scholarly journals Grain yield stability analysis using AMMI and GGE biplot models in different breeding zones of Bangladesh

2021 ◽  
Author(s):  
Marium Khatun ◽  
A. K. M. Aminul Islam ◽  
M. Rafiqul Islam ◽  
M. A. Rahman Khan ◽  
M. Kamal Hossain
Keyword(s):  
Stability Analysis ◽  
Grain Yield ◽  
Primary Component ◽  
Yield Stability ◽  
Second Primary ◽  
Gge Biplot ◽  
Environment Analysis ◽  
Biplot Analysis ◽  
Ammi Analysis ◽  
Breeding Zone

Abstract During the 2018-2019 Boro season (dry season), 70 rice genotypes were examined with alpha lattice experimental design with the goal of measuring grain yield stability analysis. Results indicated that AMMI analysis explained 100% of the G×E variance, while captured 81.74% variance. Based on the GGE and AMMI analysis, the most stable and high yielding genotype was identified G41 followed by G22, G26, G58, G24 and G61. The AMMI 1 biplot analysis revealed that the first primary component of interaction (IPC1) factor was responsible for 64.2 % variation due to G × E interaction. On other hand, the second primary component (PC2) factor accounted for 35.8% variation of the G × E interaction. These two-primary component (PC1 and PC2), all together accounted for 100% variation of the G × E interaction. The contribution of G68 was highest to the interaction followed by G70, G58, G42, G61, G45, G38, G14, G33, G60, G53, and G9. Best environment analysis indicated that the ranking was Rajshahi < Gazipur < Cumilla. GGE biplot analysis accounted for 81.74% variation comprising two principal components PC1 and PC2 with 45.62% and 36.12% variations respectively. Rajshahi was more stable than Gazipur. Based on environment analysis genotypes, G22, G26, G58, and G44 can be recommended as best stable genotypes that breeding zone. However, the genotype G61 was identified adapted to Cumilla breeding zone.

Using AMMI approach to delineate genotype by environment interaction and stability of barley (Hordeum vulgare L.) genotypes under northern Indian shivalik hill conditions

2020 ◽  
Vol 80 (03) ◽  
Author(s):  
Om Prakash Yadav ◽  
A. K. Razdan ◽  
Bupesh Kumar ◽  
Praveen Singh ◽  
Anjani K. Singh
Keyword(s):  
Hordeum Vulgare ◽  
Grain Yield ◽  
Principal Component ◽  
Genotype By Environment Interaction ◽  
Environment Interaction ◽  
Hordeum Vulgare L ◽  
Genotype By Environment ◽  
Biplot Analysis ◽  
Principal Component Axis ◽  
Ammi Analysis

Genotype by environment interaction (GEI) of 18 barley varieties was assessed during two successive rabi crop seasons so as to identify high yielding and stable barley varieties. AMMI analysis showed that genotypes (G), environment (E) and GEI accounted for 1672.35, 78.25 and 20.51 of total variance, respectively. Partitioning of sum of squares due to GEI revealed significance of interaction principal component axis IPCA1 only On the basis of AMMI biplot analysis DWRB 137 (41.03qha–1), RD 2715 (32.54qha–1), BH 902 (37.53qha–1) and RD 2907 (33.29qha–1) exhibited grain yield superiority of 64.45, 30.42, 50.42 and 33.42 per cent, respectively over farmers’ recycled variety (24.43qha–1).

