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Establishing a soybean germplasm core collection
Core collections are of strategic importance as they allow the use of a small part of a germplasm collection that is representative of the total collection. The objective of this study was to develop a soybean core collection of the USDA Soybean Germplasm Collection by comparing the results of rando...
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Published in: | Field crops research 2010-11, Vol.119 (2), p.277-289 |
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container_end_page | 289 |
container_issue | 2 |
container_start_page | 277 |
container_title | Field crops research |
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creator | Oliveira, Marcelo F. Nelson, Randall L. Geraldi, Isaias O. Cruz, Cosme D. de Toledo, José Francisco F. |
description | Core collections are of strategic importance as they allow the use of a small part of a germplasm collection that is representative of the total collection. The objective of this study was to develop a soybean core collection of the USDA Soybean Germplasm Collection by comparing the results of random, proportional, logarithmic, multivariate proportional and multivariate logarithmic sampling strategies. All but the random sampling strategy used stratification of the entire collection based on passport data and maturity group classification. The multivariate proportional and multivariate logarithmic strategies made further use of qualitative and quantitative trait data to select diverse accessions within each stratum. The 18 quantitative trait data distribution parameters were calculated for each core and for the entire collection for pairwise comparison to validate the sampling strategies. All strategies were adequate for assembling a core collection. The random core collection best represented the entire collection in statistical terms. Proportional and logarithmic strategies did not maximize statistical representation but were better in selecting maximum variability. Multivariate proportional and multivariate logarithmic strategies produced the best core collections as measured by maximum variability conservation. The soybean core collection was established using the multivariate proportional selection strategy. |
doi_str_mv | 10.1016/j.fcr.2010.07.021 |
format | article |
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The objective of this study was to develop a soybean core collection of the USDA Soybean Germplasm Collection by comparing the results of random, proportional, logarithmic, multivariate proportional and multivariate logarithmic sampling strategies. All but the random sampling strategy used stratification of the entire collection based on passport data and maturity group classification. The multivariate proportional and multivariate logarithmic strategies made further use of qualitative and quantitative trait data to select diverse accessions within each stratum. The 18 quantitative trait data distribution parameters were calculated for each core and for the entire collection for pairwise comparison to validate the sampling strategies. All strategies were adequate for assembling a core collection. The random core collection best represented the entire collection in statistical terms. Proportional and logarithmic strategies did not maximize statistical representation but were better in selecting maximum variability. Multivariate proportional and multivariate logarithmic strategies produced the best core collections as measured by maximum variability conservation. 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The objective of this study was to develop a soybean core collection of the USDA Soybean Germplasm Collection by comparing the results of random, proportional, logarithmic, multivariate proportional and multivariate logarithmic sampling strategies. All but the random sampling strategy used stratification of the entire collection based on passport data and maturity group classification. The multivariate proportional and multivariate logarithmic strategies made further use of qualitative and quantitative trait data to select diverse accessions within each stratum. The 18 quantitative trait data distribution parameters were calculated for each core and for the entire collection for pairwise comparison to validate the sampling strategies. All strategies were adequate for assembling a core collection. The random core collection best represented the entire collection in statistical terms. Proportional and logarithmic strategies did not maximize statistical representation but were better in selecting maximum variability. Multivariate proportional and multivariate logarithmic strategies produced the best core collections as measured by maximum variability conservation. The soybean core collection was established using the multivariate proportional selection strategy.