scholarly journals Genetic divergence toward the selection of promising bean progenitors via mixed multivariate models

2018 ◽  
Vol 45 (3) ◽  
pp. 251-262
Author(s):  
Cíntia Machado de Oliveira Moulin Carias ◽  
José Henrique Soler Guilhen ◽  
Tiago de Souza Marçal ◽  
Adésio Ferreira ◽  
Marcia Flores Da Silva Ferreira
Keyword(s):  
Genetic Divergence ◽  
Multivariate Models ◽  
Selection Of

scholarly journals GENETIC DIVERGENCE AND MORPHO-AGRONOMIC PERFORMANCE OF JATROPHA CURCAS L. CLONES FOR SELECTION OF CLONAL VARIETIES

2016 ◽  
Vol 29 (4) ◽  
pp. 841-849
Author(s):  
ADRIANA QUEIROZ DE ALMEIDA ◽  
SIMONE ALVES SILVA ◽  
VANESSA DE OLIVEIRA ALMEIDA ◽  
DEOCLIDES RICARDO DE SOUZA ◽  
GILMARA DE MELO ARAÚJO
Keyword(s):  
Genetic Diversity ◽  
Multivariate Analysis ◽  
Plant Height ◽  
Genetic Divergence ◽  
Morphological Characterization ◽  
Stem Diameter ◽  
Agronomic Performance ◽  
And Performance ◽  
Lower Contribution ◽  
Selection Of

ABSTRACT The knowledge about genetic diversity of jatropha crop is important for genetic conservation resources and breeding of this species. The aim of this study was to evaluate the genetic diversity and performance of jatropha clones through morphological characterization to selection of clonal varieties for biofuels production. The clones were obtained through shoot cuttings from previous selection in a population of half-sibs progenies. The morphoagronomic analyses of clones was carried out at 180 days after transplantation and were evaluated plant height, stem diameter, number of primary branches and number of secondary branches, number of bunches and number of fruits per plant. Evaluating clones performance, significant results were found for the number of secondary branches. About analysis of genetic diversity, the measures of dissimilarity genetic varied from 0.62 to 13.11, this way, the UFRBPR14 and UFRBPR15 clones were more divergent. The Tocher method was efficient to verify formation of four groups. The characteristics that most contributed to the divergence among clones were branches number, height and number of bunches, and, stem diameter had lower contribution. The jatropha clones differed only in the secondary branches number and multivariate analysis showed divergence among the jatropha clones with formation of four groups. Also, branches number, plant height and number of bunches were characteristic that contributed to genetic divergence.

scholarly journals Agronomic potential and selection of okra hybrids to obtain potential genitors

2018 ◽  
Vol 36 (1) ◽  
pp. 112-117 ◽  
Author(s):  
Gabriel M Maciel ◽  
Rafael R Finzi ◽  
Alexandre William C Marra ◽  
Fábio J Carvalho ◽  
Ana Paula O Nogueira
Keyword(s):  
Genetic Divergence ◽  
Canonical Analysis ◽  
Index Number ◽  
Clustering Methods ◽  
Germplasm Bank ◽  
Breeding Programs ◽  
Agronomic Potential ◽  
Per Se ◽  
Fruit Mass ◽  
Selection Of

ABSTRACT Evaluation of pre-commercial hybrids in a germplasm bank is essential for determining its commercial potential or its utility as a potential genitor in a breeding program. The objective of this study was to determine genetic divergence and per se behavior of 47 pre-commercial hybrids from okra germplasm bank of the Universidade Federal de Uberlândia. Precocity index (%), number of fruits (fruits per plant), average fruit mass (g) and productivity (g per plant) were evaluated. Analysis of genetic divergence was performed by multivariate analysis using Mahalanobis distance with different clustering methods (UPGMA and canonical analysis). The performance of hybrids was compared by Scott-Knott (p= 0.05). A significant genetic variability among okra hybrids was observed. UPGMA and canonical analysis grouped the hybrids similarly, being satisfactory to represent genetic divergence. Ten hybrids presented higher performance than the commercial hybrids. Among them, UFU-QB16 stood out as the most promising hybrid for being used as a potential parent in breeding programs after auto pollination.

scholarly journals Comparison of methods for selection of castor beans lineages

2019 ◽  
Vol 9 (4) ◽  
pp. 687-694
Author(s):  
Maria Márcia Pereira Sartori ◽  
Jackson da Silva ◽  
Mauricio Dutra Zanotto
Keyword(s):  
Cluster Analysis ◽  
Genetic Divergence ◽  
Oil Content ◽  
Plant Size ◽  
Comparison Of Methods ◽  
High Productivity ◽  
Components Analysis ◽  
Bean Crop ◽  
Formation Of Groups ◽  
Selection Of

