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Selection of inbred soybean progeny (Glycine max): an approach with population effect
To meet the growing demand of the soybean consumer market, cultivars increasingly early, productive and resistant to biotic and abiotic stress are sought. Several populations are obtained in soybean breeding programmes, but progeny are selected without being weighted for their respective population...
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Published in: | Plant breeding 2018-12, Vol.137 (6), p.865-872 |
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container_title | Plant breeding |
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creator | Volpato, Leonardo Simiqueli, Guilherme Ferreira Alves, Rodrigo Silva Rocha, João Romero do Amaral Santos de Carvalho Del Conte, Murilo Viotto Resende, Marcos Deon Vilela de Carneiro, Pedro Crescêncio Souza Silva, Felipe Lopes da Singh, Ram |
description | To meet the growing demand of the soybean consumer market, cultivars increasingly early, productive and resistant to biotic and abiotic stress are sought. Several populations are obtained in soybean breeding programmes, but progeny are selected without being weighted for their respective population effect. As a consequence, progeny originating from high‐merit populations may be discarded too early. Given this scenario, this study proposes to employ the selection index with progeny and population effect via best linear unbiased prediction (SIPP‐BLUP) for the genetic selection of early and productive soybean progeny. A total of 180 progeny derived from three populations were evaluated for yield‐related traits. Genetic gains from selection, Spearman correlation and coincidence index were used to check the efficiency of the models with and without the population effect. The SIPP‐BLUP index achieved greater selection accuracy and was efficient in the identification and future selection of early soybean progeny. Therefore, this study demonstrates that soybean breeding programmes should consider the population effect via SIPP‐BLUP in progeny selection to obtain future lines that really contribute to genetic gain. |
doi_str_mv | 10.1111/pbr.12648 |
format | article |
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Several populations are obtained in soybean breeding programmes, but progeny are selected without being weighted for their respective population effect. As a consequence, progeny originating from high‐merit populations may be discarded too early. Given this scenario, this study proposes to employ the selection index with progeny and population effect via best linear unbiased prediction (SIPP‐BLUP) for the genetic selection of early and productive soybean progeny. A total of 180 progeny derived from three populations were evaluated for yield‐related traits. Genetic gains from selection, Spearman correlation and coincidence index were used to check the efficiency of the models with and without the population effect. The SIPP‐BLUP index achieved greater selection accuracy and was efficient in the identification and future selection of early soybean progeny. 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Several populations are obtained in soybean breeding programmes, but progeny are selected without being weighted for their respective population effect. As a consequence, progeny originating from high‐merit populations may be discarded too early. Given this scenario, this study proposes to employ the selection index with progeny and population effect via best linear unbiased prediction (SIPP‐BLUP) for the genetic selection of early and productive soybean progeny. A total of 180 progeny derived from three populations were evaluated for yield‐related traits. Genetic gains from selection, Spearman correlation and coincidence index were used to check the efficiency of the models with and without the population effect. The SIPP‐BLUP index achieved greater selection accuracy and was efficient in the identification and future selection of early soybean progeny. Therefore, this study demonstrates that soybean breeding programmes should consider the population effect via SIPP‐BLUP in progeny selection to obtain future lines that really contribute to genetic gain.</description><subject>accuracy</subject><subject>Breeding</subject><subject>breeding values</subject><subject>Cultivars</subject><subject>earlier‐maturing progeny</subject><subject>genetic gain</subject><subject>genotype × environment interaction</subject><subject>Glycine max</subject><subject>Inbreeding</subject><subject>mixed models</subject><subject>Offspring</subject><subject>Population</subject><subject>Populations</subject><subject>Progeny</subject><subject>soybean seed yield</subject><subject>Soybeans</subject><issn>0179-9541</issn><issn>1439-0523</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><recordid>eNp1kE1PwzAMhiMEEmNw4B9E4sIO3fLZD24wwUCaBAJ2jpI0YZ26piSdRv892coVH2xZfvzaegG4xmiKY8xa5aeYpCw_ASPMaJEgTugpGCGcFUnBGT4HFyFs0KGn2QisPkxtdFe5BjoLq0Z5U8LgemVkA1vvvkzTw9tF3euqMXArfyZ3ME5kG2dSr-G-6tawde2ulkcRY22UuwRnVtbBXP3VMVg9PX7On5Pl6-Jlfr9MNCmyPGGYlYRxkpY8ZYxpxDVRShcpsypHRpcKYa4tLg3NLUGEsTzNONdIsbLEKKVjcDPoxm--dyZ0YuN2voknBcE0owzTmMdgMlDauxC8saL11Vb6XmAkDq6J6Jo4uhbZ2cDuq9r0_4Pi7eF92PgFI3BteA</recordid><startdate>201812</startdate><enddate>201812</enddate><creator>Volpato, Leonardo</creator><creator>Simiqueli, Guilherme