# Artigos

URI permanente para esta coleçãohttps://locus.ufv.br/handle/123456789/11845

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26 resultados

## Resultados da Pesquisa

Item Selection of common bean (Phaseolus vulgaris L.) genotypes using a genotype plus genotype x environment interaction biplot(Open Acess, 2016-03-11) Corrêa, A.M.; Teodoro, P.E.; Gonçalves, M.C.; Santos, A.; Torres, F.E.Recently, the genotype plus genotype x environment interaction (GGE) biplot methodology has been used to investigate genotype x environment interactions in several crop species, but has not been applied to the common bean (Phaseolus vulgaris L.) crop in Brazil. The aim of this study was to identify common bean genotypes that exhibit high grain yield and stability in the State of Mato Grosso do Sul, Brazil. We conducted 12 trials from 2000 to 2006 in the municipalities of Aquidauana and Dourados, and evaluated 13 genotypes in a randomized block design with three replications. Grain yield data were subjected to individual and joint analyses of variance. After analyzing the GE interaction, the adaptability and phenotypic stability of the common bean genotypes were analyzed using GGE biplot methodology. The genotypes EMGOPA-201, Xamego, and Aporé are recommended for growing in Mato Grosso do Sul, because they exhibited high grain yield and phenotypic stability.Item Clustering of soybean genotypes via Ward- MLM and ANNs associated with mixed models(Genetics and Molecular Research, 2016-03-11) Teodoro, P.E.; Torres, F.E.; Corrêa, A.M.The objectives of this study were to use mixed models to confirm the presence of genetic variability in 16 soybean genotypes, to compare clusters generated by artificial neural networks (ANNs) with those created by the Ward modified location model (MLM) technique, and to indicate parental combinations that hold promise for obtaining superior segregating populations of soybean. A field trial was conducted between November 2014 and February 2015 at Universidade Estadual de Mato Grosso do Sul, Aquidauana, MS. The experimental design consisted of four replications of randomized blocks, each containing 16 treatments. We assessed the following agronomic traits: plant height, first pod height, number of branches per plant, number of pods per plant, number of grains per pod, hundred-grain weight, and grain yield. Mixed models were used to estimate variance components and genetic parameters, and obtain genotypic values for each trait. After verifying the presence of genetic variability for all traits, genotypic values were submitted to both a Ward-MLM procedure and ANNs to estimate genetic divergence among genotypes. The number of groups formed by both methods was the same, but there were differences in group constitutions. ANN analysis improved soybean genotypes clustering patterns compared to Ward-MLM procedure. Based on these methods, divergent crosses may be made between genotype 97R73 with genotypes AS3797 and SYN9070, whereas convergent crosses may be made between genotypes AS3797 and SYN9070.Item Assessment of genetic divergence among coffee genotypes by Ward-MLM procedure in association with mixed models(Open Access, 2015-12-07) Rodrigues, W.P.; Vieira, H.D.; Teodoro, P.E.; Partelli, F.L.; Barbosa, D.H.S.G.Mixed linear models have been used for the analysis of the genetic diversity and provided further accurate results in crops such as eucalyptus, castor, and sugarcane. However, to date, research that combined this analysis with Ward-MLM procedure has not been reported. Therefore, the aim of the present study was to identify divergent coffee genotypes by Ward-MLM procedure, in association with the mixed-decision models. The experiment was initiated in February 2007, in the northwestern Rio de Janeiro State. The 25 evaluated genotypes were grown with a spacing of 2.5 x 0.8 m, in a randomized block design, with 5 replications, containing 8 plants each. The following agronomic traits were evaluated: plant height, stem diameter, plagiotropic branch number, and productivity. Four measurements were performed for each character from 2009 to 2012, between May and July. Data were analyzed using REML/BLUP analysis and Ward- MLM procedure. The Ward-MLM procedure in association with mixed linear models demonstrated the genetic variability among the studied coffee genotypes. We identified two groups of most divergent coffee genotypes, which can be combined by crossings and selections in order to obtain genotypes with high productivity and variability.Item Path analysis and canonical correlations for indirect selection of Jatropha genotypes with higher oil yield(Genetics and Molecular Research, 2017-03-22) Silva, L.A.; Peixoto, L.A.; Teodoro, P.E.; Rodrigues, E.V.; Laviola, B.G.; Bhering, L.L.Jatropha is a species with great potential for biodiesel production, and the knowledge on how the main agronomic traits are correlated will contribute to its improvement. Therefore, the objectives of this study were to estimate the genetic parameters of the traits: plant height at 12 and 40 months, canopy projection on the row at 12 and 40 months, canopy projection between the row at 12 and 40 months, number of branches at 40 