Identification of Lentil Desirable Genotypes Using Multivariate Statistical Methods and Selection Index of Ideal Genotype under Rainfed Conditions

Amiri, Reza; Pezeshkpour, Payam; Karami, Iraj

doi:10.52547/jcb.13.39.140

Cited by 11 publications

(1 citation statement)

References 26 publications

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“…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. However, the SIIG method has not yet been utilized in soybean breeding for selecting genotypes based on different traits.…”

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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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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Improvement and selection for drought-tolerant sugar beet (Beta vulgaris L.) pollinator lines

Taleghani

Rajabi

Hemayati

et al. 2022

Results in Engineering

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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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Identification of Lentil Desirable Genotypes Using Multivariate Statistical Methods and Selection Index of Ideal Genotype under Rainfed Conditions

Cited by 11 publications

References 26 publications

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

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

Improvement and selection for drought-tolerant sugar beet (Beta vulgaris L.) pollinator lines

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

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