The choice of the most appropriate method is determined by the precision desired by the researcher, by the ease of the analysis, as well as by the way of obtaining the data. In order to select lineages of low size and high productivity this study aimed to evaluate different methods of cluster analysis in the representation of genetic divergence, compared to univariate methods. The analyzed variables were grain yield, plant size and oil yield of 24 lineages of castor beans cultivated in the years 2014 and 2015. The Single and Average methods presented similar results in the formation of groups and different from the Complete. Evaluating the purpose of this research the Complete method and principal components analysis, together with the discriminant analysis, were considered the most appropriate methods to evaluate the genetic divergence of the castor bean crop. Lineages 18, 19 and 20 showed average grain yields above 1555 kg.ha-1, high oil content (above 46.9%), and low size plants (below 116 cm).

scholarly journals Genetic divergence and parent selection of sugarcane clones

2008 ◽  
Vol 8 (3) ◽  
pp. 225-231 ◽  
Author(s):  
V.R. Lopes ◽  
J.C. Bespalhok Filho ◽  
R.A. Oliveira ◽  
E.P. Guerra ◽  
J.L.C. Zambon ◽  
...  
Keyword(s):  
Genetic Divergence ◽  
Parent Selection ◽  
Selection Of

scholarly journals Genetic divergence among white-type acai palm accessions based on morpho-agronomic characters

2017 ◽  
Vol 52 (9) ◽  
pp. 751-760 ◽  
Author(s):  
Angela Maria de Sousa ◽  
Maria do Socorro Padilha de Oliveira ◽  
João Tomé de Farias Neto
Keyword(s):  
Genetic Divergence ◽  
Euclidean Distance ◽  
Multivariate Analyses ◽  
Arithmetic Mean ◽  
Group Method ◽  
Agronomic Characters ◽  
Germplasm Bank ◽  
Pair Group ◽  
White Type ◽  
Selection Of

Abstract: The objective of this work was to quantify the genetic divergence among accessions of white-type acai palm, through morpho-agronomic characters. The accessions belong to the active acai palm germplasm bank of Embrapa Amazônia Oriental. Thirteen characters were evaluated in 26 accessions, originated from six municipalities in the state of Pará, Brazil. The data were subjected to deviance and multivariate analyses, based on the average Euclidean distance, and were grouped by Tocher’s method and the unweighted pair group method with arithmetic mean (UPGMA). The accessions differed for eight characters. The distances among accessions ranged from 0.64 to 2.62, with an average of 1.36, and four groups were formed by Tocher’s method and two by the UPGMA. Seven major components explained 88.03% of the variation, whose graphic dispersion showed the tendency of forming four groups. The characters weight of 100 fruits, number of rachillae per bunch, and fruit yield per bunch contributed the most to the divergence, and the accessions from the municipalities of Breves, Curralinho, and Limoeiro do Ajuru were the most divergent. Therefore, the accessions of white acai palm show strong divergence and variability, which favor the selection of desirable individuals.

Time series analysis and adaptive filtering in hydrology

1984 ◽  
Vol 16 (01) ◽  
pp. 17-18
Author(s):  
J. W. Delleur
Keyword(s):  
Time Series ◽  
Parameter Estimation ◽  
River Flow ◽  
Time Series Models ◽  
Arma Models ◽  
Multivariate Models ◽  
Varying Coefficients ◽  
Daily Streamflow ◽  
Hydrologic Time Series ◽  
Selection Of

