Estimation of Genetic Parameters and Prediction of Genotypic Values in Common Beans Using Mixed Models

In the international scenario of agriculture, Brazil stands out as the main producer and consumer of common bean (Phaseolus vulgaris L.) The increase in the productive potential of the crop is mainly due to breeding programs. The objective of this study was to estimate genetic parameters, predict genotypic values with REML/BLUP (Restricted Maximum Likelihood/Best Linear Unbiased Prediction) and, based on these values, study the variability in common bean cultivars with carioca and black grain. Twenty three agromorphological descriptors were evaluated, among them grain yield. Deviance analysis detected significant differences between the cultivars in both groups. Selective accuracy (Ac) was considered high for most of the traits. Broad-sense heritability (hg2 ) ranged from 0.05 to 0.72, but it was low for the trait yield (YLD). In the carioca grain group, the hg2 values for the traits related to plant morphology were higher than in the black group. Nevertheless, the hg2 values in the black group were higher in relation to the pod and seed traits. The correlations for YLD were moderate but different in the two commercial groups studied. In the black group, variables related to the seed morphology were correlated with grain yield, and in the carioca group, traits related to seed quantity. Based on the groupings, variability among the cultivars was observed. Three distinct clusters were formed for the carioca group and four for the black group. Based on the predicted genetic values, genetic variability and the most adapted and stable cultivars were detected among the cultivars in the studied environments.

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Estimation of genetic parameters and prediction of genotypic values in common beans using mixed models#

Emirates Journal of Food and Agriculture ◽

10.9755/ejfa.2018.v30.i12.1884 ◽

2019 ◽

pp. 1026

Author(s):

Jessica Delfini, Vania Moda Cirino, C. de F. Ruas, Paulo M. Ruas, ◽

José dos Santos Neto, Leandro Simões Azeredo Gonçalves

Keyword(s):

Grain Yield ◽

Common Bean ◽

Genetic Parameters ◽

Plant Morphology ◽

Seed Morphology ◽

Linear Unbiased Prediction ◽

Breeding Programs ◽

Creative Commons ◽

Productive Potential ◽

Best Linear Unbiased

In the international scenario of agriculture, Brazil stands out as the main producer and consumer of common bean (Phaseolus vulgaris L.) The increase in the productive potential of the crop is mainly due to breeding programs. The objective of this study was to estimate genetic parameters, predict genotypic values with REML/BLUP (Restricted Maximum Likelihood/Best Linear Unbiased Prediction) and, based on these values, study the variability in common bean cultivars with carioca and black grain. Twenty three agromorphological descriptors were evaluated, among them grain yield. Deviance analysis detected significant differences between the cultivars in both groups. Selective accuracy (Ac) was considered high for most of the traits. Broad-sense heritability ( ) ranged from 0.05 to 0.72, but it was low for the trait yield (YLD). In the carioca grain group, the values for the traits related to plant morphology were higher than in the black group. Nevertheless, the values in the black group were higher in relation to the pod and seed traits. The correlations for YLD were moderate but different in the two commercial groups studied. In the black group, variables related to the seed morphology were correlated with grain yield, and in the carioca group, traits related to seed quantity. Based on the groupings, variability among the cultivars was observed. Three distinct clusters were formed for the carioca group and four for the black group. Based on the predicted genetic values, genetic variability and the most adapted and stable cultivars were detected among the cultivars in the studied environments. #This article has been posted in Preprints with a doi 10.20944/preprints201803.0215.v1 (https://www.preprints.org/manuscript/201803.0215/v1) (Creative Commons CC BY 4.0 license) *Corresponding author, Email: [email protected]

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Genetic Parameters and Selection in Full-Sib Families of Tall Fescue Using Best Linear Unbiased Prediction (BLUP) Analysis of Animal Breeding and Genetic

10.21203/rs.3.rs-1198310/v1 ◽

2021 ◽

Author(s):

Fatemeh Pirnajmedin ◽

Mohammad Mahdi Majidi ◽

Mohammad Hadi Taleb ◽

Davoud Rostami

Keyword(s):