Yield stability of rainfed durum wheat and GGE biplot analysis of multi-environment trials

2010 ◽  
Vol 61 (1) ◽  
pp. 92 ◽  
Author(s):  
Reza Mohammadi ◽  
Reza Haghparast ◽  
Ahmed Amri ◽  
Salvatore Ceccarelli
Keyword(s):  
Durum Wheat ◽  
Good Alternative ◽  
Yield Stability ◽  
Gge Biplot ◽  
Ge Interaction ◽  
Breeding Lines ◽  
Biplot Analysis ◽  
Stable Performance ◽  
Superior Genotypes ◽  
Highly Correlated

Integrating yield and stability of genotypes tested in unpredictable environments is a common breeding objective. The main goals of this research were to identify superior durum wheat genotypes for the rainfed areas of Iran and to determine the existence of different mega-environments in the growing areas of Iran by testing 20 genotypes in 4 locations for 3 years via GGE (genotype + genotype-by-environment) biplot analysis. Stability of performance was assessed by the Kang’s yield-stability statistic (YSi) and 2 new methods of yield-regression statistic (Ybi) and yield-distance statistic (Ydi).The combined analysis of variance showed that environments were the most important source of yield variability, and accounted for 76% of total variation. The magnitude of the GE interaction was ~10 times the magnitude of the G effect. The GGE biplot suggested the existence of 2 durum wheat mega-environments in Iran. The first mega-environment consisted of environments corresponding to ‘cold’ locations (Maragheh and Shirvan) and a moderately cold location (Kermanshah), where ‘Sardari’ was the best adapted cultivar; the second mega-environment comprised ‘warm’ environments, including the Ilam and Kermanshah locations, where the recommended breeding lines G16 (Gcn//Stj/Mrb3), G17 (Ch1/Brach//Mra-i), and G18 (Lgt3/4/Bcr/3/Ch1//Gta/Stk) produced the highest yields. Ranking of genotypes based on GGE was found to be highly correlated with that based on the statistics YSi and Ybi. The discriminating power v. the representative view of the GGE biplot identified Kermanshah as the location with the least discriminating ability but greater representation, suggesting the possible of testing genotypes adapted to both warm and cold locations at the Kermanshah site. The results verified that the statistics YSi and Ybi were highly correlated (r = 0.94**) and could be a good alternative for GGE biplot analysis for selecting superior genotypes with high-yielding and stable performance.

scholarly journals Genotype environment interaction and stability for yield and its components in advanced breeding lines of red rice (Oryza sativa L.)

2020 ◽  
Vol 49 (3) ◽  
pp. 425-435
Author(s):  
BM Dushyantha Kumar ◽  
AP Purushottam ◽  
P Raghavendra ◽  
T Vittal ◽  
KN Shubha ◽  
...  
Keyword(s):  
Grain Yield ◽  
Oryza Sativa L ◽  
Environment Interaction ◽  
Gge Biplot ◽  
Red Rice ◽  
Yield Performance ◽  
Breeding Lines ◽  
Genotype Environment Interaction ◽  
Ammi Analysis ◽  
Total Variability

Effects of genotype, environment and their interaction for grain yield and yield attributing characters in 20 advanced breeding lines of rice across six environments was investigated. Yield stability and adaptability of yield performance were analyzed by Eberhart and Russel model and (GGE) bi-plot. The AMMI analysis of variance indicated that mean squares due to genotypes, location and genotype location contributed per cent 59.08, 5.79 and 21.63, respectively for total variability in grain yield per hectare. Estimates of GGE bi-plot revealed that the lines G1, G3, G11, G13, G15, G12, G16, G7 and G10 were positioned near GGL bi-plot origin indicating wider adaptation for the trait grain yield per hectare. Eberhart and Russel Model and GGE biplot model showed the advanced breeding lines viz., JB 1-11-7 (G1) and JA 6-2 (G15) exhibited wider adaptability across the tested environments for number of productive tillers per plant and yield per hectare.

scholarly journals Development of Improved Mutants for Grain Yield and Related Traits in Finger Millet (Eleusine coracana L Gaertn.) Through Gamma Mutagenesis

