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http://repositorio.ugto.mx/handle/20.500.12059/1510
Full metadata record
DC Field | Value | Language |
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dc.rights.license | http://creativecommons.org/licenses/by-nc-nd/4.0 | es_MX |
dc.creator | DIXIA DANIA VEGA VALDIVIA | - |
dc.date.accessioned | 2020-03-04T15:57:02Z | - |
dc.date.available | 2020-03-04T15:57:02Z | - |
dc.date.issued | 2019-11-06 | - |
dc.identifier.uri | http://repositorio.ugto.mx/handle/20.500.12059/1510 | - |
dc.description.abstract | Conocer el sexo del venado cola blanca (Odocoileus virginianus) puede proporcionar información para establecer tasas de aprovechamiento y actividades de manejo. El objetivo de este estudio es identificar el sexo mediante la creación de funciones de clasificación para sexo obtenidas mediante morfometría de pellets fecales. Se colectaron heces durante 12 meses en Durango, México, a los cuales se les midieron sus variables morfométricas, extrajo ADNy amplificó el marcador genético SRY para identificar el sexo. Luego, se obtuvo una función de clasificación de sexo con redes neuronales y lógica difusa. Los resultados fueron validados con el gen SRY. Se utilizaron datos de adultos en invierno para obtener las funciones de clasificación. Se clasificó con precisión el sexo en 94.4% con redes neuronales y 86.9% con lógica difusa. Las redes neuronales clasificaron con mayor precisión el sexo del venado cola blanca con morfometría de pellets fecales de adultos en invierno que con lógica difusa. Esta técnica puede ser una herramienta para el estudio y monitoreo no invasivo de las poblaciones bajo manej | es_MX |
dc.language.iso | eng | es_MX |
dc.publisher | Universidad de Guanajuato | es_MX |
dc.rights | info:eu-repo/semantics/openAccess | es_MX |
dc.source | Acta Universitaria: Multidisciplinary Scientific Journal. Vol. 29 (2019) | es_MX |
dc.title | White-tailed deer sex identification from faecal DNA and pellet morphometry by neural network and fuzzy logic analyses | es_MX |
dc.title.alternative | Identificación del sexo de venado cola-blanca por ADN fecal y morfometría de los pellets mediante análisis de redes neuronales y lógica difusa | es_MX |
dc.type | info:eu-repo/semantics/article | es_MX |
dc.creator.id | info:eu-repo/dai/mx/cvu/82994 | es_MX |
dc.subject.cti | info:eu-repo/classification/cti/2 | es_MX |
dc.subject.keywords | Faecal DNA | es_MX |
dc.subject.keywords | Faecal morphometry | es_MX |
dc.subject.keywords | Sex classification function | es_MX |
dc.subject.keywords | SRY gene | es_MX |
dc.subject.keywords | White-tailed deer | es_MX |
dc.subject.keywords | ADN fecal | es_MX |
dc.subject.keywords | Morfometría fecal | es_MX |
dc.subject.keywords | Función de clasificación de sexo | es_MX |
dc.subject.keywords | Gen SRY; | es_MX |
dc.subject.keywords | Venado cola-blanca | es_MX |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_MX |
dc.creator.two | Sonia Gallina | - |
dc.creator.three | LUIS MIGUEL CORREA CASARIN | - |
dc.creator.four | GASPAR MANUEL PARRA BRACAMONTE | - |
dc.creator.five | ISAIAS CHAIREZ HERNANDEZ | - |
dc.creator.idtwo | info:eu-repo/dai/mx/orcid/0000-0002-8941-5186 | es_MX |
dc.creator.idthree | info:eu-repo/dai/mx/cvu/690061 | es_MX |
dc.creator.idfour | info:eu-repo/dai/mx/cvu/201219 | es_MX |
dc.creator.idfive | info:eu-repo/dai/mx/cvu/80217 | es_MX |
dc.description.abstractEnglish | Knowing the sex of white-tailed deer (Odocoileus virginianus) individuals canprovide information to set harvesting rates and management activities. Therefore, the aim of this study is to identify the sex through classification function by using faecal pellet morphometry. Faeces were collected for 12 months in Durango, Mexico; their morphometric variables were measured, the faecal DNA was extracted, and the SRY gene marker was amplified to identify sex. A neural network and fuzzy logic sex classificationfunctions were obtained. The outputs were validated with the SRY gene results. Data from adults in the winter were used to obtain the classification functions. Classification functions could accurately classify sex in 94.4% with neural networks and 86.9% with fuzzy logic. The neural network classified more accurately the sex of adultwhite-tailed deer studied in winter with the faecal pellets morphometry than with the fuzzy logic analysis. This technique can be a tool for non-invasive studies and monitoring of populations. | en |
Appears in Collections: | Revista Acta Universitaria |
Files in This Item:
File | Description | Size | Format | |
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White-tailed deer sex identification from faecal DNA and pellet morphometry by neural network and fuzzy logic analyses.pdf | 788.42 kB | Adobe PDF | View/Open |
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