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| Registros recuperados : 34 | |
| 6. |  | BERRUETA, C.; GIMÉNEZ, G.; GALVÁN, G.; BORGES, A. New sources of partial resistance to bacterial spot race T2 in processing tomatoes. [Novas fontes de resistência parcial à mancha bacteriana raça T2 de tomate para processamento.] Horticultura Brasileira, 2016, v. 34, no. 3, p.326-332. Article history: Received on March 16, 2015 / Accepted on February 10, 2016.| Biblioteca(s): INIA Las Brujas. |
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| 9. | | BORGES, A.; GONZÁLEZ-REYMUNDEZ, A.; ERNST, O.; CADENAZZI, M.; TERRA, J.A.; GUTIÉRREZ, L. Can spatial modeling substitute experimental design in agricultural experiments? Crop Science, 2018, v. 59, no. 1, p. 1-10. Article history: Accepted paper, posted 10/05/18. Published online December, 13. 2018.| Biblioteca(s): INIA Treinta y Tres. |
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| 10. | | GUTIERREZ, L.; BORGES, A.; QUERO, G.; GONZALEZ-REYMUNDEZ, A.; BERRO, I.; LADO, B.; CASTRO, A. Biostatistical tools for plant breeding in the genomics era. In: German, S.; Quincke, M.; Vázquez, D.; Castro, M.; Pereyra, S.; Silva, P.; García, A. (Eds.). Seminario Internacional "1914-2014: Un siglo de mejoramiento de trigo en La Estanzuela". Montevideo (UY): INIA, 2018. p.46-57. (INIA Serie Técnica; 241).| Biblioteca(s): INIA La Estanzuela. |
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| 11. | | Borges, A.; Da Cunha Barros, M.; Pardo, E.; García, M.; Franco, J.; Gravina, A. Cuajado de frutos en tangor Ortanique en respuesta a la polinización y a distintas situaciones de estrés ambiental Agrociencia, 2009, v. 13, no. 1, p. 7-18| Biblioteca(s): INIA Tacuarembó. |
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| 12. | | VALLE, D.; MUJICA, V.; SILVERA, M.; BORGES, A.; ZOPPOLO, R.; MORELLI, E. Effect of the ground cover management on Cacopsylla bidens (Sulc, 1907) populations in pear orchards. [abstract of poster]. In: Zoppolo, R. Cabrera, D. (Eds.). Growing in diversity. Proceedings of the International Pear Symposium, 13, Dec. 4-7th 2018, Montevideo, Uruguay. p. 119.| Biblioteca(s): INIA Las Brujas. |
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| 13. | | VALLE, D.; MUJICA, V.; SILVERA, M.; BORGES, A.; ZOPPOLO, R.; MORELLI, E. Effect of the ground cover management on Cacopsylla bidens (Sulc, 1907) populations in pear orchards. [Conference paper]. Acta Horticulturae, February 2021, N°1303, p. 375-380. DOI: https://doi.org/10.17660/ActaHortic.2021.1303.52 Article history: Published 5 February 2021. In: Acta Horticulturae (ISHS) 1303: XIII International Pear Symposium, Montevideo, Uruguay. Conveners: Roberto Zoppolo, Danilo Cabrera. Editors: Roberto Zoppolo, Danilo Cabrera, D. Granatstein.| Biblioteca(s): INIA Las Brujas. |
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| 14. | | SCARLATO, M.; DOGLIOTTI, S.; BERRUETA, C.; BARROS, C.; REHERMAN, F.; BORGES, A.; GARCÍA, M.; GIMÉNEZ, G. Explaining yield variability between farmers as a first step to reduce gaps. T3. Crop modeling and yield gap analysis for agricultural systems analysis and design. In: Proceedings of the 5th international symposium for farming systems design. Multi-functional farming systems in a changing world. Montpellier (Francia): European Society of Agronomy, 2015. p. 119-122 Acknowledgements. Without the help of all the farmers that gently contributed their time and fields, and the help of the technical advisers and experts
to select a representative sample of farms, this research would have not be possible,...| Biblioteca(s): INIA Las Brujas. |
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| 15. | | BORGES, A.; GONZÁLEZ-REYMÚNDEZ, A.; ERNST, O.; CADENAZZI, M.; TERRA, J.A.; GUTIÉRREZ, LUCÍA Modelación espacial y diseños experimentales en experimentos agrícolas. In: UNIVERSIDAD DE LA REPÚBLICA (UDELAR). FACULTAD DE AGRONOMÍA. Resúmenes. Jornadas de Investigación, 8-9 nov., 2018, Montevideo, Uruguay. Montevideo; FAGRO, 2019. p. 15| Biblioteca(s): INIA Treinta y Tres. |
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| 17. | | Gambetta, G.; Borges, A.; Espino, M.; Da Cunha Barros, M.; Rivas, F.; Arbiza, H.; Gravina, A. Mejora de la productividad de la mandarina Nova: aspectos fisiológicos y medidas de manejo Agrociencia, 2008, v. 12, no. 2, p. 1-9| Biblioteca(s): INIA Tacuarembó. |
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| 18. | | GONZÁLEZ-ARCOS, M.; GALVÁN, G.; SIRI, M.I.; BORGES, A.; VILARÓ, F. Resistance to bacterial wilt in Solanum commersonii Dun. [Resistencia a la marchitez bacteriana de la papa en Solanum commersonii Dun.]. [Special Issue 25 Years Agrociencia]. Plant Biology. Agrociencia Uruguay, 2022, vol. 26, NE2, e1092. doi: https://doi.org/10.31285/AGRO.26.1092 -- OPEN ACCESS. Article history: Article originally published in: Agrociencia (Uruguay). 2013;17(1):45-54. doi: https://doi.org/10.31285/AGRO.17.513 -- Correspondence: Matías González, matgon@inia.org.uy -- Special Issue 25 Years Agrociencia. --...| Biblioteca(s): INIA Las Brujas. |
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| 20. | | PELUFFO, S.; GONZÁLEZ IDIARTE, H.; BORGES, A.; GALVÁN, G.A.; ARBOLEYA, J. Producción de semilla de cebolla (Allium cepa L.) mediante el método semilla-bulbillo-semilla para tres cultivares de Uruguay (Abs.11, Sección: Mejoramiento genético, cultivares y Producción de semillas de hortalizas). IN: CONGRESO NACIONAL DE HORTI-FRUTICULTURA, 13. AÑO DE LA AGRICULTURA FAMILIAR DE LA FAO. "SOSTENIBILIDAD DE LA PRODUCCIÓN HORTIFRUTÍCOLA FAMILAR". 3-6 SETIEMBRE 2014, MONTEVIDEO (UY). Trabajos presentados. Montevideo (UY): INIA; SUHF, 2014. p.27| Biblioteca(s): INIA Las Brujas. |
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| Registros recuperados : 34 | |
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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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