2021 ◽  
pp. 225-235
Author(s):  
K. N. Ganapathy ◽  
T. S. S. K. Patro ◽  
K. B. Palanna ◽  
I. K. Das ◽  
M. Elangovan ◽  
...  
Keyword(s):  
Stability Analysis ◽  
Grain Yield ◽  
Finger Millet ◽  
Blast Resistance ◽  
Heritability Estimate ◽  
Complex Trait ◽  
Eleusine Coracana ◽  
Gge Biplot ◽  
Induced Mutagenesis ◽  
Highly Correlated

Recombination breeding is limited in finger millet due to tiny florets and irregular anthesis. Induced mutagenesis using gamma irradiation was attempted to improve grain yield and related traits in three elite cultivars (GPU28, GPU 67 and MR 6). Mean performance and estimates of BLUP and BLUE of 61 mutants showed variability among the mutants for grain yield in comparison to parental genotypes. Grain yield being a complex trait and influenced by high G × E interaction recorded low heritability estimate sand therefore BLUP provided more reliable estimates for grain yield. Stability analysis was conducted using GGE biplot techniques and also by plotting the trait means with their respective coefficient of variation values(CVs). From mean performance and stability analysis, the mutants GPU28-2212, GPU28-2086, GPU28-2082 derived from GPU 28 variety, GPU67-3358, GPU67-3359, GPU67-2094 from GPU67 variety and MR6-3393 from MR6 variety were superior for grain yield and related traits. Combined association analysis revealed tillers per plant as highly correlated trait with grain yield indicating key trait for grain yield improvement in finger millet. Mutants with improved finger traits and blast resistance are also discussed.

scholarly journals Multienvironment Evaluation of Tannin-Free Photoperiod-Insensitive Sorghum (Sorghum bicolor (L) Moench) for Yield and Resistance to Grain Mold in Senegal

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Cyril Diatta ◽  
Mame P. Sarr ◽  
Thierry Klanvi Tovignan ◽  
Ousmane Aidara ◽  
Daniel Kwadjo Dzidzienyo ◽  
...  
Keyword(s):  
Grain Yield ◽  
Gge Biplot ◽  
Rating Score ◽  
Biplot Analysis ◽  
Stability Performance ◽  
Major Interest ◽  
Grain Mold ◽  
Mold Resistance ◽  
Disease Pressure ◽  
Sorghum Bicolor L

Combining resistance to grain mold with high grain yield in tannin-free white-grained photoperiod-insensitive sorghum is of major interest for farmers in Senegal. In this study, GGE biplot analysis was used to assess the performance, adaptability, and stability of eleven sorghum parental lines and their hybrid combinations for yield and grain mold resistance under Senegalese environments. Eleven inbred lines along with their 22 hybrid combinations and one check were evaluated across three sites during the 2015 and 2016 rainy seasons under natural grain mold infestation. The results of this study showed strong genetic variability among studied genotypes for all measured traits. The highly significant G × E interaction effects for grain yield and panicle grain mold rating score (PGMR) indicated that both traits are influenced by genetics and to some extent by environment. Broad-sense heritability computed was high for all these traits except PGMR, showing a high environmental pressure on this later. The study showed that grain mold pressure in the studied sites decreased following a South-North gradient similar to the rainfall pattern, with the south region wetter, explaining the high disease pressure in Darou and Sinthiou Maleme contrary to Bambey. The GGE biplot analysis performed showed that the first two principal components explained 85.84% of the total variation of GGE sum of squares for grain yield. The which-won-where view of the GGE biplot for grain yield showed that the hybrid HB16 was the most adapted for Bambey area. The ranking of genotypes based on both yield performance and stability showed that HB16, HB5, HB21, HB18, and HB7 were the best hybrids combining high grain yield, high stability performance, and tolerance to grain mold disease across the test environments. These hybrids outperformed the best yielding inbred line P29 (2196.7 kg ha−1) with grain yield advantages ranging 17–60%. Therefore, these hybrids could be recommended to farmers in order to improve sorghum yield in Senegal.

Sign in / Sign up

Export Citation Format

Share Document