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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Article
Multi-environmental Evaluation of Triticale, Wheat and Barley Genotypes by GGE Biplot Analysis
Author(s)
Oğuz Bilgin, Alpay Balkan, Zahit Kayıhan Korkut and İsmet Başer
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DOI:10.17265/1934-7391/2018.01.002
Affiliation(s)
Department of Field Crops, Faculty of Agriculture, Namık Kemal Unıversıty, Tekirdağ 59030, Turkey
ABSTRACT
The research was carried out with 9 triticale, 3 bread wheat, 3 durum
wheat and 3 barley varieties and advanced lines in Tekirdağ, Edirne and Silivri
locations during three years. In the study, the data obtained from combined
variance analysis were performed and the
significance of the differences between the averages was determined by LSD
multiple comparison test. GGE biplot analysis and graphics were made by using
the statistical package program. The
genotypes G2 and G3 for thousand kernel weight, genotype G1 for the heading
time and test weight, genotypes G14 and G15 for the maturation time, number of
spikelets per spike and grain weight per spike and G13 for the plant height,
spike length and grain yield per hectare decare revealed the highest values. The
genotypes G6, G5, G4, G14, G9, G8 and G7 gave lower values than the average in
terms of grain yield, whereas the other genotypes gave higher values than the
general average. According to biplot graphical results, while locations 1 and 8
were closely related, locations 9, 2 and 7 were positively related to these
environments. Although the location 7 is slightly different from the other 4
locations, these 5 locations can be seen as a mega environment. Genotypes G12,
G2, G3 and G10 for this mega-environment showed the best performances.
According to the results of grain yields obtained from 9 different locations,
the location 5 was the most discriminating area while the location 1 was the
least discriminating. Location 2 was the best representative location, while
locations 4 and 7 were with the lowest representation capability. The locations
that are both descriptive and representative are good test locations for the
selection of adapted genotypes. Test environments, such as location 8, with low
ability to represent are useful for selecting genotypes that perform well in
specific regions if the target environments can be subdivided into sub-environments.
KEYWORDS
GGE biplot, genotype, mega-environment, descriptive location and representative.
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