Efficiency of methods for genetic progress estimation in common bean breeding using database information

The final field trials to evaluate elite lines developed by the Embrapa national common bean breeding program generated a phenotypic database composed by agronomic traits of 84 elite lines and nine cultivars over a 16-year period (1993–2008) and 450 environments in all Brazilian growing areas. The m...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Euphytica 2018-09, Vol.214 (9), p.1-10, Article 164
Hauptverfasser: de Faria, Luis Cláudio, Melo, Patrícia Guimarães Santos, de Souza, Thiago Lívio Pessoa Oliveira, Pereira, Helton Santos, Melo, Leonardo Cunha
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 10
container_issue 9
container_start_page 1
container_title Euphytica
container_volume 214
creator de Faria, Luis Cláudio
Melo, Patrícia Guimarães Santos
de Souza, Thiago Lívio Pessoa Oliveira
Pereira, Helton Santos
Melo, Leonardo Cunha
description The final field trials to evaluate elite lines developed by the Embrapa national common bean breeding program generated a phenotypic database composed by agronomic traits of 84 elite lines and nine cultivars over a 16-year period (1993–2008) and 450 environments in all Brazilian growing areas. The main goal of this study was to use this database as a model to compare the consistency of the results obtained from indirect methods for genetic progress estimation for grain yield in common bean breeding, using the direct method as a reference. Three indirect methods for genetic progress estimation were evaluated: (1) linear regression with unadjusted averages, (2) linear regression with averages adjusted by the mixed models, and (3) linear regression with averages adjusted by a fixed effects model with the error exception. The genetic progress estimated by the direct method was 31.3 kg ha −1 per year (1.34%**). This value was considered as the reference estimate, since it was calculated using the grain yield data from final field trials with all common bean lines evaluated under the same environmental conditions. The estimate obtained using the regression with unadjusted averages of the three best lines by cycle was 25.66 kg ha −1 per year (1.26%*), similar to the result obtained by the direct method. Considering both methods using fixed and mixed models, the genetic gain estimates were statistically null (0.42% and 0.45%, respectively). Therefore, the regression method with unadjusted means was more informative than the other indirect methods.
doi_str_mv 10.1007/s10681-018-2246-8
format Article
fullrecord <record><control><sourceid>gale_proqu</sourceid><recordid>TN_cdi_proquest_journals_2092368356</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A714074123</galeid><sourcerecordid>A714074123</sourcerecordid><originalsourceid>FETCH-LOGICAL-c355t-790b950a4b176f6f6b432ce4e74d203ed282a31bfbdc64ffeff8e1619b047c293</originalsourceid><addsrcrecordid>eNp1kUtLxTAQhYMoeL36A9wFXFcnjybtUsQXXHCj65Cmk96IbTTpXfjvTangSgYmIZxvcphDyCWDawagbzID1bAKWFNxLlXVHJENq7WoalBwTDYATFZcCHVKznJ-B4BW17Ah-3vvgws4uW8aPR1x3sc-Ux8THXDCOTj6meKQMGeKeQ6jnUOcaJioi-NYbh3a0hJiH6aBHvLSezvbzmYssjJoRc7JibcfGS9-zy15e7h_vXuqdi-Pz3e3u8qJup4r3ULX1mBlx7TypTopuEOJWvYcBPa84Vawzne9U9J79L5BpljbgdSOt2JLrta5xfbXoVg27_GQpvKl4dByoRpRq6K6XlWD_UCz2JyTdaV6HIOLE_pQ3m81k6AlK3vbErYCLsWcE3rzmcoy0rdhYJYEzJqAKQmYJQHTFIavTC7aacD0Z-V_6Ac4E4oE</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2092368356</pqid></control><display><type>article</type><title>Efficiency of methods for genetic progress estimation in common bean breeding using database information</title><source>SpringerNature Journals</source><creator>de Faria, Luis Cláudio ; Melo, Patrícia Guimarães Santos ; de Souza, Thiago Lívio Pessoa Oliveira ; Pereira, Helton Santos ; Melo, Leonardo Cunha</creator><creatorcontrib>de Faria, Luis Cláudio ; Melo, Patrícia Guimarães Santos ; de Souza, Thiago Lívio Pessoa Oliveira ; Pereira, Helton Santos ; Melo, Leonardo