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| Registros recuperados : 24 | |
| 5. |  | CASTELLS, D. Integrated parasite management strategies to control GIP (strategic control including nutrition, pasture rotation, anthelmintics, introduction to genetic selection, etc.). In: Regional Training Course on Genetics of Parasite Resistance in Sheep and Goats: Sampling, Data Collection, Management and Analyses, FAO/IAEA (International Atomic Energy Agency), December 5-9, 2016, Uruguay. 18 p.| Biblioteca(s): INIA Las Brujas. |
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| 9. | | CASTELLS, D.; MEDEROS, A.; LORENZELLI, E.; MACCHI, I. Diagnóstico de resistencia antihelmíntica de Haemonchus contortus a las ivermectinas en el Uruguay. SUL Producción Ovina, 2002, v. 15, p. 43-48 Este artículo fue publicado, también en: Castells Montes, D., coord. Resistencia genética del ovino y su aplicación en sistemas de control integrado de parásitos. Montevideo (Uruguay): FAO, 2003. p. 61-66.| Biblioteca(s): INIA Tacuarembó. |
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| 12. | | Bottaro, C.; Zavala, F.; Rabuffetti, A.; Castells, D.; Elizondo, J.; Marchesi, E. Efecto de la fertilización mineral NP en la producción estacional de pasturas naturales en algunos tipos de suelos : 1er año ln: Congreso Nacional de Producción Animal, 1 : 1973 abr : Paysandu Madalena, F.E. ; Rucks, C. ; Azzarini, M. (coord). [Memorias]. Paysandu (Uruguay): Facultad de Agronomía, 1973. p1-21| Biblioteca(s): INIA La Estanzuela. |
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| 13. | | GRASSO, A.; GOLDBERG, V.; IRIARTE, W.; GIMENO,D.; CASTELLS, D.; RINCON, G.; NAVAJAS, E.; CIAPPESONI, G. Nuevas herramientas moleculares para la selección en ovinos: ejemplo de caso resistencia a parásitos gastrointestinales ln: Jornada técnica, VI Jornada de agrobiotecnología. INIA Las Brujas, 20 de octubre de 2012 Conocimiento intensivo para el sector productivo: situación actual y perspectivas. Canelones (UY): INIA, 2012. 7-9 (Serie Actividades de Difusión; 698)| Biblioteca(s): INIA Las Brujas. |
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| 14. | | ESCRIBANO, C.; SARAVIA, A.; COSTA, M.; CASTELLS, D.; CIAPPESONI, G.; RIET-CORREA, F.; FREIRE, T. Resistance to Haemonchus contortus in Corriedale sheep is associated to high parasite-specific IgA titer and a systemic Th2 immune response. Scientific Reports, 1 December 2019, Volume 9, Issue 1, Article number 19579. OPEN ACCESS. Doi: https://doi.org/10.1038/s41598-019-55447-6 Article history: Received: 21 June 2019 / Accepted: 27 November 2019 / Published: 20 December 2019.
Funding information:
We acknowledge the personnel from Uruguayan Wool Secretariat that assisted with animal studies. This project was...| Biblioteca(s): INIA Las Brujas. |
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| 15. | | BIANCHI, G.; GARIBOTTO, G.; OLIVEIRA, G.; BENTANCUR, O.; CASARETTO, A.; CASTELLS, D.; PLATERO, M.; NIN, J.; MORROS, J. Cruzamientos terminales sobre ovejas Corriedale en el Uruguay, 1. Velocidad de crecimiento, grado de terminación y dimensiones del M. longissimus dorsi en corderos livianos y pesados. ITEA Producción Animal, 1999, v. 95A, no. 3, p. 234-247| Biblioteca(s): INIA Tacuarembó. |
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| 16. | | RODRIGUEZ, A.; CABRERA, P.; CIAPPESONI, C.; MONTOSSI, F.; CASTELLS, D.; MARTINO, P.; BONINO, J.; DE BARBIERI, I.; GIORELLO, D. Early detection of an artificial Haemonchus contortus infection in sheep using three different faecal occult blood tests In: World Buiatrics Congress, 26., Chile. 14-18 de Noviembre. 2010. Abstract| Biblioteca(s): INIA Tacuarembó. |
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| 17. | | FERREIRA, G.; DE BARBIERI, I.; CASTELLS, D.; NAVAJAS, E.; GIORELLO, D.; COSTA, J.T.C.; BANCHERO, G.; CIAPPESONI, G. Differences in growth between Corriedale sheep divergent lines for resistance to nematodes. In: Annual Meeting of the European Federation of Animal Science, 70., Ghent, Belgium, 26-30 August, 2019. Book of abstracts No. 25. p. 574| Biblioteca(s): INIA Tacuarembó. |
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| 18. | | FERREIRA, G.; CIAPPESONI, G.; CASTELLS, D.; AMARILHO-SILVEIRA, F.; NAVAJAS, E.; GIORELLO, D.; BANCHERO, G.; DE BARBIERI, I. Feed conversion efficiency in sheep genetically selected for resistance to gastrointestinal nematodes Animal Production Science, 2021, vol. 61(8), pages 754-760. OPEN ACCESS. doi: https://doi.org/10.1071/AN20121 Article history: Submitted: 24 March 2020 Accepted: 12 February 2021 Published online: 10 March 2021.| Biblioteca(s): INIA Tacuarembó. |
