Assessment of Genotype × Trait × Environment interactions of silage maize genotypes through GGE Biplot

Kaplan, Mahmut; Kökten, Kağan; Akçura, Mevlüt

doi:10.4067/s0718-58392017000300212

Cited by 21 publications

(16 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…If the angle between the two traits vectors be less than 90˚, equal to 90˚, and 180˚, the correlation between the vectors would be +1, 0, and −1, respectively. Kaplan et al (2017) and Dolatabad et al (2010) had used this type of graph for studying maize varieties, and Adedeji et al (2020) had used this type of graph for studying cowpea. Accordingly, in Karaj region, the ear length, number of rows in ear, and grain width vectors had positive and significant correlation with each other since the angle between them was less than 90˚.…”

Section: Re Sult and Discussionmentioning

confidence: 99%

“…The identification of correlation between different traits and also the cause and effect relation between them help the breeders to select the most appropriate and logical relation between the constituents that is resulted in the further yield (Mardi, Talei, & Omidi, 2003). Kaplan, Kokten, and Akcura (2017) in studying of 25 silage maize, concluded that GGE biplot method with different perspective, could reliably by used in assessment of silage characteristics of maize genotypes grown in various environments. Adedeji, Ajayi, Osekita, and Ogunruku (2020) in studying of genotype × trait correlation on the cowpea cultivars, concluded that the majority of traits are positive and significant correlation with grain yield trait.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Assessment of genotype‐trait interaction in maize (Zea mays L.) hybrids using GGT biplot analysis

Shojaei

Mostafavi

Khosroshahli

et al. 2020

Food Science & Nutrition

View full text Add to dashboard Cite

show abstract

Section: Re Sult and Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Assessment of genotype‐trait interaction in maize (Zea mays L.) hybrids using GGT biplot analysis

Shojaei

Mostafavi

Khosroshahli

et al. 2020

Food Science & Nutrition

View full text Add to dashboard Cite

show abstract

“…On the other hand, in two environments of 2014 growing season, leaf rust disease population was virulent on Lr1,Lr2a,Lr2c,Lr3,Lr16,Lr26,Lr3ka,Lr17a,Lr30,LrB,Lr10,Lr14a,Lr18,Lr3bg,Lr14b,Lr20 and To analyze disease data from multi-environment trials can be one of the big challenges due to variability in testing conditions and assessment methods (Lillemo et al, 2010). GGE analysis is widely used for the analysis of GxE interaction in multi environment yield trials (Yan and Kang, 2003;Yan, 2014;Kaplan et al, 2017). It has gained popularity since the resulting biplot gives a graphical display of which-won-where pattern and makes it easy to identify group of environments with the same winners.…”

Section: Discussionmentioning

confidence: 99%

Biplot Analysis of Leaf Rust Reaction in Pure Lines Selected From Eastern Anatolian Bread Wheat Landraces of Turkey

Akçura

Akan

Hocaoğlu

2017

Turkish Journal of Field Crops

Self Cite

View full text Add to dashboard Cite

The present research was conducted to determine the reactions of 42 pure lines selected from bread wheat landraces of Eastern Anatolia, Turkey, against the leaf rust (Puccinia triticina) disease under field conditions across 7 environments. G (Genotype), GE (Genotype Environment) biplot analysis method was used to determine the reactions of landraces against leaf rust disease. GGE-biplot graph created to assess leaf rust disease was explained a 78.12% of total variation. While E3 and E2 constituted the first and second mega environments respectively, the other four environments constituted the third and fourth mega environments. The lowest PC1 values and PC2 values close to 0.0 explaining the resistance of pure lines to leaf rust at best in the biplot. Reactions of landraces varied based on their distance from the Average Environment Axis (AEA). While the pure lines with the same or similar reactions in 7 experimental environments fell close to the axis, ones with different reactions in one or more environments were relatively distant. The pure lines of EA15 and EA19 were identified as the most resistant and stable genotypes in all environments when EA42 and EA41 were the most susceptible/stable genotypes in all environments. Pure lines that were resistant or moderately resistant at all seven tested environments should be useful for breeding wheat cultivars with resistance to leaf rust in Turkey.

show abstract

“…Since the environment is an uncontrollable factor, the GGE biplot method uses the genotype change sources and the genotype-environment interaction to achieve reliable results (Yan et al 2000). GGE biplot method can be used to reliably in the evaluation of different maize genotypes grown in different environments (Kaplan et al 2017).…”

Section: Methodsmentioning

confidence: 99%

The plant nutrition impact on the quality and quantity parameters of maize hybrids grain yield based on different statistical methods

Illés

Mousavi

Bojtor

et al. 2020

CEREAL RESEARCH COMMUNICATIONS

View full text Add to dashboard Cite

In recent years, producers of agricultural products have increased the use of chemical fertilizers per unit area. The goal of this research was to analyze the interaction of genotype in treatment (NPK fertilizer) on grain yield, protein content, oil content, and the starch content on 13 maize hybrids using analysis by the model of additive and multiplier effects AMMI and to evaluate genotypes, treatments, and their interactions using biplot in Hungary. Treatments include NPK0 (N: 0 kg/ ha, P 2 O 5 :0 kg/ha, K 2 O: 0 kg/ha), NPK1 (N: 30 kg/ha, P 2 O 5 : 23 kg/ha, K 2 O: 27 kg/ha), NPK2 (N: 60 kg/ha, P 2 O 5 : 46 kg/ha, K 2 O: 54 kg/ha), NPK3 (N: 90 kg/ha, P 2 O 5 : 69 kg/ha, K 2 O: 81 kg/ha), NPK4 (N: 120 kg/ha, P 2 O 5 : 92 kg/ha, K 2 O: 108 kg/ ha), NPK5 (N: 150 kg/ha, P 2 O 5 : 115 kg/ha, K 2 O: 135 kg/ha) in four replications based on complete randomized block design in 2019. The NPK fertilizer effects indicate that the fertilizers are different on yield genotype. AMMI analysis showed that there was a significant difference between genotypes, treatment, and the interaction effect of genotype * treatment at one percent. Besides, the maximum yield had Loupiac and NPK3 on grain yield, Loupiac and NPK2 on oil content, P0023, and NPK3 for starch content, DKC 3/ES4725 (DKC4725) and NPK3 for protein content. Also, GGE biplot analysis indicates that had maximum grain yield in Loupiac, protein content in P9978, oil content in MV Maronetta, and starch content in Sushi.

show abstract

Assessment of Genotype × Trait × Environment interactions of silage maize genotypes through GGE Biplot

Cited by 21 publications

References 12 publications

Assessment of genotype‐trait interaction in maize (Zea mays L.) hybrids using GGT biplot analysis

Assessment of genotype‐trait interaction in maize (Zea mays L.) hybrids using GGT biplot analysis

Biplot Analysis of Leaf Rust Reaction in Pure Lines Selected From Eastern Anatolian Bread Wheat Landraces of Turkey

The plant nutrition impact on the quality and quantity parameters of maize hybrids grain yield based on different statistical methods

Contact Info

Product

Resources

About