, Alexandra and Fabiola cultivars, After
Nkarmoni and Altesse cultivars were stable genotypes.
But in terms of the graph of the position were not so
good selection.
Conclusion
In this experiment, the cultivars Azargol, Nkarmoni,
Alexandra and Melody known for stable grain yield
and consistent varieties. Also among the places,
Birjand showed high performance in the environment.
Karaj locations had the lowest performance. As well
as the location of Birjand in the Fabiola cultivar, and
in place of the figure, the Nkarmoni cultivar and to
place the Joana Karaj cultivar, and to place the Sari
Pomar cultivar, respectively, stable component in the
survey figures for grain yield.
References
Albert M.J.A., 2004, A comparison of statistical methods to describe
genotype ×environment interaction and yield stability in multi-location
maize trials. M. Sc. Thesis. Department of Plant Sci., The University of
the Free State, Bloemfontein
F.A.O., 2011. Data Stat Year 1988., UN Food and Agriculture Organization.
Rome. Italy
Farshadfar E., Poursiahbidi M.M., and Jasemi m., 2012, Evaluation of
phenotypic stability in bread wheat genotypes using GGE-biplot,
International Journal of Agriculture and Crop Sciences, 4(13): 904-910
Khajehpour M.R., 2008, Industrial plants, University of Esfahan Technology
Shadpour S., Peighambari S.A., and Jahromi M.A., Effect of genotype ×
environment interaction in tobacco greenhouse by using regression
analysis, The first national conference on issues of modern agriculture,
Islamic Azad University, November 2011
Scchoemam L.J., 2003, Genotype × environment interaction in sunflower
(
Helianthus annuus
) in South Africa.M.SC. Thesis, department of
agronomy, Faculty of agricultural., university of free state.,
Bloemfontein.
Sial M.A., Arain M.A., and Ahmad M., 2000, Genotype× Environment
interaction on bread wheat grown over multiple sites and years in
Pakistan,
Pak J Bot
, 32(1), 85-91
Yan W., Hunt L.A., Sheng Q., and Szlavnics Z., 2000, Cultivar evaluation
and mega-environment investigation based on the GGE biplot, Crop
Sci. 40(3): 597-605
Yan W., and Hunt L.A., 1998, Genotype by environment interaction and
crop yield, Plant Breed, 16: 135–178
Yan W., and Hunt L.A., 2002, Biplot analysis of multi- environment trial
data, In M.S. Kang (ed.), pp. 289-303
Yan W., and Kang M.S., 2003, GGE biplot analysis: a graphical tool for
breeders, geneticists and agronomist, CRC Press, Boca Raton, FL.
271pp
Yan W., and Rajcan I., 2002, Biplot analysis of test sites and trait relations
of soybean in Ontario, Crop Sci., 42(1): 11–20
Yan W., Tinker N.A., 2005, An integrated system of biplot analysis for
displaying, interpreting, and exploring genotype by environment
interactions, Crop Sci., 45(3): 1004-1016
Yan W., 2001, GGEbiplot-A Windows application for graphical analysis of
multi-environment trial data and other types of two-way data,
Agronomy Journal, 93(5): 1111-1118
Yan W., 2002, Singular-value partitioning in biplot analysis of
multi-environment trial data, Agronomy Journal, 94(5): 990-996
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