Cunha</creatorcontrib><description>The final field trials to evaluate elite lines developed by the Embrapa national common bean breeding program generated a phenotypic database composed by agronomic traits of 84 elite lines and nine cultivars over a 16-year period (1993–2008) and 450 environments in all Brazilian growing areas. The main goal of this study was to use this database as a model to compare the consistency of the results obtained from indirect methods for genetic progress estimation for grain yield in common bean breeding, using the direct method as a reference. Three indirect methods for genetic progress estimation were evaluated: (1) linear regression with unadjusted averages, (2) linear regression with averages adjusted by the mixed models, and (3) linear regression with averages adjusted by a fixed effects model with the error exception. The genetic progress estimated by the direct method was 31.3 kg ha −1 per year (1.34%**). This value was considered as the reference estimate, since it was calculated using the grain yield data from final field trials with all common bean lines evaluated under the same environmental conditions. The estimate obtained using the regression with unadjusted averages of the three best lines by cycle was 25.66 kg ha −1 per year (1.26%*), similar to the result obtained by the direct method. Considering both methods using fixed and mixed models, the genetic gain estimates were statistically null (0.42% and 0.45%, respectively). Therefore, the regression method with unadjusted means was more informative than the other indirect methods.</description><identifier>ISSN: 0014-2336</identifier><identifier>EISSN: 1573-5060</identifier><identifier>DOI: 10.1007/s10681-018-2246-8</identifier><language>eng</language><publisher>Dordrecht: Springer Netherlands</publisher><subject>Agronomy ; Analysis ; Biomedical and Life Sciences ; Biotechnology ; Breeding ; Crop yield ; Cultivars ; Environmental conditions ; Genetic improvement ; Grain ; Life Sciences ; Methods ; Plant breeding ; Plant Genetics and Genomics ; Plant Pathology ; Plant Physiology ; Plant Sciences ; Regression ; Regression analysis ; Statistical analysis</subject><ispartof>Euphytica, 2018-09, Vol.214 (9), p.1-10, Article 164</ispartof><rights>Springer Nature B.V. 2018</rights><rights>COPYRIGHT 2018 Springer</rights><rights>Euphytica is a copyright of Springer, (2018). All Rights Reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c355t-790b950a4b176f6f6b432ce4e74d203ed282a31bfbdc64ffeff8e1619b047c293</citedby><cites>FETCH-LOGICAL-c355t-790b950a4b176f6f6b432ce4e74d203ed282a31bfbdc64ffeff8e1619b047c293</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s10681-018-2246-8$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s10681-018-2246-8$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>315,781,785,27929,27930,41493,42562,51324</link.rule.ids></links><search><creatorcontrib>de Faria, Luis Cláudio</creatorcontrib><creatorcontrib>Melo, Patrícia Guimarães Santos</creatorcontrib><creatorcontrib>de Souza, Thiago Lívio Pessoa Oliveira</creatorcontrib><creatorcontrib>Pereira, Helton Santos</creatorcontrib><creatorcontrib>Melo, Leonardo Cunha</creatorcontrib><title>Efficiency of methods for genetic progress estimation in common bean breeding using database information</title><title>Euphytica</title><addtitle>Euphytica</addtitle><description>The final field trials to evaluate elite lines developed by the Embrapa national common bean breeding program generated a phenotypic database composed by agronomic traits of 84 elite lines and nine cultivars over a 16-year period (1993–2008) and 450 environments in all Brazilian growing areas. The main goal of this study was to use this database as a model to compare the consistency of the results obtained from indirect methods for genetic progress estimation for grain yield in common bean breeding, using the direct method as a reference. Three indirect methods for genetic progress estimation were