Yield adaptability and stability of semi-prostrate cowpea genotypes in the
            Northeast region of Brazil by REML/BLUP

Rocha, M. de M.; Damasceno‐Silva, Kaesel Jackson; Menezes-Júnior, José Ângelo Nogueira de; Carvalho, H. W. L. de; Lima, João Maria Pinheiro de; Santos, João Felinto dos; Bertini, Cândida Hermínia Campos de Magalhães; Passos, Adriana Rodrigues; Morais, Otoniel Magalhães

doi:10.5935/1806-6690.20170104

Cited by 6 publications

(6 citation statements)

References 2 publications

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“…These results were expected to happen, since grain yield is a quantitative-nature characteristic and, consequently, very environmentally influential. Similar results were reported by PEREIRA et al (2016) andROCHA et al (2017) in studies with different bean species.…”

Section: Resultssupporting

confidence: 91%

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Assessing the genotypic performance of carioca beans through mixed models

et al. 2018

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Using genotypes adapted to different regions is one of the main ways to increase Brazilian bean yield. The aim of the present study was to assess the genotypic performance of Carioca beans through mixed models. Fourteen Carioca bean genotypes were assessed in four locations in Pernambuco State (Arcoverde, Caruaru, Belém de São Francisco and São João counties) in 2015. The experiments followed a completely randomized block design, with three repetitions. Genetic parameters were estimated according to the REML/BLUP methodology, whereas genotype selection was based on the harmonic mean of relative performance of genetic values method (MHPRVG). The mean genotype heritability had moderate magnitude, high selective accuracy, besides allowing selection of agronomically superior individuals. Genotypes ‘BRS Notável’, CNFC 15480 and ‘IPR 139’ showed good adaptability and grain yield stability. There was agreement among the statistics μ ̂ + g ̂…, stability (MHVG), adaptability (PRVG), and stability and adaptability of genetic values (MHPRVG) in the discrimination of the most productive genotypes, which presented high adaptability and stability. This outcome indicated that these genotypes can be part of the selection criteria regularly used in bean breeding programs.

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Section: Resultssupporting

confidence: 91%

“…Coefficient of genetic variation reached 6.93%, and it indicated that the median portion of genetic variances were extracted from the total phenotypic variance. Similar results were also reported by TORRES et al (2016) and ROCHA et al (2017), who assessed grain yield in cowpea genotypes subjected to multiple environments.…”

Section: Resultssupporting

confidence: 88%

Assessing the genotypic performance of carioca beans through mixed models

et al. 2018

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“…Given this context, the importance of the analysis of adaptability and stability is unequivocal, to generate reliable and accurate information regarding the selection of cowpea strains for grain productivity with greater predictability. Similar reports of G x E interaction as a component of most considerable influence on phenotypic variation were found by (ROCHA et al 2017), when evaluating the grain yield of 20 cowpea genotypes in Northeast Brazil.…”

Section: Resultssupporting

confidence: 78%

“…The expected genetic gain for these strains supplanted the performance of commercial cultivars 13 (BRS-Tumucumaque), 14 (BRS-Imponente) 26 (BRS-Itaim) and 27 (CB -27). ROCHA et al (2017), obtained similar predicted gains when evaluating cowpea strains of semi-erect size for adaptability and stability and high grain yield in the Northeast region of Brazil using the REML / BLUP methodology.…”

Section: Resultsmentioning

confidence: 67%

“…The individual phenotypic variance is composed by the computation of the genotypic variance, the residual variation between plots and the variation of the genotype x environment interaction (CARVALHO et al, 2016). The high magnitude of environmental variation over the other components of the phenotypic variation can be explained by the polygenic nature and low heritability of the trait and the fluctuations of the edaphoclimatic variables of each environment (SILVA et al, 2013b;BARILI et al, 2015).Studies reported by (TORRES et al, 2015;ROCHA et al, 2017), in multiple environments, presented a higher proportion of environmental variation concerning the (1) Deviance model adjusted without the quoted effects;…”

Section: Resultsmentioning

confidence: 99%

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Combined selection for adaptability, genotypic stability and cowpea yield from mixed models

et al. 2021

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The potential expression of crop productivity is a constant challenge for plant breeders in the face of oscillations in environmental variables, making selection difficult and increasing the operational and methodological costs in obtaining the ideal cultivar for a determined region. The objective of the research was to investigate the effects of genotype x environment interaction in the selection of cowpea lines with high grain yield, adaptability, and genotypic stability simultaneously, in environments of the Northwest region of Rio de Janeiro State, using mixed models (Maximum Restricted Likelihood - REML/Best Linear Unbiased Prediction - BLUP). 27 cowpea genotypes were evaluated in six environments by combining location (Cambuci-RJ and Bom Jesus do Itabapoana-RJ) and year (2016, 2017 and 2018). A randomized block design with four replications was performed. The genetic parameters were estimated via the REML/BLUP procedure, and the selection was based on the harmonic mean method of the relative performance of the genetic values (HMRPGV). A meaningful difference was observed for environment and genotype x environment interaction. The residual variance and the variance of the genotype x environment interaction formed the most significant fractions of the phenotypic variance. Lines 4 (Bico-de-ouro 1-5-24), 6 (Pingo-de-Ouro 1-5-4), 5 (Pingo-de-Ouro 1-5-26), and 9 (Pingo-de-Ouro 1-5-8), stood out as superior in terms of stability and adaptability and grain yield by HMRPGV. Commercial cultivars 13 (BRS-Tumucumaque) and 26 (BRS-Itaim) had high grain yield, adaptability, and specific stability in the evaluated edaphoclimatic conditions.

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Multi-environmental evaluation of winter oilseed rape genotypic performance using mixed models

Bocianowski

Liersch

2021

Euphytica

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The production of winter oilseed rape (WOSR) (Brassica napus) together with increasing seed yields per hectare is one of the strategies for breeding the genetic base of oilseed rape genotypes adapted to different environments. The main objective of this study was to evaluate the genotypic performance of 25 winter oilseed rape genotypes using mixed models. The plant material was examined in five locations in Poland. Field trials were carried out in a randomized complete block design with four replicates. The REML/BLUP was used to estimate genetic parameters. Selection of genotypes was made on the basis of genetic values by the harmonic mean of relative performance these parameters. The mean heritability for genotype had an average value at a high accuracy of selection, while additionally it facilitated selection of agronomically superior individuals. Three restorer lines PN18, PN17 and PN21, CMS ogura line PN64 as well as hybrids PN66 × PN21 and PN64 × PN21 characterized good adaptability and stability of seed yield. There were similarities among the statistics ($$\hat{\mu } + \hat{g}$$ μ ^ + g ^ ), adaptability and stability of genetic values in the discrimination of the most productive genotypes by best linear unbiased predictor analysis. Mixed models can be recommended as a potential selection method for the inclusion of new plant material in different oilseed rape breeding programs aimed at developing new WOSR cultivars.

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Yield adaptability and stability of semi-prostrate cowpea genotypes in the Northeast region of Brazil by REML/BLUP

Cited by 6 publications

References 2 publications

Assessing the genotypic performance of carioca beans through mixed models

Assessing the genotypic performance of carioca beans through mixed models

Combined selection for adaptability, genotypic stability and cowpea yield from mixed models

Multi-environmental evaluation of winter oilseed rape genotypic performance using mixed models

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