Grain yield stability of barley genotypes in uniform regional yield trails in warm and semi warm dry land area

2017 ◽  
Author(s):  
Hassan Khanzadeh ◽  
Behroz Vaezi ◽  
Rahmatolah Mohammadi ◽  
Asghar Mehraban1 ◽  
Tahmaseb Hosseinpor ◽  
...  
Keyword(s):  
Grain Yield ◽  
Agricultural Research ◽  
Gge Biplot ◽  
Ge Interaction ◽  
Dry Land ◽  
Biplot Analysis ◽  
Ammi Model ◽  
Cropping Seasons ◽  
Ideal Genotype ◽  
Better Than

The aim of this study was to assess the effect of GEI on grain yield of barley advanced lines and exploit the positive GEI effect using AMMI and SREG GGE biplot analysis. Therefore, 18 lines were evaluated at five research stations (Ghachsaran, Mogan, Lorestan, Gonbad and Ilam) of Dryland Agricultural Research Institute (DARI), in the semi-warm regions in Iran, in 2012, 2013 and 2014 cropping seasons under rain-fed conditions. Analysis of variance showed that grain yield variation due to the environments, genotypes and GE interaction were highly significant (p>0.01), which accounted for 68.9%, 9.3% and 22.7% of the treatment combination sum of squares, respectively. To determine the effects of GEI on yields, the data were subjected to AMMI and GGE biplot analysis. The first five AMMI model terms were highly significant (p>0.01) and the first two terms explained 59.56% of the GEI. There were two mega-environments according to the SREG GGE model. The best genotype in one location was not always the best in other test locations. According to AMMI1 biplot, G2, G4, G5 and G6 were better than all other genotypes across environments. G2 was the ideal genotype to plant in Gachsaran. It seems that Ghachsaran is the stable environment between the environments studied and next in rank was Gonbad. In finally, the ATC method indicated that G1, G3, G4 and G6 were more stable as well as high yielding.

scholarly journals AMMI and GGE Biplot Analysis for Seed Yield and Oil Content of Sesame (Sesamum indicum L.) Genotypes in Tigray Northern Ethiopia

2020 ◽  
pp. 58-67 ◽  
Author(s):  
Yirga Belay Kindeya ◽  
Firew Mekbib ◽  
Eyasu Abraha Alle
Keyword(s):  
Seed Yield ◽  
Oil Content ◽  
Northern Ethiopia ◽  
Block Designs ◽  
Gge Biplot ◽  
Local Varieties ◽  
Biplot Analysis ◽  
Cropping Seasons ◽  
Ideal Genotype ◽  
Sesame Genotypes

Seventeen sesame genotypes were tested at ten environments in Tigray, Northern Ethiopia during 2014-2015 cropping seasons. Randomized Complete Block Designs (RCBD) with three replications was used in the study. According to the GGE bi-plot different sesame growing environments grouped into two mega-environments: The first mega-environment contained the favorable environments Dansha area with a vertex G4 and Sheraro area with winner G3 and the second environment included medium to low environments E2 (Humera-2), E4 (Dansha-2), E5 (Sheraro-1), E7 (Wargiba-1), E8 (Wargiba-2) and E9 (Maykadra) for seed yield. Three mega-environments identified for oil content: The 1st environment contained G12, G7 and G2 in the mega-environment group of Humera, Dansha and Gendawuha, The 2nd environment, Sheraro location contained G9 and the 3rd environment Wargiba, was containing G17. G1 (HuRC-4) identified as an “ideal” genotype and E1 (Humera-1) also identified as an ideal environment the most representative of the overall environments and the most powerful to discriminate genotypes. The multivariate approaches AMMI and GGEbi-plot were better for partitioning the GEI into the causes of variation. According to different stability models, G1, G7, and G3 were high yielder and the most stable both in terms of seed yield and oil content. Moreover, showed yield advantages over the released and local varieties. The stable genotypes recommended for wider areas while G14 and G4 were for specific favorable environments Sheraro and Dansha, respectively.

scholarly journals Evaluation of genotype x environment interactions in maize hybrids using GGE biplot analysis

