scholarly journals Genetic parameters and agronomic evaluation of cassava genotypes

2016 ◽  
Vol 51 (7) ◽  
pp. 834-841 ◽  
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.

scholarly journals On Marker-Assisted Prediction of Genetic Value: Beyond the Ridge

Genetics ◽  
2003 ◽  
Vol 163 (1) ◽  
pp. 347-365 ◽  
Author(s):  
Daniel Gianola ◽  
Miguel Perez-Enciso ◽  
Miguel A Toro
Keyword(s):  
Genetic Variability ◽  
Multilevel Models ◽  
Selection Index ◽  
Spatial Covariance ◽  
Linear Unbiased Prediction ◽  
Lorenz Curves ◽  
Gini Coefficients ◽  
Best Linear Unbiased ◽  
Genetic Value ◽  
Dense Marker

Abstract Marked-assisted genetic improvement of agricultural species exploits statistical dependencies in the joint distribution of marker genotypes and quantitative traits. An issue is how molecular (e.g., dense marker maps) and phenotypic information (e.g., some measure of yield in plants) is to be used for predicting the genetic value of candidates for selection. Multiple regression, selection index techniques, best linear unbiased prediction, and ridge regression of phenotypes on marker genotypes have been suggested, as well as more elaborate methods. Here, phenotype-marker associations are modeled hierarchically via multilevel models including chromosomal effects, a spatial covariance of marked effects within chromosomes, background genetic variability, and family heterogeneity. Lorenz curves and Gini coefficients are suggested for assessing the inequality of the contribution of different marked effects to genetic variability. Classical and Bayesian methods are presented. The Bayesian approach includes a Markov chain Monte Carlo implementation. The generality and flexibility of the Bayesian method is illustrated when a Lorenz curve is to be inferred.

scholarly journals Response of yams exposed to different sources and doses of nitrogen fertilizers in the State of Maranhão, Brazil

2015 ◽  
Vol 36 (6) ◽  
pp. 3605
Author(s):  
Francisco Nóbrega dos Santos ◽  
Ademar Pereira de Oliveira ◽  
José Ribamar Gusmão Araújo ◽  
Ovidio Paulo Rodrigues da Silva ◽  
Débora Tuane de Araújo Ferreira Silva ◽  
...  
Keyword(s):  
Ammonium Sulfate ◽  
Starch Content ◽  
N Fertilization ◽  
The State ◽  
Nitrogen Fertilizers ◽  
State University ◽  
Root Yield ◽  
The Mean ◽  
Leaf N Content ◽  
Different Sources

This study was carried out at the State University of Maranhão, São Luís, Brazil from January to November 2012. We assessed the behavior of the yam Dioscorea cayenensis ‘Da Costa’, fertilized with different rates and sources of nitrogen (N). The experimental design was randomized, with treatments in a 6 × 2 factorial design. The factors were represented by six rates of N fertilization (0, 50, 100, 150, 200, and 250 kg·ha-1) and two sources (ammonium sulfate and urea) by using four replicates. We evaluated the mean mass, commercial root yield, leaf N content, starch content in the tubers, and percentage of tubers with symptoms of nematode infection (dry and thick skins). The maximum values for the mean masses of commercial tubers were 2.5 and 1.9 kg with doses of 130 and 160 kg of N ha-1 from ammonium sulfate and urea, respectively. Doses of 130 and 154.3 kg of N ha-1 produced the maximum yields of commercial tubers of 19.7 and 14.9 t·ha-1 with ammonium sulfate and urea fertilization, respectively. The maximum levels of foliar N by using urea and ammonium sulfate were 36.5 and 29.3 g·kg-1, respectively, at a dosage of 250 kg·ha-1. The maximum starch contents of 25.7 and 28.3 % were obtained at doses of 114 and 116 kg of N ha-1 of ammonium sulfate and urea, respectively. The percentage of tubers infected with nematodes was 10% when the N source was urea and 15.6% when the source was ammonium sulfate, both at a dosage of 250 kg·ha-1.

scholarly journals Selection of corn cultivars for yield, stability, and adaptability in the state of Amazonas, Brazil

