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Registro completo
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Biblioteca (s) : |
INIA La Estanzuela. |
Fecha : |
09/09/2020 |
Actualizado : |
05/09/2022 |
Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
Autor : |
RAEGAN HOEFLER; GONZALEZ-BARRIOS , P.; MADHAV BHATTA; NUNES, J.A.R.; BERRO, I.; NALIN, R.S.; BORGES, A.; COVARRUBIAS, E.; DIAZ-GARCIA, L.; QUINCKE, M.; GUTIERREZ, L. |
Afiliación : |
HOEFLER, R., Department of Agronomy, University of Wisconsin?Madison, 1575 Linden Dr., Madison, WI, 53706, USA.; PABLO GONZALEZ-BARRIOS, Dpartment of Agronomy, University of Wisconsin?Madison, 1575 Linden Dr., Madison, WI, 53706, USA.; BHATTA, M., Department of Agronomy, University of Wisconsin?Madison, 1575 Linden Dr., Madison, WI, 53706, USA.; JOSE A. R. NUNES, Department of Agronomy, University of Wisconsin?Madison, 1575 Linden Dr., Madison, WI, 53706, USA.; INES BERRO, Department of Agronomy, University of Wisconsin–Madison, 1575 Linden Dr., Madison, WI, 53706, USA; RAFAEL S. NALIN, Department of Genetics, Escola Superior de Agricultura “Luiz de Queiroz”, Universidade de São Paulo, Piracicaba, São Paulo, 131418-900, Brazil.; ALEJANDRA BORGES, Statistics Department, Facultad de Agronomía, Univesidad de la República, Garzón 780, Montevideo, Uruguay.; EDUARDO COVARRUBIAS, CGIAR Excellence in Breeding Platform (EiB), El Batan, Mexico International Maize and Wheat Improvement Center (CIMMYT), El Batan, Mexico.; LUIS DIAZ-GARCIA, Instituto Nacional de Investigaciones Forestales, Agricolas y Pecuarias, 20676, Aguascalientes, Mexico.; MARTIN CONRADO QUINCKE WALDEN, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; LUCIA GUTIERREZ, Department of Agronomy, University of Wisconsin–Madison, 1575 Linden Dr., Madison, WI, 53706, USA. |
Título : |
Do Spatial Designs Outperform Classic Experimental Designs?. |
Fecha de publicación : |
2020 |
Fuente / Imprenta : |
Journal of Agricultural, Biological, and Environmental Statistics, 1 December 2020, volume 25, number 4, pag.523-552, 1 December 2020. OPEN ACCESS. Doi: https://doi.org/10.1007/s13253-020-00406-2 |
DOI : |
10.1007/s13253-020-00406-2 |
Idioma : |
Inglés |
Notas : |
Article history: Received 15 October 2019/Accepted 01 July 2020/Published 29 August 2020. This project was partially funded through a USDA_AFRI_NIFA_2018-67013-27620 award and by the Hatch Act Formula Fund WISO1984 and WIS03002. Additionally, JARN received funding from CAPES CAPES_PrInt_UFLA 88887.318846_2019-00 as Senior Visiting Professor at the University of Wisconsin-Madison. |
Contenido : |
Controlling spatial variation in agricultural field trials is the most important step to compare treatments efficiently and accurately. Spatial variability can be controlled at the experimental design level with the assignment of treatments to experimental units and at the modeling level with the use of spatial corrections and other modeling strategies. The goal of this study was to compare the efficiency of methods used to control spatial variation in a wide range of scenarios using a simulation approach based on real wheat data. Specifically, classic and spatial experimental designs with and without a twodimensional autoregressive spatial correction were evaluated in scenarios that include differing experimental unit sizes, experiment sizes, relationships among genotypes, genotype by environment interaction levels, and trait heritabilities. Fully replicated designs outperformed partially and unreplicated designs in terms of accuracy; the alpha-lattice incomplete block design was best in all scenarios of the medium-sized experiments.
