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Biblioteca (s) : |
INIA Las Brujas. |
Fecha : |
18/06/2015 |
Actualizado : |
20/06/2015 |
Tipo de producción científica : |
Informes Agroclimáticos |
Autor : |
CASTAÑO, J.; GIMENEZ, A.; FUREST, J.; AUNCHAYNA, R. |
Afiliación : |
JOSE PEDRO CASTAÑO SANCHEZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; AGUSTIN EDUARDO GIMENEZ FUREST, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; JOSE MARIA FUREST CROCCO, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; ROSSINA MARIANA AUNCHAYNA REILLY, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
Título : |
Informe Agroclimático 2009 - Situación a Abril. |
Fecha de publicación : |
2009 |
Fuente / Imprenta : |
Montevideo (Uruguay): INIA, 2009. |
Páginas : |
4 p. |
Idioma : |
Español |
Palabras claves : |
AGROCLIMA; AGROCLIMATOLOGÍA; BOLETIN AGROCLIMÁTICO; CARACTERIZACIÓN AGROCLIMÁTICA; DIRECCION VIENTO; ESTACIONES AGROMETEOROLOGICAS; ESTACIONES AUTOMATICAS; ESTACIONES INIA; ESTADO DEL TIEMPO; ESTRÉS HÍDRICO; GRAFICAS AGROCLIMATICOS; GRAS; HELIOFANOGRAFO; INFORMACION SATELITAL; INUNDACIONES; LLUVIAS DIARIAS; MAXIMA; MEDIA; MINIMA; PANEL SOLAR; PERSPECTIVAS CLIMATICAS; PLUVIOMETRO; PRECIPITACION NACIONAL; PREVENCION HELADAS; PRONOSTICO; SENSOR; SIMETRICO; TANQUE A; TERMOCUPLAS; TERMOHIDROGRAFO; VARIABLES AGROCLIMATICAS; VELETA. |
Thesagro : |
AGROCLIMATOLOGIA; CAMBIO CLIMATICO; CLIMA; CLIMATOLOGIA; ESTACIONES METEOROLOGICAS; ESTRES HIDRICO; EVAPORACION; EVAPOTRANSPIRACION; HUMEDAD; HUMEDAD RELATIVA; LLUVIA; METEOROLOGIA; PERSPECTIVAS; PLUVIOMETROS; PRONOSTICO DEL TIEMPO; SENSORES; SISTEMAS; SISTEMAS DE INFORMACION; SUELO; TEMPERATURA; TERMOMETROS. |
Asunto categoría : |
P40 Meteorología y climatología |
URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/4662/1/Inf.Agr.-abril-2009.pdf
http://www.inia.uy/Publicaciones/Paginas/publicacion-1886.aspx
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Marc : |
LEADER 02039nam a2200781 a 4500 001 1052818 005 2015-06-20 008 2009 bl uuuu u0uu1 u #d 100 1 $aCASTAÑO, J. 245 $aInforme Agroclimático 2009 - Situación a Abril.$h[electronic resource] 260 $aMontevideo (Uruguay): INIA$c2009 300 $a4 p. 650 $aAGROCLIMATOLOGIA 650 $aCAMBIO CLIMATICO 650 $aCLIMA 650 $aCLIMATOLOGIA 650 $aESTACIONES METEOROLOGICAS 650 $aESTRES HIDRICO 650 $aEVAPORACION 650 $aEVAPOTRANSPIRACION 650 $aHUMEDAD 650 $aHUMEDAD RELATIVA 650 $aLLUVIA 650 $aMETEOROLOGIA 650 $aPERSPECTIVAS 650 $aPLUVIOMETROS 650 $aPRONOSTICO DEL TIEMPO 650 $aSENSORES 650 $aSISTEMAS 650 $aSISTEMAS DE INFORMACION 650 $aSUELO 650 $aTEMPERATURA 650 $aTERMOMETROS 653 $aAGROCLIMA 653 $aAGROCLIMATOLOGÍA 653 $aBOLETIN AGROCLIMÁTICO 653 $aCARACTERIZACIÓN AGROCLIMÁTICA 653 $aDIRECCION VIENTO 653 $aESTACIONES AGROMETEOROLOGICAS 653 $aESTACIONES AUTOMATICAS 653 $aESTACIONES INIA 653 $aESTADO DEL TIEMPO 653 $aESTRÉS HÍDRICO 653 $aGRAFICAS AGROCLIMATICOS 653 $aGRAS 653 $aHELIOFANOGRAFO 653 $aINFORMACION SATELITAL 653 $aINUNDACIONES 653 $aLLUVIAS DIARIAS 653 $aMAXIMA 653 $aMEDIA 653 $aMINIMA 653 $aPANEL SOLAR 653 $aPERSPECTIVAS CLIMATICAS 653 $aPLUVIOMETRO 653 $aPRECIPITACION NACIONAL 653 $aPREVENCION HELADAS 653 $aPRONOSTICO 653 $aSENSOR 653 $aSIMETRICO 653 $aTANQUE A 653 $aTERMOCUPLAS 653 $aTERMOHIDROGRAFO 653 $aVARIABLES AGROCLIMATICAS 653 $aVELETA 700 1 $aGIMENEZ, A. 700 1 $aFUREST, J. 700 1 $aAUNCHAYNA, R.
