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      Selection and genetic dissimilarity in S2 families of guava through seed attributes

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          Abstract

          ABSTRACT This study was developed to carry out selection, estimate genetic parameters and predict individual genetic values of 55 genotypes from S2 families as well as estimate genetic dissimilarity based on physiological seed attributes. All S2 genotypes evaluated were obtained from self-pollination of S1 genotypes from the guava breeding program. The experiment was laid out in blocks with 55 S2 genotypes and four blocks. Genetic parameters were estimated and the best genotypes were selected based on the genetic value, using the statistical method of mixed models. In addition, genetic divergence was estimated based on the mean Euclidean distance. Although heritability values were considered medium to high magnitude for germination (0.22) and germination speed index (0.35), genetic gains were obtained for all traits. Based on the evaluation of individual BLUPs, the S2 genotypes that contributed to most of the evaluated traits were: 5, 31, 85, 214, 369, 393, 398, 442, 443, 444, 449 and 529, suggesting potential to generate vigorous. Through genetic dissimilarity, it was possible to verify the formation of five distinct groups. Therefore, the selection of divergent genotypes with high average for germination is recommended for the advancement of generation in the guava breeding plant.

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          Most cited references30

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          Speed of Germination—Aid In Selection And Evaluation for Seedling Emergence And Vigor1

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            GENES: a software package for analysis in experimental statistics and quantitative genetics

            GENES is a software package used for data analysis and processing with different biometric models and is essential in genetic studies applied to plant and animal breeding. It allows parameter estimation to analyze biological phenomena and is fundamental for the decision-making process and predictions of success and viability of selection strategies. The program can be downloaded from the Internet (http://www.ufv.br/dbg/genes/genes.htm or http://www.ufv.br/dbg/biodata.htm) and is available in Portuguese, English and Spanish. Specific literature (http://www.livraria.ufv.br/) and a set of sample files are also provided, making GENES easy to use. The software is integrated into the programs MS Word, MS Excel and Paint, ensuring simplicity and effectiveness in data import and export of results, figures and data. It is also compatible with the free software R and Matlab, through the supply of useful scripts available for complementary analyses in different areas, including genome wide selection, prediction of breeding values and use of neural networks in genetic improvement.
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              MEGA: a biologist-centric software for evolutionary analysis of DNA and protein sequences.

              The Molecular Evolutionary Genetics Analysis (MEGA) software is a desktop application designed for comparative analysis of homologous gene sequences either from multigene families or from different species with a special emphasis on inferring evolutionary relationships and patterns of DNA and protein evolution. In addition to the tools for statistical analysis of data, MEGA provides many convenient facilities for the assembly of sequence data sets from files or web-based repositories, and it includes tools for visual presentation of the results obtained in the form of interactive phylogenetic trees and evolutionary distance matrices. Here we discuss the motivation, design principles and priorities that have shaped the development of MEGA. We also discuss how MEGA might evolve in the future to assist researchers in their growing need to analyze large data set using new computational methods.

                Author and article information

                Journal
                rceres
                Revista Ceres
                Rev. Ceres
                Universidade Federal de Viçosa (Viçosa, MG, Brazil )
                0034-737X
                2177-3491
                August 2023
                : 70
                : 4
                : 73-81
                Affiliations
                [01] Campos dos Goytacazes Rio de Janeiro orgnameUniversidade Estadual do Norte Fluminense orgdiv1Centro de Ciências e Tecnologias Agropecuárias Brazil marianaquintasm@ 123456gmail.com
                [02] Tangará da Serra MT orgnameUniversidade Estadual do Mato Grosso orgdiv1Centro de Pesquisa, Estudo e Desenvolvimento Agroambiental Brazil eileenazevedo@ 123456yahoo.com.br
                Article
                S0034-737X2023000400073 S0034-737X(23)07000400073
                10.1590/0034-737x202370040010
                c2791669-b13f-44fc-b4d1-940bcbe6b5d6

                This work is licensed under a Creative Commons Attribution 4.0 International License.

                History
                : 03 November 2022
                : 30 June 2022
                Page count
                Figures: 0, Tables: 0, Equations: 0, References: 30, Pages: 9
                Product

                SciELO Brazil

                Categories
                Plant Breeding Applied to Agriculture

                vigor,self-pollination,mixed models,Psidium guajava
                vigor, self-pollination, mixed models, Psidium guajava

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