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| 19. | | FERREIRA, G.; CIAPPESONI, G.; CASTELLS, D.; BANCHERO, G.; AMARILHO, F.; NAVAJAS, E.; GIORELLO, D.; DE BARBIERI, I. La resiliencia y la eficiencia en conversión de alimento en la producción ovina. Revista INIA Uruguay, 2020, no. 60, p. 27-30. (Revista INIA; 60)| Biblioteca(s): INIA La Estanzuela; INIA Las Brujas. |
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| 20. | | CASTELLS, M.; GIANNITTI, F.; CAFFARENA, D.; CASAUX, M.L.; SCHILD, C.; CASTELLS, D.; RIET-CORREA, F.; VICTORIA, M.; PAREÑO, V.; COLINA, R. Bovine coronavirus in Uruguay: genetic diversity, risk factors and transboundary introductions from neighboring countries. Archives of Virology,2019 Nov, Vol. 164 (11), p. 2715-2724. DOI: https://10.1007/s00705-019-04384-w Article history:Received 26 June 2019/Accepted 30 July 2019/Published 27 August 2019.| Biblioteca(s): INIA La Estanzuela. |
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| Registros recuperados : 24 | |
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 | Acceso al texto completo restringido a Biblioteca INIA Treinta y Tres. Por información adicional contacte bibliott@inia.org.uy. |
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Registro completo
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Biblioteca (s) : |
INIA Treinta y Tres. |
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Fecha actual : |
16/10/2018 |
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Actualizado : |
11/02/2019 |
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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 : |
BORGES, A.; GONZÁLEZ-REYMUNDEZ, A.; ERNST, O.; CADENAZZI, M.; TERRA, J.A.; GUTIÉRREZ, L. |
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Afiliación : |
ALEJANDRA BORGES, Departamento de Estadística. Facultad de Agronomía, UdelaR.; AGUSTÍN GONZÁLEZ-REYMUNDEZ, Departamento de Estadística. Facultad de Agronomía, UdelaR.; OSVALDO, ERNST, Departamento de Producción de Cultivos. EEMAC, Facultad de Agronomía, UdelaR.; MÓNICA CADENAZZI, Departamento de Estadística. Facultad de Agronomía, UdelaR.; JOSÉ ALFREDO TERRA FERNÁNDEZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; LUCÍA GUTIÉRREZ, Department of Agronomy, University of Wisconsin. |
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Título : |
Can spatial modeling substitute experimental design in agricultural experiments? |
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Fecha de publicación : |
2018 |
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Fuente / Imprenta : |
Crop Science, 2018, v. 59, no. 1, p. 1-10. |
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DOI : |
10.2135/cropsci2018.03.0177 |
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Idioma : |
Inglés |
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Notas : |
Article history: Accepted paper, posted 10/05/18. Published online December, 13. 2018. |
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Contenido : |
Abstract:
One of the most critical aspects of agricultural experimentation is the proper choice of experimental design to control field heterogeneity, especially for large experiments. However, even with complex experimental designs, spatial variability may not be properly controlled if it occurs at scales smaller than blocks. Therefore, modeling spatial variability can be beneficial and some studies even propose spatial modeling instead of experimental design. Our goal was to evaluate the effect of experimental design, spatial modeling, and a combination of both under real field conditions using GIS and simulating experiments. Yield data from cultivars was simulated using real spatial variability from a large uniformity trial of one hundred independent locations and different sizes of experiments for four experimental designs: completely randomized design (CRD), randomized complete block design (RCBD), alpha-lattice incomplete block design (ALPHA), and partially replicated design (PREP). Each realization was analyzed using different levels of spatial correction. Models were compared by precision, accuracy, and the recovery of superior genotypes. For moderate and large experiment sizes, ALPHA was the best experimental design in terms of precision and accuracy. In most situations, models that included spatial correlation were better than models with no spatial correlation but they did not outperformed better experimental designs. Therefore, spatial modeling is not a substitute for good experimental design. MenosAbstract:
One of the most critical aspects of agricultural experimentation is the proper choice of experimental design to control field heterogeneity, especially for large experiments. However, even with complex experimental designs, spatial variability may not be properly controlled if it occurs at scales smaller than blocks. Therefore, modeling spatial variability can be beneficial and some studies even propose spatial modeling instead of experimental design. Our goal was to evaluate the effect of experimental design, spatial modeling, and a combination of both under real field conditions using GIS and simulating experiments. Yield data from cultivars was simulated using real spatial variability from a large uniformity trial of one hundred independent locations and different sizes of experiments for four experimental designs: completely randomized design (CRD), randomized complete block design (RCBD), alpha-lattice incomplete block design (ALPHA), and partially replicated design (PREP). Each realization was analyzed using different levels of spatial correction. Models were compared by precision, accuracy, and the recovery of superior genotypes. For moderate and large experiment sizes, ALPHA was the best experimental design in terms of precision and accuracy. In most situations, models that included spatial correlation were better than models with no spatial correlation but they did not outperformed better experimental designs. Therefore, spatial modeling is not a substitut... Presentar Todo |
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Palabras claves : |
EFFICIENCY STATISTICS; EXPERIMENTAL DESIGN; FIELD VARIABILITY; SPATIAL MODELS; UNIFORMITY TRIAL. |
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Thesagro : |
DISENO ESTADISTICO; DISENO EXPERIMENTAL; MODELOS ESTADISTICOS; VARIABILIDAD. |
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Asunto categoría : |
U30 Métodos de investigación |
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Marc : |
LEADER 02512naa a2200313 a 4500
001 1059193
005 2019-02-11
008 2018 bl uuuu u00u1 u #d
024 7 $a10.2135/cropsci2018.03.0177$2DOI
100 1 $aBORGES, A.
245 $aCan spatial modeling substitute experimental design in agricultural experiments?$h[electronic resource]
260 $c2018
500 $aArticle history: Accepted paper, posted 10/05/18. Published online December, 13. 2018.
520 $aAbstract: One of the most critical aspects of agricultural experimentation is the proper choice of experimental design to control field heterogeneity, especially for large experiments. However, even with complex experimental designs, spatial variability may not be properly controlled if it occurs at scales smaller than blocks. Therefore, modeling spatial variability can be beneficial and some studies even propose spatial modeling instead of experimental design. Our goal was to evaluate the effect of experimental design, spatial modeling, and a combination of both under real field conditions using GIS and simulating experiments. Yield data from cultivars was simulated using real spatial variability from a large uniformity trial of one hundred independent locations and different sizes of experiments for four experimental designs: completely randomized design (CRD), randomized complete block design (RCBD), alpha-lattice incomplete block design (ALPHA), and partially replicated design (PREP). Each realization was analyzed using different levels of spatial correction. Models were compared by precision, accuracy, and the recovery of superior genotypes. For moderate and large experiment sizes, ALPHA was the best experimental design in terms of precision and accuracy. In most situations, models that included spatial correlation were better than models with no spatial correlation but they did not outperformed better experimental designs. Therefore, spatial modeling is not a substitute for good experimental design.
650 $aDISENO ESTADISTICO
650 $aDISENO EXPERIMENTAL
650 $aMODELOS ESTADISTICOS
650 $aVARIABILIDAD
653 $aEFFICIENCY STATISTICS
653 $aEXPERIMENTAL DESIGN
653 $aFIELD VARIABILITY
653 $aSPATIAL MODELS
653 $aUNIFORMITY TRIAL
700 1 $aGONZÁLEZ-REYMUNDEZ, A.
700 1 $aERNST, O.
700 1 $aCADENAZZI, M.
700 1 $aTERRA, J.A.
700 1 $aGUTIÉRREZ, L.
773 $tCrop Science, 2018$gv. 59, no. 1, p. 1-10.
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