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Biblioteca (s) : |
INIA Treinta y Tres. |
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Fecha : |
11/05/2018 |
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Actualizado : |
28/05/2019 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Autor : |
MONTEVERDE, E.; ROSAS, J.E.; BLANCO, P.H.; PÉREZ DE VIDA, F.; BONNECARRERE, V.; QUERO, G.; GUTIERREZ, L.; MCCOUCH, S. |
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Afiliación : |
ELIANA MONTEVERDE, Plant Breeding and Genetics Section, School of Integrative Plant Science, Cornell University, USA.; JUAN EDUARDO ROSAS CAISSIOLS, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; PEDRO HORACIO BLANCO BARRAL, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; FERNANDO BLAS PEREZ DE VIDA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; MARIA VICTORIA BONNECARRERE MARTINEZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; GASTÓN QUERO CORRALLO, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; LUCÍA GUTIERREZ, Department of Agronomy, University of Wisconsin, WI, USA.; SUSAN MCCOUCH, Plant Breeding and Genetics Section, School of Integrative Plant Science, Cornell University, USA. |
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Título : |
Multienvironment models increase prediction accuracy of complex traits in advanced breeding lines of rice (O. sativa). |
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Fecha de publicación : |
2018 |
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Fuente / Imprenta : |
Crop Science, 2018, 58:1519-1530. |
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DOI : |
10.2135/cropsci2017.09.0564 |
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Idioma : |
Inglés |
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Notas : |
Article history: Accepted on May 09, 2018. Published online June 21, 2018. |
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Contenido : |
ABSTRACT: Genotype x environment interaction (G x E) is the differential response of genotypes in different environments and represents a major challenge for breeders. Genotype x year-interaction (G x Y) is a relevant component of G x E, and accounting for it is an important strategy for identifying lines with stable and superior performance across years. In this study, we compared the prediction accuracy of modeling G x Y using covariance structures that differ in their ability to
accommodate correlation among environments.
We present the use of these approaches in two different rice (Oryza sativa L.) breeding populations (indica and tropical japonica) for predicting grain yield, plant height, and three milling quality traits—milling yield, head rice percentage, and grain chalkiness—under different cross-validation (CV) scenarios. We also compared model performance in the context of global predictions (i.e., predictions across years). Most of the benefits of multienvironment models come from modeling genetic correlations between environments when predicting performance of lines that have been tested in some environments but not others (CV2). For predicting the performance of newly developed lines (CV1), modeling between environment correlations has no effect compared with considering environments independently. Response to selection of multienvironment models when modeling covariance structures that accommodate covariances between environments was always beneficial when predicting the performance of lines across years. We also show that, for some traits, high prediction accuracies can be obtained in untested years, which is important for resource allocation in small breeding programs. MenosABSTRACT: Genotype x environment interaction (G x E) is the differential response of genotypes in different environments and represents a major challenge for breeders. Genotype x year-interaction (G x Y) is a relevant component of G x E, and accounting for it is an important strategy for identifying lines with stable and superior performance across years. In this study, we compared the prediction accuracy of modeling G x Y using covariance structures that differ in their ability to
accommodate correlation among environments.
We present the use of these approaches in two different rice (Oryza sativa L.) breeding populations (indica and tropical japonica) for predicting grain yield, plant height, and three milling quality traits—milling yield, head rice percentage, and grain chalkiness—under different cross-validation (CV) scenarios. We also compared model performance in the context of global predictions (i.e., predictions across years). Most of the benefits of multienvironment models come from modeling genetic correlations between environments when predicting performance of lines that have been tested in some environments but not others (CV2). For predicting the performance of newly developed lines (CV1), modeling between environment correlations has no effect compared with considering environments independently. Response to selection of multienvironment models when modeling covariance structures that accommodate covariances between environments was always beneficial when pr... Presentar Todo |
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Palabras claves : |
GENOTYPE X ENVIRONMENT INTERACTION; INTERACCIONES GENOTIPO-AMBIENTE. |
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Thesagro : |
ARROZ; GENOTIPOS; RICE. |
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Asunto categoría : |
F30 Genética vegetal y fitomejoramiento |
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Marc : |
LEADER 02635naa a2200289 a 4500
001 1058574
005 2019-05-28
008 2018 bl uuuu u00u1 u #d
024 7 $a10.2135/cropsci2017.09.0564$2DOI
100 1 $aMONTEVERDE, E.
