Population improvement via recurrent selection drives genetic gain in upland rice breeding
One of the main challenges of breeding programs is to identify superior genotypes from a large number of candidates. By gradually increasing the frequency of favorable alleles in the breeding population, recurrent selection improves the population mean for target traits, increasing the chance to ide...
Gespeichert in:
| Veröffentlicht in: | Heredity 2023-09, Vol.131 (3), p.201-210 |
|---|---|
| Hauptverfasser: | , , , , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 210 |
|---|---|
| container_issue | 3 |
| container_start_page | 201 |
| container_title | Heredity |
| container_volume | 131 |
| creator | Pereira de Castro, Adriano Breseghello, Flávio Furtini, Isabela Volpi Utumi, Marley Marico Pereira, José Almeida Cao, Tuong-Vi Bartholomé, Jérôme |
| description | One of the main challenges of breeding programs is to identify superior genotypes from a large number of candidates. By gradually increasing the frequency of favorable alleles in the breeding population, recurrent selection improves the population mean for target traits, increasing the chance to identify promising genotypes. In rice, population improvement through recurrent selection has been used very little to date, except in Latin America. At Embrapa (Brazilian Agricultural Research Corporation), the upland rice breeding program is conducted in two phases: population improvement followed by product development. In this study, the CNA6 population, evaluated over five cycles (3 to 7) of selection, including 20 field trials, was used to assess the realized genetic gain. A high rate of genetic gain was observed for grain yield, at 215 kg.ha
per cycle or 67.8 kg.ha
per year (3.08%). The CNA6 population outperformed the controls only for the last cycle, with a yield difference of 1128 kg.ha
. An analysis of the product development pipeline, based on 29 advanced yield trials with lines derived from cycles 3 to 6, showed that lines derived from the CNA6 population had high grain yield, but did not outperform the controls. These results demonstrate that the application of recurrent selection to a breeding population with sufficient genetic variability can result in significant genetic gains for quantitative traits, such as grain yield. The integration of this strategy into a two-phase breeding program also makes it possible to increase quantitative traits while selecting for other traits of interest. |
| doi_str_mv | 10.1038/s41437-023-00636-3 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_10462700</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2833997752</sourcerecordid><originalsourceid>FETCH-LOGICAL-c465t-6e1f9af6cf6d32cb8275b47092b28afad3c163069ce7a075e6d52be75115ae663</originalsourceid><addsrcrecordid>eNpdkUtv1DAUhS0EosPAH2CBIrEpi8D1O1mhqgKKNFK7AAmxsRznZuoqiYOdROLf19MpFe3Ksv2dcx-HkLcUPlLg1ackqOC6BMZLAMVVyZ-RDeVKlkwKeE42ALQqQelfJ-RVSjcAwDWrX5ITrgVoVfMN-X0VpqW3sw9j4YcphhUHHOdi9baI6JYYD7eEPbo7po1-xVTsccTZu2JvfdaNxTL1dmyL6B0WTURs_bh_TV50tk_45v7ckp9fv_w4vyh3l9--n5_tSieUnEuFtKttp1ynWs5cUzEtG6GhZg2rbGdb7qjioGqH2oKWqFrJGtSSUmlRKb4ln4--09IM2LrccLS9maIfbPxrgvXm8c_or80-rIaCUEznpWzJh6PD9RPdxdnOHN5ACK0ZUyvN7Ol9tRj-LJhmM_jksM_zY1iSYRXnda21ZBl9_wS9CUsc8y4yJSuoaiYOhuxIuRhSitg9dEDBHHI2x5xNztnc5Wx4Fr37f-YHyb9g-S32sKRC</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2858089241</pqid></control><display><type>article</type><title>Population improvement via recurrent selection drives genetic gain in upland rice breeding</title><source>MEDLINE</source><source>Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals</source><source>Nature Journals Online</source><source>PubMed Central</source><source>SpringerLink Journals - AutoHoldings</source><creator>Pereira de Castro, Adriano ; Breseghello, Flávio ; Furtini, Isabela Volpi ; Utumi, Marley Marico ; Pereira, José Almeida ; Cao, Tuong-Vi ; Bartholomé, Jérôme</creator><creatorcontrib>Pereira de Castro, Adriano ; Breseghello, Flávio ; Furtini, Isabela Volpi ; Utumi, Marley Marico ; Pereira, José Almeida ; Cao, Tuong-Vi ; Bartholomé, Jérôme</creatorcontrib><description>One of the main challenges of breeding programs is to identify superior genotypes from a large number of candidates. By gradually increasing the frequency of favorable alleles in the breeding population, recurrent selection improves the population mean for target traits, increasing the chance to identify promising genotypes. In rice, population improvement through recurrent selection has been used very little to date, except in Latin America. At Embrapa (Brazilian Agricultural Research Corporation), the upland rice breeding program is conducted in two phases: population improvement followed by product development. In this study, the CNA6 population, evaluated over five cycles (3 to 7) of selection, including 20 field trials, was used to assess the realized genetic gain. A high rate of genetic gain was observed for grain yield, at 215 kg.ha
