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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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INIA Treinta y Tres (TT) |
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Registro completo
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Biblioteca (s) : |
INIA La Estanzuela. |
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Fecha actual : |
27/11/2020 |
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Actualizado : |
27/11/2020 |
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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 : |
CASTELLS, M.; CAFFARENA, D.; CASAUX, M.L.; SCHILD, C.; CASTELLS, F.; CASTELLS, D.; VICTORIA , M.; RIET-CORREA, F.; GIANNITTI, F.; PARREÑO, V.; COLINA, R. |
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Afiliación : |
MATÍAS CASTELLS BAUER, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay./Matías Castells Laboratorio de Virología Molecular, CENUR Litoral Norte, Centro Universitario de Salto, Universidad de la República, Rivera 1350, 50000 Salto, Uruguay.; RUBEN DARÍO CAFFARENA LEDESMA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay./Facultad de Veterinaria, Universidad de la República, Alberto Lasplaces 1620, Montevideo, Uruguay.; MARÍA LAURA CASAUX, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; CARLOS SCHILD, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; FELIPE CASTELLS, Felipe Castells Doctor en Veterinaria en ejercicio libre, asociado al Laboratorio de Virología Molecular, CENUR Litoral Norte, Centro Universitario de Salto, Universidad de la República, Uruguay.; DANIEL CASTELLS, Centro de Investigación y Experimentación Dr. Alejandro Gallinal, Secretariado Uruguayo de la Lana, Ruta 7 km 140, Cerro Colorado, Florida, Uruguay.; MATÍAS VICTORIA, Laboratorio de Virología Molecular, CENUR Litoral Norte, Centro Universitario de Salto, Universidad de la República, Rivera 1350, 50000 Salto, Uruguay.; FRANKLIN RIET-CORREA AMARAL, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; FEDERICO GIANNITTI, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; VIVIANA PARREÑO, Sección de Virus Gastroentéricos, Instituto de Virología, CICV y A, INTA Castelar, Buenos Aires, Argentina.; RODNEY COLINA, Laboratorio de Virología Molecular, CENUR Litoral Norte, Centro Universitario de Salto, Universidad de la República, Rivera 1350, 50000 Salto, Uruguay. |
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Título : |
Detection, risk factors and molecular diversity of norovirus GIII in cattle in Uruguay. |
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Fecha de publicación : |
2020 |
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Fuente / Imprenta : |
Infection, Genetics and Evolution, December 2020, Volume 86, Article number 104613. Doi: https://doi.org/10.1016/j.meegid.2020.104613 |
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DOI : |
10.1016/j.meegid.2020.104613 |
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Idioma : |
Inglés |
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Notas : |
Article history: Received 1 August 2020 / Revised 27 October 2020 / Accepted 28 October 2020 / Available online 4 November 2020./ Corresponding authors at.: Laboratorio de Virología Molecular, CENUR Litoral Norte, Centro Universitario de Salto, Universidad de la República, Rivera, 1350,50000 Salto, Uruguay. |
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Contenido : |
Abstracts. Uruguay is a leading exporter of bovine meat and dairy products, and cattle production is one of the principal economic backbones in this country. A main clinical problem faced by livestock farmers is neonatal calf diarrhea (NCD); however, causes of NCD have not been extensively studied in Uruguay. Bovine norovirus (BoNoV) has been proposed as one of the possible etiologies of NCD as experimentally infected calves developed diarrhea and enteropathy, although limited information is available from field surveys. The aims of this study were to
determine the frequency of infection, to investigate possible risk factors, and to determine the molecular diversity of BoNoV in Uruguay. A total of 761 samples of feces or intestinal contents from dairy and beef calves were analyzed through RT-qPCR. The overall frequency of detection of BoNoV was 66.1% with higher frequency in dairy (70.5%) than beef (15.9%) calves (p < 0.01). BoNoV was detected similarly in diarrheic (78.8%) and non-diarrheic (76.2%) dairy calves (p = 0.50). Calves ?2 weeks of age (84%) were infected more often than older
(62.7%) calves (p < 0.01). Phylogenetic analysis confirmed the presence of GIII.1 and GIII.2 genotypes. In addition, we reported the circulation of recombinant strains and the detection of a strain with the recently described novel VP1 genotype. This study represents the first report describing the circulation, the associated risk factors, and the molecular diversity of BoNoV in Uruguay. |
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Palabras claves : |
BOVINE NOROVIRUS; CATTLE; DIARRHEA; GENOTYPES; PLATAFORMA DE SALUD ANIMAL. |
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Thesagro : |
GANADERIA; URUGUAY. |
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Asunto categoría : |
L73 Enfermedades de los animales |
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Marc : |
LEADER 02830naa a2200349 a 4500
001 1061525
005 2020-11-27
008 2020 bl uuuu u00u1 u #d
024 7 $a10.1016/j.meegid.2020.104613$2DOI
100 1 $aCASTELLS, M.
245 $aDetection, risk factors and molecular diversity of norovirus GIII in cattle in Uruguay.$h[electronic resource]
260 $c2020
500 $aArticle history: Received 1 August 2020 / Revised 27 October 2020 / Accepted 28 October 2020 / Available online 4 November 2020./ Corresponding authors at.: Laboratorio de Virología Molecular, CENUR Litoral Norte, Centro Universitario de Salto, Universidad de la República, Rivera, 1350,50000 Salto, Uruguay.
520 $aAbstracts. Uruguay is a leading exporter of bovine meat and dairy products, and cattle production is one of the principal economic backbones in this country. A main clinical problem faced by livestock farmers is neonatal calf diarrhea (NCD); however, causes of NCD have not been extensively studied in Uruguay. Bovine norovirus (BoNoV) has been proposed as one of the possible etiologies of NCD as experimentally infected calves developed diarrhea and enteropathy, although limited information is available from field surveys. The aims of this study were to determine the frequency of infection, to investigate possible risk factors, and to determine the molecular diversity of BoNoV in Uruguay. A total of 761 samples of feces or intestinal contents from dairy and beef calves were analyzed through RT-qPCR. The overall frequency of detection of BoNoV was 66.1% with higher frequency in dairy (70.5%) than beef (15.9%) calves (p < 0.01). BoNoV was detected similarly in diarrheic (78.8%) and non-diarrheic (76.2%) dairy calves (p = 0.50). Calves ?2 weeks of age (84%) were infected more often than older (62.7%) calves (p < 0.01). Phylogenetic analysis confirmed the presence of GIII.1 and GIII.2 genotypes. In addition, we reported the circulation of recombinant strains and the detection of a strain with the recently described novel VP1 genotype. This study represents the first report describing the circulation, the associated risk factors, and the molecular diversity of BoNoV in Uruguay.
650 $aGANADERIA
650 $aURUGUAY
653 $aBOVINE NOROVIRUS
653 $aCATTLE
653 $aDIARRHEA
653 $aGENOTYPES
653 $aPLATAFORMA DE SALUD ANIMAL
700 1 $aCAFFARENA, D.
700 1 $aCASAUX, M.L.
700 1 $aSCHILD, C.
700 1 $aCASTELLS, F.
700 1 $aCASTELLS, D.
700 1 $aVICTORIA , M.
700 1 $aRIET-CORREA, F.
700 1 $aGIANNITTI, F.
700 1 $aPARREÑO, V.
700 1 $aCOLINA, R.
773 $tInfection, Genetics and Evolution, December 2020, Volume 86, Article number 104613. Doi: https://doi.org/10.1016/j.meegid.2020.104613
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