245 $aMultienvironment models increase prediction accuracy of complex traits in advanced breeding lines of rice (O. sativa).$h[electronic resource]
260 $c2018
500 $aArticle history: Accepted on May 09, 2018. Published online June 21, 2018.
520 $aABSTRACT: Genotype x environment interaction (G x E) is the differential response of genotypes in different environments and represents a major challenge for breeders. Genotype x year-interaction (G x Y) is a relevant component of G x E, and accounting for it is an important strategy for identifying lines with stable and superior performance across years. In this study, we compared the prediction accuracy of modeling G x Y using covariance structures that differ in their ability to accommodate correlation among environments. We present the use of these approaches in two different rice (Oryza sativa L.) breeding populations (indica and tropical japonica) for predicting grain yield, plant height, and three milling quality traits—milling yield, head rice percentage, and grain chalkiness—under different cross-validation (CV) scenarios. We also compared model performance in the context of global predictions (i.e., predictions across years). Most of the benefits of multienvironment models come from modeling genetic correlations between environments when predicting performance of lines that have been tested in some environments but not others (CV2). For predicting the performance of newly developed lines (CV1), modeling between environment correlations has no effect compared with considering environments independently. Response to selection of multienvironment models when modeling covariance structures that accommodate covariances between environments was always beneficial when predicting the performance of lines across years. We also show that, for some traits, high prediction accuracies can be obtained in untested years, which is important for resource allocation in small breeding programs.
650 $aARROZ
650 $aGENOTIPOS
650 $aRICE
653 $aGENOTYPE X ENVIRONMENT INTERACTION
653 $aINTERACCIONES GENOTIPO-AMBIENTE
700 1 $aROSAS, J.E.
700 1 $aBLANCO, P.H.
700 1 $aPÉREZ DE VIDA, F.
700 1 $aBONNECARRERE, V.
700 1 $aQUERO, G.
700 1 $aGUTIERREZ, L.
700 1 $aMCCOUCH, S.
773 $tCrop Science, 2018, 58:1519-1530.
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Registro original : |
INIA Treinta y Tres (TT) |
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Registro completo
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Biblioteca (s) : |
INIA Las Brujas. |
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Fecha actual : |
06/12/2022 |
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Actualizado : |
06/12/2022 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Circulación / Nivel : |
Internacional - -- |
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Autor : |
DE SANTIAGO, F.; BARRIOS, M.; D'ANATRO, A.; GARCÍA, L.F.; MAILHOS, A.; POMPOZZI, G.; REHERMANN, S.; SIMÓ, M.; TESITORE, G.; DE MELLO, F.T.; VALTIERRA, V.; BLUMETTO, O. |
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Afiliación : |
MARÍA FERNANDA DE SANTIAGO, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; MARGENNY BARRIOS, Departamento de Ecología y Gestión Ambiental, Centro Universitario Regional del Este (CURE), Universidad de la República, Av. Tacuarembó s/n, Entre Av. Artigas y Aparicio Saravia, Maldonado CP 20000, Uruguay; ALEJANDRO D'ANATRO, Laboratorio de Evolución, Facultad de Ciencias, Universidad de la República, Iguá 4225, Montevideo CP 11400, Uruguay; LUIS FERNANDO GARCÍA, Centro Universitario Regional del Este (CURE), Universidad de la República, Ruta 8 km 282, Treinta y Tres CP 33000, Uruguay; ARY MAILHOS, Laboratorio de Botánica, Facultad de Agronomía, Universidad de la República, Montevideo CP 12900, Uruguay; GABRIEL POMPOZZI, Laboratorio de Entomología, IADIZA (CCT CONICET-Mendoza), Mendoza CP 5500, Argentina; SOFÍA REHERMANN, Departamento de Ecología y Gestión Ambiental, Centro Universitario Regional del Este (CURE), Universidad de la República, Av. Tacuarembó s/n, Entre Av. Artigas y Aparicio Saravia, Maldonado CP 20000, Uruguay; MIGUEL SIMÓ, Sección Entomología, Facultad de Ciencias, Universidad de la República, Montevideo CP 11400, Uruguay; GIANCARLO TESITORE, Departamento de Ecología y Gestión Ambiental, Centro Universitario Regional del Este (CURE), Universidad de la República, Av. Tacuarembó s/n, Entre Av. Artigas y Aparicio Saravia, Maldonado CP 20000, Uruguay; FRANCO TEIXEIRA DE MELLO, Departamento de Ecología y Gestión Ambiental, Centro Universitario Regional del Este (CURE), Universidad de la República, Av. Tacuarembó s/n, Entre Av. Artigas y Aparicio Saravia, Maldonado CP 20000, Uruguay; VICTORIA VALTIERRA, Laboratorio de Botánica, Facultad de Agronomía, Universidad de la República, Montevideo CP 12900, Uruguay; OSCAR RICARDO BLUMETTO VELAZCO, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