2011 ◽  
Vol 11 (1) ◽  
pp. 01-09 ◽  
Author(s):  
Fatma Aykut Tonk ◽  
Emre Ilker ◽  
Muzaffer Tosun
Keyword(s):  
Grain Yield ◽  
Gge Biplot ◽  
Maize Breeding ◽  
Private Companies ◽  
Breeding Programs ◽  
Maize Hybrids ◽  
Biplot Analysis ◽  
Maize Genotypes ◽  
Cropping Seasons ◽  
Hybrid Maize

Seventeen hybrid maize genotypes were evaluated at four different locations in 2005 and 2006 cropping seasons under irrigated conditions in Turkey. The analysis of variance showed that mean squares of environments (E), genotypes (G) and GE interactions (GEI) were highly significant and accounted for 74, 7 and 19 % of treatment combination sum squares, respectively. To determine the effects of GEI on grain yield, the data were subjected to the GGE biplot analysis. Maize hybrid G16 can be proposed as reliably growing in test locations for high grain yield. Also, only the Yenisehir location could be best representative of overall, locations for deciding about which experimental hybrids can be recommended for grain yield in this study. Consequently, using of grain yield per plant instead of grain yield per plot in hybrid maize breeding programs could be preferred by private companies due to some advantages.

scholarly journals THE ANALYSIS OF GENOTYPE × ENVIRONMENT INTERACTION USING RAPESEED (BRASSICA NAPUS L.) BY GGE BIPLOT METHOD

2020 ◽  
Vol 51 (5) ◽  
pp. 1337-1349
Author(s):  
Motahhari & et al.
Keyword(s):  
Seed Yield ◽  
Agricultural Research ◽  
Environment Interaction ◽  
Block Designs ◽  
Gge Biplot ◽  
Ge Interaction ◽  
Brassica Napus L ◽  
Biplot Analysis ◽  
Genotype Environment Interaction ◽  
Selection Of

This study was aimed to asses seed yield performances of 16 rapeseed genotypes  in randomized complete block designs (RCBD) with three replications at four Agricultural Research Stations of cold and mid-cold regions over two years in Iran (2015-2017). GGE biplot analysis indicated that the first two components explained 83% of seed yield variations. Genotype, location and their interaction explained 18%, 52% and 30%of the total GE variation, respectively. In this research, a graphically represented GGE biplot analysis enabled selection of stable and high-yielding genotypes for all investigated locations, as well as genotypes with specific adaptability. The GGE biplot analysis was adequate in explaining GE interaction for seed yield in rapeseed. It can be concluded that genotypes G2, G4 and G13 had the highest mean seed yield and stability in four investigated locations. For specific adaptability, G13 was recommended for Isfahan, Karaj and Kermanshah and G4 for Mashhad.

Biplot analysis of genotype-environment interaction in durum wheat using the AMMI model

2006 ◽  
Vol 54 (4) ◽  
pp. 459-467 ◽  
Author(s):  
E. Farshadfar ◽  
J. Sutka
Keyword(s):  
Grain Yield ◽  
Durum Wheat ◽  
Field Experiments ◽  
Block Design ◽  
Environment Interaction ◽  
Ge Interaction ◽  
Biplot Analysis ◽  
Randomized Block Design ◽  
Total Variability ◽  
Ammi Model

The genotype by environment (GE) interaction is a major problem in the study of quantitative traits because it complicates the interpretation of genetic experiments and makes predictions difficult. In order to quantify GE interaction effects on the grain yield of durum wheat and to determine stable genotypes, field experiments were conducted with ten genotypes for four consecutive years in two different conditions (irrigated and rainfed) in a completely randomized block design with three replications in each environment. Combined analysis of variance exhibited significant differences for the GE interaction, indicating the possibility of stable entries. The results of additive main effect and multiplicative interaction (AMMI) analysis revealed that 12% of total variability was justified by the GE interaction, which was six times more than that of genotype. Ordination techniques displayed high differences for the interaction principal components (IPC1, IPC2 and IPC3), indicating that 92.5% of the GE sum of squares was justified by AMMI1, AMMI2 and AMMI3, i.e. 4.5 times more than that explained by the linear regression model. The results of the AMMI model and biplot analysis showed two stable genotypes with high grain yield, due to general adaptability to both rainfed and irrigated conditions, and one with specific adaptation.

