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Registro completo
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Biblioteca (s) : |
INIA La Estanzuela; INIA Treinta y Tres. |
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Fecha : |
21/02/2014 |
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Actualizado : |
24/10/2022 |
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Autor : |
MELGAR, R.; VITTI, G.; BENITES, V.M. |
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Afiliación : |
Instito Internacional de la Potasa; Instito Internacional de la Potasa; Instito Internacional de la Potasa. |
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Título : |
Soja en Latinoamérica : fertilizando para altos rendimientos. |
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Fecha de publicación : |
2011 |
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Fuente / Imprenta : |
Horgen: Instituto Internacional de la Potasa, 2011. |
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Páginas : |
81 p. |
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Serie : |
IIP Boletín ; 20 |
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ISBN : |
978-3-9523243-7-0 |
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Idioma : |
Español |
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Notas : |
Donación |
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Palabras claves : |
CONDICIONES CLIMÁTICAS DE LA SOJA; CONDICIONES EDÁFICAS DE LA SOJA; FERTILIZACIÓN Y MANAEJO DEL SUELO; IMOPORTANCIA ECONÓMICA Y AGRICOLA DE LA SOJA; NUTRIENTES MINERALES. |
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Thesagro : |
AMERICA LATINA; APLICACION DE ABONOS; CLIMA; GLYCINE MAX; NUTRICION DE LAS PLANTAS; SOJA; SUELO; VALOR ECONOMICO. |
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Asunto categoría : |
F01 Cultivo
F04 Fertilización |
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Marc : |
LEADER 00950nam a2200325 a 4500
001 1040981
005 2022-10-24
008 2011 bl uuuu u00u1 u #d
020 $a978-3-9523243-7-0
100 1 $aMELGAR, R.
245 $aSoja en Latinoamérica$bfertilizando para altos rendimientos.
260 $aHorgen: Instituto Internacional de la Potasa$c2011
300 $a81 p.
490 $aIIP Boletín ; 20
500 $aDonación
650 $aAMERICA LATINA
650 $aAPLICACION DE ABONOS
650 $aCLIMA
650 $aGLYCINE MAX
650 $aNUTRICION DE LAS PLANTAS
650 $aSOJA
650 $aSUELO
650 $aVALOR ECONOMICO
653 $aCONDICIONES CLIMÁTICAS DE LA SOJA
653 $aCONDICIONES EDÁFICAS DE LA SOJA
653 $aFERTILIZACIÓN Y MANAEJO DEL SUELO
653 $aIMOPORTANCIA ECONÓMICA Y AGRICOLA DE LA SOJA
653 $aNUTRIENTES MINERALES
700 1 $aVITTI, G.
700 1 $aBENITES, V.M.
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Registro original : |
INIA La Estanzuela (LE) |
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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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INIA Treinta y Tres (TT) |
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