<?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>2007-0934</journal-id>
<journal-title><![CDATA[Revista mexicana de ciencias agrícolas]]></journal-title>
<abbrev-journal-title><![CDATA[Rev. Mex. Cienc. Agríc]]></abbrev-journal-title>
<issn>2007-0934</issn>
<publisher>
<publisher-name><![CDATA[Instituto Nacional de Investigaciones Forestales, Agrícolas y Pecuarias]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S2007-09342025000300111</article-id>
<article-id pub-id-type="doi">10.29312/remexca.v16i3.3636</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[Estimación de rendimiento del maíz mediante tratamientos de imágenes obtenidas por Sentinel 2: caso de Las Arenas, Acambay]]></article-title>
<article-title xml:lang="en"><![CDATA[Estimation of corn yield thro ugh image treatments obtained by Sentinel 2: case of Las Arenas, Acambay]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[García-Martínez]]></surname>
<given-names><![CDATA[Mónica Ivonne]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Antonio-Némiga]]></surname>
<given-names><![CDATA[Xanat]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Ramírez-Dávila]]></surname>
<given-names><![CDATA[José Francisco]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Salazar-Garibay]]></surname>
<given-names><![CDATA[Adán]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Universidad Autónoma del Estado de México Facultad de Geografía ]]></institution>
<addr-line><![CDATA[Toluca Estado de México]]></addr-line>
<country>Mexico</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Universidad Autónoma del Estado de México Facultad de Agronomía ]]></institution>
<addr-line><![CDATA[Toluca Estado de México]]></addr-line>
<country>Mexico</country>
</aff>
<aff id="Af3">
<institution><![CDATA[,Agencia Espacial Mexicana  ]]></institution>
<addr-line><![CDATA[Ciudad de México ]]></addr-line>
<country>Mexico</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>05</month>
<year>2025</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>05</month>
<year>2025</year>
</pub-date>
<volume>16</volume>
<numero>3</numero>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_arttext&amp;pid=S2007-09342025000300111&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_abstract&amp;pid=S2007-09342025000300111&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_pdf&amp;pid=S2007-09342025000300111&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen El maíz (Zea mays L.) es la base de la alimentación y cultura en el Estado de México, por lo que estimar su producción para sostener a una población creciente es una necesidad actual. Por ello, se usaron imágenes obtenidas por Sentinel 2 de ESA Copérnico para estimar el rendimiento de maíz en parcelas de la localidad Las Arenas, Acambay, Estado de México. Se probó la eficiencia de diversos índices e indicadores biofísicos calculados con información de estas imágenes, para establecer su correlación contra la cosecha medida en campo. Los índices calculados en Sentinel 2 fueron: el NDVI y el EVI, así como los indicadores LAI y FAPAR. En esta región y bajo condiciones de sequía intensa, el NDVI calculado en Sentinel 2 tuvo la mejor capacidad predictiva del rendimiento de maíz (ajuste del modelo r2= 0.79). Con base en la correlación se estimó la producción de 10 parcelas seleccionadas aleatoriamente, demostrando que en el rango de valores entre 0.4 y 0.5 el NDVI es un excelente predictor de la cosecha de maíz en condiciones de sequía, mientras que valores superiores de NDVI tienden a sobreestimar el rendimiento hasta por 1 t ha-1. Esta información es de utilidad para la estimación de la cosecha y de seguros de la producción agrícola.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract Corn (Zea mays L.) is the basis of food and culture in the state of Mexico, so estimating its production to sustain a growing population is a current need. Therefore, images obtained by ESA Copernicus&#8217; Sentinel 2 were used to estimate corn yield in plots in the localities of Las Arenas, Acambay, state of Mexico. The efficiency of various indices and biophysical indicators calculated with information from these images was tested to establish their correlation against the harvest measured in the field. The indices calculated in Sentinel 2 were: NDVI and EVI and the LAI and FAPAR indicators. In this region and under conditions of intense drought, the NDVI calculated in Sentinel 2 had the best predictive ability for corn yield (model fit r2= 0.79). Based on the correlation, the production of 10 randomly selected plots was estimated, demonstrating that, in the range of values between 0.4 and 0.5, NDVI is an excellent predictor of corn harvest under drought conditions, whereas higher NDVI values tend to overestimate yield by up to 1 t ha-1. This information is useful for estimating the harvest and insurance of agricultural production.]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[indicadores biofísicos]]></kwd>
<kwd lng="es"><![CDATA[índices de vegetación]]></kwd>
<kwd lng="es"><![CDATA[producción de maíz]]></kwd>
<kwd lng="en"><![CDATA[biophysical indicators]]></kwd>
<kwd lng="en"><![CDATA[corn production]]></kwd>
<kwd lng="en"><![CDATA[vegetation indices]]></kwd>
</kwd-group>
</article-meta>
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