scholarly journals AMMI and GGE Biplot Analysis for G×E Interaction of Wheat Genotypes under Different Irrigation and Sowing Condition

2021 ◽  
Author(s):  
Ragini Dolhey ◽  
V.S. Kandalkar
Keyword(s):  
Concentric Circle ◽  
Environment Interaction ◽  
Gge Biplot ◽  
Wheat Genotypes ◽  
Biplot Analysis ◽  
Genotype Environment Interaction ◽  
Significant Difference ◽  
Ammi Model ◽  
Ideal Genotype ◽  
Main Effects

Background: AMMI analysis showed that genotype, environment and genotype-environment interaction had a highly significant variation for 20 wheat genotypes analyzed over four environments. ASV ranking revealed G15 (RVW-4275) as a stable genotype while G3 (RVW-4263) and G9 (RVW-4269) as unstable genotypes. GGE biplot analysis for environment interrelationship revealed that E1 (Irrigated timely sown), E2 (Restricted irrigation timely sown) were correlated forming one group and E3 (Irrigated late sown), E4 (Restricted irrigation late sown) were correlated forming another group. Polygon view showed that G9 (RVW-4269) was found stable and better performing in E1, G12 (RVW-4272) was stable under the E2 environment and G3 (RVW-4263) was stable in E3. Ideal genotype graph with concentric circles having ideal genotype at the center and genotypes G12(RVW-4272), G18(RVW-4278), G13(RVW-4273), G11(RVW-4271), G10 (RVW4270) present in a concentric circle close to the center can to considered as stable and desirable genotypes.Methods: In the present study the plant material comprised of 20 wheat genotypes. These genotypes were randomly allocated in different replication under different environmental condition. The field trial was evaluated at four different environments viz., E1- Irrigated timely sown, E2- Restricted irrigation is timely sown (RI- 2 irrigation), E3- Irrigated late sown, E4- Restricted irrigation late sown during Rabi season of 2016-2017 at research farms, college of agriculture, Gwalior, MP. The genotype main effects and genotype × environment interaction effects (GGE) model and additive main effects and multiplicative interaction (AMMI) model were two statistical approaches used to determine stable genotype in R software.Result: Highly significant difference was seen for genotype and G×E interaction in our study, revealing that genotype yield output was highly impacted by G×E. In all four environments and G3, G9 as unstable genotypes in all four environments, ASV ranking revealed G15 as a stable genotype. For further breeding, these genotypes G12, G18, G13, G11, G2, G10 and G15 may be used to grow genotypes adapted to conditions of partial irrigation or drought stress.

scholarly journals GGE Biplot Analysis for Yield Stability in Multi-environment Trials of Promising Hybrid Rice (Oryza sativa L.)

2015 ◽  
Vol 19 (1) ◽  
pp. 1-8 ◽  
Author(s):  
Anowara Akter ◽  
M Jamil Hasan ◽  
Umma Kulsum ◽  
MH Rahman ◽  
M Khatun ◽  
...  
Keyword(s):  
Grain Yield ◽  
Oryza Sativa L ◽  
High Yield ◽  
Gge Biplot ◽  
Yield Data ◽  
Biplot Analysis ◽  
Stability Performance ◽  
Sources Of Variation ◽  
The Difference ◽  
Ideal Genotype

