<?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>2007-1124</journal-id>
<journal-title><![CDATA[Revista mexicana de ciencias pecuarias]]></journal-title>
<abbrev-journal-title><![CDATA[Rev. mex. de cienc. pecuarias]]></abbrev-journal-title>
<issn>2007-1124</issn>
<publisher>
<publisher-name><![CDATA[Instituto Nacional de Investigaciones Forestales, Agrícolas y Pecuarias]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S2007-11242024000300721</article-id>
<article-id pub-id-type="doi">10.22319/rmcp.v15i3.6365</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[Estimación de parámetros genéticos para características de flujo y conductividad de la leche en un sistema de ordeño robotizado]]></article-title>
<article-title xml:lang="en"><![CDATA[Estimation of genetic parameters for milk flow rate and conductivity traits in a robotic milking system]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Cornejo-García]]></surname>
<given-names><![CDATA[Norma Leticia]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
<xref ref-type="aff" rid="Aaf"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Durán-Aguilar]]></surname>
<given-names><![CDATA[Marina]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Ruiz-López]]></surname>
<given-names><![CDATA[Felipe de Jesús]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Cantó-Alarcón]]></surname>
<given-names><![CDATA[Germinal Jorge]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Romano-Muñoz]]></surname>
<given-names><![CDATA[José Luis]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Primate Products LLC  ]]></institution>
<addr-line><![CDATA[ Florida]]></addr-line>
<country>E.E.U.U</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Universidad Autónoma de Querétaro Facultad de Ciencias Naturales Maestría en Salud y Producción Animal Sustentable]]></institution>
<addr-line><![CDATA[ Querétaro]]></addr-line>
<country>Mexico</country>
</aff>
<aff id="Af3">
<institution><![CDATA[,Instituto Nacional de Investigaciones Forestales, Agrícolas y Pecuarias Centro Nacional de Investigación Disciplinaria en Fisiología y Mejoramiento Animal ]]></institution>
<addr-line><![CDATA[Colón Querétaro]]></addr-line>
<country>Mexico</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>09</month>
<year>2024</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>09</month>
<year>2024</year>
</pub-date>
<volume>15</volume>
<numero>3</numero>
<fpage>721</fpage>
<lpage>733</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_arttext&amp;pid=S2007-11242024000300721&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_abstract&amp;pid=S2007-11242024000300721&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_pdf&amp;pid=S2007-11242024000300721&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen El objetivo de este trabajo fue estimar los componentes de varianza y correlaciones genéticas para la producción de leche (PLe), el flujo medio (FMd), el flujo máximo (FMx) y la conductividad eléctrica (CE) de la leche, en un sistema de ordeño robotizado. Se analizaron 137 lactaciones de 110 vacas Holstein primíparas y multíparas, con 42,009 observaciones, desde el año 2018 hasta el 2020 en un hato lechero en el estado de Querétaro. Se realizó la evaluación genética utilizando un modelo animal de regresión mixta. Para estimar la heredabilidad (h2) se utilizó el algoritmo de máxima verosimilitud restringida para calcular los componentes de varianza, el estimador BLUE y el predictor BLUP, para cada una de las variables sujetas en la investigación. La h2 estimada para PLe (0.62) fue la más alta de las calculadas, de igual modo se estimó la h2 para FMd (0.44), FMx (0.33) y CE (0.28); se considera que uno de los aspectos que influyó en los valores obtenidos se debió a la variabilidad de cada observación diaria. Las correlaciones genéticas para la PLe fueron negativas para el FMd (-0.6117) y FMx (-0.7666); en contraste, para la característica de CE (-0.1669) la correlación fue baja. Las correlaciones genéticas estimadas para FMx fueron positivas para FMd (0.7422) y CE (0.5351), finalmente se estimó una correlación genética positiva para FMd y CE (0.3546). Los resultados presentados permiten entender las relaciones existentes entre flujo, conductividad y producción e indican la importancia de estas características para un programa de selección genética.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract This work aimed to estimate the variance components and genetic correlations for milk yield (MiY), mean flow rate (MnF), maximum flow rate (MxF), and electrical conductivity (EC) of milk, in a robotic milking system. IT was analyzed a total of 137 lactations from 110 primiparous and multiparous Holstein cows, with 42,009 observations, from 2018 to 2020 in a dairy herd in the state of Querétaro. Genetic evaluation was performed using a mixed regression animal model. To estimate heritability (h2), the restricted maximum likelihood algorithm was used to calculate the variance components, the BLUE estimator and the BLIP predictor, for each of the variables subject to the research. The estimated h2 for MiY (0.62) was the highest of those calculated, and h2 was also estimated for MnF (0.44), MxF (0.33), and EC (0.28); it is considered that one of the aspects that influenced the values was the variability of each daily observation. Genetic correlations for MiY were negative for MnF (-0.6117) and MxF (-0.7666); in contrast, for the trait of EC (-0.1669), the correlation was low. The estimated genetic correlations for MxF were positive for MnF (0.7422) and EC (0.5351); finally, a positive genetic correlation was estimated for MnF and EC (0.3546). The results presented allow to understand the relationships between flow rate, conductivity, and yield, and they indicate the importance of these characteristics for a genetic selection program.]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[Heredabilidad]]></kwd>
<kwd lng="es"><![CDATA[Producción de leche]]></kwd>
<kwd lng="es"><![CDATA[Conductividad eléctrica]]></kwd>
<kwd lng="es"><![CDATA[Flujo de leche]]></kwd>
<kwd lng="en"><![CDATA[Heritability]]></kwd>
<kwd lng="en"><![CDATA[Milk yield]]></kwd>
<kwd lng="en"><![CDATA[Electrical conductivity]]></kwd>
<kwd lng="en"><![CDATA[Milk flow rate]]></kwd>
</kwd-group>
</article-meta>
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