Evaluation of Durum Wheat Cultivars and Promising Lines for Yield and Yield Stability in Warm and Dry Areas using AMMI Model and GGE Biplot

Mirak, T Najafi; Dastfal, Manoochehr; Andarzian, B; Farzadi, H; Bahari, Mohammad; Zali, Hassan

doi:10.29252/jcb.10.28.1

Cited by 14 publications

(3 citation statements)

References 16 publications

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“…Multi-criteria decision analysis methods have been used in various studies to identify ideal genotypes. These indices have been used to identify superior genotypes in durum wheat stability analysis (44), drought tolerant genotypes in bread wheat (45), lentil (46) and sugar beet (1), heavy metal tolerant genotypes in durum wheat (47) and cold tolerant genotypes in canola (48). In general, according to the results of the present research, it can be stated that the use of TOPSIS makes it easier and more efficient to select the desired genotypes by integrating various statistics and ranking the experimental germplasm.…”

Section: Additive Main Effects and Multiplicative Interaction (Ammi)mentioning

confidence: 99%

Evaluation of resistance and stability of new sugar beet hybrids in field conditions infected with rhizoctonia root and crown rot disease

Rajabi

Saremirad

Rezaei

et al. 2023

Preprint

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Background The methods utilized to analyze genotype by environment interaction (GEI) and assess the stability and adaptability of genotypes are constantly changing and developing. In this study, 13 different sugar beet genotypes were grown in four naturally infected locations over two years. They were also assessed for resistance to Rhizoctonia disease in microplots artificially inoculated with the R133 isolate of Rhizoctonia solani. Results The additive main effect and multiplicative interaction (AMMI) analysis showed that both environment and genotype had significant additive effects, while GEI had a significant multiplicative effect. Further analysis of the interaction effects using IPCs revealed that the first three IPCs were significant. Based on the AMMI1 biplot, Rc3, Rc6, and Rc11 were recognized as the most stable genotypes. The TOPSIS calculated from AMMI statistics identified Rc3 as the most stable genotype. The LMM showed that the genotype and GEI were significant. Based on the best linear unbiased prediction (BLUP), Rc6 had the highest predicted mean white sugar yield (WSY). The obtained TOPSIS from BLUP statistics introduced Rc3 and Rc9 as the most stable genotypes. The WSY and WAASB biplot showed that Rc3, Rc5, and Rc11 had higher WSY in addition to stability. In terms of WAASBY/WSY ratio, BTS233, Rc5, and Rc7 were found to be stable genotypes. The simultaneous ranking and selection of genotypes based on the 50/50 ratio for WAASB and WSY yielded somewhat different results, with Rc3, Rc6, and Rc11 having relatively higher WAASBY values. Conclusion Based on the results, the AMMI alone cannot be successful in analyzing the structure of the LMM. In such a situation, using BLUP can bring better and more reliable results. However, the combination of AMMI power and BLUP prediction accuracy made it possible to investigate the genotypic stability and GEI derived from the LMM, and to reveal a complete view of the GEI of sugar beet product while eliminating the limitations of AMMI. In total, Rc3 followed by Rc6 and Rc11 were recognized as stable genotypes with high WSY. In addition to stability and high WSY, these genotypes also had genetic resistance against R. solani.

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Section: Additive Main Effects and Multiplicative Interaction (Ammi)mentioning

confidence: 99%

Evaluation of resistance and stability of new sugar beet hybrids in field conditions infected with rhizoctonia root and crown rot disease

Rajabi

Saremirad

Rezaei

et al. 2023

Preprint

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show abstract

“…It is noteworthy that as the number of traits or indicators increases, selecting the right genotype can become challenging. However, with the help of the SIIG discriminator, all parameters, despite having different measurement units, are consolidated into one parameter, simplifying the ranking and determination of the superior genotype (Najafi Mirak et al., 2018 ). This approach has been applied to a few crops, including bread wheat (Yaghutipoor et al., 2017 ), durum wheat (Najafi Mirak et al., 2018 ; Ramzi et al., 2018 ), lentil (Amiri et al., 2021 ), rapeseed (Abdollahi Hesar et al., 2021 ), sugar beet (Taleghani et al., 2022 ), and barley (Zali et al., 2023 ), for the assessment of superior genotypes according to a set of attributes or scales.…”