However, in terms of response to selection, partially replicated experiments that evaluate large population sizes were superior in most scenarios. The AR1×AR1 spatial correction had little benefit in most scenarios except for the medium-sized experiments with the largest experimental unit size and low GE. Overall, the results from this study provide a guide to researchers designing and analyzing large field experiments. Supplementary materials accompanying this paper appear online. MenosControlling spatial variation in agricultural field trials is the most important step to compare treatments efficiently and accurately. Spatial variability can be controlled at the experimental design level with the assignment of treatments to experimental units and at the modeling level with the use of spatial corrections and other modeling strategies. The goal of this study was to compare the efficiency of methods used to control spatial variation in a wide range of scenarios using a simulation approach based on real wheat data. Specifically, classic and spatial experimental designs with and without a twodimensional autoregressive spatial correction were evaluated in scenarios that include differing experimental unit sizes, experiment sizes, relationships among genotypes, genotype by environment interaction levels, and trait heritabilities. Fully replicated designs outperformed partially and unreplicated designs in terms of accuracy; the alpha-lattice incomplete block design was best in all scenarios of the medium-sized experiments.
However, in terms of response to selection, partially replicated experiments that evaluate large population sizes were superior in most scenarios. The AR1×AR1 spatial correction had little benefit in most scenarios except for the medium-sized experiments with the largest experimental unit size and low GE. Overall, the results from this study provide a guide to researchers designing and analyzing large field experiments. Supplementary materials ... Presentar Todo |
Palabras claves : |
AUTOREGRESSIVE PROCESS; EXPERIMENTAL DESIGN; PREDICTION ACCURACY; RANDOMIZATION-BASED EXPERIMENTAL DESIGNS; RESPONSE TO SELECTION; SPATIAL CORRECTION. |
Thesagro : |
DISENO EXPERIMENTAL. |
Asunto categoría : |
-- |
URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/16700/1/JABES-2020.pdf
https://link.springer.com/content/pdf/10.1007/s13253-020-00406-2.pdf
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Marc : |
LEADER 03067naa a2200349 a 4500 001 1061304 005 2022-09-05 008 2020 bl uuuu u00u1 u #d 024 7 $a10.1007/s13253-020-00406-2$2DOI 100 1 $aRAEGAN HOEFLER 245 $aDo Spatial Designs Outperform Classic Experimental Designs?.$h[electronic resource] 260 $c2020 500 $aArticle history: Received 15 October 2019/Accepted 01 July 2020/Published 29 August 2020. This project was partially funded through a USDA_AFRI_NIFA_2018-67013-27620 award and by the Hatch Act Formula Fund WISO1984 and WIS03002. Additionally, JARN received funding from CAPES CAPES_PrInt_UFLA 88887.318846_2019-00 as Senior Visiting Professor at the University of Wisconsin-Madison. 520 $aControlling spatial variation in agricultural field trials is the most important step to compare treatments efficiently and accurately. Spatial variability can be controlled at the experimental design level with the assignment of treatments to experimental units and at the modeling level with the use of spatial corrections and other modeling strategies. The goal of this study was to compare the efficiency of methods used to control spatial variation in a wide range of scenarios using a simulation approach based on real wheat data. Specifically, classic and spatial experimental designs with and without a twodimensional autoregressive spatial correction were evaluated in scenarios that include differing experimental unit sizes, experiment sizes, relationships among genotypes, genotype by environment interaction levels, and trait heritabilities. Fully replicated designs outperformed partially and unreplicated designs in terms of accuracy; the alpha-lattice incomplete block design was best in all scenarios of the medium-sized experiments. However, in terms of response to selection, partially replicated experiments that evaluate large population sizes were superior in most scenarios. The AR1×AR1 spatial correction had little benefit in most scenarios except for the medium-sized experiments with the largest experimental unit size and low GE. Overall, the results from this study provide a guide to researchers designing and analyzing large field experiments. Supplementary materials accompanying this paper appear online. 