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Registro completo
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Biblioteca (s) : |
INIA Las Brujas. |
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Fecha : |
24/04/2023 |
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Actualizado : |
09/05/2023 |
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Tipo de producción científica : |
Capítulo en Libro Técnico-Científico |
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Autor : |
QUIÑONES, A.; KASPARY, T. E.; GARCIA, A. |
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Afiliación : |
AMPARO QUIÑONES DELLEPIANE, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; TIAGO EDU KASPARY, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; MILTON ALEJANDRO GARCIA LATASA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
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Título : |
Malezas en sistemas ganaderos y agrícolas. (Capítulo 6). |
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Complemento del título : |
Primera sección: Transitando hacia la protección agroecológica de los cultivos. Editora: Carolina Leoni. |
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Fecha de publicación : |
2023 |
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Fuente / Imprenta : |
In: Georgina Paula García-Inza; José María Paruelo; Roberto Zoppolo. (eds). Aportes científicos y tecnológicos del Instituto Nacional de Investigación Agropecuaria (INIA) del Uruguay a las trayectorias agroecológicas. Ciudad Autónoma de Buenos Aires : Fundación CICCUS, 2023. p.107-128. |
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Páginas : |
p.107-128. |
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ISBN : |
978-987-693-926-3 |
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Idioma : |
Español |
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Contenido : |
Las malezas son plantas no deseadas que se desarrollan fuera de lugar e interfieren con las actividades o el bienestar humano (WSSA, 1956). ---- 1. Introducción. --
1.1. Contextualización de la problemática de malezas. -- 1.2. Las malezas y el uso de herbicidas en Uruguay. -- 2. Abordaje actual del manejo de malezas. -- 2.1. Sistemas ganaderos. -- 2.2. Sistemas agrícolas. -- 3. Tecnología propuesta. -- 3.1. Sistema ganadero. Manejo integrado de malezas. -- 3.2. Sistemas agrícolas. Uso de cultivos de cobertura y rolado en el manejo de malezas. -- 4. Mejoras a partir del uso/de la implementación de la tecnología propuesta. -- 4.1. Sistema ganadero. Efectos directos e indirectos del control de malezas. -- 4.2. Sistemas agrícolas. -- Densidad de siembra de avena negra y control de malezas. -- Rolado como método de terminación en avena negra. -- 5. Nuevas tecnologías y perspectivas. -- 5.1. Uso de Paspalum notatum INIA Sepé para el manejo de capín Annoni. -- 5.2. Aplicaciones de precisión para el manejo de malezas. -- |
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Thesagro : |
HERBICIDAS; MALEZAS; SISTEMAS DE PRODUCCIÓN. |
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Asunto categoría : |
F01 Cultivo |
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URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/17070/1/Capitulo6Malezasensistemasganaderosyagricolas.pdf
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Marc : |
LEADER 01854naa a2200205 a 4500
001 1064051
005 2023-05-09
008 2023 bl uuuu u00u1 u #d
020 $a978-987-693-926-3
100 1 $aQUIÑONES, A.
245 $aMalezas en sistemas ganaderos y agrícolas. (Capítulo 6).$h[electronic resource]
260 $c2023
300 $ap.107-128.
520 $aLas malezas son plantas no deseadas que se desarrollan fuera de lugar e interfieren con las actividades o el bienestar humano (WSSA, 1956). ---- 1. Introducción. -- 1.1. Contextualización de la problemática de malezas. -- 1.2. Las malezas y el uso de herbicidas en Uruguay. -- 2. Abordaje actual del manejo de malezas. -- 2.1. Sistemas ganaderos. -- 2.2. Sistemas agrícolas. -- 3. Tecnología propuesta. -- 3.1. Sistema ganadero. Manejo integrado de malezas. -- 3.2. Sistemas agrícolas. Uso de cultivos de cobertura y rolado en el manejo de malezas. -- 4. Mejoras a partir del uso/de la implementación de la tecnología propuesta. -- 4.1. Sistema ganadero. Efectos directos e indirectos del control de malezas. -- 4.2. Sistemas agrícolas. -- Densidad de siembra de avena negra y control de malezas. -- Rolado como método de terminación en avena negra. -- 5. Nuevas tecnologías y perspectivas. -- 5.1. Uso de Paspalum notatum INIA Sepé para el manejo de capín Annoni. -- 5.2. Aplicaciones de precisión para el manejo de malezas. --
650 $aHERBICIDAS
650 $aMALEZAS
650 $aSISTEMAS DE PRODUCCIÓN
700 1 $aKASPARY, T. E.