</description><subject>Conservation</subject><subject>DNA fingerprinting</subject><subject>Genetic diversity</subject><subject>genetic variation</subject><subject>genotype</subject><subject>Germplasm bank</subject><subject>germplasm conservation</subject><subject>germplasm core collections</subject><subject>Glycine max</subject><subject>methodology</subject><subject>multivariate proportional selection strategy</subject><subject>plant genetic resources</subject><subject>qualitative analysis</subject><subject>quantitative trait loci</subject><subject>quantitative traits</subject><subject>sampling</subject><subject>Sampling strategies</subject><subject>soybeans</subject><subject>validity</subject><issn>0378-4290</issn><issn>1872-6852</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2010</creationdate><recordtype>article</recordtype><recordid>eNp9kEtLxDAQgIMouK7-AE_25ql1krRJiydZ1gcseNA9hySdrln6WJOusP_elHoWhnnANwPzEXJLIaNAxcM-a6zPGMQZZAaMnpEFLSVLRVmwc7IALss0ZxVckqsQ9gAgBBULAuswatO68OX6XaKTMJwM6j7Zoe8OrQ5dYgePMbUt2tEN_TW5aHQb8OavLsn2ef25ek037y9vq6dNanNajSkzdS6FqazFgtnCCEO5bTQHqxlS0JRSy0xRSy400oIbkGh4zWqMLbKCL8n9fPfgh-8jhlF1LlhsW93jcAyqLIScYiLpTFo_hOCxUQfvOu1PioKa5Ki9inLUJEeBVFFO3Lmbdxo9KL3zLqjtRwQ40LIqIWeReJwJjE_-OPQqWIe9xdr5aELVg_vn_i8K7nW_</recordid><startdate>20101101</startdate><enddate>20101101</enddate><creator>Oliveira, Marcelo F.</creator><creator>Nelson, Randall L.</creator><creator>Geraldi, Isaias O.</creator><creator>Cruz, Cosme D.</creator><creator>de Toledo, José Francisco F.</creator><general>Elsevier B.V</general><general>[Amsterdam]: Elsevier</general><scope>FBQ</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7ST</scope><scope>7U6</scope><scope>C1K</scope><scope>SOI</scope></search><sort><creationdate>20101101</creationdate><title>Establishing a soybean germplasm core collection</title><author>Oliveira, Marcelo F. ; Nelson, Randall L. ; Geraldi, Isaias O. ; Cruz, Cosme D. ; de Toledo, José Francisco F.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c419t-2bd476b9cce52c5b6b13cfa30ca2e10a111c2b5d736ae153b07eb3d2de3b0e253</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2010</creationdate><topic>Conservation</topic><topic>DNA fingerprinting</topic><topic>Genetic diversity</topic><topic>genetic variation</topic><topic>genotype</topic><topic>Germplasm bank</topic><topic>germplasm conservation</topic><topic>germplasm core collections</topic><topic>Glycine max</topic><topic>methodology</topic><topic>multivariate proportional selection strategy</topic><topic>plant genetic resources</topic><topic>qualitative analysis</topic><topic>quantitative trait loci</topic><topic>quantitative traits</topic><topic>sampling</topic><topic>Sampling strategies</topic><topic>soybeans</topic><topic>validity</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Oliveira, Marcelo F.</creatorcontrib><creatorcontrib>Nelson, Randall L.</creatorcontrib><creatorcontrib>Geraldi, Isaias O.</creatorcontrib><creatorcontrib>Cruz, Cosme D.</creatorcontrib><creatorcontrib>de Toledo, José Francisco F.</creatorcontrib><collection>AGRIS</collection><collection>CrossRef</collection><collection>Environment Abstracts</collection><collection>Sustainability Science Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Environment Abstracts</collection><jtitle>Field crops research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Oliveira, Marcelo F.</au><au>Nelson, Randall L.</au><au>Geraldi, Isaias O.</au><au>Cruz, Cosme D.</au><au>de Toledo, José Francisco F.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Establishing a soybean germplasm core collection</atitle><jtitle>Field crops research</jtitle><date>2010-11-01</date><risdate>2010</risdate><volume>119</volume><issue>2</issue><spage>277</spage><epage>289</epage><pages>277-289</pages><issn>0378-4290</issn><eissn>1872-6852</eissn><abstract>Core collections are of strategic importance as they allow the use of a small part of a germplasm collection that is representative of the total collection. The objective of this study was to develop a soybean core collection of the USDA Soybean Germplasm Collection by comparing the results of random, proportional, logarithmic, multivariate proportional and multivariate logarithmic sampling strategies. All but the random sampling strategy used stratification of the entire collection based on passport data and maturity group classification. The multivariate proportional and multivariate logarithmic strategies made further use of qualitative and quantitative trait data to select diverse accessions within each stratum. The 18 quantitative trait data distribution parameters were calculated for each core and for the entire collection for pairwise comparison to validate the sampling strategies. All strategies were adequate for assembling a core collection. The random core collection best represented the entire collection in statistical terms. Proportional and logarithmic strategies did not maximize statistical representation but were better in selecting maximum variability. Multivariate proportional and multivariate logarithmic strategies produced the best core collections as measured by maximum variability conservation. The soybean core collection was established using the multivariate proportional selection strategy.</abstract><pub>Elsevier B.V</pub><doi>10.1016/j.fcr.2010.07.021</doi><tpages>13</tpages></addata></record> |
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subjects | Conservation DNA fingerprinting Genetic diversity genetic variation genotype Germplasm bank germplasm conservation germplasm core collections Glycine max methodology multivariate proportional selection strategy plant genetic resources qualitative analysis quantitative trait loci quantitative traits sampling Sampling strategies soybeans validity |
title | Establishing a soybean germplasm core collection |
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