per cycle or 67.8 kg.ha
per year (3.08%). The CNA6 population outperformed the controls only for the last cycle, with a yield difference of 1128 kg.ha
. An analysis of the product development pipeline, based on 29 advanced yield trials with lines derived from cycles 3 to 6, showed that lines derived from the CNA6 population had high grain yield, but did not outperform the controls. These results demonstrate that the application of recurrent selection to a breeding population with sufficient genetic variability can result in significant genetic gains for quantitative traits, such as grain yield. The integration of this strategy into a two-phase breeding program also makes it possible to increase quantitative traits while selecting for other traits of interest.</description><identifier>ISSN: 0018-067X</identifier><identifier>ISSN: 1365-2540</identifier><identifier>EISSN: 1365-2540</identifier><identifier>EISSN: 0018-067X</identifier><identifier>DOI: 10.1038/s41437-023-00636-3</identifier><identifier>PMID: 37407693</identifier><language>eng</language><publisher>England: Springer Nature B.V</publisher><subject>Agricultural production ; Agricultural research ; Climate change ; Crop yield ; Drought ; Edible Grain - genetics ; Gene frequency ; Genetic improvement ; Genetic variability ; Genotype ; Genotypes ; Grain ; Life Sciences ; Oryza - genetics ; Performance evaluation ; Phenotype ; Plant breeding ; Plant Breeding - methods ; Population ; Population genetics ; Population studies ; Product development ; Rice ; Selection, Genetic</subject><ispartof>Heredity, 2023-09, Vol.131 (3), p.201-210</ispartof><rights>2023. The Author(s), under exclusive licence to The Genetics Society.</rights><rights>The Author(s), under exclusive licence to The Genetics Society 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.</rights><rights>Distributed under a Creative Commons Attribution 4.0 International License</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c465t-6e1f9af6cf6d32cb8275b47092b28afad3c163069ce7a075e6d52be75115ae663</citedby><cites>FETCH-LOGICAL-c465t-6e1f9af6cf6d32cb8275b47092b28afad3c163069ce7a075e6d52be75115ae663</cites><orcidid>0000-0002-6202-4767 ; 0000-0002-0855-3828</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC10462700/pdf/$$EPDF$$P50$$Gpubmedcentral$$H</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC10462700/$$EHTML$$P50$$Gpubmedcentral$$H</linktohtml><link.rule.ids>230,314,725,778,782,883,27913,27914,53780,53782</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/37407693$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink><backlink>$$Uhttps://hal.inrae.fr/hal-04477226$$DView record in HAL$$Hfree_for_read</backlink></links><search><creatorcontrib>Pereira de Castro, Adriano</creatorcontrib><creatorcontrib>Breseghello, Flávio</creatorcontrib><creatorcontrib>Furtini, Isabela Volpi</creatorcontrib><creatorcontrib>Utumi, Marley Marico</creatorcontrib><creatorcontrib>Pereira, José Almeida</creatorcontrib><creatorcontrib>Cao, Tuong-Vi</creatorcontrib><creatorcontrib>Bartholomé, Jérôme</creatorcontrib><title>Population improvement via recurrent selection drives genetic gain in upland rice breeding</title><title>Heredity</title><addtitle>Heredity (Edinb)</addtitle><description>One of the main challenges of breeding programs is to identify superior genotypes from a large number of candidates. By gradually increasing the frequency of favorable alleles in the breeding population, recurrent selection improves the population mean for target traits, increasing the chance to identify promising genotypes. In rice, population improvement through recurrent selection has been used very little to date, except in Latin America. At Embrapa (Brazilian Agricultural Research Corporation), the upland rice breeding program is conducted in two phases: population improvement followed by product development. In this study, the CNA6 population, evaluated over five cycles (3 to 7) of selection, including 20 field trials, was used to assess the realized genetic gain. A high rate of genetic gain was observed for grain yield, at 215 kg.ha
per cycle or 67.8 kg.ha
per year (3.08%). The CNA6 population outperformed the controls only for the last cycle, with a yield difference of 1128 kg.ha
