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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 : |
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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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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| Registros recuperados : 7 | |
| 1. |  | QUEZADA, M.; AMADEU, R. R.; VIGNALE, B.; CABRERA, D.; PRITSCH, C.; GARCIA, A. A. F. Construction of a high-density genetic map of Acca sellowiana (Berg.) Burret, an outcrossing species, based on two connected mapping populations. Original Research Article. Frontiers in Plant Science, 23 February 2021, Volume 12, Article number 626811. OPEN ACCESS. Doi: https://doi.org/10.3389/fpls.2021.626811 Article history: Received: 06 November 2020; Accepted: 12 January 2021; Published: 23 February 2021.
Edited by: Maria Luisa Badenes, Instituto Valenciano de Investigaciones Agrarias, Spain.
Reviewed by: Shouvik Das, Indian Agricultural...| Tipo: Artículos en Revistas Indexadas Internacionales | Circulación / Nivel : Internacional - -- |
| Biblioteca(s): INIA Las Brujas. |
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| 2. | | QUEZADA, M.; PRITSCH, C.; VIGNALE, B.; CABRERA, D.; GARCÍA, A.A.F. Primer reporte de la construcción de un mapa genético en Acca sellowiana (Berg.) Burret empleando genotyping by sequencing. MV 38 - COMUNICACIONES LIBRES - MV. MEJORAMIENTO VEGETAL In: JOURNAL OF BASIC & APPLIED GENETICS, 2016, Vol.27, Iss. 1 (Supp.). XVI LATIN AMERICAN CONGRESS OF GENETICS, IV CONGRESS OF THE URUGUAYAN SOCIETY OF GENETICS, XLIX ANNUAL MEETING OF THE GENETICS SOCIETY OF CHILE, XLV ARGENTINE CONGRESS OF GENETICS, 9-12 October 2016. PROCEEDINGS. Montevideo (Uruguay): SAG, 2016. p. 299| Tipo: Trabajos en Congresos/Conferencias |
| Biblioteca(s): INIA Las Brujas. |
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| 3. | | PRITSCH, C.; QUEZADA, M.; VAZQUEZ, S.; MAZZELLA, C.; VAIO, M.; VIGNALE, B.; CABRERA, D.; GARCÍA, A.A.F. Progresos en la caracterización del genoma de Acca sellowiana (Berg.) Burret. 1 - SIMPOSIOS "GENÉTICA Y GENÓMICA DE FRUTALES" In: JOURNAL OF BASIC & APPLIED GENETICS, 2016, Vol.27, Iss. 1 (Supp.). XVI LATIN AMERICAN CONGRESS OF GENETICS, IV CONGRESS OF THE URUGUAYAN SOCIETY OF GENETICS, XLIX ANNUAL MEETING OF THE GENETICS SOCIETY OF CHILE, XLV ARGENTINE CONGRESS OF GENETICS, 9-12 October 2016. PROCEEDINGS. Montevideo (Uruguay): SAG, 2016. p. 56-57| Tipo: Trabajos en Congresos/Conferencias |
| Biblioteca(s): INIA Las Brujas. |
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| 4. | | PRITSCH, C.; QUEZADA, M.; GARCÍA, A.A.F.; ÁLVAREZ, M.; MACHADO, G.; BERNAL, J.; CAZZULO, Y.; MALOSETTI, M.; ZÁCCARI, F.; RIVAS, M.; CABRERA, D.; VIGNALE, B. Caracterización genética del guayabo del país. [Presentación oral] In: UNIVERSIDAD DE LA REPÚBLICA (UDELAR)/ FACULTAD DE AGRONOMÍA; MGAP/ DGF (DIRECCIÓN GENERAL FORESTAL); INIA, PROGRAMA NACIONAL PRODUCCIÓN FRUTÍCOLA. 7° Encuentro Nacional sobre Frutos Nativos. Colonia: Estación Experimental "Alberto Boerger", INIA La Estanzuela, 9 y 10 de abril de 2015.| Tipo: Presentaciones Orales |
| Biblioteca(s): INIA Las Brujas. |
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| 5. | | PRITSCH, C.; QUEZADA, M.; GARCÍA, A.A.F.; ÁLVAREZ, M.; MACHADO, G.; BERNAL, J.; CAZZULLO, Y.; MALOSETTI, M.; ZÁCCARI, F.; RIVAS, M.; CABRERA, D.; VIGNALE, B. Caracterización genética del Guayabo del País. In: INIA (Instituto Nacional de Investigación Agropecuaria), Programa Nacional Producción Frutícola. 7° Encuentro Nacional sobre Frutos Nativos. Colonia (UY): INIA, 2015. p. 53-58 (INIA Serie Actividades de Difusión; 745)| Biblioteca(s): INIA Las Brujas. |
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| 6. | | QUEZADA, M.; PASTINA, M.M.; RAVEST, G.; SILVA, P.; VIGNALE, B.; CABRERA, D.; HINRICHSEN, P.; GARCÍA, A.A.F.; PRITSCH, C. A first genetic map of Acca sellowiana based on ISSR, AFLP and SSR markers. Scientia Horticulturae, 2014, v.169, no.2, p. 138-146. Article history: Received 13 May 2013 / Received in revised form 24 January 2014 / Accepted 12 February 2014 / Available online 14 March 2014.| Tipo: Artículos en Revistas Indexadas Internacionales | Circulación / Nivel : A - 2 |
| Biblioteca(s): INIA Las Brujas. |
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| 7. | | PRITSCH, C.; MAZZELLA, C.; QUEZADA, M.; DA CRUZ, I.; VÁZQUEZ, S.; GAIERO, P.; VAIO, M.; SILVA, P.; BACCINO, E.; LOMBARDO, P.; HINRICHSEN, P.; GARCIA, A.A.F.; CABRERA, D.; VIGNALE, B. Avances en estudios genómicos en guayabo del país (Acca sellowiana). In: INIA, Programa Nacional Investigación Producción Frutícola; Universidad de la República (UdelaR), Facultad de Agronomía; MGAP, DGF (Dirección General Forestal). Encuentro Nacional de Frutos Nativos, 6. Canelones (Uruguay): INIA, 2012. p.16-22 (INIA Serie Actividades de Difusión; 679)| Biblioteca(s): INIA Las Brujas; INIA Tacuarembó. |
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| Registros recuperados : 7 | |
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