The genotype and genotype by environment biplot model is an excellent tool for visual multi-environment trials data analysis. In this study we investigated grain yield of six rice genotypes (three tested, one released hybrids and two inbred check varieties) in five environments. The combined analysis of variance for grain yield data indicated that the differences among all sources of variation were highly significant (P<0.001). Environment (E), Genotype (G) and G × E interaction effects accounted for 12.49, 76.51 and 10.21% of the total sum of squares respectively. The first two principal components (PC1 and PC2) were used to display a two-dimensional GGE biplot. Thus, genotypic PC1 scores>0 classified the high yielding genotypes while PC1 scores<0 identified low yielding genotypes. Unlike genotypic PC1, genotypic PC2 scores discriminated the unstable ones. The GGE biplot analysis was useful in identifying stable genotypes with high yield performance. In this study, the polygon view of GGE biplot showed that the vertex genotypes were BRRI1A/BR168R (G1), BRRI10A/BRRI10R (G2) and BRRI dhan28 (G5) having the largest distance from the origin, which was most discriminated genotypes with the unstable ones. These vertex genotypes BRRI1A/BR168R (G1) and BRRI10A/BRRI10R (G2) gave higher yield (PC1 scores>0) while another vertex genotype BRRI dhan28 (G5) produced low yield (PC1 score<0). Hence, the vertex genotype BRRI10A/BRRI10R (G2) was high yielding for all environments and it fell into section 1 following IR58025A/BRRI10R (G3) and BRRI hybrid dhan1 (G4). Mean yield and stability performance over environments of each genotype is explored by using the average environment (tester) coordinate (AEC) methods. These methods show that the genotypes BRRI10A/BRRI10R (G2), IR58025A/BRRI10R (G3) and BRRI hybrid dhan1 (G4) had higher stability as well as higher mean yield while the genotype IR58025A/BRRI10R (G3) had the highest stability out of these three genotypes. The ideal genotype biplot suggests that the closer to ‘ideal’ genotype was IR58025A/BRRI10R (G3) followed by G2 and G4 being more desirable than the other genotypes. Similarly, the environment Barisal (E3) was ‘ideal’ environment followed by E1 (Gazipur), E2 (Comilla) and E5 (Satkhira). Hence, the environment Barisal (E3) is more stable and suitable for all genotypes following Satkhira (E5) because it has large PC1 and small PC2 score but Rangpur (E4) is a discriminating environment because it has large PC2 score. The interrelationship among the environments according to the small angles of test environments was highly positively correlated. Gazipur (E1), Comilla (E2), Barisal (E3) and Satkhira (E5) were closely correlated with small angles but Rangpur (E4) had medium long angles. Comparison between two genotypes showed that BRRI10A/BRRI10R (G2) and IR58025A/BRRI10R (G3) were high yielder in test environments. Thus, the difference between G2 and G3 was relatively small in test environments.Bangladesh Rice j. 2015, 19(1): 1-8

scholarly journals Stability Assessment of Single-Cross Maize Hybrids Using GGE-Biplot Analysis

2021 ◽  
Vol 13 (2) ◽  
pp. 78
Author(s):  
L. Musundire ◽  
J. Derera ◽  
S. Dari ◽  
A. Lagat ◽  
P. Tongoona
Keyword(s):  
Grain Yield ◽  
South African ◽  
Inbred Line ◽  
Inbred Lines ◽  
Yield Potential ◽  
Research Station ◽  
Gge Biplot ◽  
Single Cross ◽  
Ideal Genotype ◽  
Single Cross Hybrids

Grain yield potential of new maize hybrid varieties across target environments contributes to the uptake of these varieties by farmers. Evaluation of single-cross hybrids developed from test crossing introgressed inbred lines bred for three distinct environments to elite tropical inbred line testers was carried out. The study&rsquo;s objective was to assess grain yield stability and genotype adaptability of the single-cross hybrids across South African environments relative to adapted commercial hybrid checks. One hundred and twenty-two introgressed inbred lines developed using the pedigree breeding program were crossed to four tropical elite inbred line testers using line &times; tester mating design to obtain 488 experimental single cross hybrids. Subject to availability of adequate seed for evaluation, a panel of 444 experimental single-cross hybrids was evaluated using an augmented design in two experiments defined as Population A and B for the study&rsquo;s convenience in South African environments. Data for grain yield (t/ha) performance for experimental single-cross hybrids and commercial check hybrids in Population A and B across environments and individual environments identified experimental single-cross hybrids that had significant comparable grain yield (t/ha) performance relative to best commercial check hybrid (PAN6Q445B) on the market. The selected experimental single-cross hybrids 225, 89, 246 and 43 (Population A) and 112 (Population B) also had a better average rank position for grain yield (t/ha) relative to best commercial check hybrid. These selected experimental single-cross hybrids had a grain yield (t/ha) advantage range of 0.9-6.7% for Population A and 7.3% for Population A and B, respectively, relative to the adapted commercial check hybrid. GGE biplot patterns for which won-where for Population A indicated that at Potchefstroom Research Station and Ukulinga Research Station experimental single-cross hybrids 127 and135 were the vertex (winning) hybrids. Cedera Research Station did not have a vertex hybrid for Population A. For Population B, experimental single-cross hybrids 112, 117 and 18 were the vertex hybrids at Cedera Research Station, Ukulinga Research Station and Potchefstroom Research Station, respectively. Experimental single-cross hybrid 257 was identified as ideal genotype for Population A, while experimental single-cross hybrid 121 in Population B was the ideal genotype. Ideal environments were also identified as Ukulinga Research Station for Population A, and Cedera Research Station for Population B. Average-environment coordination (AEC) view of the GGE biplot in Population A indicated that experimental single-cross hybrids 1 was highly stable across environments. In comparison, Population B experimental single-cross hybrid 161 was highly stable across environments. In conclusion, selected single-cross hybrids in the current study can also be advanced for further evaluation with a possibility for identifying high yielding and stable single-cross hybrids for variety registration and release in target environments in South Africa.