. An analysis of the product development pipeline, based on 29 advanced yield trials with lines derived from cycles 3 to 6, showed that lines derived from the CNA6 population had high grain yield, but did not outperform the controls. These results demonstrate that the application of recurrent selection to a breeding population with sufficient genetic variability can result in significant genetic gains for quantitative traits, such as grain yield. The integration of this strategy into a two-phase breeding program also makes it possible to increase quantitative traits while selecting for other traits of interest.</description><subject>Agricultural production</subject><subject>Agricultural research</subject><subject>Climate change</subject><subject>Crop yield</subject><subject>Drought</subject><subject>Edible Grain - genetics</subject><subject>Gene frequency</subject><subject>Genetic improvement</subject><subject>Genetic variability</subject><subject>Genotype</subject><subject>Genotypes</subject><subject>Grain</subject><subject>Life Sciences</subject><subject>Oryza - genetics</subject><subject>Performance evaluation</subject><subject>Phenotype</subject><subject>Plant breeding</subject><subject>Plant Breeding - methods</subject><subject>Population</subject><subject>Population genetics</subject><subject>Population studies</subject><subject>Product development</subject><subject>Rice</subject><subject>Selection, Genetic</subject><issn>0018-067X</issn><issn>1365-2540</issn><issn>1365-2540</issn><issn>0018-067X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>8G5</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNpdkUtv1DAUhS0EosPAH2CBIrEpi8D1O1mhqgKKNFK7AAmxsRznZuoqiYOdROLf19MpFe3Ksv2dcx-HkLcUPlLg1ackqOC6BMZLAMVVyZ-RDeVKlkwKeE42ALQqQelfJ-RVSjcAwDWrX5ITrgVoVfMN-X0VpqW3sw9j4YcphhUHHOdi9baI6JYYD7eEPbo7po1-xVTsccTZu2JvfdaNxTL1dmyL6B0WTURs_bh_TV50tk_45v7ckp9fv_w4vyh3l9--n5_tSieUnEuFtKttp1ynWs5cUzEtG6GhZg2rbGdb7qjioGqH2oKWqFrJGtSSUmlRKb4ln4--09IM2LrccLS9maIfbPxrgvXm8c_or80-rIaCUEznpWzJh6PD9RPdxdnOHN5ACK0ZUyvN7Ol9tRj-LJhmM_jksM_zY1iSYRXnda21ZBl9_wS9CUsc8y4yJSuoaiYOhuxIuRhSitg9dEDBHHI2x5xNztnc5Wx4Fr37f-YHyb9g-S32sKRC</recordid><startdate>20230901</startdate><enddate>20230901</enddate><creator>Pereira de Castro, Adriano</creator><creator>Breseghello, Flávio</creator><creator>Furtini, Isabela Volpi</creator><creator>Utumi, Marley Marico</creator><creator>Pereira, José Almeida</creator><creator>Cao, Tuong-Vi</creator><creator>Bartholomé, Jérôme</creator><general>Springer Nature B.V</general><general>Nature Publishing Group</general><general>Springer International Publishing</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7QL</scope><scope>7SN</scope><scope>7SS</scope><scope>7T7</scope><scope>7TK</scope><scope>7U9</scope><scope>7X7</scope><scope>7XB</scope><scope>88A</scope><scope>88E</scope><scope>88I</scope><scope>8AO</scope><scope>8C1</scope><scope>8FD</scope><scope>8FE</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>8G5</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>H94</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>LK8</scope><scope>M0S</scope><scope>M1P</scope><scope>M2O</scope><scope>M2P</scope><scope>M7N</scope><scope>M7P</scope><scope>MBDVC</scope><scope>P64</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>Q9U</scope><scope>RC3</scope><scope>7X8</scope><scope>1XC</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0002-6202-4767</orcidid><orcidid>https://orcid.org/0000-0002-0855-3828</orcidid></search><sort><creationdate>20230901</creationdate><title>Population improvement via recurrent selection drives genetic gain in upland rice breeding</title><author>Pereira de Castro, Adriano ; Breseghello, Flávio ; Furtini, Isabela Volpi ; Utumi, Marley Marico ; Pereira, José Almeida ; Cao, Tuong-Vi ; Bartholomé, Jérôme</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c465t-6e1f9af6cf6d32cb8275b47092b28afad3c163069ce7a075e6d52be75115ae663</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Agricultural production</topic><topic>Agricultural research</topic><topic>Climate change</topic><topic>Crop yield</topic><topic>Drought</topic><topic>Edible Grain - genetics</topic><topic>Gene frequency</topic><topic>Genetic improvement</topic><topic>Genetic variability</topic><topic>Genotype</topic><topic>Genotypes</topic><topic>Grain</topic><topic>Life Sciences</topic><topic>Oryza - genetics</topic><topic>Performance evaluation</topic><topic>Phenotype</topic><topic>Plant breeding</topic><topic>Plant Breeding - methods</topic><topic>Population</topic><topic>Population genetics</topic><topic>Population studies</topic><topic>Product development</topic><topic>Rice</topic><topic>Selection, Genetic</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Pereira de Castro, Adriano</creatorcontrib><creatorcontrib>Breseghello, Flávio</creatorcontrib><creatorcontrib>Furtini, Isabela Volpi</creatorcontrib><creatorcontrib>Utumi, Marley Marico</creatorcontrib><creatorcontrib>Pereira, José Almeida</creatorcontrib><creatorcontrib>Cao, Tuong-Vi</creatorcontrib><creatorcontrib>Bartholomé, Jérôme</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Ecology Abstracts</collection><collection>Entomology Abstracts (Full archive)</collection><collection>Industrial and Applied Microbiology Abstracts (Microbiology A)</collection><collection>Neurosciences Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Biology Database (Alumni Edition)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Science Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Public Health