2017 ◽  
Vol 52 (6) ◽  
pp. 455-463 ◽  
Author(s):  
Inocencio Junior de Oliveira ◽  
André Luiz Atroch ◽  
Miguel Costa Dias ◽  
Lauro José Guimarães ◽  
Paulo Evaristo de Oliveira Guimarães
Keyword(s):  
Grain Yield ◽  
Genetic Parameters ◽  
Block Design ◽  
The State ◽  
Environment Interaction ◽  
Growing Seasons ◽  
Randomized Complete Block Design ◽  
Selection For ◽  
Genetic Value ◽  
Selection Of

Abstract: The objective of this work was to evaluate corn cultivars grown in the state of Amazonas, Brazil, which simultaneously show high grain yield, adaptability, and stability. The trials were carried out in seven environments in the state of Amazonas, in a randomized complete block design, with two replicates. The grain yield of 30 corn cultivars was evaluated in four growing seasons, from 2011/2012 to 2014/2015. The genetic parameters were estimated by the REML/Blup methodology. The selection for adaptability and stability was based on the predicted genetic value and on the harmonic mean of the relative performance of the genetic values. Despite the existence of genotype x environment interaction, cultivars with high adaptability and stability were identified. Iranduba - lowland, in 2011/2012 and 2014/2015 - and Rio Preto da Eva - upland, in 2012/2013 - stood out as favorable environments, while Iranduba - upland, in 2011/2012 and 2012/2013 - and Manaus - upland, in 2012/2013 and 2013/2014 - were classified as unfavorable environments. The single-cross hybrid BRS 1055 showed productive superiority and high stability in this region. The Sint 10771, Sint 10781, and Sint 10699 synthetic varieties showed high adaptability. BRS Caimbé shows specific adaptability to cropping in upland environments of the state of Amazonas, Brazil.

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

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.

Optimisation of selection decisions in the UK Meatlinc breed of sheep

2002 ◽  
Vol 2002 ◽  
pp. 194-194
Author(s):  
S. Avendaño ◽  
B. Villanueva ◽  
J.A. Woolliams
Keyword(s):  
Population Dynamic ◽  
Best Linear Unbiased Prediction ◽  
Small Population ◽  
Nineteen Nineties ◽  
Linear Unbiased Prediction ◽  
Sheep Population ◽  
Genetic Gains ◽  
Selection Decisions ◽  
Best Linear Unbiased ◽  
The Uk

Best Linear Unbiased Prediction (BLUP) estimates of breeding values (EBVs) have been routinely used for selection decisions in the UK Meatlinc (ML) population since the early nineteen nineties. This has enabled accurate selection and has allowed higher genetic gains for traits of economic relevance than in other terminal sheep breeds (MLC, 1999). However, concerns regarding increased rates of inbreeding (ΔF) by selecting exclusively on BLUP-EBVs have arisen in this small population. Dynamic rules to maximise genetic merit while ΔF is constrained to a pre-defined level using BLUP EBVs are currently available (e.g. Grundy et al 1998). They found higher gains than standard BLUP selection at the same ΔF by using these rules. The objective of this study was to investigate the potential of these procedures for optimising selection decisions under constrained inbreeding in the UK ML sheep population.

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

2018 ◽  
Author(s):  
Jessica Delfini ◽  
Vania Moda Cirino ◽  
Claudete de Fátima Ruas ◽  
Paulo Mauricio Ruas ◽  
José dos Santos Neto ◽  
...  
Keyword(s):  
Grain Yield ◽  
Common Bean ◽  
Genetic Parameters ◽  
Plant Morphology ◽  
Seed Morphology ◽  
Linear Unbiased Prediction ◽  
Breeding Programs ◽  
Productive Potential ◽  
Best Linear Unbiased ◽  
Main Producer

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.

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

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.