scholarly journals Adaptability and stability of erect cowpea genotypes via REML/BLUP and GGE Biplot

Bragantia ◽  
2016 ◽  
Vol 75 (3) ◽  
pp. 299-306 ◽  
Author(s):  
Adriano dos Santos ◽  
Gessi Ceccon ◽  
Paulo Eduardo Teodoro ◽  
Agenor Martinho Correa ◽  
Rita de Cássia Félix Alvarez ◽  
...  
Keyword(s):  
Grain Yield ◽  
The State ◽  
Gge Biplot ◽  
Phenotypic Stability ◽  
Ge Interaction ◽  
Mato Grosso ◽  
Mato Grosso Do Sul ◽  
The Ideal

ABSTRACT The objective of this study was to investigate the association between the GGE Biplot and REML/BLUP methods and select cowpea genotypes that meet simultaneously high grain yield, adaptability and stability in the Mato Grosso do Sul environments. The experiments were carried out from February to July 2010, 2011 and 2012 in the municipalities of Dourados, Aquidauana and Chapadão do Sul. The experiments in Chapadão do Sul were conducted only in the years of 2010 and 2011, totaling eight environments. After detecting significant genotypes × environments (GE) interaction, the adaptability and the phenotypic stability of cowpea genotypes were analyzed by GGE Biplot and REML/BLUP methods. These methods were concordant in the identification of the best cowpea genotypes for the State of Mato Grosso do Sul. The BRS- Tumucumaque and BRS-Guariba cultivars are the closest to the ideal in terms of high grain yield and phenotypic stability, being suitable for cultivation in the State.

Physiological Basis of Yield Differences in Quality Protein Maize Genotypes of Different Maturity Groups

2019 ◽  
pp. 1-7
Author(s):  
Olasoji, Julius Oluseyi ◽  
Ajayi, Sunday Adesola
Keyword(s):  
Grain Yield ◽  
Agricultural Research ◽  
Block Design ◽  
Quality Protein Maize ◽  
Physiological Basis ◽  
Maize Genotypes ◽  
Southwest Nigeria ◽  
Ear Height ◽  
Cropping Seasons ◽  
Maturity Groups

Yield performance of early maturing maize (Zea mays L.) varieties in the rainforest agroecology of southwest Nigeria, is lower than that of intermediate varieties  and that there was no yield advantage in the late varieties over the intermediate maturing varieties. However, the physiological basis of yield differences is yet to be fully investigated. This study was carried out to investigate the physiological basis underlying yield differences in quality protein maize genotypes of different maturity groups. Field experiment was conducted as randomized complete block design (RCBD) with three replicates at Institute of Agricultural Research and Training, Obafemi Awolowo University, Moor Plantation, Ibadan during 2013 and 2014 cropping seasons. The results indicated that season influenced days to 50% Anthesis (DTA), days to 50% silking (DTS), anthesis silking interval (ASI), plant height (PLHT), ear height (EHT), ear per plant (EPP), ear aspect (EASP), kernel width (KWDT) and grain yield (GYD). Maturity groups also influenced DTA, DTS, PASP, PLHT, EHT, and with no effect on GYD. The overall mean grain yields across seasons were 4.44, 4.16, 3.64 and 3.36 t/ha for season 1, 2, 3 and 4, respectively.  It was concluded from this study that all the maturity groups used had similar grain yield.

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