Ssr Markers ◽

Tall Fescue ◽

Genetic Parameters ◽

Best Linear Unbiased Prediction ◽

Forage Yield ◽

Linear Unbiased Prediction ◽

Breeding Programs ◽

Sib Families ◽

Best Linear Unbiased ◽

Selection Of

Abstract Background: Better understanding of genetic structure of economic traits is crucial for identification and selection of superior genotypes in specific breeding programs. Best linear unbiased prediction (BLUP) is the most efficient method in this regards, which is poorly used in forage plant breeding. The present study aimed to assess genetic variation, estimate genetic parameters, and predict breeding values of five essential traits in full sib families (recognized by EST-SSR markers) of tall fescue using REML/BLUP procedure. Method: Forty-two full-sib families of tall fescue (included of 120 individual genotypes), recognized by EST-SSR markers’ along with twenty-one their corresponding parental genotypes were assessed for biomass production and agro-morphological traits at three harvests (spring, summer, and autumn) in the field during 4 years (2017-2020). Results: Considerable genotypic variability was observed for all traits. Low narrow-sense heritability (h2n) for dry forage yield (DFY) at three harvest indicates that non-additive gene actions may play an important role in the inheritance of this trait. Higher h2n of yield related traits and flowering time and also significant genetic correlation of these traits with forage yield, suggests that selection based on these traits via developing an index may lead to indirect genetic improvement of DFY. Conclusion: Our results showed the adequacy of REML/BLUP procedure for identification and selection of preferable parental genotypes and progenies with higher breeding values for future breeding programs such as variety development in tall fescue. Parental genotypes 21M, 1M, and 20L were identified as superior and stable genotypes and could also produce the best hybrid combinations when they were mostly used as maternal parent.

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Quantitative genetic analysis of methylxanthines and phenolic compounds in mate progenies

Pesquisa Agropecuária Brasileira ◽

10.1590/s0100-204x2010000200008 ◽

2010 ◽

Vol 45 (2) ◽

pp. 171-177 ◽

Cited By ~ 8

Author(s):

Euclides Lara Cardozo Junior ◽

Carmen Maria Donaduzzi ◽

Osvaldo Ferrarese-Filho ◽

Juliana Cristhina Friedrich ◽

Adriana Gonela ◽

...

Keyword(s):

Phenolic Compounds ◽

High Performance ◽

Genetic Parameters ◽

Best Linear Unbiased Prediction ◽

Region Of Origin ◽

Linear Unbiased Prediction ◽

Breeding Programs ◽

Quantitative Genetic ◽

Sib Families ◽

Best Linear Unbiased

The objective of this work was to determine the contents of methylxanthines, caffeine and theobromine, and phenolic compounds, chlorogenic and caffeic acids, in 51 mate progenies (half-sib families) and estimate the heritability of genetic parameters. Mate progenies were from five Brazilian municipalities: Pinhão, Ivaí, Barão de Cotegipe, Quedas do Iguaçu, and Cascavel. The progenies were grown in the Ivaí locality. The contents of the compounds were obtained by high performance liquid chromatography (HPLC). The estimation of genetic parameters by the restricted maximum likelihood (REML) and the prediction of genotypic values via best linear unbiased prediction (BLUP) were obtained by the Selegen - REML/BLUP software. Caffeine (0.248-1.663%) and theobromine (0.106-0.807%) contents were significantly different (p<0.05) depending on the region of origin, with high individual heritability (ĥ²>0.5). The two different progeny groups determined for chlorogenic (1.365-2.281%) and caffeic (0.027-0.037%) acid contents were not significantly different (p<0.05) depending on the locality of origin. Individual heritability values were low to medium for chlorogenic (ĥ²<0.4) and caffeic acid (ĥ²<0.3). The content of the compounds and the values of genetic parameters could support breeding programs for mate.

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Prediction of genotypic values and estimation of genetic parameters in common bean

Brazilian Archives of Biology and Technology ◽

10.1590/s1516-89132008000300005 ◽

2008 ◽

Vol 51 (3) ◽

pp. 465-472 ◽

Cited By ~ 12

Author(s):

Alisson Fernando Chiorato ◽

Sérgio Augusto Morais Carbonell ◽

Luiz Antônio dos Santos Dias ◽

Marcos Deon Vilela de Resende

Keyword(s):