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Registro original : |
INIA Las Brujas (LB) |
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Biblioteca (s) : |
INIA Las Brujas. |
Fecha actual : |
04/10/2014 |
Actualizado : |
10/02/2020 |
Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
Circulación / Nivel : |
A - 2 |
Autor : |
FORNI, S.; AGUILAR, I.; MISZTAL, I. |
Afiliación : |
IGNACIO AGUILAR GARCIA, Instituto Nacional de Investigación Agropecuaria (INIA), Uruguay. |
Título : |
Different genomic relationship matrices for single-step analysis using phenotypic, pedigree and genomic information. |
Fecha de publicación : |
2011 |
Fuente / Imprenta : |
Genetics Selection Evolution, 2011, v.43, no.1, p.443-447. |
ISSN : |
0999-193X |
DOI : |
10.1186/1297-9686-43-1 |
Idioma : |
Inglés |
Notas : |
ARTICULO OPEN ACCESS. |
Contenido : |
BACKGROUND:
The incorporation of genomic coefficients into the numerator relationship matrix allows estimation of breeding values using all phenotypic, pedigree and genomic information simultaneously. In such a single-step procedure, genomic and pedigree-based relationships have to be compatible. As there are many options to create genomic relationships, there is a question of which is optimal and what the effects of deviations from optimality are. Methods. Data of litter size (total number born per litter) for 338,346 sows were analyzed. Illumina PorcineSNP60 BeadChip genotypes were available for 1,989. Analyses were carried out with the complete data set and with a subset of genotyped animals and three generations pedigree (5,090 animals). A single-trait animal model was used to estimate variance components and breeding values. Genomic relationship matrices were constructed using allele frequencies equal to 0.5 (G05), equal to the average minor allele frequency (GMF), or equal to observed frequencies (GOF). A genomic matrix considering random ascertainment of allele frequencies was also used (GOF*). A normalized matrix (GN) was obtained to have average diagonal coefficients equal to 1. The genomic matrices were combined with the numerator relationship matrix creating H matrices. Results: In G05 and GMF, both diagonal and off-diagonal elements were on average greater than the pedigree-based coefficients. In GOF and GOF*, the average diagonal elements were smaller than pedigree-based coefficients. The mean of off-diagonal coefficients was zero in GOF and GOF*. Choices of G with average diagonal coefficients different from 1 led to greater estimates of additive variance in the smaller data set. The correlation between EBV and genomic EBV (n = 1,989) were: 0.79 using G05, 0.79 using GMF, 0.78 using GOF, 0.79 using GOF*, and 0.78 using GN. Accuracies calculated by inversion increased with all genomic matrices. The accuracies of genomic-assisted EBV were inflated in all cases except when GN was used. Conclusions: Parameter estimates may be biased if the genomic relationship coefficients are in a different scale than pedigree-based coefficients. A reasonable scaling may be obtained by using observed allele frequencies and re-scaling the genomic relationship matrix to obtain average diagonal elements of 1.
