Multivariate selection of AFLP markers associated with [beta]-carotene in sweetpotatoes
A population that consisted of F.sub.1 half-sibs and their parents was replicated in field plantings to generate roots to identify AFLP molecular markers and compare statistical models for selection of trait-linked markers using [beta]-carotene content as the grouping variable. Genotypes were groupe...
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| Veröffentlicht in: | Euphytica 2010-09, Vol.175 (1), p.123 |
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| creator | Mcharo, Mwamburi LaBonte, Don R |
| description | A population that consisted of F.sub.1 half-sibs and their parents was replicated in field plantings to generate roots to identify AFLP molecular markers and compare statistical models for selection of trait-linked markers using [beta]-carotene content as the grouping variable. Genotypes were grouped into high and low [beta]-carotene classes based on hierarchical cluster analysis. Association parameters between the high and low phenotypic classes of [beta]-carotene and molecular marker profiles were made using logistic regression and discriminant analysis. Logistic regression selected 8 markers less that were associated with [beta]-carotene content compared to discriminant analysis. Further analysis showed that logistic regression achieved 100% correct classification with the 9 markers selected compared to 17 markers that were required by discriminant analysis thus making logistic regression more efficient than discriminant analysis. Logistic regression based on Frequentist hypothesis testing differs from Bayesian based discriminant analysis. This difference may account for the percent correct classification observed. |
| doi_str_mv | 10.1007/s10681-010-0193-0 |
| format | Article |
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Genotypes were grouped into high and low [beta]-carotene classes based on hierarchical cluster analysis. Association parameters between the high and low phenotypic classes of [beta]-carotene and molecular marker profiles were made using logistic regression and discriminant analysis. Logistic regression selected 8 markers less that were associated with [beta]-carotene content compared to discriminant analysis. Further analysis showed that logistic regression achieved 100% correct classification with the 9 markers selected compared to 17 markers that were required by discriminant analysis thus making logistic regression more efficient than discriminant analysis. Logistic regression based on Frequentist hypothesis testing differs from Bayesian based discriminant analysis. 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Genotypes were grouped into high and low [beta]-carotene classes based on hierarchical cluster analysis. Association parameters between the high and low phenotypic classes of [beta]-carotene and molecular marker profiles were made using logistic regression and discriminant analysis. Logistic regression selected 8 markers less that were associated with [beta]-carotene content compared to discriminant analysis. Further analysis showed that logistic regression achieved 100% correct classification with the 9 markers selected compared to 17 markers that were required by discriminant analysis thus making logistic regression more efficient than discriminant analysis. Logistic regression based on Frequentist hypothesis testing differs from Bayesian based discriminant analysis. This difference may account for the percent correct classification observed.</description><subject>Analysis</subject><subject>Beta carotene</subject><subject>Genetic markers</subject><subject>Genotype & phenotype</subject><subject>Genotypes</subject><subject>Multivariate analysis</subject><subject>Selective breeding</subject><subject>Statistical models</subject><subject>Vegetables</subject><subject>Vitamin A</subject><issn>0014-2336</issn><issn>1573-5060</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2010</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNotjUFLAzEQhYMoWKs_wFvwnjqzySa7x1KsChU9FDyIlGw6qanbTd2k9u-7ogyPBx8fbxi7RpgggLlNCLpCAQhDainghI2wNFKUoOGUjQBQiUJKfc4uUtoCQG1KGLHXp0Obw7ftg83EE7Xkcogdj55P54sXvrP9J_WJ25Si-3XW_BjyB39rKNt34WwfM3XEQ8fTkSjvY7Y5UrpkZ962ia7-e8yW87vl7EEsnu8fZ9OF2GiNwpeFR7BqrbCpSNYFeFP4csDa1eTI-2aAUjlrsVEO64a0klYb2bi6rGo5Zjd_s_s-fh0o5dU2Hvpu-LgySlYVKMRBmvxJG9vSKnQ-5t664da0Cy525MPApwYVGNQg5Q-3LWO7</recordid><startdate>20100901</startdate><enddate>20100901</enddate><creator>Mcharo, Mwamburi</creator><creator>LaBonte, Don R</creator><general>Springer</general><general>Springer Nature B.V</general><scope>3V.</scope><scope>7SN</scope><scope>7SS</scope><scope>7T7</scope><scope>7TM</scope><scope>7X2</scope><scope>7XB</scope><scope>88I</scope><scope>8FD</scope><scope>8FE</scope><scope>8FH</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>M0K</scope><scope>M2P</scope><scope>M7N</scope><scope>P64</scope><scope>PATMY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PYCSY</scope><scope>Q9U</scope><scope>RC3</scope></search><sort><creationdate>20100901</creationdate><title>Multivariate selection of AFLP markers associated with [beta]-carotene in sweetpotatoes</title><author>Mcharo, Mwamburi ; LaBonte, Don R</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-g661-f52f10a4d41b8e3920f72f5f526c9eceffb39234caa1b4c19be643a673bc95893</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2010</creationdate><topic>Analysis</topic><topic>Beta carotene</topic><topic>Genetic markers</topic><topic>Genotype & phenotype</topic><topic>Genotypes</topic><topic>Multivariate analysis</topic><topic>Selective breeding</topic><topic>Statistical models</topic><topic>Vegetables</topic><topic>Vitamin A</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Mcharo, Mwamburi</creatorcontrib><creatorcontrib>LaBonte, Don R</creatorcontrib><collection>ProQuest Central (Corporate)</collection><collection>Ecology Abstracts</collection><collection>Entomology Abstracts (Full archive)</collection><collection>Industrial and Applied Microbiology Abstracts (Microbiology A)</collection><collection>Nucleic Acids Abstracts</collection><collection>Agricultural Science Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Science Database (Alumni Edition)</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>Agricultural Science Database</collection><collection>Science Database</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Environmental Science Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Environmental Science Collection</collection><collection>ProQuest Central Basic</collection><collection>Genetics Abstracts</collection><jtitle>Euphytica</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Mcharo, Mwamburi</au><au>LaBonte, Don R</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Multivariate selection of AFLP markers associated with [beta]-carotene in sweetpotatoes</atitle><jtitle>Euphytica</jtitle><date>2010-09-01</date><risdate>2010</risdate><volume>175</volume><issue>1</issue><spage>123</spage><pages>123-</pages><issn>0014-2336</issn><eissn>1573-5060</eissn><abstract>A population that consisted of F.sub.1 half-sibs and their parents was replicated in field plantings to generate roots to identify AFLP molecular markers and compare statistical models for selection of trait-linked markers using [beta]-carotene content as the grouping variable. 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| subjects | Analysis Beta carotene Genetic markers Genotype & phenotype Genotypes Multivariate analysis Selective breeding Statistical models Vegetables Vitamin A |
| title | Multivariate selection of AFLP markers associated with [beta]-carotene in sweetpotatoes |
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