Evaluation the Mean Performance and Stability of Rice Genotypes by Combining Features of AMMI and BLUP Techniques and Selection Based on Multiple Traits

Sharifi, Peyman; Abbasian, A.; Mohaddesi, Ali

doi:10.52547/pgr.7.2.13

Cited by 15 publications

(10 citation statements)

References 26 publications

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“…In other words, they had low alpha‐amino N values and stability. These results were consistent with the findings of Sharifi et al (2021) who used the MTSI stability index for the evaluation of yield and other agronomic traits in a set of rice genotypes and showed that this index is well able to identify superior genotypes in terms of yield stability and other agronomic traits.…”

Section: Resultssupporting

confidence: 92%

“…Eigenvalues, relative and cumulative variance as well as factor coefficients after varimax rotation in factor analysis based on principal component analysis with the findings ofSharifi et al (2021) who used the MTSI stability index for the evaluation of yield and other agronomic traits in a set of rice genotypes and showed that this index is well able to identify superior genotypes in terms of yield stability and other agronomic traits.…”

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confidence: 84%

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Evaluation of resistance and determination of stability of different sugar beet (Beta vulgaris L.) genotypes in rhizomania‐infected conditions

Rajabi

Ahmadi

Bazrafshan

et al. 2022

Food Science & Nutrition

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Plant diseases are considered one of the main factors reducing yield and quality of crops, which are constantly developing and creating more virulent races and cause the resistance of more genes to break. Identifying resistance sources and including them in breeding programs will improve resistant genotypes. Rhizomania is the most common, widespread, and devastating disease of sugar beet in Iran and worldwide.Breeding genotypes with disease resistance genes is one of the most important ways to deal with this destructive disease. Twenty sugar beet genotypes along with five controls were evaluated in a randomized complete block design with four replications in rhizomania-infected conditions in four regions of Mashhad, Shiraz, Miandoab, and Hamedan for 2 years. The results of genotypic reaction to rhizomania showed that the genotypes with resistance reaction were much more frequent than those with susceptibility reaction. The analysis of multiplicative effects of the AMMI model showed that the first six components were significant and explained 98.80% of the interaction variations. The biplot obtained from the mean white sugar yield and the first interaction principal component confirmed the superiority of the RM5 genotype due to its high white sugar yield and stability in infected conditions. The results obtained from the first three principal components biplot showed that the RM9 genotype with a mean white sugar yield of 11.91 t. ha −1 was a genotype with vast general stability in all disease-infected environments. Based on the results of the MTSI index, RM3, RM17, RM9, RM13, and RM15 are introduced as stable genotypes under rhizomaniainfected conditions. In conclusion, it seems that the studied genotypes have valuable and useful genes inherited from their parents to deal with rhizomania disease.Applying these genotypes in sugar beet breeding programs can effectively prevent the threat of rhizomania.

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Section: Resultssupporting

confidence: 92%

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confidence: 84%

Evaluation of resistance and determination of stability of different sugar beet (Beta vulgaris L.) genotypes in rhizomania‐infected conditions

Rajabi

Ahmadi

Bazrafshan

et al. 2022

Food Science & Nutrition

View full text Add to dashboard Cite

show abstract

“…In general, the selected genotypes caused favorable selection differential in all traits (Table 7 ). Sharifi et al 50 and Koundinya et al 36 reported that MTSI would be very useful to the plant breeders for the selection of superior genotypes for multiple traits based on multi-environment data. Zuffo et al 51 used MTIS to identify stable soybean genotypes under drought and salinity stress conditions.…”

Section: Resultsmentioning

confidence: 99%

Stability analysis and selection of sugar beet (Beta vulgaris L.) genotypes using AMMI, BLUP, GGE biplot and MTSI

