<?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>S1405-31952016000100001</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[Predicción de variables meteorológicas por medio de modelos ARIMA]]></article-title>
<article-title xml:lang="en"><![CDATA[Meteorological variables prediction through ARIMA models]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Aguado-Rodríguez]]></surname>
<given-names><![CDATA[G. Javier]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Quevedo-Nolasco]]></surname>
<given-names><![CDATA[Abel]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Castro-Popoca]]></surname>
<given-names><![CDATA[Martiniano]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Arteaga-Ramírez]]></surname>
<given-names><![CDATA[Ramón]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Vázquez-Peña]]></surname>
<given-names><![CDATA[M. Alberto]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Zamora-Morales]]></surname>
<given-names><![CDATA[B. Patricia]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Colegio de Postgraduados  ]]></institution>
<addr-line><![CDATA[Montecillo Estado de México]]></addr-line>
<country>Mexico</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Universidad Autónoma Chapingo  ]]></institution>
<addr-line><![CDATA[Chapingo Estado de México]]></addr-line>
<country>Mexico</country>
</aff>
<aff id="Af3">
<institution><![CDATA[,Instituto Nacional de Investigaciones Forestales, Agrícolas y Pecuarias  ]]></institution>
<addr-line><![CDATA[Texcoco Estado de México]]></addr-line>
<country>Mexico</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>02</month>
<year>2016</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>02</month>
<year>2016</year>
</pub-date>
<volume>50</volume>
<numero>1</numero>
<fpage>1</fpage>
<lpage>13</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_arttext&amp;pid=S1405-31952016000100001&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_abstract&amp;pid=S1405-31952016000100001&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_pdf&amp;pid=S1405-31952016000100001&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen La predicción de las variables meteorológicas se aplica en la agricultura al predecir el consumo de agua de las plantas para planear la lámina de riego. En esta investigación se elaboró un programa para realizar la predicción de la temperatura, radiación solar, evapotranspiración de referencia y humedad relativa con modelos autorregresivos integrados de media móvil (ARIMA) y se probó la efectividad del programa para realizar la predicción en condiciones de alta y baja precipitación. Los periodos de predicción evaluados fueron en marzo y en junio de 2013 en tres estaciones meteorológicas automáticas (EMAS) del Servicio Meteorológico Nacional (SMN). El análisis de los resultados indicó que la predicción de las variables meteorológicas con modelos ARIMA fue mejor que con la predicción persistente en el periodo con condiciones de baja precipitación (marzo).]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract Meteorological variables prediction is applied in agriculture to predict water uptake of plants for planning irrigation depths. In the present study a program was made for the prediction of temperature, solar radiation, reference evapotranspiration and relative humidity by means of autoregressive integrated mobile media models. The effectiveness of the program was tested for prediction under high and low rainfall conditions. The prediction periods evaluated were in March and in June, 2013, in three automatic meteorological stations (EMAS) of the National Meteorological Service (SMN). The analysis of results indicated that the prediction of meteorological variables with ARIMA models was better than with persistent prediction in the period with low rainfall conditions (March).]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[Prónostico]]></kwd>
<kwd lng="es"><![CDATA[R Statictics]]></kwd>
<kwd lng="es"><![CDATA[tiempo real]]></kwd>
<kwd lng="en"><![CDATA[Prediction]]></kwd>
<kwd lng="en"><![CDATA[R Statistics]]></kwd>
<kwd lng="en"><![CDATA[real time]]></kwd>
</kwd-group>
</article-meta>
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