Most time series models in hydrology are used for river flow forecasting, for generation of synthetic data sequences or for the study of physical characteristics underlying the hydrological processes. The models are formulated as linear stochastic difference equations. Three phases are considered for the selection of a model based on a satisfactory representation of a given empirical time series: identification, estimation and validation. Several criteria have been proposed for the selection of the order of ARMA models. The Akaike information criterion (Ale) is popular among hydrologists, but the posterior probability criterion has the advantage of optimality and asymptotic consistency. There are numerous applications of AR or ARMA models to annual streamflow series which are stationary. Seasonal, monthly, weekly or daily streamflow series are cyclically stationary and generally exhibit periodicities in the mean and variance and possibly in the autocorrelation structure. Removal of the periodicity has been accomplished by fitting harmonic series or by subtracting the seasonal mean and dividing by the seasonal standard deviation, and a time series model is then fitted to the residual series. Alternatively, ARMA models with time-varying coefficients are also used. The multiplicative ARlMA model of Box and Jenkins is less frequent in hydrology because of the difficulty in the identification of the parameter structure. Multivariate models are used when river flows at different sites are considered. Parameter estimation in multivariate time series models can become cumbersome because of the dimensionality of the problem. Often the covariance matrix of the noise term is not known in advance and limited information estimates are used. Multivariate models have been used for annual and monthly series. Disaggregation models have been used to subdivide a yearly series into monthly or weekly series or to disaggregate a main river flow into tributary flows while maintaining certain space and time cross-correlations. The aggregation of monthly into yearly time series has been shown to improve the parameter estimation of the yearly series. Hydrologic time series occasionally exhibit changes in level due to natural or man-made causes such as forest fires, volcanic eruption, climatological change, urbanization etc. These situations can be treated making use of intervention analysis.

Time series analysis and adaptive filtering in hydrology

1984 ◽  
Vol 16 (1) ◽  
pp. 17-18
Author(s):  
J. W. Delleur
Keyword(s):  
Time Series ◽  
Parameter Estimation ◽  
River Flow ◽  
Time Series Models ◽  
Arma Models ◽  
Multivariate Models ◽  
Varying Coefficients ◽  
Daily Streamflow ◽  
Hydrologic Time Series ◽  
Selection Of

Most time series models in hydrology are used for river flow forecasting, for generation of synthetic data sequences or for the study of physical characteristics underlying the hydrological processes. The models are formulated as linear stochastic difference equations. Three phases are considered for the selection of a model based on a satisfactory representation of a given empirical time series: identification, estimation and validation. Several criteria have been proposed for the selection of the order of ARMA models. The Akaike information criterion (Ale) is popular among hydrologists, but the posterior probability criterion has the advantage of optimality and asymptotic consistency. There are numerous applications of AR or ARMA models to annual streamflow series which are stationary. Seasonal, monthly, weekly or daily streamflow series are cyclically stationary and generally exhibit periodicities in the mean and variance and possibly in the autocorrelation structure. Removal of the periodicity has been accomplished by fitting harmonic series or by subtracting the seasonal mean and dividing by the seasonal standard deviation, and a time series model is then fitted to the residual series. Alternatively, ARMA models with time-varying coefficients are also used. The multiplicative ARlMA model of Box and Jenkins is less frequent in hydrology because of the difficulty in the identification of the parameter structure. Multivariate models are used when river flows at different sites are considered. Parameter estimation in multivariate time series models can become cumbersome because of the dimensionality of the problem. Often the covariance matrix of the noise term is not known in advance and limited information estimates are used. Multivariate models have been used for annual and monthly series. Disaggregation models have been used to subdivide a yearly series into monthly or weekly series or to disaggregate a main river flow into tributary flows while maintaining certain space and time cross-correlations. The aggregation of monthly into yearly time series has been shown to improve the parameter estimation of the yearly series. Hydrologic time series occasionally exhibit changes in level due to natural or man-made causes such as forest fires, volcanic eruption, climatological change, urbanization etc. These situations can be treated making use of intervention analysis.

scholarly journals Assessment of Genetic Diversity using D2 Statistics in Chickpea (Cicer arietinum L.) under Late Sown Conditions

2021 ◽  
pp. 48-53
Author(s):  
Velugoti Priyanka Reddy ◽  
Gaibriyal. M. Lal ◽  
Subhadra Pattanayak ◽  
Jakkam Mahipal Reddy
Keyword(s):  
Genetic Diversity ◽  
Genetic Variability ◽  
Plant Breeding ◽  
Cicer Arietinum ◽  
Analysis Of Variance ◽  
Genetic Divergence ◽  
Indian Institute ◽  
Cicer Arietinum L ◽  
Cluster Distance ◽  
Selection Of

An experiment was conducted during Rabi, 2019-20 at Department of Genetics and Plant Breeding, Sam Higginbottom University of Agriculture, Technology and Sciences, Prayagraj (Allahabad) consisting of 36 chickpea genotypes obtained from ICAR-Indian Institute of Pulses Research, Kanpur, U.P in RBD with three replications. The data was recorded on 13 traits to study the genetic divergence. Analysis of variance revealed that there was considerable genetic variability in the available germplasm for all the characters studied. Divergence analysis revealed that highest inter cluster distance (1505.25) was found between clusters I and V indicates that there is ample scope for selection of better parents.