650 $aDISENO EXPERIMENTAL 653 $aAUTOREGRESSIVE PROCESS 653 $aEXPERIMENTAL DESIGN 653 $aPREDICTION ACCURACY 653 $aRANDOMIZATION-BASED EXPERIMENTAL DESIGNS 653 $aRESPONSE TO SELECTION 653 $aSPATIAL CORRECTION 700 1 $aGONZALEZ-BARRIOS , P. 700 1 $aMADHAV BHATTA 700 1 $aNUNES, J.A.R. 700 1 $aBERRO, I. 700 1 $aNALIN, R.S. 700 1 $aBORGES, A. 700 1 $aCOVARRUBIAS, E. 700 1 $aDIAZ-GARCIA, L. 700 1 $aQUINCKE, M. 700 1 $aGUTIERREZ, L. 773 $tJournal of Agricultural, Biological, and Environmental Statistics, 1 December 2020, volume 25, number 4, pag.523-552, 1 December 2020. OPEN ACCESS. Doi: https://doi.org/10.1007/s13253-020-00406-2
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Registro original : |
INIA La Estanzuela (LE) |
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Biblioteca (s) : |
INIA Treinta y Tres. |
Fecha actual : |
10/05/2019 |
Actualizado : |
10/05/2019 |
Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
Circulación / Nivel : |
-- - -- |
Autor : |
BAO, L.; CASTIGLIONI, E.; MARTÍNEZ, S.; SAVARIS, M.; MARINONI, L. |
Afiliación : |
LETICIA BAO, Universidad de la República, Facultad de Agronomía, Departamento de Protección Vegetal, Unidad de Entomología, UY.; ENRIQUE CASTIGLIONI, Centro Universitario Regional del Este, Universidad de la República. Rocha, UY.; SEBASTIÁN MARTÍNEZ KOPP, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; MARCOANDRE SAVARIS, Escola Superior de Agricultura "Luiz de Queiroz" ESALQ-USP, Departamento de Entomología e Acarología - LEA, BR.; LUCIANE MARINONI, Universidade Federal do Paraná, Setor de Ciencias Biológicas, Departamento de Zoología, Programa de Pos-Graduacao em Entomologia, Curitiba, PR, Brasil. |
Título : |
First records of Sepedonea lindneri (Hendel, 1932) and Protodictya lilloana Steyskal, 1953 (Diptera, Sciomyzidae) from Uruguay with an overview on their biology. |
Fecha de publicación : |
2019 |
Fuente / Imprenta : |
Check List, Jannuary 2019, 15(1), p. 71-77. |
ISSN : |
1809127X |
DOI : |
10.15560/15.1.71 |
Idioma : |
Inglés |
Notas : |
Article history: Received 26 September 2018. Accepted 19 December 2018. Published 25 January 2019. |
Contenido : |
Sciomyzidae (Diptera) has been recorded in several countries of South America, but few species have been found in Uruguay. We report the first record of Sepedonea lindneri (Hendel, 1932) and Protodictya lilloana Steyskal, 1953 (Diptera, Sciomyzidae) from Uruguay. The specimens were collected in rice crops and in adjacent native vegetation with sweep net and vacuum sampler from December to March (2012?2015) in the Eastern region of the country. Photos of collection areas, habitus of adults and distribution map of the species are provided. |
Palabras claves : |
APPLE SNAIL CONTROL; GEOGRAPHIC DISTRIBUTION; MARSH FLIES; NEOTROPICAL REGION; RICE CROP. |
Asunto categoría : |
H20 Enfermedades de las plantas |
URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/12647/1/Martinez-Check-List-2019.pdf
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Marc : |
LEADER 01450naa a2200265 a 4500 001 1059756 005 2019-05-10 008 2019 bl uuuu u00u1 u #d 022 $a1809127X 024 7 $a10.15560/15.1.71$2DOI 100 1 $aBAO, L. 245 $aFirst records of Sepedonea lindneri (Hendel, 1932) and Protodictya lilloana Steyskal, 1953 (Diptera, Sciomyzidae) from Uruguay with an overview on their biology.$h[electronic resource] 260 $c2019 500 $aArticle history: Received 26 September 2018. Accepted 19 December 2018. Published 25 January 2019. 520 $aSciomyzidae (Diptera) has been recorded in several countries of South America, but few species have been found in Uruguay. We report the first record of Sepedonea lindneri (Hendel, 1932) and Protodictya lilloana Steyskal, 1953 (Diptera, Sciomyzidae) from Uruguay. The specimens were collected in rice crops and in adjacent native vegetation with sweep net and vacuum sampler from December to March (2012?2015) in the Eastern region of the country. Photos of collection areas, habitus of adults and distribution map of the species are provided. 653 $aAPPLE SNAIL CONTROL 653 $aGEOGRAPHIC DISTRIBUTION 653 $aMARSH FLIES 653 $aNEOTROPICAL REGION 653 $aRICE CROP 700 1 $aCASTIGLIONI, E. 700 1 $aMARTÍNEZ, S. 700 1 $aSAVARIS, M. 700 1 $aMARINONI, L. 773 $tCheck List, Jannuary 2019, 15(1), p. 71-77.
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