AMMI Biplot Analysis for Genotype X Environment Interaction and Stability for Yield in Hybrid Rice (Oryza sativa L.) Under Different Production Seasons

Devi, K. Rukmini; Venkanna, V.; Lingaiah, N.; Prasad, K. Rajendra; Chandra, B. Satish; Hari, Yosuke; Rao, P. Jagan Mohan

doi:10.9734/cjast/2020/v39i4831214

Cited by 8 publications

(6 citation statements)

References 9 publications

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“…In the present study, the rice landraces, G10 (Chandikar) and G5 (Kuruvaikalanjium) were found to be more sensitive to environments. Similar results were previously reported by Devi et al (2020). The striking feature of what-won-where GGE biplot is its ability to show the what-won-where pattern of a genotype by environment.…”

Section: Resultssupporting

confidence: 89%

“…This implied that the first two principal components are enough to explain the interaction effects of 15 rice landraces in five production years/seasons. These findings are in agreement with the findings of Devi et al (2020). Biplots are graphs where both genotypes and environments are plotted on the same axes that interrelationships can be visualized (Anowara et al 2014).…”

Section: Resultssupporting

confidence: 81%

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Ammi Analysis for Yield and Stability in Direct Seeded Rainfed Rice

Muthuramu

Ragavan

2022

Bangladesh J. Bot.

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The genotype × environment interaction and stability performance of 15 rice landraces was studied using the additive mean effects and multiplicative interaction (AMMI) analysis. The overall, results indicated that significant genotype × environmental interaction (GEI) influenced the relative ranking of the rice landraces across the years/seasons. It was evident from AMMI analysis that first two principal components accounted for 91.90%, which is enough to explain the variability among the landraces. The landraces, G8 (Kallurundaikar), G4 (Sivapuchithiraikar) and G5 (Kuruvaikalanjiyam) exhibited high grain yield. The AMMI 2biplot revealed that the rice landraces, G12 (Poongar), G14(Kala namak) and G15 (Kichali samba) are close to the origin indicating non sensitive nature of these genotypes with the years/seasons and highly stable genotypes across the environments with low yield potential when compared to others. According to the polygon view of GGE biplot, the genotype G8 (Kallurundaikar) was the winner in the environments E2 and E5 whereas the genotypes G5 (Kuruvaikalanjium) and G7 (Mattaikar) were the winners in the environment E1, E3 and E4. The landrace, G8 (Kallurundaikar), has high mean yield with stable performance over five environments being the overall best and it may be considered for the direct seeded rice cultivation in the rainfed ecosystem. Bangladesh J. Bot. 51(3): 469-475, 2022 (September)

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Section: Resultssupporting

confidence: 89%

Section: Resultssupporting

confidence: 81%

Ammi Analysis for Yield and Stability in Direct Seeded Rainfed Rice

Muthuramu

Ragavan

2022

Bangladesh J. Bot.

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“…However, G6 (WGL 1370) and G8 (MTU 1010) were plotted near to zero IPCA1 axis indicating that these hybrids are relatively more stable across locations. The genotype, G4 (WGL 1367), was found superior among all the genotypes as well as over the checks and across all the environments under study.These findings were in agreement with Rukmini Devi et al [26], Kesh et al [23], Mohan et al [17], Siddi et al [27].The remaining genotypes had less than the mean grain yield and found specific adaptation to few tested environments. Likewise, Jain et al [28] reported that "genotypes with PC1 scores close to zero are usually widely adapted and they were considered more stable in their performance across test environments".…”

Section: Ammi 1 Biplotsupporting

confidence: 90%

Evaluation of Phenotypic Stability for Grain Yield in Rice (Oryza sativa L.) Genotypes Using AMMI and GGE Biplot Models

Chandra

Devi²,

Lingaiah³

et al. 2022

IJECC

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The experimens were carried out under four seasons with 9 rice genotypes at Regional Agricultural Research Station, Warangal, Telangana State, India during kharif season (July to November) 2019 (E1), rabi season (December to April) 2019-20 (E2), kharif season (July to November) 2020 (E3) and rabi season (December to April) 2020-21 (E4). The objective of the study was to assess the stability and adaptability of 9 rice genotypes over four seasons. Analysis of variance clearly showed that environments contributed the highest (69.66%) in the total sum of squares followed by genotypes×environments (12.66%) indicating a very greater role played by environments and their interactions in realizing final grain yield. AMMI 1 analysis revealed that rice genotypes viz., G4 (WGL 1367), G3 (WGL 1362), and G6 (WGL 1370) recorded higher mean grain yield with positive IPCA1 scores. AMMI 2 revealed that the genotypes, G6 (WGL 1370) and G3 (WGL 1362) were plotted near to zero IPCA1 axis indicating that these genotypes are relatively more stable across locations. GGE bi-plot genotype view depicts that the genotypes G4 (WGL 1367) and G3 (WGL 1362) were fell in the second concentric circle and found to be more stable across environments. GGE bi-plot environment view showed that rabi season of 2020-21 (E4) was the most ideal environment. However, rabi season of 2019-20 (E2) and kharif season 2020 (E3) were poor and most discriminating. What-won-where biplot indicated that four environments fell into two mega environments. Hence the genotype G4 (WGL 1367) was the winning genotype in the mega environment 1 viz., rabi season of 2019-20 (E2), rabi season of 2020-21 (E4) and kharif season of 2019 (E1). Whereas the genotype G9 (KNM 118) was the winner in the mega environment 2 i.e., Kharif, season of 2020 (E3).

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“…Comparably, Mary et al, (2019) reported that the biplot for yield during the wet season showed that G10 was the winner genotype in E4, and G7 in E8 and E9. Rukmini Devi et al, (2020) reported the rice genotypes, G2 (WGRH-6) and G3 (WGRH-10), had better performance in mega environment E3 and the genotype, G9 (WGRH-18), exhibited better…”

Section: What-won-where Bi-plotmentioning

confidence: 99%

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

Mohan¹,

Krishna²,

Sreedhar³

et al. 2021

IJBSM

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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.

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AMMI Biplot Analysis for Genotype X Environment Interaction and Stability for Yield in Hybrid Rice (Oryza sativa L.) Under Different Production Seasons

Cited by 8 publications

References 9 publications

Ammi Analysis for Yield and Stability in Direct Seeded Rainfed Rice

Ammi Analysis for Yield and Stability in Direct Seeded Rainfed Rice

Evaluation of Phenotypic Stability for Grain Yield in Rice (Oryza sativa L.) Genotypes Using AMMI and GGE Biplot Models

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

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