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Título : |
From theory to practice: can LEAP/FAO biodiversity assessment guidelines be a useful tool for knowing the environmental status of livestock systems? |
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Fecha de publicación : |
2022 |
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Fuente / Imprenta : |
Sustainability, 2022, Volume 14, Issue 23, e16259. OPEN ACCESS. doi: https://doi.org/10.3390/su142316259 |
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ISSN : |
EISSN 2071-1050 |
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DOI : |
10.3390/su142316259 |
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Idioma : |
Inglés |
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Notas : |
Article history: Received 6 November 2022; Revised 29 November 2022; Accepted 29 November 2022; Published 6 December 2022. -- Academic Editor: Andrea Pezzuolo. -- LICENSE: Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons
Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
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Contenido : |
ABSTRACT.- Biodiversity loss is a global concern, and agriculture is one of the economic sectors responsible for this impact. The assessment of ecosystems under the influence of livestock production is essential for knowing their integrity and ability to provide ecosystem services. The aim of this investigation was to evaluate the application of LEAP/FAO guidelines for quantitative assessment of biodiversity in the livestock sector at the local scale (farm level) in a group of six study cases in Uruguay. A set of 20 indicators was used, including seven key thematic issues: habitat protection, habitat change, wildlife conservation, invasive species, pollution, aquatic biodiversity, off-farm feed, and landscape-scale conservation. The results show that the LEAP biodiversity assessment guidelines can be useful to characterize the state of ecosystems under pastoral use and some specific components of their biodiversity, as well as assess the interaction of the production system with the environment and plan management accordingly. This work also provides an analysis of the methodology used and recommendations to facilitate its application by the sector. The results from the application of the indicators show a great deal of wild biodiversity that uses grazing systems based on native grasslands as habitats and the acceptable integrity of these ecosystems. On average, farms have 83% of their native ecosystem, with a value of 3.5 for the Ecosystem Integrity Index. In terms of the richness of different groups, there was an average number of species of 112 herbaceous plants, 48 woody plants, 48 spiders, 150 birds, and 14 fish. The main goal of this work is to help in the wider application of the guidelines by facilitating decisions about methodology, necessary resources, and technical support. Moreover, another goal is to show the importance of native grasslands-based livestock systems for biodiversity conservation. Copyright © 2022 by the authors. MenosABSTRACT.- Biodiversity loss is a global concern, and agriculture is one of the economic sectors responsible for this impact. The assessment of ecosystems under the influence of livestock production is essential for knowing their integrity and ability to provide ecosystem services. The aim of this investigation was to evaluate the application of LEAP/FAO guidelines for quantitative assessment of biodiversity in the livestock sector at the local scale (farm level) in a group of six study cases in Uruguay. A set of 20 indicators was used, including seven key thematic issues: habitat protection, habitat change, wildlife conservation, invasive species, pollution, aquatic biodiversity, off-farm feed, and