scholarly journals STABILNOST PRINOSA ZRNA LINIJA PŠENICE CENTRA ZA STRNA ŽITA KRAGUJEVAC

2021 ◽  
Author(s):  
Kristina Lukovic ◽  
◽  
Veselinka Zečevic ◽  
Vladimir Perišic ◽  
Milivoje Milovanovic ◽  
...  
Keyword(s):  
Grain Yield ◽  
Total Variation ◽  
Bread Wheat ◽  
Analysis Of Variance ◽  
Complex Trait ◽  
Yield Stability ◽  
Experimental Part ◽  
Winter Bread Wheat ◽  
Ammi Analysis ◽  
Sources Of Variation

In these investigations, the yield stability of 14 winter bread wheat genotypes were analyzed. The experimental part of the trial was performed at three locations (Kragujevac, Kruševac and Sombor) during 2013/2014. AMMI analysis of variance for grain yield showed that all sources of variation (genotype, environment, their interaction) had a significant effect on the expression of this complex trait. In the total variation of the experiment, the largest contribution had genotype/enviroment interaction, and genotype had the least. The most stable genotypes have been identified, which can be considered as a desirable genotypes, widely adapted to different agroecological conditions.

scholarly journals Morphological characterization and genetic analysis in bread wheat germplasm: A combined study of heritability, genetic variance, genetic divergence and association of characters

2020 ◽  
Vol 12 (4) ◽  
pp. 301-311
Author(s):  
G. Gerema ◽  
D. Lule ◽  
F. Lemessa ◽  
T. Mekonnen
Keyword(s):  
Grain Yield ◽  
Plant Height ◽  
Bread Wheat ◽  
Analysis Of Variance ◽  
Coefficient Of Variation ◽  
Grain Filling ◽  
Path Coefficient ◽  
Wheat Genotypes ◽  
Lattice Design ◽  
Positive Direct

Abstract. The present study was conducted to assess the nature and magnitude of genetic variability and traits association of bread wheat genotypes for yield and related traits. A total of 180 genotypes were evaluated in alpha lattice design with three replications in 2017/18 cropping season. Data for 10 quantitative traits were collected and subjected to analysis of variance. The result from the analysis of variance revealed highly significant variability observed among genotypes for all traits studied. Phenotypic coefficient of variation (PCV) is superior over genotypic coefficient of variation (GCV) for most traits but narrow variations were found between PCV and GCV for most of the traits. Heritability in broad sense and genetic advance as percent of the mean (GA%) were relatively higher for Kernels per spike and grain filling period. Grain yield showed positive and highly significant (p≤0.01) association with number of tillers, kernel per spike and plant height both on genotypic and phenotypic levels.The path coefficient analysis showed that spike length, plant height and kernels per spike had positive direct effect on grain yield on both genotypic and phenotypic levels. Divergence analysis (D2) grouped the total test germplasm into 10 clusters. Among those, clusters IV and IX showed the highest genetic distance and thus the possibility to develop segregating populations upon the crossing of widely related genotypes in those clusters. The results could help researches to utilize the most promising wheat genotypes of this study in future breeding programmes for enhancing desirable traits.

scholarly journals Stability Analysis of Rice Hybrids for Grain Yield in Telangana through AMMI and GGE Bi-plot Model

2021 ◽  
Vol 12 (6) ◽  
pp. 687-695
Author(s):  
Y. Chandra Mohan ◽  
◽  
L. Krishna ◽  
S. Sreedhar ◽  
B. Satish Chandra ◽  
...  
Keyword(s):  
Stability Analysis ◽  
Grain Yield ◽  
Analysis Of Variance ◽  
Concentric Circle ◽  
Sum Of Squares ◽  
Highly Dispersed ◽  
Ammi Analysis ◽  
Rice Genotypes ◽  
Telangana State ◽  
Agroclimatic Zones