months, grain yield, and oil yield; to verify the existence of phenotypic correlation between these traits; to verify the influence of the morphological traits on oil yield by means of path analysis; and to evaluate the relationship between the productive traits in Jatropha and the morphological traits measured at different ages. Sixty-seven half-sib families were evaluated using a completely randomized block design with two replications and five plants per plot. Analysis of variance was used to estimate the genetic value. Phenotypic correlations were given by the Pearson correlation between traits. For the canonical correlation analysis, two groups of traits were established: group I, consisting of traits of economic importance for the culture, and group II, consisting of morphological traits. Path analysis was carried out considering oil yield as the main dependent variable. Genetic variability was observed among Jatropha families. Productive traits can be indirectly selected via morphological traits due to the correlation between these two groups of traits. Therefore, canonical correlations and path analysis are two strategies that may be useful in Jatropha-breeding program when the objective is to select productive traits via morphological traits.Item Minimum number of measurements for evaluating Bertholletia excelsa(Genetics and Molecular Research, 2017-09-27) Baldoni, A.B.; Tonini, H.; Tardin, F.D.; Botelho, S.C.C.; Teodoro, P.E.Repeatability studies on fruit species are of great importance to identify the minimum number of measurements necessary to accurately select superior genotypes. This study aimed to identify the most efficient method to estimate the repeatability coefficient (r) and predict the minimum number of measurements needed for a more accurate evaluation of Brazil nut tree (Bertholletia excelsa) genotypes based on fruit yield. For this, we assessed the number of fruits and dry mass of seeds of 75 Brazil nut genotypes, from native forest, located in the municipality of Itaúba, MT, for 5 years. To better estimate r, four procedures were used: analysis of variance (ANOVA), principal component analysis based on the correlation matrix (CPCOR), principal component analysis based on the phenotypic variance and covariance matrix (CPCOV), and structural analysis based on the correlation matrix (mean r - AECOR). There was a significant effect of genotypes and measurements, which reveals the need to study the minimum number of measurements for selecting superior Brazil nut genotypes for a production increase. Estimates of r by ANOVA were lower than those observed with the principal component methodology and close to AECOR. The CPCOV methodology provided the highest estimate of r, which resulted in a lower number of measurements needed to identify superior Brazil nut genotypes for the number of fruits and dry mass of seeds. Based on this methodology, three measurements are necessary to predict the true value of the Brazil nut genotypes with a minimum accuracy of 85%.Item Diversity among elephant grass genotypes using Bayesian multi-trait model(Genetics and Molecular Research, 2017-09-27) Rossi, D.A.; Daher, R.F.; Barbé, T.C.; Lima, R.S.N.; Costa, A.F.; Ribeiro, L.P.; Teodoro, P.E.; Bhering, L.L.Elephant grass is a perennial tropical grass with great potential for energy generation from biomass. The objective of this study was to estimate the genetic diversity among elephant grass accessions based on morpho-agronomic and biomass quality traits and to identify promising genotypes for obtaining hybrids with high energetic biomass production capacity. The experiment was installed at experimental area of the State Agricultural College Antônio Sarlo, in Campos dos Goytacazes. Fifty-two elephant grass genotypes were evaluated in a randomized block design with two replicates. Components of variance and the genotypic means were obtained using a Bayesian multi-trait model. We considered 350,000 iterations in the Gibbs sampler algorithm for each parameter adopted, with a warm-up period (burn-in) of 50,000 Iterations. For obtaining an uncorrelated sample, we considered five iterations (thinning) as a spacing between sampled points, which resulted in a final sample size 60,000. Subsequently, the Mahalanobis distance between each pair of genotypes was estimated. Estimates of genotypic variance indicated a favorable condition for gains in all traits. Elephant grass accessions presented greater variability for biomass quality traits, for which three groups were formed, while for the agronomic traits, two groups were formed. Crosses between Mercker Pinda México x Mercker 86-México, Mercker Pinda México x Turrialba, and Mercker 86-México x Taiwan A-25 can be carried out for obtaining elephant grass hybrids for energy purposes.Item Estimates of repeatability coefficients and the number of the optimum measure to select superior genotypes in Annona muricata L.