Genetic gains and levels of relatedness from best linear unbiased prediction selection of Eucalyptus urophylla for pulp production in southeastern China

2000 ◽  
Vol 30 (10) ◽  
pp. 1601-1607 ◽  
Author(s):  
Xianming Wei ◽  
Nuno MG Borralho
Keyword(s):  
Tree Height ◽  
Best Linear Unbiased Prediction ◽  
Eucalyptus Urophylla ◽  
Multiple Trait ◽  
Southeastern China ◽  
Linear Unbiased Prediction ◽  
Genetic Gains ◽  
Breeding Objectives ◽  
Best Linear Unbiased ◽  
Unbiased Prediction

Breeding values for diameter at breast height (DBH), tree height (HT), relative bark thickness (BKR), and pilodyn penetration (PP) in Eucalyptus urophylla St. Blake plantations were predicted with best linear unbiased prediction (BLUP) approach. These values along with their economic weights derived from a previous study were then used to estimate economic genetic gains for three breeding objectives (pulp, woodchips, and wood volume) in southeastern China. The results showed substantial gain can be expected from selecting top 5% trees, with a reduction of up to US$35 for producing a tonne of ovendry pulp. However, actual gains can be strongly influenced by how the breeding objectives have been defined and whether the key traits have been included in the selection criteria. This study also showed that problem in the increase of coancestry associated with selection on BLUP would not be serious, with average coancestry amongst the selected population was less than 1%. More importantly, an unrestricted multiple-trait BLUP selection did not result in the same increase in relatedness in the selected population than it does for the single trait situation.

Estimation of genetic parameters for conformation traits assessed on a linear scale in ayrshire cattle

1992 ◽  
Vol 1992 ◽  
pp. 125-125
Author(s):  
HJ. Bellamy ◽  
R.A. Mrode ◽  
G.J.T. Swanson
Keyword(s):  
Genetic Parameters ◽  
Best Linear Unbiased Prediction ◽  
Linear Scale ◽  
Linear Unbiased Prediction ◽  
The Past ◽  
Sire Model ◽  
Holstein Friesian ◽  
Best Linear Unbiased ◽  
Milk Marketing ◽  
Estimation Of Genetic Parameters

Information on the conformation of Ayrshire cattle has been collected by the Ayrshire Cattle Society (ACS) since 1985. Seventeen traits are recorded on a scale of 1 to 9 where 1 and 9 represent the biological extremes of the population. Approximately 2000 records are collected annually and analysed by the Milk Marketing Board using Best Linear Unbiased Prediction to provide sire evaluations on Ayrshire bulls, fitting a sire model. In the past there have been insufficient records to produce reasonable estimates of heritabilities for the traits and those from the Holstein/Friesian population have been used. The purpose of this study was to produce heritability estimates for each trait for use in future analyses.

scholarly journals Genetic parameters and simultaneous selection for root yield, adaptability and stability of cassava genotypes

2013 ◽  
Vol 48 (12) ◽  
pp. 1562-1568 ◽  
Author(s):  
João Tomé de Farias Neto ◽  
Elisa Ferreira Moura ◽  
Marcos Deon Vilela de Resende ◽  
Pedro Celestino Filho ◽  
Sebastião Geraldo Augusto
Keyword(s):  
Genetic Parameters ◽  
Mixed Model ◽  
Block Design ◽  
Genotypic Variation ◽  
Root Yield ◽  
Growing Seasons ◽  
Randomized Block Design ◽  
Simultaneous Selection ◽  
Selection For ◽  
Mixed Model Methodology

The objective of this work was to estimate genetic parameters and to evaluate simultaneous selection for root yield and for adaptability and stability of cassava genotypes. The effects of genotypes were assumed as fixed and random, and the mixed model methodology (REML/Blup) was used to estimate genetic parameters and the harmonic mean of the relative performance of genotypic values (HMRPGV), for simultaneous selection purposes. Ten genotypes were analyzed in a complete randomized block design, with four replicates. The experiment was carried out in the municipalities of Altamira, Santarém, and Santa Luzia do Pará in the state of Pará, Brazil, in the growing seasons of 2009/2010, 2010/2011, and 2011/2012. Roots were harvested 12 months after planting, in all tested locations. Root yield had low coefficients of genotypic variation (4.25%) and broad-sense heritability of individual plots (0.0424), which resulted in low genetic gain. Due to the low genotypic correlation (0.15), genotype classification as to root yield varied according to the environment. Genotypes CPATU 060, CPATU 229, and CPATU 404 stood out as to their yield, adaptability, and stability.

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