Database</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Research Library (Alumni Edition)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</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>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>ProQuest Biological Science Collection</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Research Library</collection><collection>Science Database (ProQuest)</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biological Science Database</collection><collection>Research Library (Corporate)</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central Basic</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><collection>Hyper Article en Ligne (HAL)</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Heredity</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Pereira de Castro, Adriano</au><au>Breseghello, Flávio</au><au>Furtini, Isabela Volpi</au><au>Utumi, Marley Marico</au><au>Pereira, José Almeida</au><au>Cao, Tuong-Vi</au><au>Bartholomé, Jérôme</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Population improvement via recurrent selection drives genetic gain in upland rice breeding</atitle><jtitle>Heredity</jtitle><addtitle>Heredity (Edinb)</addtitle><date>2023-09-01</date><risdate>2023</risdate><volume>131</volume><issue>3</issue><spage>201</spage><epage>210</epage><pages>201-210</pages><issn>0018-067X</issn><issn>1365-2540</issn><eissn>1365-2540</eissn><eissn>0018-067X</eissn><abstract>One of the main challenges of breeding programs is to identify superior genotypes from a large number of candidates. By gradually increasing the frequency of favorable alleles in the breeding population, recurrent selection improves the population mean for target traits, increasing the chance to identify promising genotypes. In rice, population improvement through recurrent selection has been used very little to date, except in Latin America. At Embrapa (Brazilian Agricultural Research Corporation), the upland rice breeding program is conducted in two phases: population improvement followed by product development. In this study, the CNA6 population, evaluated over five cycles (3 to 7) of selection, including 20 field trials, was used to assess the realized genetic gain. A high rate of genetic gain was observed for grain yield, at 215 kg.ha
per cycle or 67.8 kg.ha
per year (3.08%). The CNA6 population outperformed the controls only for the last cycle, with a yield difference of 1128 kg.ha
. An analysis of the product development pipeline, based on 29 advanced yield trials with lines derived from cycles 3 to 6, showed that lines derived from the CNA6 population had high grain yield, but did not outperform the controls. These results demonstrate that the application of recurrent selection to a breeding population with sufficient genetic variability can result in significant genetic gains for quantitative traits, such as grain yield. The integration of this strategy into a two-phase breeding program also makes it possible to increase quantitative traits while selecting for other traits of interest.</abstract><cop>England</cop><pub>Springer Nature B.V</pub><pmid>37407693</pmid><doi>10.1038/s41437-023-00636-3</doi><tpages>10</tpages><orcidid>https://orcid.org/0000-0002-6202-4767</orcidid><orcidid>https://orcid.org/0000-0002-0855-3828</orcidid><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0018-067X |
| ispartof | Heredity, 2023-09, Vol.131 (3), p.201-210 |
| issn | 0018-067X 1365-2540 1365-2540 0018-067X |
| language | eng |
| recordid | cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_10462700 |
| source | MEDLINE; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; Nature Journals Online; PubMed Central; SpringerLink Journals - AutoHoldings |
| subjects | Agricultural production Agricultural research Climate change Crop yield Drought Edible Grain - genetics Gene frequency Genetic improvement Genetic variability Genotype Genotypes Grain Life Sciences Oryza - genetics Performance evaluation Phenotype Plant breeding Plant Breeding - methods Population Population genetics Population studies Product development Rice Selection, Genetic |
| title | Population improvement via recurrent selection drives genetic gain in upland rice breeding |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-15T07%3A47%3A25IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_pubme&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Population%20improvement%20via%20recurrent%20selection%20drives%20genetic%20gain%20in%20upland%20rice%20breeding&rft.jtitle=Heredity&rft.au=Pereira%20de%20Castro,%20Adriano&rft.date=2023-09-01&rft.volume=131&rft.issue=3&rft.spage=201&rft.epage=210&rft.pages=201-210&rft.issn=0018-067X&rft.eissn=1365-2540&rft_id=info:doi/10.1038/s41437-023-00636-3&rft_dat=%3Cproquest_pubme%3E2833997752%3C/proquest_pubme%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2858089241&rft_id=info:pmid/37407693&rfr_iscdi=true |