<?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>S1405-31952016000200215</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[Localización del ápice del ajo mediante técnicas de análisis digital de imagen]]></article-title>
<article-title xml:lang="en"><![CDATA[Localization of garlic apex by digital image analysis techniques]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Saldaña-Robles]]></surname>
<given-names><![CDATA[Noé]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Serwatowski Hlawinska]]></surname>
<given-names><![CDATA[Ryszard J.]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Aguilera Hernández]]></surname>
<given-names><![CDATA[Ruth A.]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Saldaña-Robles]]></surname>
<given-names><![CDATA[Alberto]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Martínez-Jaime]]></surname>
<given-names><![CDATA[Oscar A.]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Gutiérrez-Vaca]]></surname>
<given-names><![CDATA[César]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Universidad de Guanajuato División de Ciencias de la Vida ]]></institution>
<addr-line><![CDATA[Irapuato Guanajuato]]></addr-line>
<country>Mexico</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>03</month>
<year>2016</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>03</month>
<year>2016</year>
</pub-date>
<volume>50</volume>
<numero>2</numero>
<fpage>215</fpage>
<lpage>225</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_arttext&amp;pid=S1405-31952016000200215&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_abstract&amp;pid=S1405-31952016000200215&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_pdf&amp;pid=S1405-31952016000200215&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen: La siembra y la cosecha son las operaciones más costosas en la producción del ajo (Allium sativum L.), pues se realizan a mano. Para hacer factible la siembra mecanizada, el diente de ajo se debe colocar en el suelo con el ápice hacia arriba porque colocarlo al azar reduce el rendimiento hasta en 23 %. El objetivo de este estudio fue desarrollar un algoritmo para identificar el ápice del ajo mediante visión artificial. Para ello se empleó una cámara de video y lámparas de iluminación, con lo cual se obtuvieron imágenes digitales de dientes de ajo. Las imágenes se procesaron para identificar el ápice en cuatro pasos: 1) captura de la imagen; 2) detección del borde perimetral de los dientes de ajo; 3) cálculo de ángulos en el interior del borde de los dientes y localización del ápice bajo la hipótesis de que éste coincide con el ángulo más pequeño en el interior del borde; 4) identificación de la necesidad de reorientar el ápice. El impacto de la posición y tamaño en la correcta identificación del ápice se evaluó estadísticamente y se compararon los métodos de detección de bordes Canny, Roberts y Sobel. Los resultados no mostraron diferencias estadísticas significativas (p&gt;0.10) entre los diferentes tamaños y las posiciones del ajo al localizar el ápice, lo cual resulta conveniente. Pero sí hubo diferencias estadísticas significativas (p&#8804;0.10) entre los métodos de detección de bordes utilizados, porque el de Canny tuvo mejor desempeño en la localización del ápice. El algoritmo desarrollado en esta investigación se podría usar para diseñar un sistema mecánico que reoriente el ápice a través de visión artificial en la siembra de ajo.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract: Sowing and harvesting are the most costly operations in the garlic production (Allium sativum L.), because they are carried out by hand. In order for mechanized sowing to be feasible, the garlic clove must be placed in the soil with the apex facing upwards because placing it randomly reduces its yield in up to 23 %. The objective of this study was to develop an algorithm to identify the garlic apex through artificial vision. For this purpose, a video camera and illumination lamps were used, with which digital images of the cloves of garlic were obtained. The images were processed to identify the apex in four steps: 1) capturing the image; 2) detecting the perimeter edge of the garlic cloves; 3) calculating the angles on the inside edge of the cloves and localizing the apex under the hypothesis that it coincides with the smallest angle on the inside edge; 4) identifying the need of reorienting the apex. The impact of the location and size in the correct identification of the apex was evaluated statistically and the border detection methods Canny, Roberts and Sobel were compared. The results did not show significant statistical differences (p&gt;0.10) between the different sizes and positions of the garlic when localizing the apex, which is convenient. However, there were significant statistical differences (p&#8804;0.10) between the border detection methods, because Canny&#8217;s had a better performance in the localization of the apex. The algorithm developed in this research could be used to design a mechanical system to reorient the apex through artificial vision in garlic sowing.]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[Allium sativum L.]]></kwd>
<kwd lng="es"><![CDATA[detección de bordes]]></kwd>
<kwd lng="es"><![CDATA[Canny]]></kwd>
<kwd lng="es"><![CDATA[mecanización de la siembra]]></kwd>
<kwd lng="es"><![CDATA[visión artificial]]></kwd>
<kwd lng="en"><![CDATA[Allium sativum L.]]></kwd>
<kwd lng="en"><![CDATA[border detection]]></kwd>
<kwd lng="en"><![CDATA[Canny]]></kwd>
<kwd lng="en"><![CDATA[mechanization of sowing]]></kwd>
<kwd lng="en"><![CDATA[artificial vision]]></kwd>
</kwd-group>
</article-meta>
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