<?xml version="1.0" encoding="ISO-8859-1"?><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
<front>
<journal-meta>
<journal-id>1405-3195</journal-id>
<journal-title><![CDATA[Agrociencia]]></journal-title>
<abbrev-journal-title><![CDATA[Agrociencia]]></abbrev-journal-title>
<issn>1405-3195</issn>
<publisher>
<publisher-name><![CDATA[Colegio de Postgraduados]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S1405-31952007000300271</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[Análisis univariado vs multivariado en la evaluación genética de variables de crecimiento en dos razas bovinas]]></article-title>
<article-title xml:lang="en"><![CDATA[Univariate vs multivariate analyses in genetic evaluation of growth traits in two cattle breeds]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Ramírez-Valverde]]></surname>
<given-names><![CDATA[Rodolfo]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Hernández-Alvarez]]></surname>
<given-names><![CDATA[O. César]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Núñez-Domínguez]]></surname>
<given-names><![CDATA[Rafael]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Ruíz-Flores]]></surname>
<given-names><![CDATA[Agustín]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[García-Muñiz]]></surname>
<given-names><![CDATA[J. Guadalupe]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Universidad Autónoma Chapingo Producción Animal ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Mexico</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>05</month>
<year>2007</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>05</month>
<year>2007</year>
</pub-date>
<volume>41</volume>
<numero>3</numero>
<fpage>271</fpage>
<lpage>282</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_arttext&amp;pid=S1405-31952007000300271&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_abstract&amp;pid=S1405-31952007000300271&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_pdf&amp;pid=S1405-31952007000300271&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen La predicción de valores genéticos de los animales para variables con selección secuencial requiere identificar modelos estadísticos que maximicen la respuesta a la selección. El objetivo del presente trabajo fue comparar el uso de análisis univariados y multivariados de variables de crecimiento en la evaluación genética de bovinos Angus y Tropicarne. Las variables analizadas fueron los pesos al nacimiento (PN), al destete (PD) y al año (PA), procedentes de los registros genealógicos (n=9933) y productivos de la Asociación Angus Mexicana, y la Asociación Mexicana de Criadores de Ganado Tropicarne (n=5724). Las evaluaciones genéticas se realizaron utilizando el Modelo Animal, con análisis univariados y bivariados en ambas poblaciones, y trivariados en Tropicarne. Los criterios de comparación fueron: magnitud de los estimadores de parámetros genéticos, habilidad de predicción de los modelos, y tamaño de la exactitud de los valores genéticos predichos para PN, PD, leche y PA; además se evaluó el efecto de la alternativa de análisis en la jerarquización de los animales. Para algunas variables la utilización de análisis bivariados mejoró la estimación de las heredabilidades directas y maternas, la exactitud de las predicciones de los valores genéticos, y la habilidad de predicción de los modelos, pero no se observaron ventajas al usar trivariados. El uso de análisis multivariados con respecto a univariados cambió la jerarquización de los animales en casi todas las variables, lo que sugiere la necesidad de evaluar la alternativa de análisis más apropiada para la población y variables específicas. En Angus se recomienda análisis individual para PN, y bivariado para PD y PA; mientras que en Tropicarne, para PN se recomienda análisis bivariado de PN y PD, y para PD y PA el análisis bivariado de ambas.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract The prediction of genetic values of animals for variables with sequential selection requires the identification of statistical models that maximize the response to selection. The objective of the present study was to compare the use of univariate and multivariate analyses of growth variables in the genetic evaluation of Angus and Tropicarne cattle. The variables analyzed were the weights at birth (BW), at weaning (WW) and at one year (YW), obtained from the genealogical (n=9933) and productive records of the Asociación Angus Mexicana, and the Asociación Mexicana de Criadores de Ganado Tropicarne (n=5724). The genetic evaluations were carried out using an Animal Model, with univariate and bivariate analyses in both populations, and trivariate analysis in Tropicarne. The comparison criteria were: magnitude of the estimators of genetic parameters, prediction ability of the models, and size of the accuracy of the genetic values predicted for BW, WW, milk and YW; in addition, the effect of the alternatives of analysis in the ranking of animals was evaluated. For some variables, the use of bivariate analyses improved the estimation of the direct and maternal heritabilities, the accuracy of the predictions of the genetic values, and the prediction ability of the models, but no advantages were observed when using trivariate analyses. The use of multivariate analysis with respect to univariate analysis changed the ranking of animals in nearly all of the variables, which suggests the need to evaluate the most appropriate alternative of analysis for population and specific variables. In Angus, individual analysis is recommended for BW, and bivariate analysis for WW and YW; whereas in Tropicarne, for BW, bivariate analysis of BW and WW is recommended, and for WW and YW, the bivariate analysis of both traits.]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[Análisis univariado y multivariado]]></kwd>
<kwd lng="es"><![CDATA[Angus]]></kwd>
<kwd lng="es"><![CDATA[bovinos para carne]]></kwd>
<kwd lng="es"><![CDATA[parámetros genéticos]]></kwd>
<kwd lng="es"><![CDATA[Tropicarne]]></kwd>
<kwd lng="es"><![CDATA[valor genético]]></kwd>
<kwd lng="en"><![CDATA[Univariate and multivariate analyses]]></kwd>
<kwd lng="en"><![CDATA[Angus]]></kwd>
<kwd lng="en"><![CDATA[beef cattle]]></kwd>
<kwd lng="en"><![CDATA[genetic parameters]]></kwd>
<kwd lng="en"><![CDATA[Tropicarne]]></kwd>
<kwd lng="en"><![CDATA[genetic value]]></kwd>
</kwd-group>
</article-meta>
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