Comparações entre métodos quantitativos e métodos baseados em marcadores RAPD para a predição do comportamento de populações de soja Article Swipe
Paulo Augusto Vianna Barroso
·
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.11606/t.11.2019.tde-20191220-125817
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.11606/t.11.2019.tde-20191220-125817
\n Este estudo comparou a distância genética baseada em marcadores RAPD com a média dos genitores, a distância euclidiana e a capacidade geral de combinação estimada em F2 quanto a: a) eficiência das predições dom potencial de populações endogâmicas de soja; b) eficiência na escolha de linhagens não adaptadas a serem utilizadas como genitoras doadoras em programas de melhoramento. As populações empregadas foram obtidas pelo cruzamento biparental entre oito linhagens, cinco adaptadas e três não adaptadas. Para o primeiro objetivo foram utilizadas todas as 25 populações disponíveis e para o segundo apenas as 14 formadas pelo cruzamento entre genitores adaptados com não adaptados. O potencial das populações foi avaliado pela proporção de progênies com médias superiores à média de todas as 493 progênies utilizadas. Os caracteres avaliados foram: produção de grãos, altura das plantas na maturação, altura das plantas no florescimento, número de dias para o florescimento, número de dias para a maturação e acamamento. De modo geral, os melhores métodos preditivos foram a média dos genitores e a capacitação geral de combinação estimada na geração F2. A distância genética foi capaz de realizar predições com confiabilidade semelhante a estes métodos em parte dos caracteres, entre os quais se inclui a produção de grãos. A distância genética geral apresentou capacidade preditiva ainda mais alta, mostrando que a partição da distância genética baseada em marcadores RAPD pode ser recomendada para situações semelhantes às existentes neste estudo. Conclui-se que a distância genética baseada em marcadores RAPD e a distância genética geral podem ser utilizadas como métodos preditivos para selecionar genitores de populações mais promissoras e para identificar a linhagem não adaptada mais adequada, principalmente quando as linhagens não foram avaliadas em experimentos ou então quando as predições são necessárias em um curto espaço de tempo.\n
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Metadata
- Type
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- Language
- pt
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- http://www.teses.usp.br/teses/disponiveis/11/11137/tde-20191220-125817/publico/BarrosoPauloAugustoVianna.pdf
- OA Status
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https://doi.org/10.11606/t.11.2019.tde-20191220-125817Digital Object Identifier
- Title
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Comparações entre métodos quantitativos e métodos baseados em marcadores RAPD para a predição do comportamento de populações de sojaWork title
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dissertationOpenAlex work type
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ptPrimary language
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2019Year of publication
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2019-12-20Full publication date if available
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Paulo Augusto Vianna BarrosoList of authors in order
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https://doi.org/10.11606/t.11.2019.tde-20191220-125817Publisher landing page
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https://www.teses.usp.br/teses/disponiveis/11/11137/tde-20191220-125817/publico/BarrosoPauloAugustoVianna.pdfDirect link to full text PDF
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://www.teses.usp.br/teses/disponiveis/11/11137/tde-20191220-125817/publico/BarrosoPauloAugustoVianna.pdfDirect OA link when available
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RAPD, Biology, Horticulture, Sociology, Population, Genetic diversity, DemographyTop concepts (fields/topics) attached by OpenAlex
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| abstract_inverted_index.maturação, | 135 |
| abstract_inverted_index.necessárias | 286 |
| abstract_inverted_index.populações | 37, 60, 85, 106, 259 |
| abstract_inverted_index.capacitação | 169 |
| abstract_inverted_index.melhoramento. | 58 |
| abstract_inverted_index.confiabilidade | 186 |
| abstract_inverted_index.florescimento, | 140, 146 |
| abstract_inverted_index.principalmente | 271 |
| cited_by_percentile_year | |
| corresponding_author_ids | https://openalex.org/A5103201604 |
| countries_distinct_count | 0 |
| institutions_distinct_count | 1 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/2 |
| sustainable_development_goals[0].score | 0.6100000143051147 |
| sustainable_development_goals[0].display_name | Zero hunger |
| citation_normalized_percentile |