Common Bean ◽

Genetic Parameters ◽

High Accuracy ◽

Best Linear Unbiased Prediction ◽

Broad Sense Heritability ◽

Phaseolus Vulgaris L ◽

Linear Unbiased Prediction ◽

Best Linear Unbiased ◽

Estimation Of Genetic Parameters ◽

Selection Of

Eighteen common bean (Phaseolus vulgaris L.) genotypes were evaluated in 25 environments of the state of São Paulo in 2001 and 2002. The estimation of genetic parameters by the Restricted Maximum Likelihood (REML) and the prediction of genotypic values via Best Linear Unbiased Prediction (BLUP) were obtained by software Selegen-REML/BLUP. The estimate of the broad-sense heritability was low for the grain yield (0.03), since it took individual plots into consideration and was free of the effects of interaction with years, cultivation periods and site. Nevertheless, the heritability at the level of line means across the various environments was high (0.75), allowing a high accuracy (0.87) in the selection of lines for planting in the environment mean. Among the 18 genotypes, the predicted genotypic values of nine were higher than the general mean. The genetic gain predicted with the selection of the best line, in this case line Gen 96A31 of the IAC, was 16.25%.

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Five decades of black common bean genetic breeding in Brazil

Pesquisa Agropecuária Tropical ◽

10.1590/1983-40632016v4641371 ◽

2016 ◽

Vol 46 (3) ◽

pp. 259-266 ◽

Cited By ~ 4

Author(s):

Leiri Daiane Barili ◽

Naine Martins do Vale ◽

José Eustáquio de Souza Carneiro ◽

Fabyano Fonseca e Silva ◽

Felipe Lopes da Silva

Keyword(s):

Grain Yield ◽

Common Bean ◽

Seed Weight ◽

Regression Models ◽

Plant Architecture ◽

Agronomic Traits ◽

Linear Regression Models ◽

Genetic Progress ◽

Breeding Programs ◽

Genetic Breeding

ABSTRACT The increase in grain yield and other agronomic traits, in common bean cultivars, is due, in large part, to its genetic breeding. This study aimed at estimating the genetic progress for grain yield and other important agronomic traits in black common bean cultivars recommended by Brazilian breeding programs between 1960 and 2013. A randomized blocks design was used, with three replications and 40 black common bean cultivars. The following traits were evaluated: grain yield and appearance, plant architecture, number of pods per plant and seeds per pod and 1,000-seed weight. The genetic progress was estimated from the trait averages over the years, using bissegmented linear regression models that allowed the inference of the exact year in which the black common bean breeding began to present significant genetic progress. For grain yield, the genetic progress was observed from 1988, with an annual gain of 2.42 %. Improvements also occurred to grain appearance (1.85 %), plant architecture (1.35 %), number of pods per plant (2.36 %) and seeds per pod (2.24 %) and 1,000-seed weight (1.42 %), mainly after 1989.

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Selection of common bean land cultivars based on agronomic performance, cooking time, and mineral concentration

Semina Ciências Agrárias ◽

10.5433/1679-0359.2016v37n3p1255 ◽

2016 ◽

Vol 37 (3) ◽

pp. 1255 ◽

Cited By ~ 2

Author(s):

Narielen Moreira de Morais ◽

Nerinéia Dalfollo Ribeiro ◽

Lindolfo Storck ◽

Paulo Rogério Franco dos Santos ◽

Micheli Thaise Della Flora Possobom

Keyword(s):