Taleghani

Rajabi

Saremirad

et al. 2023

Sci Rep

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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 regard, often instead of depending on a single analysis, it is better to use a combination of several methods to measure the nature of the GEI from various dimensions. In this study, the GEI was investigated using different methods. For this purpose, 18 sugar beet genotypes were evaluated in randomized complete block design in five research stations over 2 years. The additive effects analysis of the additive main effects and multiplicative interaction (AMMI) model showed that the effects of genotype, environment and GEI were significant for root yield (RY), white sugar yield (WSY), sugar content (SC), and extraction coefficient of sugar (ECS). The multiplicative effect's analysis of AMMI into interaction principal components (IPCs) showed that the number of significant components varies from one to four in the studied traits. According to the biplot of the mean yield against the weighted average of absolute scores (WAAS) of the IPCs, G2 and G16 for RY, G16 and G2 for WSY, G6, G4, and G1 for SC and G8, G10 and G15 for ECS were identified as stable genotypes with optimum performance. The likelihood ratio test showed that the effects of genotype and GEI was significant for all studied traits. In terms of RY and WSY, G3 and G4 had high mean values of the best linear unbiased predictions (BLUP), so they were identified as suitable genotypes. However, in terms of SC and ECS, G15 obtained high mean values of the BLUP. The GGE biplot method classified environments into four (RY and ECS) and three (WSY and SC) mega-environments (MEs). Based on the multi-trait stability index (MTSI), G15, G10, G6, and G1 were the most ideal genotypes.

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“…In a recent study by Olivoto et al 37 , they introduced a new index called the multi-trait stability index (MTSI). This index is highly efficient in selecting stable genotypes in multi-environment experiments based on multiple traits 8 , 11 , 38 , 39 . It considers the correlation structure among traits and provides a unique selection process that is easy to interpret 37 .…”

Section: Introductionmentioning

confidence: 99%

Genotype by environment and genotype by yield*trait interactions in sugar beet: analyzing yield stability and determining key traits association

Hassani,

Mahmoudi,

Saremirad

et al. 2024

Sci Rep

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The genotype by environment interaction significantly influences plant yield, making it imperative to understand its nature for the creation of breeding programs to enhance crop production. However, this is not the only obstacle in the yield improvement process. Breeders also face the significant challenge of unfavorable and negative correlations among key traits. In this study, the stability of root yield and white sugar yield, and the association between the key traits of root yield, sugar content, nitrogen, sodium, and potassium were examined in 20 sugar beet genotypes. The study was conducted using a randomized complete block design with four replications over two consecutive years across five locations. The combined analysis of variance results revealed significant main effects of year, location, and genotype on both root yield and white sugar yield. Notably, two-way and three-way interactions between these main effects on root yield and white sugar yield resulted in a significant difference. The additive main effect and multiplicative interaction analysis revealed that the first five interaction principal components significantly impacted both the root yield and white sugar yield. The linear mixed model results for root yield and white sugar yield indicated that the genotype effect and the genotype by environment interaction were significant. The weighted average absolute scores of the best linear unbiased predictions biplot demonstrated that genotypes 20, 4, 7, 2, 16, 3, 6, 1, 14, and 15 were superior in terms of root yield. For white sugar yield, genotypes 4, 16, 3, 7, 5, 1, 10, 20, 2, and 6 stood out. These genotypes were not only stable but also had a yield value higher than the total average. All key traits, which include sugar content, sodium, potassium, and alpha amino nitrogen, demonstrated a negative correlation with root yield. Based on the genotype by yield*trait analysis results, genotypes 20, 19, and 16 demonstrated optimal performance when considering the combination of root yield with sugar content, sodium, alpha amino nitrogen, and potassium. The multi-trait stability study, genotype 13 ranked first, and genotypes 10, 8, and 9 were identified as the most ideal stable genotypes across all traits. According to the multi-trait stability index, genotype 13 emerged as the top-ranking genotype. Additionally, genotypes 10, 8, and 9 were recognized as the most stable genotypes.

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Evaluation the Mean Performance and Stability of Rice Genotypes by Combining Features of AMMI and BLUP Techniques and Selection Based on Multiple Traits

Cited by 15 publications

References 26 publications

Evaluation of resistance and determination of stability of different sugar beet (Beta vulgaris L.) genotypes in rhizomania‐infected conditions

Evaluation of resistance and determination of stability of different sugar beet (Beta vulgaris L.) genotypes in rhizomania‐infected conditions

Stability analysis and selection of sugar beet (Beta vulgaris L.) genotypes using AMMI, BLUP, GGE biplot and MTSI

Genotype by environment and genotype by yield*trait interactions in sugar beet: analyzing yield stability and determining key traits association

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