(Genetics and Molecular Research, 2017-09-21) Sanchéz, C.F.B.; Alves, R.S.; Garcia, A.D.P.; Teodoro, P.E.; Peixoto, L.A.; Silva, L.A.; Bhering, L.L.; Resende, M.D.V.The aim of this study was to evaluate repeated measures over the years to estimate repeatability coefficient and the number of the optimum measure to select superior genotypes in Annona muricata L. The fruit production was evaluated over 16 years in 71 genotypes without an experimental design. The estimation of variance components and the prediction of the permanent phenotypic value were performed using REML/BLUP proceedings. The coefficient of determination, accuracy, and selective efficiency increased when measures increased. The coefficient of determination of 80% was reached beyond 8 crop seasons with high accuracy and selective efficiency. Thus, the evaluation of 8 crop seasons can be suitable to select superior genotypes in the A. muricata L. breeding program. Predicted selection gain had a high magnitude for fruit production indicating that it is possible to take a progressive genetic advance for this trait over cycle breeding.Item Adaptability and phenotypic stability of common bean genotypes through Bayesian inference(Genetics and Molecular Research, 2016-04-26) Corrêa, A.M.; Teodoro, P.E.; Gonçalves, M.C.; Barroso, L.M.A.; Nascimento, M.; Santos, A.; Torres, F.E.This study used Bayesian inference to investigate the genotype x environment interaction in common bean grown in Mato Grosso do Sul State, and it also evaluated the efficiency of using informative and minimally informative a priori distributions. Six trials were conducted in randomized blocks, and the grain yield of 13 common bean genotypes was assessed. To represent the minimally informative a priori distributions, a probability distribution with high variance was used, and a meta-analysis concept was adopted to represent the informative a priori distributions. Bayes factors were used to conduct comparisons between the a priori distributions. The Bayesian inference was effective for the selection of upright common bean genotypes with high adaptability and phenotypic stability using the Eberhart and Russell method. Bayes factors indicated that the use of informative a priori distributions provided more accurate results than minimally informative a priori distributions. According to Bayesian inference, the EMGOPA-201, BAMBUÍ, CNF 4999, CNF 4129 A 54, and CNFv 8025 genotypes had specific adaptability to favorable environments, while the IAPAR 14 and IAC CARIOCA ETE genotypes had specific adaptability to unfavorable environments.Item Minimum number of measurements for evaluating soursop (Annona muricata L.) yield(Genetics and Molecular Research, 2017-05-31) Sánchez, C.F.B.; Teodoro, P.E.; Londoño, S.; Silva, L.A.; Peixoto, L.A.; Bhering, L.L.Repeatability studies on fruit species are of great importance to identify the minimum number of measurements necessary to accurately select superior genotypes. This study aimed to identify the most efficient method to estimate the repeatability coefficient (r) and predict the minimum number of measurements needed for a more accurate evaluation of soursop (Annona muricata L.) genotypes based on fruit yield. Sixteen measurements of fruit yield from 71 soursop genotypes were carried out between 2000 and 2016. In order to estimate r with the best accuracy, four procedures were used: analysis of variance, principal component analysis based on the correlation matrix, principal component analysis based on the phenotypic variance and covariance matrix, and structural analysis based on the correlation matrix. The minimum number of measurements needed to predict the actual value of individuals was estimated. Principal component analysis using the phenotypic variance and covariance matrix provided the most accurate estimates of both r and the number of measurements required for accurate evaluation of fruit yield in soursop. Our results indicate that selection of soursop genotypes with high fruit yield can be performed based on the third and fourth measurements in the early years and/or based on the eighth and ninth measurements at more advanced stages.Item Identification of sorghum hybrids with high phenotypic stability using GGE biplot methodology(Genetics and Molecular Research, 2016-06-10) Teodoro, P.E.; Almeida Filho, J.E.; Daher, R.F.; Menezes, C.B.; Cardoso, M.J.; Godinho, V.P.C.; Torres, F.E.; Tardin, F.D.The aim of this study was to identify sorghum hybrids that have both high yield and phenotypic stability in Brazilian environments. Seven trials were conducted between February and March 2011. The experimental design was a randomized complete block with 25 treatments and three replicates. The treatments consisted of 20 simple pre-commercial hybrids and five witnesses of grain sorghum. Sorghum genotypes were analyzed by the genotype main effects + genotype environment interaction (GGE) biplot method if significant genotype x environment interaction, adaptability, and phenotypic stability were detected. GGE biplot methodology identified two groups of environments, the first composed of Água Comprida-MG, Montividiu-GO, and Vilhena- RO and the second of Guaíra-SP and Sete Lagoas-MG. The BRS 308 and 1G282 genotypes were found to have high grain yield, adaptability, and phenotypic stability and are thus indicated for cultivation in the first and second groups of environments, respectively.

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