Section: Introductionmentioning

confidence: 99%

Deciphering genotype‐by‐environment interaction in new soybean lines based on multiple traits using different adaptability and stability methods

Majidian,

Masoudi,

Hezarjaribi

et al. 2024

Food Science & Nutrition

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The multi‐environmental trials aid breeders in selecting the best genotypes for specific or general adaptability to different environments before commercial release. This study aimed to assess the stability of 13 new soybean pure lines, along with two controls, in terms of seed yield and important agronomic traits. The assessment was based on a completely randomized block design with three replications across four areas during 2020–2022. Various adaptability methods, including parametric, AMMI, GGE biplot, PCA, and SIIG were employed. The mixed analysis showed that the effects of environment, genotype, and genotype–environment (GE) interaction were significant for most studied traits. The AMMI showed the highest portion of environment (65.89%) in soybean seed yield. Based on all stability parameters, lines 2 and 5 were selected for their average seed yields of 3349 and 3142 kg ha−1, respectively. Additionally, lines 6 and 5 showed the most stability, yielding higher than the average, which were 2992 and 3142 kg ha−1, respectively, according to GGE biplot results. Furthermore, lines 2, 5, and 8 were identified as the ideal genotypes concerning seed yield and other agronomic traits, with high SIIG parameters and yields exceeding the average. Finally, the soybean line 5 was deemed the most suitable due to its higher yield, stability, and early maturity (128‐day growth period). Therefore, line 5 is considered appropriate for its high stability and earliness in various regions of Iran.

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“…In the SIIG method, all the calculated stability indices of the genotypes are converted to a single index with a value in the range of 0-1, which makes it easier to determine the stable genotypes. It has been used to select the most stable genotypes by considering the different stability parameters (Zali et al 2015;Najafi Mirak et al 2018). Keeping in view the above, the objectives of the present study were to: (i) investigate the GE interactions on groundnut genotypes yield across different environments, (ii) compare parametric, AMMI stability, and GGE biplot analysis and, (iii) to select groundnut genotypes with a high and stable yield based on ideal genotype selection index (IGSI).…”

Section: Introductionmentioning

confidence: 99%

Stability analysis of groundnut (Arachis hypogaea L.) genotypes using AMMI and GGE biplot models and ideal genotype selection indicator

Navrood,

Zakaria,

Rad

et al. 2023

IJGPB

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A study on stability analysis was carried out on groundnut (Arachis hypogaea L.) genotypes grown at multilocation over two cropseasons. Based on additive main effects and multiplicative interaction (AMMI) analysis, the first two IPCAs explained 91.93% of the GEIvariation (74.84 and 17.09% for IPCA1 and IPCA2, respectively). Based on AMMI 2, the best genotype for environments RA1 and RA2 was 201. The genotypes, ICG192 and ICG130 were found suitable for environments TA1 and TA2, respectively. ICG178 was better adapted to environment MA2, whereas ICG140 and the control NC2 were the best genotypes for environment RA2. In the GGE biplot, PC1 and PC2 explained 81.22 and 13.33% of the total GGE variance. Based on the ideal genotype selection index (IGSI), the genotypes, ICG115, ICG201, and ICG178 were stable and can be used in the breeding programs to develop new varieties.

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Evaluation of Durum Wheat Cultivars and Promising Lines for Yield and Yield Stability in Warm and Dry Areas using AMMI Model and GGE Biplot

Cited by 14 publications

References 16 publications

Evaluation of resistance and stability of new sugar beet hybrids in field conditions infected with rhizoctonia root and crown rot disease

Evaluation of resistance and stability of new sugar beet hybrids in field conditions infected with rhizoctonia root and crown rot disease

Deciphering genotype‐by‐environment interaction in new soybean lines based on multiple traits using different adaptability and stability methods

Stability analysis of groundnut (Arachis hypogaea L.) genotypes using AMMI and GGE biplot models and ideal genotype selection indicator

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