scholarly journals ​​Genetic Divergence in Leafy Mustard (Brassica juncea var. rugosa) Germplasm Grown under Tarai Condition of Uttarakhand

2021 ◽  
Author(s):  
Dhiraj Bhandari ◽  
Anita Singh
Keyword(s):  
Brassica Juncea ◽  
Genetic Divergence ◽  
Block Design ◽  
Research Centre ◽  
Rich Diversity ◽  
Randomized Block Design ◽  
Cluster Distance ◽  
Qualitative Characters ◽  
Clustering Pattern ◽  
Selection Of

Background: Mustard represents a rich diversity and widely cultivated in 23 states and union territories of India. However, much of this diversity is concentrated in the Indo-Gangetic plains and the sub-mountain Himalayas. Genetic diversity plays a significant role in plant improvement because a hybrid between the lines of diverse origin usually display a greater heterosis than those between closely related ones which permit the selection of genetically divergent plants to obtain the desirable recombination of segregating generation. Therefore, the present study was undertaken to assess “Genetic Divergence in Leafy Mustard (Brassica juncea. var. rugosa) germplasm grown under Tarai condition of Uttarakhand” and to identify divergent parents for hybridization program, which would provide superior transgressive segregants from collected germplasm. Methods: The present investigation consisted of thirty-two genotypes of leafy mustard and the research was carried out at Vegetable Research Centre (VRC), G.B. Pant University of Agriculture and Technology, Pantnagar, U.S. Nagar (Uttarakhand) in rabi season of 2015-2016. Mustard genotypes were sown in randomized block design with three replications in field and data were observed for seventeen quantitative and qualitative characters. The estimation of genetic divergence was done with the help of Mahalonobis D2 statistic as suggested by Rao (1952). Cluster analysis by Tocher method for all the traits was done. Result: Thirty two germplasm of leafy mustard for different characters and grouped them into six clusters using Mahalanobis D2 statistic. The analysis revealed the maximum inter cluster distance was (20534.12) between cluster V and cluster VI so, we can create variation by inter mating genotypes from these two clusters to each other and the maximum intra cluster distance in cluster III (441.91) with six germplasm. It means we can intermate genotypes of this cluster with each other (2014/MGVAR-2, FS-13-1, FS-13-4, 2014/MGVAR-4, PRHC-12-9-1, PRHC-12-7-2, FS-13-3 and Pusa Sag 1) to create variation in next generations. The clustering pattern could be utilized in selection of parents for crossing and deciding the best cross combinations which may generate the highest possible variability for various traits.

scholarly journals Genetic divergence among interspecific Paspalum hybrids based on seed production traits

2017 ◽  
Vol 41 (4) ◽  
pp. 390-401
Author(s):  
Rodrigo Ramos Lopes ◽  
Lucia Brandão Franke ◽  
Cléber Henrique Lopes de Souza ◽  
Patrícia Bertoncelli ◽  
Larissa Arnhold Graminho
Keyword(s):  
Seed Production ◽  
Genetic Divergence ◽  
Block Design ◽  
Optimization Methods ◽  
Production Traits ◽  
Randomized Block Design ◽  
Heterosis Effect ◽  
High Concordance ◽  
Selection Of ◽  
Production Characteristics

ABSTRACT The use of genetic divergence as a basis for identifying superior individuals, with greater heterozygosity, is important in view of the difficulty when selecting of dissimilar genotypes exhibiting high average for interest traits. The aim of this study was to evaluate the genetic divergence and the expression of seed production traits in seventeen apomictic Paspalum plicatulum × Paspalum guenoarum hybrids and two male parents (P. guenoarum). A randomized block design was used, with genotypes individually arranged into ten blocks. The following traits were assessed: total number of tillers/plant (TT), reproductive tiller/plant (RT), number of racemes per inflorescence (NRI), reproductive tiller height (RTH), inflorescence rachis length (IRL), number of seeds/inflorescence (NSI), weight of a thousand seeds (WTS) and seed production (SP). Genetic divergence among the genotypes was estimated using the Tocher method and UPGMA clustering, based on the generalized Mahalanobis distance (D2 ii’). The Tocher and UPGMA optimization methods showed high concordance. The traits that most contributed to genetic divergence were RTH (23.59%), IRL (21.63%), WTS (16.67%) and SP (14.23%). The presence of genetic diversity made it possible to identify divergent genotypes and those with high means for the traits studied, allowing the selection of genotypes with significant breeding potential. Repeated cross-breeding of female superior plants with the genotypes Azulão and H20 can result in a high heterosis effect on seed production characteristics.

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