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Biblioteca (s) : |
INIA Treinta y Tres. |
Fecha : |
16/10/2018 |
Actualizado : |
11/02/2019 |
Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
Autor : |
BORGES, A.; GONZÁLEZ-REYMUNDEZ, A.; ERNST, O.; CADENAZZI, M.; TERRA, J.A.; GUTIÉRREZ, L. |
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. |
Título : |
Can spatial modeling substitute experimental design in agricultural experiments? |
Fecha de publicación : |
2018 |
Fuente / Imprenta : |
Crop Science, 2018, v. 59, no. 1, p. 1-10. |
DOI : |
10.2135/cropsci2018.03.0177 |
Idioma : |
Inglés |
Notas : |
Article history: Accepted paper, posted 10/05/18. Published online December, 13. 2018. |
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 |
Palabras claves : |
EFFICIENCY STATISTICS; EXPERIMENTAL DESIGN; FIELD VARIABILITY; SPATIAL MODELS; UNIFORMITY TRIAL. |
Thesagro : |
DISENO ESTADISTICO; DISENO EXPERIMENTAL; MODELOS ESTADISTICOS; VARIABILIDAD. |
Asunto categoría : |
U30 Métodos de investigación |
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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INIA Treinta y Tres (TT) |
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Biblioteca (s) : |
INIA Tacuarembó. |
Fecha actual : |
21/02/2014 |
Actualizado : |
07/10/2016 |
Autor : |
MORON, A.; QUINCKE, A.; CUADRO, R.; GIORELLO, D.; BERMÚDEZ, R.; PRAVIA, V. |
Afiliación : |
DAVID ALEJANDRO MORON YACOEL, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; JUAN ANDRES QUINCKE WALDEN, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; WASHINGTON ROBIN CUADRO LOPEZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; DIEGO GERMAN GIORELLO LEITES, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; RAÚL ENRIQUE BERMÚDEZ COQUARD, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; MARIA VIRGINIA PRAVIA NIN, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
Título : |
Red de fertilización de pasturas (2008-2011). |
Fecha de publicación : |
2011 |
Fuente / Imprenta : |
In: GIRA NACIONAL DE PASTURAS, 1-13 DE OCTUBRE, INIA TREINTA Y TRES; INIA TACUAREMBÓ; INIA LA ESTANZUELA, 2011. Montevideo: INIA, 2011. |
Páginas : |
p. 1-24 |
Idioma : |
Español |
Contenido : |
En el marco del proyecto de Manejo Agronómico de Pasturas, desde el año 2008 el INIA está conduciendo una Red de Experimentos de Fertiilzación de Pasturas. El objetivo general es seleccionar y calibrar métodos de análisis de fósforo en suelo y en planta para viabilizar una nueva guía de fertilización de pasturas que pueda comprender la amplia diversidad de suelos del país. Durante lo tres días de la presente gira se visitarán 3 de los 14 sitios que están instalados: Rincón de Ramírez, Sauce del Cañote y Florida. A continuación se presentan algunos detalles adicionales de esta red de fertilización de pasturas. |
Thesagro : |
FORRAJES; PASTURAS. |
Asunto categoría : |
P30 Ciencia del suelo y manejo del suelo |
Marc : |
LEADER 01251naa a2200217 a 4500 001 1020800 005 2016-10-07 008 2011 bl uuuu u00u1 u #d 100 1 $aMORON, A. 245 $aRed de fertilización de pasturas (2008-2011). 260 $c2011 300 $ap. 1-24 520 $aEn el marco del proyecto de Manejo Agronómico de Pasturas, desde el año 2008 el INIA está conduciendo una Red de Experimentos de Fertiilzación de Pasturas. El objetivo general es seleccionar y calibrar métodos de análisis de fósforo en suelo y en planta para viabilizar una nueva guía de fertilización de pasturas que pueda comprender la amplia diversidad de suelos del país. Durante lo tres días de la presente gira se visitarán 3 de los 14 sitios que están instalados: Rincón de Ramírez, Sauce del Cañote y Florida. A continuación se presentan algunos detalles adicionales de esta red de fertilización de pasturas. 650 $aFORRAJES 650 $aPASTURAS 700 1 $aQUINCKE, A. 700 1 $aCUADRO, R. 700 1 $aGIORELLO, D. 700 1 $aBERMÚDEZ, R. 700 1 $aPRAVIA, V. 773 $tIn: GIRA NACIONAL DE PASTURAS, 1-13 DE OCTUBRE, INIA TREINTA Y TRES; INIA TACUAREMBÓ; INIA LA ESTANZUELA, 2011. Montevideo: INIA, 2011.
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