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Registro completo
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Biblioteca (s) : |
INIA Las Brujas. |
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Fecha : |
16/06/2022 |
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Actualizado : |
16/06/2022 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Autor : |
GALLINO, J. P.; CASTILLO, A.; CERETTA, S.; ESTEVES, P.; BONNECARRERE, V. |
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Afiliación : |
JUAN PABLO GALLINO, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; ALICIA MARIA CASTILLO SALLE, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; SERGIO EDUARDO CERETTA SORIA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; PATRICIO ESTEVES, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; MARIA VICTORIA BONNECARRERE MARTINEZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
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Título : |
A simple and inexpensive procedure to more quickly obtain new varieties in soybean. |
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Fecha de publicación : |
2022 |
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Fuente / Imprenta : |
Crop Breeding and Applied Biotechnology, 2022, volume 22, Issue 1, e38212216. OPEN ACCESS. doi: https://doi.org/10.1590/1984-70332022v22n1a06 |
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ISSN : |
1518-7853 |
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DOI : |
10.1590/1984-70332022v22n1a06 |
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Idioma : |
Inglés |
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Notas : |
Article history: Received 24 May 2021; Accepted 12 Aug 2021; Published 30 Mar 2022; Publication in this collection 04 May 2022; Date of issue 2022.
Corresponding author: Gallino, J.P.; INIA, Estación Experimental "Wilson Ferreira Aldunate", Las Brujas, Ruta 48, km 10, Rincón del Colorado, Canelones, Uruguay; email:jpgallino@gmail.com -- The authors thanks the Instituto Nacional de Investigación Agropecuaria (INIA) for financial support and use of facilities.
License: This is an open-access article distributed under the terms of the Creative Commons Attribution License: https://creativecommons.org/licenses/by/4.0/ |
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Contenido : |
ABSTRACT - Soybean (Glycine max L.) is one of the four most important crops in the world. The creation of new commercial varieties is a long-term activity that requires from seven to eight years from the beginning of the cross design up to registration for commercialization of cultivars. Rapid generation advance (RGA) is a technique that consists of controlling external factors that affect plant growth with the aim of shortening the sowing to harvest cycle. In the present study, an optimized method is described that can accelerate soybean breeding by means of RGA using inexpensive facilities and that can be easily applied by breeders. Our breeding method uses a modified cold storage chamber fitted with fluorescent lamps delivering a 12/24 h light photoperiod, while temperature is set at 24 °C. This method allows development of up to 5 generations per year instead of the 1-2 generations currently possible under field or greenhouse conditions. © 2022, Brazilian Society of Plant Breeding. All rights reserved. |
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Palabras claves : |
Genetic gain; Rapid generation advance; Selection cycle; Soybean. |
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Asunto categoría : |
F30 Genética vegetal y fitomejoramiento |
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URL : |
https://www.scielo.br/j/cbab/a/CX3xLpkzDjsvGDkMvKxDnHh/?format=pdf&lang=en
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Marc : |
LEADER 02458naa a2200253 a 4500
001 1063312
005 2022-06-16
008 2022 bl uuuu u00u1 u #d
022 $a1518-7853
024 7 $a10.1590/1984-70332022v22n1a06$2DOI
100 1 $aGALLINO, J. P.
245 $aA simple and inexpensive procedure to more quickly obtain new varieties in soybean.$h[electronic resource]
260 $c2022
500 $aArticle history: Received 24 May 2021; Accepted 12 Aug 2021; Published 30 Mar 2022; Publication in this collection 04 May 2022; Date of issue 2022. Corresponding author: Gallino, J.P.; INIA, Estación Experimental "Wilson Ferreira Aldunate", Las Brujas, Ruta 48, km 10, Rincón del Colorado, Canelones, Uruguay; email:jpgallino@gmail.com -- The authors thanks the Instituto Nacional de Investigación Agropecuaria (INIA) for financial support and use of facilities. License: This is an open-access article distributed under the terms of the Creative Commons Attribution License: https://creativecommons.org/licenses/by/4.0/
520 $aABSTRACT - Soybean (Glycine max L.) is one of the four most important crops in the world. The creation of new commercial varieties is a long-term activity that requires from seven to eight years from the beginning of the cross design up to registration for commercialization of cultivars. Rapid generation advance (RGA) is a technique that consists of controlling external factors that affect plant growth with the aim of shortening the sowing to harvest cycle. In the present study, an optimized method is described that can accelerate soybean breeding by means of RGA using inexpensive facilities and that can be easily applied by breeders. Our breeding method uses a modified cold storage chamber fitted with fluorescent lamps delivering a 12/24 h light photoperiod, while temperature is set at 24 °C. This method allows development of up to 5 generations per year instead of the 1-2 generations currently possible under field or greenhouse conditions. © 2022, Brazilian Society of Plant Breeding. All rights reserved.
653 $aGenetic gain
653 $aRapid generation advance
653 $aSelection cycle
653 $aSoybean
700 1 $aCASTILLO, A.
700 1 $aCERETTA, S.
700 1 $aESTEVES, P.
700 1 $aBONNECARRERE, V.