Grain Yield ◽

Common Bean ◽

Nutritional Quality ◽

Cooking Time ◽

Agronomic Performance ◽

Mineral Concentration ◽

Breeding Programs ◽

Calcium Iron ◽

Santa Maria ◽

Potential Use

The potential use of common bean land cultivars with respect to their agronomic performance, cooking time and nutritional quality has scarcely been evaluated in breeding programs. The objective of the present study was to evaluate 19 common bean land cultivars for their agronomic traits, cooking time, and mineral concentration in grains to identify cultivars for potential use by a higher number of farmers or even breeding programs. Two field experiments were conducted in Alegrete and Santa Maria, Rio Grande do Sul (RS), Brazil, in the 2012/2013 season. The experimental design consisted of randomized blocks with three replications. A total of 23 cultivars were evaluated; 19 land cultivars were obtained from smallholder farmers from RS, and there were four control cultivars (Carioca, Pérola, Valente, and Guapo Brilhante). The traits evaluated included the cycle, insertion of the first pod, grain yield, cooking time, and concentrations of calcium, iron, zinc, and copper in the grains. The data were subjected to joint variance analysis, Pearson correlation analysis, and the Z index. The common bean cultivars showed differences in the cycle, insertion of the first pod, grain yield, cooking time, calcium, iron, zinc, and copper concentrations in grains, and the Z index. The cultivars Preto Miúdo and Cavalo Rajado had a high grain yield, i.e., greater than 2,900 kg ha-1. The land cultivars were classified as having early and intermediate cycles, and all had cooking times less than 30 min. Palha Roxa, Carioca Vermelho, and Perdiz had high concentrations of calcium, iron, zinc, and copper in the grains, an intermediate cycle, and low grain yield. Positive correlations of moderate magnitude were observed between the calcium and iron (r= 0.597), iron and zinc (r= 0.570), and zinc and copper (r= 0.548) concentrations. Indirect selection for high iron or zinc concentrations in grains will be effective for obtaining common bean cultivars with a higher nutritional quality. A cross between Carioca Santa Maria and Guapo Brilhante cultivar is recommended to obtain segregants with high agronomic performance, fast cooking, and high minerals concentration of in the grains.

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Use of the REML/BLUP methodology for the selection of sweet orange genotypes

Pesquisa Agropecuária Brasileira ◽

10.1590/s1678-3921.pab2021.v56.02032 ◽

2021 ◽

Vol 56 ◽

Author(s):

Márcia da Costa Capistrano ◽

Romeu de Carvalho Andrade Neto ◽

Vanderley Borges dos Santos ◽

Lauro Saraiva Lessa ◽

Marcos Deon Vilela de Resende ◽

...

Keyword(s):

Genetic Parameters ◽

Sweet Orange ◽

Superior Performance ◽

Yield Potential ◽

Components Of Variance ◽

Linear Unbiased Prediction ◽

Character Set ◽

Best Linear Unbiased ◽

Fruit Mass ◽

Selection Of

Abstract: The objective of this work was to select superior sweet orange (Citrus sinensis) genotypes with higher yield potential based on data from eight harvests, using the residual or restricted maximum likelihood/best linear unbiased prediction (REML/BLUP) methodology. The experiment was carried out from 2002 to 2008 and in 2010 in the municipality of Rio Branco, in the state of Acre, Brazil. Analyzes of deviance were performed to test the significance of the components of variance according to the random effects of the used model, and parameters were estimated from individual genotypic and phenotypic variances. A selection intensity of 20% was adopted regarding genotypic selection, i.e., only the best 11 of the 55 genotypes tested were selected. The estimates of the genetic parameters show the existence of genetic variability and the selection potential of the studied sweet orange genotypes. The genotypic correlation between harvests is of low magnitude, except for the variable average fruit mass, and, as a reflex, there is a change in the ordering of the genotypes. Genotypes 5, 48, 19, 14, and 47 stand out as being the most productive, and, therefore, are the most suitable for selection purposes. Genotypes 14 and 47 show superior performance for the character set evaluated.

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GENETIC PARAMETERS OF GIROLANDO CROSSBRED COWS IN DAIRY HERDS IN THE STATE OF ACRE, BRAZIL

Arquivos de Ciências Veterinárias e Zoologia da UNIPAR ◽

10.25110/arqvet.v23i1cont.2020.7644 ◽

2020 ◽

Vol 23 (1cont) ◽

Author(s):

Andressa Pereira Braga ◽

José Marques Carneiro Júnior ◽

Antônia Kaylyanne Pinheiro ◽

Maurício Santos Silva

Keyword(s):

Maximum Likelihood ◽

Milk Production ◽

Genetic Parameters ◽

Heritability Estimate ◽

Restricted Maximum Likelihood ◽

Dairy Herds ◽

Genetic Progress ◽

Linear Unbiased Prediction ◽

Best Linear Unbiased ◽

Selection For

This study aimed at estimating genetic parameters for milk production and conformation characteristics in Girolando crossbred dairy cows reared in the High and Low Acre region using the restricted maximum likelihood methodology, under an animal model. We estimated the variance components and genetic parameters using the REML/BLUP procedure (Restricted Maximum Likelihood Methodology/Best Linear Unbiased Prediction). The estimated average for milk production for 305 days of lactation (P305) was of 1523.25 ± 481.11 kg, with a heritability of 0.38 for this characteristic. The conformation characteristics showed no significant correlation with milk production. The phenotypical correlations between the linear characteristics of type were, in general, positive and moderate. The P305 obtained in this study can be considered low and indicates that there is a possibility of increasing milk production through selection in herds along with the use of tested and proven bulls. The heritability estimate found (0.38) indicates that there is genetic variability for milk production, demonstrating that selection for this characteristic would result in genetic progress.