evaluated: (1) linear regression with unadjusted averages, (2) linear regression with averages adjusted by the mixed models, and (3) linear regression with averages adjusted by a fixed effects model with the error exception. The genetic progress estimated by the direct method was 31.3 kg ha −1 per year (1.34%**). This value was considered as the reference estimate, since it was calculated using the grain yield data from final field trials with all common bean lines evaluated under the same environmental conditions. The estimate obtained using the regression with unadjusted averages of the three best lines by cycle was 25.66 kg ha −1 per year (1.26%*), similar to the result obtained by the direct method. Considering both methods using fixed and mixed models, the genetic gain estimates were statistically null (0.42% and 0.45%, respectively). Therefore, the regression method with unadjusted means was more informative than the other indirect methods.</description><subject>Agronomy</subject><subject>Analysis</subject><subject>Biomedical and Life Sciences</subject><subject>Biotechnology</subject><subject>Breeding</subject><subject>Crop yield</subject><subject>Cultivars</subject><subject>Environmental conditions</subject><subject>Genetic improvement</subject><subject>Grain</subject><subject>Life Sciences</subject><subject>Methods</subject><subject>Plant breeding</subject><subject>Plant Genetics and Genomics</subject><subject>Plant Pathology</subject><subject>Plant Physiology</subject><subject>Plant Sciences</subject><subject>Regression</subject><subject>Regression analysis</subject><subject>Statistical analysis</subject><issn>0014-2336</issn><issn>1573-5060</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</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>eNp1kUtLxTAQhYMoeL36A9wFXFcnjybtUsQXXHCj65Cmk96IbTTpXfjvTangSgYmIZxvcphDyCWDawagbzID1bAKWFNxLlXVHJENq7WoalBwTDYATFZcCHVKznJ-B4BW17Ah-3vvgws4uW8aPR1x3sc-Ux8THXDCOTj6meKQMGeKeQ6jnUOcaJioi-NYbh3a0hJiH6aBHvLSezvbzmYssjJoRc7JibcfGS9-zy15e7h_vXuqdi-Pz3e3u8qJup4r3ULX1mBlx7TypTopuEOJWvYcBPa84Vawzne9U9J79L5BpljbgdSOt2JLrta5xfbXoVg27_GQpvKl4dByoRpRq6K6XlWD_UCz2JyTdaV6HIOLE_pQ3m81k6AlK3vbErYCLsWcE3rzmcoy0rdhYJYEzJqAKQmYJQHTFIavTC7aacD0Z-V_6Ac4E4oE</recordid><startdate>20180901</startdate><enddate>20180901</enddate><creator>de Faria, Luis Cláudio</creator><creator>Melo, Patrícia Guimarães Santos</creator><creator>de Souza, Thiago Lívio Pessoa Oliveira</creator><creator>Pereira, Helton Santos</creator><creator>Melo, Leonardo Cunha</creator><general>Springer Netherlands</general><general>Springer</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><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>20180901</creationdate><title>Efficiency of methods for genetic progress estimation in common bean breeding using database information</title><author>de Faria, Luis Cláudio ; Melo, Patrícia Guimarães Santos ; de Souza, Thiago Lívio Pessoa Oliveira ; Pereira, Helton Santos ; Melo, Leonardo Cunha</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c355t-790b950a4b176f6f6b432ce4e74d203ed282a31bfbdc64ffeff8e1619b047c293</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Agronomy</topic><topic>Analysis</topic><topic>Biomedical and Life Sciences</topic><topic>Biotechnology</topic><topic>Breeding</topic><topic>Crop yield</topic><topic>Cultivars</topic><topic>Environmental conditions</topic><topic>Genetic improvement</topic><topic>Grain</topic><topic>Life Sciences</topic><topic>Methods</topic><topic>Plant breeding</topic><topic>Plant Genetics and Genomics</topic><topic>Plant Pathology</topic><topic>Plant Physiology</topic><topic>Plant Sciences</topic><topic>Regression</topic><topic>Regression analysis</topic><topic>Statistical analysis</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>de Faria, Luis Cláudio</creatorcontrib><creatorcontrib>Melo, Patrícia Guimarães Santos</creatorcontrib><creatorcontrib>de Souza, Thiago Lívio Pessoa Oliveira</creatorcontrib><creatorcontrib>Pereira, Helton