Factor analysis applied in genomic selection studies in the breeding of Coffea canephora
Brazil stands out worldwide in the production of coffee. The observed increases in its productivity and morpho agronomic traits are the results of the improvement of several methodologies applied in obtaining improved cultivars, among which the predictive methods of genetic value stand out. These co...
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| Veröffentlicht in: | Euphytica 2022-04, Vol.218 (4), p.42-42, Article 42 |
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| creator | Paixão, Pedro Thiago Medeiros Nascimento, Ana Carolina Campana Nascimento, Moysés Azevedo, Camila Ferreira Oliveira, Gabriela França da Silva, Felipe Lopes Caixeta, Eveline Teixeira |
| description | Brazil stands out worldwide in the production of coffee. The observed increases in its productivity and morpho agronomic traits are the results of the improvement of several methodologies applied in obtaining improved cultivars, among which the predictive methods of genetic value stand out. These contribute significantly to the selection of higher genotypes, increasing the genetic gain per unit time. In this context, genomic-wide selection (GWS) is a tool that stands out, since it allows predicting the future phenotype of an individual based only on molecular information. Performing joint selection of traits is the interest of most breeding programs, and factor analysis (FA) has been used to assist in this end. The aim of this study was to evaluate the use of FA in the context of GWS, in genotypes of
Coffea canephora
. It was found that FA was efficient to elucidate the relationships between the traits and generate new variables. The factors formed can assist in the selection, as in addition to allowing joint interpretations, they present good estimates of predictive capacity, heritability and accuracy. Furthermore, high agreement was observed between the individuals selected based on the factors and those selected considering the individual traits. Additionally, it was observed agreement between the top 10% individuals selected based on the “vigor factor” and each variable individually. However, the selection based on “vigor factor” presented individuals with more suitable size from the phytotechnical point of view. |
| doi_str_mv | 10.1007/s10681-022-02998-x |
| format | Article |
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Coffea canephora
. It was found that FA was efficient to elucidate the relationships between the traits and generate new variables. The factors formed can assist in the selection, as in addition to allowing joint interpretations, they present good estimates of predictive capacity, heritability and accuracy. Furthermore, high agreement was observed between the individuals selected based on the factors and those selected considering the individual traits. Additionally, it was observed agreement between the top 10% individuals selected based on the “vigor factor” and each variable individually. However, the selection based on “vigor factor” presented individuals with more suitable size from the phytotechnical point of view.</description><identifier>ISSN: 0014-2336</identifier><identifier>EISSN: 1573-5060</identifier><identifier>DOI: 10.1007/s10681-022-02998-x</identifier><identifier>PMID: 35310815</identifier><language>eng</language><publisher>Dordrecht: Springer Netherlands</publisher><subject>Accuracy ; Analysis ; Biomedical and Life Sciences ; Biotechnology ; Cattle ; Coffea canephora ; Coffee ; Context ; Cultivars ; Factor analysis ; Genetic improvement ; Genomic analysis ; Genotypes ; Heritability ; Life Sciences ; Phenotypes ; Plant breeding ; Plant Genetics and Genomics ; Plant Pathology ; Plant Physiology ; Plant Sciences ; Variables</subject><ispartof>Euphytica, 2022-04, Vol.218 (4), p.42-42, Article 42</ispartof><rights>The Author(s), under exclusive licence to Springer Nature B.V. 2022</rights><rights>The Author(s), under exclusive licence to Springer Nature B.V. 2022.</rights><rights>COPYRIGHT 2022 Springer</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c513t-a438c883bf2feee5fd3b018ff47c72776a95374bfd826d76f082df78bdc76ee63</citedby><cites>FETCH-LOGICAL-c513t-a438c883bf2feee5fd3b018ff47c72776a95374bfd826d76f082df78bdc76ee63</cites><orcidid>0000-0002-6985-1490</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s10681-022-02998-x$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s10681-022-02998-x$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>230,314,780,784,885,27923,27924,41487,42556,51318</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/35310815$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Paixão, Pedro Thiago Medeiros</creatorcontrib><creatorcontrib>Nascimento, Ana Carolina Campana</creatorcontrib><creatorcontrib>Nascimento, Moysés</creatorcontrib><creatorcontrib>Azevedo, Camila Ferreira</creatorcontrib><creatorcontrib>Oliveira, Gabriela França</creatorcontrib><creatorcontrib>da Silva, Felipe Lopes</creatorcontrib><creatorcontrib>Caixeta, Eveline Teixeira</creatorcontrib><title>Factor analysis applied in genomic selection studies in the breeding of Coffea canephora</title><title>Euphytica</title><addtitle>Euphytica</addtitle><addtitle>Euphytica</addtitle><description>Brazil stands out worldwide in the production of coffee. The observed increases in its productivity and morpho agronomic traits are the results of the improvement of several methodologies applied in obtaining improved cultivars, among which the predictive methods of genetic value stand out. These contribute significantly to the selection of higher genotypes, increasing the genetic gain per unit time. In this context, genomic-wide selection (GWS) is a tool that stands out, since it allows predicting the future phenotype of an individual based only on molecular information. Performing joint selection of traits is the interest of most breeding programs, and factor analysis (FA) has been used to assist in this end. The aim of this study was to evaluate the use of FA in the context of GWS, in genotypes of
Coffea canephora
. It was found that FA was efficient to elucidate the relationships between the traits and generate new variables. The factors formed can assist in the selection, as in addition to allowing joint interpretations, they present good estimates of predictive capacity, heritability and accuracy. Furthermore, high agreement was observed between the individuals selected based on the factors and those selected considering the individual traits. Additionally, it was observed agreement between the top 10% individuals selected based on the “vigor factor” and each variable individually. 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Coffea canephora
. It was found that FA was efficient to elucidate the relationships between the traits and generate new variables. The factors formed can assist in the selection, as in addition to allowing joint interpretations, they present good estimates of predictive capacity, heritability and accuracy. Furthermore, high agreement was observed between the individuals selected based on the factors and those selected considering the individual traits. Additionally, it was observed agreement between the top 10% individuals selected based on the “vigor factor” and each variable individually. However, the selection based on “vigor factor” presented individuals with more suitable size from the phytotechnical point of view.</abstract><cop>Dordrecht</cop><pub>Springer Netherlands</pub><pmid>35310815</pmid><doi>10.1007/s10681-022-02998-x</doi><tpages>1</tpages><orcidid>https://orcid.org/0000-0002-6985-1490</orcidid><oa>free_for_read</oa></addata></record> |
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| ispartof | Euphytica, 2022-04, Vol.218 (4), p.42-42, Article 42 |
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| subjects | Accuracy Analysis Biomedical and Life Sciences Biotechnology Cattle Coffea canephora Coffee Context Cultivars Factor analysis Genetic improvement Genomic analysis Genotypes Heritability Life Sciences Phenotypes Plant breeding Plant Genetics and Genomics Plant Pathology Plant Physiology Plant Sciences Variables |
| title | Factor analysis applied in genomic selection studies in the breeding of Coffea canephora |
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