Ferreira</creator><creator>Alves, Rodrigo Silva</creator><creator>Rocha, João Romero do Amaral Santos de Carvalho</creator><creator>Del Conte, Murilo Viotto</creator><creator>Resende, Marcos Deon Vilela de</creator><creator>Carneiro, Pedro Crescêncio Souza</creator><creator>Silva, Felipe Lopes da</creator><creator>Singh, Ram</creator><general>Wiley Subscription Services, Inc</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7QO</scope><scope>7T7</scope><scope>8FD</scope><scope>C1K</scope><scope>FR3</scope><scope>P64</scope><scope>RC3</scope><orcidid>https://orcid.org/0000-0003-1119-0615</orcidid><orcidid>https://orcid.org/0000-0001-9866-9615</orcidid><orcidid>https://orcid.org/0000-0002-0976-0917</orcidid></search><sort><creationdate>201812</creationdate><title>Selection of inbred soybean progeny (Glycine max): an approach with population effect</title><author>Volpato, Leonardo ; Simiqueli, Guilherme Ferreira ; Alves, Rodrigo Silva ; Rocha, João Romero do Amaral Santos de Carvalho ; Del Conte, Murilo Viotto ; Resende, Marcos Deon Vilela de ; Carneiro, Pedro Crescêncio Souza ; Silva, Felipe Lopes da ; Singh, Ram</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c2978-414d24526d56444c05c2bbc964fb80ecdb015cf1de38f2024486755c0b4dd1063</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>accuracy</topic><topic>Breeding</topic><topic>breeding values</topic><topic>Cultivars</topic><topic>earlier‐maturing progeny</topic><topic>genetic gain</topic><topic>genotype × environment interaction</topic><topic>Glycine max</topic><topic>Inbreeding</topic><topic>mixed models</topic><topic>Offspring</topic><topic>Population</topic><topic>Populations</topic><topic>Progeny</topic><topic>soybean seed yield</topic><topic>Soybeans</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Volpato, Leonardo</creatorcontrib><creatorcontrib>Simiqueli, Guilherme Ferreira</creatorcontrib><creatorcontrib>Alves, Rodrigo Silva</creatorcontrib><creatorcontrib>Rocha, João Romero do Amaral Santos de Carvalho</creatorcontrib><creatorcontrib>Del Conte, Murilo Viotto</creatorcontrib><creatorcontrib>Resende, Marcos Deon Vilela de</creatorcontrib><creatorcontrib>Carneiro, Pedro Crescêncio Souza</creatorcontrib><creatorcontrib>Silva, Felipe Lopes da</creatorcontrib><creatorcontrib>Singh, Ram</creatorcontrib><collection>CrossRef</collection><collection>Biotechnology Research Abstracts</collection><collection>Industrial and Applied Microbiology Abstracts (Microbiology A)</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Engineering Research Database</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Genetics Abstracts</collection><jtitle>Plant breeding</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Volpato, Leonardo</au><au>Simiqueli, Guilherme Ferreira</au><au>Alves, Rodrigo Silva</au><au>Rocha, João Romero do Amaral Santos de Carvalho</au><au>Del Conte, Murilo Viotto</au><au>Resende, Marcos Deon Vilela de</au><au>Carneiro, Pedro Crescêncio Souza</au><au>Silva, Felipe Lopes da</au><au>Singh, Ram</au><au>Singh, Ram</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Selection of inbred soybean progeny (Glycine max): an approach with population effect</atitle><jtitle>Plant breeding</jtitle><date>2018-12</date><risdate>2018</risdate><volume>137</volume><issue>6</issue><spage>865</spage><epage>872</epage><pages>865-872</pages><issn>0179-9541</issn><eissn>1439-0523</eissn><abstract>To meet the growing demand of the soybean consumer market, cultivars increasingly early, productive and resistant to biotic and abiotic stress are sought. Several populations are obtained in soybean breeding programmes, but progeny are selected without being weighted for their respective population effect. As a consequence, progeny originating from high‐merit populations may be discarded too early. Given this scenario, this study proposes to employ the selection index with progeny and population effect via best linear unbiased prediction (SIPP‐BLUP) for the genetic selection of early and productive soybean progeny. A total of 180 progeny derived from three populations were evaluated for yield‐related traits. Genetic gains from selection, Spearman correlation and coincidence index were used to check the efficiency of the models with and without the population effect. The SIPP‐BLUP index achieved greater selection accuracy and was efficient in the identification and future selection of early soybean progeny. 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subjects | accuracy Breeding breeding values Cultivars earlier‐maturing progeny genetic gain genotype × environment interaction Glycine max Inbreeding mixed models Offspring Population Populations Progeny soybean seed yield Soybeans |
title | Selection of inbred soybean progeny (Glycine max): an approach with population effect |
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