Path analysis of genotype × environment interaction in wheat-barley disomic addition lines

Farshadfar, Ezatollah

doi:10.1556/aagr.61.2013.4.2

Cited by 59 publications

(84 citation statements)

References 35 publications

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“…The AMMI analysis of variance of grain yield of the fifty five genotypes tested in three environments showed that 71.65% of the total sum of squares was attributable to genotypic effects, 10.51%to environmental effects and 17.83% to genotype × environment interaction effects (Table 2). This is in accordance with the report of Kaya et al (2006);Farshadfar et al (2012) and Mohamed et al (2013). In their study, the effects of E, G and GEI accounted for 81, 7.3 and 11.7% of the total treatments variation respectively.…”

Section: Resultssupporting

confidence: 93%

Grain Yield Performance and Stability of Quality Protein Maize Single Cross Hybrids in Mid-altitude Environment in Uganda

Ayiga-Aluba¹,

Asea²,

Kwemoi³

et al. 2018

JAS

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Stability in performance is important for determining adaptation and recommendation of pre-commercial crop varieties. This study was conducted with the following objectives: i) to determine stability of grain yield for 55 quality protein maize (QPM) single cross hybrids generated from 14 inbred lines ii) to determine the pattern of grouping of QPM hybrids and test environments based on grain yield response. The test hybrids were generated during the second season of 2015 and evaluated in three agro-ecological zones during the first season of 2016. Two checks were used: Longe 5D, a popular QPM hybrid and a top cross of Longe 5D with CML511. Additive main effects and multiplicative interaction (AMMI) and genotype and genotype by environment interaction (GGE) analyses were used to assess the stability of the hybrids. Results showed highly significant differences between genotypes, environments and GEI. The first principal component axis (IPCAI) was significant (p < 0.01) and accounted for 61.5% of the interaction effect. Both (IPCAI) and IPCAII) cumulatively contributed to entire degrees of freedom available for interaction component. Hybrid QPMSC-29 had the highest grain yield across environments. The AMMI biplot clearly depicted the genotypes on the bases of their adaptation patterns. Hybrids QPMSC-43, QPMSC-12, QPMSC-18 and QPMSC-29 were found to be more stable and responsive to favorable environments. Among them QPMSC-18 was more stable across locations. The AMMI biplot successfully identified 2 mega-environments as Namulonge and Bulindi in the first mega-environment with QPMSC-29 as the winning genotype and Masaka as the second mega-environment with QPMSC-10 as the winning genotypes. Hybrid, QPMSC-46 was an ideal genotype with above average score for grain yield. The single cross hybrids QPMSC-29, QPMSC-18 and QPMSC-10 were identified as stable yielder across environments in addition to higher yield. These hybrids can be recommended for all the three locations, for cultivation.

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Section: Resultssupporting

confidence: 93%

Grain Yield Performance and Stability of Quality Protein Maize Single Cross Hybrids in Mid-altitude Environment in Uganda

Ayiga-Aluba¹,

Asea²,

Kwemoi³

et al. 2018

JAS

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“…An interesting application of GGE biplot software is the evaluation of genotype relative to an ideal genotype. The ideal genotype as virtual genotype is one that has both high mean yield across test environments and is absolutely stable in performance (Yan and Rajcan, 2002;Yan and Kang, 2003;Farshadfar et al, 2012). This genotype has large PC1 scores (high mean yield) and small (absolute) PC2 scores (high stability).…”

Section: Evaluation Of Genotypes Relative To Idealmentioning

confidence: 99%

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

et al. 2015

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The genotype and genotype by environment biplot model is an excellent tool for visual multienvironment 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.

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“…Thus, using the ideal genotype as the centre, concentric circles were drawn to help visualize the distance between each genotype and the ideal genotype (Yan and Tinker, 2005). The ranking based on the genotype -focused scaling assumes that stability and mean yield are equally important (Farshadfar et al, 2012;Yan and Hunt, 2001). Fig.…”

Section: Fig 2 Ammi Biplot Graph For Ipca 2 and Grain Yield Genotymentioning

confidence: 99%

AMMI and GGE biplots for G×E analysis of wheat genotypes under rain fed conditions in central zone of India

Verma

Chatrath

Sharma

2015

JANS

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Abstract:The highly significant environments, genotypes and G×E interaction observed by AMMI analysis of 17 wheat genotypes evaluated at 8 locations in the central zone of the country. Environments(E), genotypes -environment interaction(GE) and genotypes explained 68.8%, 17.6% and 3.2% of the total sum of squares respectively. First four interaction principal components accounted 33.7%, 30.2%, 14.6% and 12.6% of the G×E interaction variation, respectively. The highest positive IPCA1 score of genotype G 8 followed by G 11 and G 10 supported by yield higher than the grand mean 21.8q/ha. Environments E 4 (Jabalpur) and E 8 (Partapgarh) recorded maximum yield 32.6q/ha and 28.4q/ha while lowest yield was realized in E 1

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Path analysis of genotype × environment interaction in wheat-barley disomic addition lines

Cited by 59 publications

References 35 publications

Grain Yield Performance and Stability of Quality Protein Maize Single Cross Hybrids in Mid-altitude Environment in Uganda

Grain Yield Performance and Stability of Quality Protein Maize Single Cross Hybrids in Mid-altitude Environment in Uganda

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

AMMI and GGE biplots for G×E analysis of wheat genotypes under rain fed conditions in central zone of India

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