© 2011 Forni et al; licensee BioMed Central Ltd. MenosBACKGROUND:
The incorporation of genomic coefficients into the numerator relationship matrix allows estimation of breeding values using all phenotypic, pedigree and genomic information simultaneously. In such a single-step procedure, genomic and pedigree-based relationships have to be compatible. As there are many options to create genomic relationships, there is a question of which is optimal and what the effects of deviations from optimality are. Methods. Data of litter size (total number born per litter) for 338,346 sows were analyzed. Illumina PorcineSNP60 BeadChip genotypes were available for 1,989. Analyses were carried out with the complete data set and with a subset of genotyped animals and three generations pedigree (5,090 animals). A single-trait animal model was used to estimate variance components and breeding values. Genomic relationship matrices were constructed using allele frequencies equal to 0.5 (G05), equal to the average minor allele frequency (GMF), or equal to observed frequencies (GOF). A genomic matrix considering random ascertainment of allele frequencies was also used (GOF*). A normalized matrix (GN) was obtained to have average diagonal coefficients equal to 1. The genomic matrices were combined with the numerator relationship matrix creating H matrices. Results: In G05 and GMF, both diagonal and off-diagonal elements were on average greater than the pedigree-based coefficients. In GOF and GOF*, the average diagonal elements were smaller than ped... Presentar Todo |
Thesagro : |
CERDOS; GENOTIPOS; MEJORAMIENTO GENÉTICO ANIMAL. |
Asunto categoría : |
L10 Genética y mejoramiento animal |
URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/3441/1/Aguilar-I.-2011.-GSE-v.431-OPEN-ACCESS.pdf
http://www.biomedcentral.com/content/pdf/1297-9686-43-1.pdf
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Marc : |
LEADER 03070naa a2200217 a 4500 001 1050906 005 2020-02-10 008 2011 bl uuuu u00u1 u #d 022 $a0999-193X 024 7 $a10.1186/1297-9686-43-1$2DOI 100 1 $aFORNI, S. 245 $aDifferent genomic relationship matrices for single-step analysis using phenotypic, pedigree and genomic information.$h[electronic resource] 260 $c2011 500 $aARTICULO OPEN ACCESS. 520 $aBACKGROUND: The incorporation of genomic coefficients into the numerator relationship matrix allows estimation of breeding values using all phenotypic, pedigree and genomic information simultaneously. In such a single-step procedure, genomic and pedigree-based relationships have to be compatible. As there are many options to create genomic relationships, there is a question of which is optimal and what the effects of deviations from optimality are. Methods. Data of litter size (total number born per litter) for 338,346 sows were analyzed. Illumina PorcineSNP60 BeadChip genotypes were available for 1,989. Analyses were carried out with the complete data set and with a subset of genotyped animals and three generations pedigree (5,090 animals). A single-trait animal model was used to estimate variance components and breeding values. Genomic relationship matrices were constructed using allele frequencies equal to 0.5 (G05), equal to the average minor allele frequency (GMF), or equal to observed frequencies (GOF). A genomic matrix considering random ascertainment of allele frequencies was also used (GOF*). A normalized matrix (GN) was obtained to have average diagonal coefficients equal to 1. The genomic matrices were combined with the numerator relationship matrix creating H matrices. Results: In G05 and GMF, both diagonal and off-diagonal elements were on average greater than the pedigree-based coefficients. In GOF and GOF*, the average diagonal elements were smaller than pedigree-based coefficients. The mean of off-diagonal coefficients was zero in GOF and GOF*. Choices of G with average diagonal coefficients different from 1 led to greater estimates of additive variance in the smaller data set. The correlation between EBV and genomic EBV (n = 1,989) were: 0.79 using G05, 0.79 using GMF, 0.78 using GOF, 0.79 using GOF*, and 0.78 using GN. Accuracies calculated by inversion increased with all genomic matrices. The accuracies of genomic-assisted EBV were inflated in all cases except when GN was used. Conclusions: Parameter estimates may be biased if the genomic relationship coefficients are in a different scale than pedigree-based coefficients. A reasonable scaling may be obtained by using observed allele frequencies and re-scaling the genomic relationship matrix to obtain average diagonal elements of 1. © 2011 Forni et al; licensee BioMed Central Ltd. 650 $aCERDOS 650 $aGENOTIPOS 650 $aMEJORAMIENTO GENÉTICO ANIMAL 700 1 $aAGUILAR, I. 700 1 $aMISZTAL, I. 773 $tGenetics Selection Evolution, 2011$gv.43, no.1, p.443-447.
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