700 1 $aGARCIA, A.
773 $tIn: Georgina Paula García-Inza; José María Paruelo; Roberto Zoppolo. (eds). Aportes científicos y tecnológicos del Instituto Nacional de Investigación Agropecuaria (INIA) del Uruguay a las trayectorias agroecológicas. Ciudad Autónoma de Buenos Aires : Fundación CICCUS, 2023. p.107-128.
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Registro original : |
INIA Las Brujas (LB) |
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Biblioteca (s) : |
INIA La Estanzuela. |
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Fecha actual : |
18/03/2022 |
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Actualizado : |
02/09/2022 |
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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 : |
SILVA, P.; EVERS, B.; KIEFFABER, A.; WANG, X.; BROWN, R.; GAO, L.; FRITZ, A.; CRAIN, J.; POLAND, J. |
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Afiliación : |
MARIA PAULA SILVA VILLELLA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay./ Department of Plant Pathology, College of Agriculture, Kansas State University, Manhattan, USA.; BYRON EVERS, Department of Plant Pathology, College of Agriculture, Kansas State University, Manhattan, Kansas, USA.; ALEXANDRIA KIEFFABER, Department of Plant Pathology, College of Agriculture, Kansas State University, Manhattan, Kansas, USA.; XU WANG, Department of Agricultural and Biological Engineering, University of Florida, IFAS Gulf Coast , Research and Education Center, Wimauma, Florida,USA.; RICHARD BROWN, Department of Plant Pathology, College of Agriculture, Kansas State University, Manhattan, USA.; LIANGLIANG GAO, Department of Plant Pathology, College of Agriculture, Kansas State University, Manhattan, USA.; ALLAN FRITZ, Department of Agronomy, College of Agriculture, Kansas State University, Manhattan, Kansas, 66506, USA.; JARED CRAIN, Department of Plant Pathology, College of Agriculture, Kansas State University, Manhattan, Kansas, 66506, USA.; JESSE POLAND, Department of Plant Pathology, College of Agriculture, Kansas State University, Manhattan, Kansas, 66506, USA. |
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Título : |
Applied phenomics and genomics for improving barley yellow dwarf resistance in winter wheat. |
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Fecha de publicación : |
2022 |
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Fuente / Imprenta : |
G3 Genes| Genomes| Genetics, (Bethesda, Md.), 2022;, jkac064, Open Access. DOI:https://doi.org/10.1093/g3journal/jkac064 |
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DOI : |
10.1093/g3journal/jkac064 |
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Idioma : |
Inglés |
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Notas : |
Article history: Received: 22 December 2021/Accepted: 12 March 2022/Published: 30 March 2022.
The Author(s) (2022) . Published by Oxford University Press on behalf of the Genetics Society of America. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
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Contenido : |
Abstract:
Barley yellow dwarf (BYD) is one of the major viral diseases of cereals. Phenotyping BYD in wheat is extremely challenging due to similarities to other biotic and abiotic stresses. Breeding for resistance is additionally challenging as the wheat primary germplasm pool lacks genetic resistance, with most of the few resistance genes named to date originating from a wild relative species. The objectives of this study were to, i) evaluate the use of high-throughput phenotyping (HTP) from unmanned aerial systems to improve BYD assessment and selection, ii) identify genomic regions associated with BYD resistance, and iii) evaluate genomic prediction models ability to predict BYD resistance. Up to 107 wheat lines were phenotyped during each of five field seasons under both insecticide treated and untreated plots. Across all seasons, BYD severity was lower with the insecticide treatment and plant height (PTHTM) and grain yield (GY) showed increased values relative to untreated entries. Only 9.2% of the lines were positive for the presence of the translocated segment carrying resistance gene Bdv2 on chromosome 7DL. Despite the low frequency, this region was identified through association mapping. Furthermore, we mapped a potentially novel genomic region for resistance on chromosome 5AS. Given the variable heritability of the trait (0.211 ? 0.806), we obtained relatively good predictive ability for BYD severity ranging between 0.06 ? 0.26. Including Bdv2 on the predictive model had a large effect for predicting BYD but almost no effect for PTHTM and GY. This study was the first attempt to characterize BYD using field-HTP and apply GS to predict the disease severity. These methods have the potential to improve BYD characterization and identifying new sources of resistance will be crucial for delivering BYD resistant germplasm. MenosAbstract:
Barley yellow dwarf (BYD) is one of the major viral diseases of cereals. Phenotyping BYD in wheat is extremely challenging due to similarities to other biotic and abiotic stresses. Breeding for resistance is additionally challenging as the wheat primary germplasm pool lacks genetic resistance, with most of the few resistance genes named to date originating from a wild relative species. The objectives of this study were to, i) evaluate the use of high-throughput phenotyping (HTP) from unmanned aerial systems to improve BYD assessment and selection, ii) identify genomic regions associated with BYD resistance, and iii) evaluate genomic prediction models ability to predict BYD resistance. Up to 107 wheat lines were phenotyped during each of five field seasons under both insecticide treated and untreated plots. Across all seasons, BYD severity was lower with the insecticide treatment and plant height (PTHTM) and grain yield (GY) showed increased values relative to untreated entries. Only 9.2% of the lines were positive for the presence of the translocated segment carrying resistance gene Bdv2 on chromosome 7DL. Despite the low frequency, this region was identified through association mapping. Furthermore, we mapped a potentially novel genomic region for resistance on chromosome 5AS. Given the variable heritability of the trait (0.211 ? 0.806), we obtained relatively good predictive ability for BYD severity ranging between 0.06 ? 0.26. Including Bdv2 on the predictive mo... Presentar Todo |
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Palabras claves : |
Barley yellow dwarf (BYD); Genomic Selection (GS); High-throughput Phenotyping (HTP); Resistance; Tolerance; Triticum aestivum; Virus. |
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Asunto categoría : |
-- |
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URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/16662/1/Applied-phenomics-and-genomics-for-improving-barley-yellow-dwarf-resistance-in-winter.-2022.Silva.pdf
https://academic.oup.com/g3journal/article-pdf/12/7/jkac064/44473353/jkac064.pdf
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Marc : |
LEADER 03303naa a2200325 a 4500
001 1062870
005 2022-09-02
008 2022 bl uuuu u00u1 u #d
024 7 $a10.1093/g3journal/jkac064$2DOI
100 1 $aSILVA, P.
245 $aApplied phenomics and genomics for improving barley yellow dwarf resistance in winter wheat.$h[electronic resource]
260 $c2022
500 $aArticle history: Received: 22 December 2021/Accepted: 12 March 2022/Published: 30 March 2022. The Author(s) (2022) . Published by Oxford University Press on behalf of the Genetics Society of America. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
520 $aAbstract: Barley yellow dwarf (BYD) is one of the major viral diseases of cereals. Phenotyping BYD in wheat is extremely challenging due to similarities to other biotic and abiotic stresses. Breeding for resistance is additionally challenging as the wheat primary germplasm pool lacks genetic resistance, with most of the few resistance genes named to date originating from a wild relative species. The objectives of this study were to, i) evaluate the use of high-throughput phenotyping (HTP) from unmanned aerial systems to improve BYD assessment and selection, ii) identify genomic regions associated with BYD resistance, and iii) evaluate genomic prediction models ability to predict BYD resistance. Up to 107 wheat lines were phenotyped during each of five field seasons under both insecticide treated and untreated plots. Across all seasons, BYD severity was lower with the insecticide treatment and plant height (PTHTM) and grain yield (GY) showed increased values relative to untreated entries. Only 9.2% of the lines were positive for the presence of the translocated segment carrying resistance gene Bdv2 on chromosome 7DL. Despite the low frequency, this region was identified through association mapping. Furthermore, we mapped a potentially novel genomic region for resistance on chromosome 5AS. Given the variable heritability of the trait (0.211 ? 0.806), we obtained relatively good predictive ability for BYD severity ranging between 0.06 ? 0.26. Including Bdv2 on the predictive model had a large effect for predicting BYD but almost no effect for PTHTM and GY. This study was the first attempt to characterize BYD using field-HTP and apply GS to predict the disease severity. These methods have the potential to improve BYD characterization and identifying new sources of resistance will be crucial for delivering BYD resistant germplasm.
653 $aBarley yellow dwarf (BYD)
653 $aGenomic Selection (GS)
653 $aHigh-throughput Phenotyping (HTP)
653 $aResistance
653 $aTolerance
653 $aTriticum aestivum
653 $aVirus
700 1 $aEVERS, B.
700 1 $aKIEFFABER, A.
700 1 $aWANG, X.
700 1 $aBROWN, R.
700 1 $aGAO, L.
700 1 $aFRITZ, A.
700 1 $aCRAIN, J.
700 1 $aPOLAND, J.
773 $tG3 Genes| Genomes| Genetics, (Bethesda, Md.), 2022;, jkac064, Open Access. DOI:https://doi.org/10.1093/g3journal/jkac064
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