Graphical Analysis of Multi-environmental Trials for Bread Wheat (Triticum aestivum L.) Grain Yield Based on GGE Bi-Plot Analysis
Gadisa Alemu *
Ethiopia Institute of Agricultural Research, Kulumsa Agricultural Research Center, Asella, PO Box 489 Ethiopia.
Abebe Delesa
Ethiopia Institute of Agricultural Research, Kulumsa Agricultural Research Center, Asella, PO Box 489 Ethiopia.
Ruth Duga
Ethiopia Institute of Agricultural Research, Kulumsa Agricultural Research Center, Asella, PO Box 489 Ethiopia.
Alemu Dabi
Ethiopia Institute of Agricultural Research, Kulumsa Agricultural Research Center, Asella, PO Box 489 Ethiopia.
Berhanu Sime
Ethiopia Institute of Agricultural Research, Kulumsa Agricultural Research Center, Asella, PO Box 489 Ethiopia.
Negash Geleta
Ethiopia Institute of Agricultural Research, Kulumsa Agricultural Research Center, Asella, PO Box 489 Ethiopia.
Habtemariam Zegaye
Ethiopia Institute of Agricultural Research, Kulumsa Agricultural Research Center, Asella, PO Box 489 Ethiopia.
Tafesse Solomon
Ethiopia Institute of Agricultural Research, Kulumsa Agricultural Research Center, Asella, PO Box 489 Ethiopia.
Demeke Zewdu
Ethiopia Institute of Agricultural Research, Kulumsa Agricultural Research Center, Asella, PO Box 489 Ethiopia.
Abebe Getamesay
Ethiopia Institute of Agricultural Research, Kulumsa Agricultural Research Center, Asella, PO Box 489 Ethiopia.
Bayisa Asefa
Ethiopia Institute of Agricultural Research, Kulumsa Agricultural Research Center, Asella, PO Box 489 Ethiopia.
Bekele Geleta
CIMMYT, P.O. Box 5689, Addis Ababa, Ethiopia.
Ayele Badebo
CIMMYT, P.O. Box 5689, Addis Ababa, Ethiopia.
Tilahun Bayisa
Sinana Agricultural Research Center, Bale, Ethiopia.
*Author to whom correspondence should be addressed.
Abstract
Bread wheat (Triticum aestivum L.) is a crucial crop in Ethiopia, and breeders test newly developed elite lines for superiority to existing cultivars to boost national productivity. The study was undertaken during the 2021–22 to 2022–23 cropping seasons at seven environments in optimum moisture areas of Ethiopian using 36 diverse and advanced bread wheat genotypes to evaluate the GEI by the graphical method of GGE biplot and to identify the genotypes with high mean yield performance and stability. Field experiments were conducted at the Adet, Asasa, Kulumsa, and Sinana research centers in Ethiopia. The experiments were planted in an alpha lattice design replicated three times in six rows of 2.5m long. Row-to-row distance and distance between blocks were 0.2m and 1.5m, respectively. The analysis of variance revealed that genotype, environment, and their interaction showed a highly significant effect on the yield as reflected in the GGE model and the GGE model indicated the suitability of the genotypes EBW202136 (33), Boru (1), and EBW202172 (12), with high mean yield and stability, whereas the genotypes EBW202185 (16) and Deka (36) produced high mean yield, but unstable. Likewise, the genotypes EBW202164 (27) and EBW202192 (29) produced low mean yield and unstable. The AMMI analysis of variance for grain yield across the environments showed that 17.26% of the total variation was attributed to genotypic effects, 64.03% to environmental effects, and 18.71% to GEI effects. Two mega environments were identified based on GGE biplot analysis and the which-won–model indicated the adaptation of genotypes Boru (1), EBW202159 (4), EBW202172 (12), EBW202171 (19), and EBW202136 (33) to first mega-environment and genotypes EBW202157 (3), EBW202166 (5), EBW202160 (6), EBW202162 (9), EBW202185 (16), Dursa (17) and Deka (36) in the second. These approaches allowed the identification of stable and high-yielding genotypes (EBW202136 (33) and EBW202172 (12)) which can be included in the national verification program, with a plan to release a new variety, and other genotypes with high yield could be utilized in breeding programs to further improve grain yield in bread wheat.
Keywords: AMMI, environment, high yielding, GGE, stability