An investigation was carried out on fifteen rice genotypes to identify stable rice hybrids across six different agroclimatic zones in Telangana state using AMMI and GGE bi-plot analyses during July to November, 2020. Analysis of variance clearly showed that environments contributed highest (65.47%) in total sum of squares followed by genotypes×environments (21.19%) indicating very greater role played by environments and their interactions in realizing final grain yield. AMMI analysis revealed that rice hybrids viz., RNRH 39 (G6), 27P31 (G14) and RNRH 15 (G1) were recorded higher mean grain yield with positive IPCA1 scores. The hybrids, JGLH 275 (G11) and JGLH 365 (G15) were plotted near to zero IPCA1 axis indicating that these hybrids are relatively more stable across locations. GGE bi-plot genotype view depicts that the hybrids, JGLH 365 (G15) and US 314 (G8) were inside the first concentric circle and found to be more stable across environments. GGE bi-plot environment view showed that Rudrur (E4) location was the most ideal environment. However, Warangal (E6) and Jagtial (E1) locations were poor and most discriminating. Depending on dispersion of environments in different directions, six locations were partitioned into three mega zones as first zone comprised of four locations viz., Kunaram (E2), Kampasagar (E3), Rudrur (E4) and Rajendranagar (E5) whereas highly dispersed Jagtial (E1) and Warangal (E6) were identified as two separate mega environments. The bi-plot view identified that 27P31 (G14), JGL 24423 (G2) and RNRH 39 (G6) were the best performing genotypes in first zone comprising four locations.

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.

Performance and Grain Yield Stability of Bread Wheat Genotypes under Different Environments

2013 ◽  
Vol 17 (2) ◽  
pp. 97-112
Author(s):  
F. F. Saad ◽  
A. A. EL-Genayni ◽  
M. M. Abd El-Aleem ◽  
A. M. Al-Fadel ◽  
Thanaa H.A. Abdel Kreem
Keyword(s):  
Grain Yield ◽  
Bread Wheat ◽  
Yield Stability ◽  
Wheat Genotypes

scholarly journals Genotype X Environment Interaction and Yield Stability of Bread Wheat Genotypes in central Ethiopia

2019 ◽  
Vol 7 (2) ◽  
pp. 87-94
Author(s):  
Gadisa A. Wardofa ◽  
Hussein Mohammed ◽  
Dawit Asnake ◽  
Tesfahun Alemu
Keyword(s):  
Grain Yield ◽  
Bread Wheat ◽  
Response Pattern ◽  
Yield Response ◽  
Similar Response ◽  
Environment Interaction ◽  
Wheat Genotypes ◽  
Main Effect ◽  
Ammi Analysis ◽  
Similar Yield

The present study was conducted to interpret Genotype main effect and GEI obtained by AMMI analysis and group the genotype having similar response pattern over all environments. Fifteen bread wheat genotypes were evaluated by RCBD using four replications at six locations in Ethiopia. The main effect differences among genotypes, environments, and the interaction effects were highly significant (P ≤ 0.001) for the total variance of grain yield. Results of AMMI analysis of mean grain yield for the six locations showed significant differences (P0.001) among the genotypes, environments and GEI. The environment had the greatest effect with the environmental sum of squares (35.28%) than the genotypes (33.46%) and GEI (31.45%) effect. The AMMI analysis for the IPCA1 captured 46.1% and the IPCA2 explained 28.6%. The two IPC cumulatively captured 74.7% of the sum of square the GEI of bread wheat genotypes, when the IPCA1 was plotted against IPCA2. The genotype ETBW8075, ETBW8070 and ETBW9470 were unstable as they are located far apart from the other genotypes in the biplot when plotted on the IPCA1 and IPCA2 scores. The ETBW8078, ETBW8459, Hidase and ETBW8311 were genotype located near to the origin of the biplot which implying that it was stable bread wheat genotypes across environments. There is closer association between Lemu and ETBW8065 which indicate similar response of the genotypes to the environment. The best genotype with respect to location Kulumsa was ETBW9470, ETBW8075 was the best genotype for Dhera, ETBW8070 was the best genotype for Holeta while ETBW9466 was the best genotype for Arsi Robe. Arsi Robe and Kulumsa is the most favorable environment for all genotypes with nearly similar yield response for grain yield.

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