landscape-scale conservation. The results show that the LEAP biodiversity assessment guidelines can be useful to characterize the state of ecosystems under pastoral use and some specific components of their biodiversity, as well as assess the interaction of the production system with the environment and plan management accordingly. This work also provides an analysis of the methodology used and recommendations to facilitate its application by the sector. The results from the application of the indicators show a great deal of wild biodiversity that uses grazing systems based on native grasslands as habitats and the acceptable integrity of these ecosystems. On average, farms have 83% of their native ecosystem, with a value of 3.5 for the Ecosystem Integrity Index. In terms of the ... Presentar Todo |
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Palabras claves : |
ÁREA DE RECURSOS NATURALES, PRODUCCIÓN Y AMBIENTE - INIA; BIODIVERSITY; GRASSLAND; LEAP guidelines; LIVESTOCK. |
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Asunto categoría : |
-- |
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URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/16907/1/sustainability-14-16259.pdf
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Marc : |
LEADER 03461naa a2200349 a 4500
001 1063823
005 2022-12-06
008 2022 bl uuuu u00u1 u #d
022 $aEISSN 2071-1050
024 7 $a10.3390/su142316259$2DOI
100 1 $aDE SANTIAGO, F.
245 $aFrom theory to practice$bcan LEAP/FAO biodiversity assessment guidelines be a useful tool for knowing the environmental status of livestock systems?$h[electronic resource]
260 $c2022
500 $aArticle history: Received 6 November 2022; Revised 29 November 2022; Accepted 29 November 2022; Published 6 December 2022. -- Academic Editor: Andrea Pezzuolo. -- LICENSE: Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
520 $aABSTRACT.- Biodiversity loss is a global concern, and agriculture is one of the economic sectors responsible for this impact. The assessment of ecosystems under the influence of livestock production is essential for knowing their integrity and ability to provide ecosystem services. The aim of this investigation was to evaluate the application of LEAP/FAO guidelines for quantitative assessment of biodiversity in the livestock sector at the local scale (farm level) in a group of six study cases in Uruguay. A set of 20 indicators was used, including seven key thematic issues: habitat protection, habitat change, wildlife conservation, invasive species, pollution, aquatic biodiversity, off-farm feed, and landscape-scale conservation. The results show that the LEAP biodiversity assessment guidelines can be useful to characterize the state of ecosystems under pastoral use and some specific components of their biodiversity, as well as assess the interaction of the production system with the environment and plan management accordingly. This work also provides an analysis of the methodology used and recommendations to facilitate its application by the sector. The results from the application of the indicators show a great deal of wild biodiversity that uses grazing systems based on native grasslands as habitats and the acceptable integrity of these ecosystems. On average, farms have 83% of their native ecosystem, with a value of 3.5 for the Ecosystem Integrity Index. In terms of the richness of different groups, there was an average number of species of 112 herbaceous plants, 48 woody plants, 48 spiders, 150 birds, and 14 fish. The main goal of this work is to help in the wider application of the guidelines by facilitating decisions about methodology, necessary resources, and technical support. Moreover, another goal is to show the importance of native grasslands-based livestock systems for biodiversity conservation. Copyright © 2022 by the authors.
653 $aÁREA DE RECURSOS NATURALES, PRODUCCIÓN Y AMBIENTE - INIA
653 $aBIODIVERSITY
653 $aGRASSLAND
653 $aLEAP guidelines
653 $aLIVESTOCK
700 1 $aBARRIOS, M.
700 1 $aD'ANATRO, A.
700 1 $aGARCÍA, L.F.
700 1 $aMAILHOS, A.
700 1 $aPOMPOZZI, G.
700 1 $aREHERMANN, S.
700 1 $aSIMÓ, M.
700 1 $aTESITORE, G.
700 1 $aDE MELLO, F.T.
700 1 $aVALTIERRA, V.
700 1 $aBLUMETTO, O.
773 $tSustainability, 2022, Volume 14, Issue 23, e16259. OPEN ACCESS. doi: https://doi.org/10.3390/su142316259
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