Restricted maximum likelihood/best linear unbiased prediction (REML/BLUP) for analyzing the agronomic performance of corn

Nardino, Maicon; Baretta, Diego; Carvalho, Ivan Ricardo; Olivoto, Tiago; Follmann, Diego Nicolau; Szareski, VinÃ­cius Jardel; Ferrari, Maurício; Pelegrin, Alan Junior de; Konflanz, Valmor Antônio; Souza, V. Q. de

doi:10.5897/ajar2016.11691

Cited by 11 publications

(2 citation statements)

References 13 publications

(14 reference statements)

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“…The BLUP has been used in the evaluation of various crops such as rice (53), corn (54), cotton (55) and sugarcane (56) and useful results have been presented. One of the most important advantages of the mentioned method is the accurate estimation of the mean performance of genotypes, especially in LMMs (28,49,57). In addition, when there is a LMM effect in the results, the BLUP allows optimal prediction of random effects (58,59).…”

Section: Table 3 Estimation Of Phenotypic Variance Components Of Whit...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: Table 3 Estimation Of Phenotypic Variance Components Of Whit...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

View full text Add to dashboard Cite

show abstract

“…The fertilization of 300 kg ha -1 of NPK in the formulation 05-20-20 was applied, and 180 kg ha -1 of nitrogen in the amide form was applied for top dressing, on the stages V4 and V6, following the phenological scale proposed by (Ritchie et al, 1993). The control of invasive plants, insect-pests, and diseases were carried out in a preventive way in order to minimize biotic influences in the experiment (Nardino et al, 2016a).…”

Section: Methodsmentioning

confidence: 99%

Interrelations of Characters and Multivariate Analysis in Corn

Szareski¹,

Carvalho²,

Kehl³

et al. 2018

JAS

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The objective of this work was to evaluate the agronomic performance of corn hybrids, the interrelations of the characters with the grain yield, and to genetically discriminate the corn hybrids by means of the dispersion analysis of the canonical variables. The experiment was conducted in the agricultural crop of 2013/2014, in an area belonging to the Federal University of Santa Maria, Campus of Frederico Westphalen, RS. The experimental design was a randomized block design, with four replications. The treatments were composed of seven maize hybrids with different genetic bases and maturation cycles. The LG 6304 modified simple hybrid has higher grain yield than the others. The characters plant height, spike insertion height and number of grains per row of spike have positive interrelations with grain yield of corn hybrids. Hybrids are not grouped according to the genetic basis and maturation cycle. The canonical variables explain 94.62% of the existing genetic variation, and allows the formation of five groups of maize hybrids.

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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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Restricted maximum likelihood/best linear unbiased prediction (REML/BLUP) for analyzing the agronomic performance of corn

Cited by 11 publications

References 13 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

Interrelations of Characters and Multivariate Analysis in Corn

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

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