Santos</creatorcontrib><creatorcontrib>Melo, Leonardo Cunha</creatorcontrib><collection>CrossRef</collection><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 &amp; Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Natural Science Collection (ProQuest)</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>de Faria, Luis Cláudio</au><au>Melo, Patrícia Guimarães Santos</au><au>de Souza, Thiago Lívio Pessoa Oliveira</au><au>Pereira, Helton Santos</au><au>Melo, Leonardo Cunha</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Efficiency of methods for genetic progress estimation in common bean breeding using database information</atitle><jtitle>Euphytica</jtitle><stitle>Euphytica</stitle><date>2018-09-01</date><risdate>2018</risdate><volume>214</volume><issue>9</issue><spage>1</spage><epage>10</epage><pages>1-10</pages><artnum>164</artnum><issn>0014-2336</issn><eissn>1573-5060</eissn><abstract>The final field trials to evaluate elite lines developed by the Embrapa national common bean breeding program generated a phenotypic database composed by agronomic traits of 84 elite lines and nine cultivars over a 16-year period (1993–2008) and 450 environments in all Brazilian growing areas. The main goal of this study was to use this database as a model to compare the consistency of the results obtained from indirect methods for genetic progress estimation for grain yield in common bean breeding, using the direct method as a reference. Three indirect methods for genetic progress estimation were evaluated: (1) linear regression with unadjusted averages, (2) linear regression with averages adjusted by the mixed models, and (3) linear regression with averages adjusted by a fixed effects model with the error exception. The genetic progress estimated by the direct method was 31.3 kg ha −1 per year (1.34%**). This value was considered as the reference estimate, since it was calculated using the grain yield data from final field trials with all common bean lines evaluated under the same environmental conditions. The estimate obtained using the regression with unadjusted averages of the three best lines by cycle was 25.66 kg ha −1 per year (1.26%*), similar to the result obtained by the direct method. Considering both methods using fixed and mixed models, the genetic gain estimates were statistically null (0.42% and 0.45%, respectively). Therefore, the regression method with unadjusted means was more informative than the other indirect methods.</abstract><cop>Dordrecht</cop><pub>Springer Netherlands</pub><doi>10.1007/s10681-018-2246-8</doi><tpages>10</tpages></addata></record>
fulltext fulltext
identifier ISSN: 0014-2336
ispartof Euphytica, 2018-09, Vol.214 (9), p.1-10, Article 164
issn 0014-2336
1573-5060
language eng
recordid cdi_proquest_journals_2092368356
source SpringerNature Journals
subjects Agronomy
Analysis
Biomedical and Life Sciences
Biotechnology
Breeding
Crop yield
Cultivars
Environmental conditions
Genetic improvement
Grain
Life Sciences
Methods
Plant breeding
Plant Genetics and Genomics
Plant Pathology
Plant Physiology
Plant Sciences
Regression
Regression analysis
Statistical analysis
title Efficiency of methods for genetic progress estimation in common bean breeding using database information
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-12T13%3A49%3A11IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_proqu&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Efficiency%20of%20methods%20for%20genetic%20progress%20estimation%20in%20common%20bean%20breeding%20using%20database%20information&rft.jtitle=Euphytica&rft.au=de%20Faria,%20Luis%20Cl%C3%A1udio&rft.date=2018-09-01&rft.volume=214&rft.issue=9&rft.spage=1&rft.epage=10&rft.pages=1-10&rft.artnum=164&rft.issn=0014-2336&rft.eissn=1573-5060&rft_id=info:doi/10.1007/s10681-018-2246-8&rft_dat=%3Cgale_proqu%3EA714074123%3C/gale_proqu%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2092368356&rft_id=info:pmid/&rft_galeid=A714074123&rfr_iscdi=true