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A Bayesian Genomic Multi-output Regressor Stacking Model for Predicting Multi-trait Multi-environment Plant Breeding Data

G3 Genes|Genome|Genetics ◽

10.1534/g3.119.400336 ◽

2019 ◽

Vol 9 (10) ◽

pp. 3381-3393 ◽

Cited By ~ 4

Author(s):

Osval A. Montesinos-López ◽

Abelardo Montesinos-López ◽

José Crossa ◽

Jaime Cuevas ◽

José C. Montesinos-López ◽

...

Keyword(s):

Ridge Regression ◽

Prediction Accuracy ◽

Best Linear Unbiased Prediction ◽

Environment Interaction ◽

Linear Unbiased Prediction ◽

Breeding Programs ◽

Second Stage ◽

Genotype Environment Interaction ◽

Best Linear Unbiased ◽

Two Stages

In this paper we propose a Bayesian multi-output regressor stacking (BMORS) model that is a generalization of the multi-trait regressor stacking method. The proposed BMORS model consists of two stages: in the first stage, a univariate genomic best linear unbiased prediction (GBLUP including genotype × environment interaction GE) model is implemented for each of the L traits under study; then the predictions of all traits are included as covariates in the second stage, by implementing a Ridge regression model. The main objectives of this research were to study alternative models to the existing multi-trait multi-environment (BMTME) model with respect to (1) genomic-enabled prediction accuracy, and (2) potential advantages in terms of computing resources and implementation. We compared the predictions of the BMORS model to those of the univariate GBLUP model using 7 maize and wheat datasets. We found that the proposed BMORS produced similar predictions to the univariate GBLUP model and to the BMTME model in terms of prediction accuracy; however, the best predictions were obtained under the BMTME model. In terms of computing resources, we found that the BMORS is at least 9 times faster than the BMTME method. Based on our empirical findings, the proposed BMORS model is an alternative for predicting multi-trait and multi-environment data, which are very common in genomic-enabled prediction in plant and animal breeding programs.

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Genetic parameters and agronomic evaluation of cassava genotypes

Pesquisa Agropecuária Brasileira ◽

10.1590/s0100-204x2016000700006 ◽

2016 ◽

Vol 51 (7) ◽

pp. 834-841 ◽

Cited By ~ 5

Author(s):

Rodrigo de Souza Silva ◽

Elisa Ferreira Moura ◽

João Tomé de Farias Neto ◽

José Edson Sampaio

Keyword(s):

Genetic Variability ◽

Genetic Parameters ◽

Starch Content ◽

The State ◽

Root Yield ◽

Linear Unbiased Prediction ◽

Genetic Gains ◽

Growing Seasons ◽

Best Linear Unbiased ◽

Shoot Weight

Abstract: The objective of this work was to estimate genetic parameters and predict genetic values for the selection of cassava (Manihot esculenta) genotypes in the state of Pará, Brazil. The trial was performed with 56 genotypes in two growing seasons (2012/2013 and 2013/2014), in the municipality of Igarapé-Açu, in the state of Pará, using the augmented blocks design with two control treatments. The evaluated traits were: plant shoot weight (PSW), number of roots per plant (NRP), number of rotten roots per plant (NRRP), fresh root yield (FRY), harvest index (HI), and starch content in the roots (SCR). The restricted maximum likelihood (REML) and best linear unbiased prediction (BLUP) methods were used. There was genetic variability among genotypes for PSW, NRP, HI, and SCR. Broad-sense heritability estimates were low for PSW and SCR, but were moderate for NRP and HI. However, the heritabilities of the average of genotypes were higher for PSW and SCR. The genetic gains of the five best genotypes varied from 6.0 to 11.08% (PSW), 15.81 to 27.10% (NRP), 9.82 to 12.14% (HI), and 1.90 to 2.20% (SCR). There is genetic variability among cassava genotypes, and the possibility of genetic gains based on selection is moderate for this region in the state of Pará.

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