773 $tCrop Breeding and Applied Biotechnology, 2022, volume 22, Issue 1, e38212216. OPEN ACCESS. doi: https://doi.org/10.1590/1984-70332022v22n1a06
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Registro original : |
INIA Las Brujas (LB) |
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Registro completo
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Biblioteca (s) : |
INIA Las Brujas. |
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Fecha actual : |
26/04/2023 |
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Actualizado : |
26/04/2023 |
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Tipo de producción científica : |
Artículos Indexados |
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Autor : |
REBOLLO, I.; SCHEFFEL, S.; BLANCO, P.H.; MOLINA, F.; MARTÍNEZ, S.; CARRACELAS, G.; PÉREZ DE VIDA, F.; ROSAS, J.E. |
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Afiliación : |
MARÍA INÉS REBOLLO PANUNCIO, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; SHEILA SCHEFFEL, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; PEDRO HORACIO BLANCO BARRAL, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; FEDERICO MOLINA CASELLA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; SEBASTIÁN MARTÍNEZ KOPP, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; JULIO GONZALO CARRACELAS GARRIDO, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; FERNANDO BLAS PEREZ DE VIDA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; JUAN EDUARDO ROSAS CAISSIOLS, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
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Título : |
Instituto Nacional de Investigación Agropecuaria (INIA) Rice Breeding Program Historical Dataset. [Dataset]. |
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Fecha de publicación : |
2023 |
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Fuente / Imprenta : |
DRYAD Dataset, 2024. https://doi.org/10.5061/dryad.x69p8czn8 |
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DOI : |
10.5061/dryad.x69p8czn8 |
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Idioma : |
Inglés |
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Notas : |
Correspondence author: Juan E. Rosas, email: jrosas@inia.org.uy -- Publication date: February 16, 2024. -- This dataset is embargoed and will be released when the associated article is published. Lists of files and downloads will become available to the public when released. -- FUNDING: Agencia Nacional de Investigación e Innovación, Award: FSDA_1_2018_1_154120; Instituto Nacional de Investigación Agropecuaria, Award: AZ13; Instituto Nacional de Investigación Agropecuaria, Award: AZ35. |
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Contenido : |
Breeding programs generate vast amounts of data which are often scattered in separate files. This hinders the application of modern breeding tools such as multi-environment analyses and genomic selection. This dataset is the result of consolidating 23 years of phenotypic, pedigree, and genomic records from the Uruguayan national rice breeding program. All the available data from 1997 to 2020 corresponding to field trials, blast nurseries, laboratory analyses of milling and cooking quality, pedigree information, and genomic information for selected advanced breeding lines are gathered. Records of 996 trials in 12 locations over a span of 23 years, 91,636 field plots with information on 14 phenotypic variables, pedigree for 19,447 genotypes, and genomic information regarding 61,260 SNP markers for 965 genotypes were recovered. The dataset is structured in Trials, Phenotypes, Lines, Genomic Information, and SNP Tables. Genotype identification has been coded. Copyright (c) 2023 Dryad |
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Palabras claves : |
Agricultural sciences; Agronomic performance; Breeding trials; Disease phenotype; Genotypic data; Genotyping by sequencing (GBS); Grain yield; Phenotypic data; Rice Breeding Program; SNP; Temperate region. |
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Thesagro : |
ORYZA SATIVA L; URUGUAY. |
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Asunto categoría : |
F30 Genética vegetal y fitomejoramiento |
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URL : |
https://datadryad.org/stash/dataset/doi:10.5061/dryad.x69p8czn8
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Marc : |
LEADER 02599naa a2200385 a 4500
001 1064058
005 2023-04-26
008 2023 bl uuuu u00u1 u #d
024 7 $a10.5061/dryad.x69p8czn8$2DOI
100 1 $aREBOLLO, I.
245 $aInstituto Nacional de Investigación Agropecuaria (INIA) Rice Breeding Program Historical Dataset. [Dataset].$h[electronic resource]
260 $c2023
500 $aCorrespondence author: Juan E. Rosas, email: jrosas@inia.org.uy -- Publication date: February 16, 2024. -- This dataset is embargoed and will be released when the associated article is published. Lists of files and downloads will become available to the public when released. -- FUNDING: Agencia Nacional de Investigación e Innovación, Award: FSDA_1_2018_1_154120; Instituto Nacional de Investigación Agropecuaria, Award: AZ13; Instituto Nacional de Investigación Agropecuaria, Award: AZ35.
520 $aBreeding programs generate vast amounts of data which are often scattered in separate files. This hinders the application of modern breeding tools such as multi-environment analyses and genomic selection. This dataset is the result of consolidating 23 years of phenotypic, pedigree, and genomic records from the Uruguayan national rice breeding program. All the available data from 1997 to 2020 corresponding to field trials, blast nurseries, laboratory analyses of milling and cooking quality, pedigree information, and genomic information for selected advanced breeding lines are gathered. Records of 996 trials in 12 locations over a span of 23 years, 91,636 field plots with information on 14 phenotypic variables, pedigree for 19,447 genotypes, and genomic information regarding 61,260 SNP markers for 965 genotypes were recovered. The dataset is structured in Trials, Phenotypes, Lines, Genomic Information, and SNP Tables. Genotype identification has been coded. Copyright (c) 2023 Dryad
650 $aORYZA SATIVA L
650 $aURUGUAY
653 $aAgricultural sciences
653 $aAgronomic performance
653 $aBreeding trials
653 $aDisease phenotype
653 $aGenotypic data
653 $aGenotyping by sequencing (GBS)
653 $aGrain yield
653 $aPhenotypic data
653 $aRice Breeding Program
653 $aSNP
653 $aTemperate region
700 1 $aSCHEFFEL, S.
700 1 $aBLANCO, P.H.
700 1 $aMOLINA, F.
700 1 $aMARTÍNEZ, S.
700 1 $aCARRACELAS, G.
700 1 $aPÉREZ DE VIDA, F.
700 1 $aROSAS, J.E.
773 $tDRYAD Dataset, 2024. https://doi.org/10.5061/dryad.x69p8czn8
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