Development of a Backpropagation Neural Network to Assist Cell Identification in Herbivore Diet at the Semiarid Chaco of North-West Argentina

Autores
Costaguta, Rosanna; Larcher, Ledda
Año de publicación
2002
Idioma
español castellano
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
Raising goats is a strong component of regional economies and a main activity of little farmers in Argentina. Knowing the diet is fundamental to correct nutritional lacks resulting from grazing native species, as it will help to design management strategies both for the native forage resource and for the nutritional state of the animal. This fact has a preponderant relevance when goat production is done at natural areas. Microhistology is one of the more frequently used methodology to determine the botanical composition of herbivorous diet. The specialist working at a microscope, according to his training and experience, can identify the species taken by the animal and to which those cells belong. Neural network approaches are suited for recognition problems, this article presents a backpropagation neural network initially trained to identify the four most significant vegetal species found in goat diet that graze freely in the Semiarid Chaco of North-West Argentina.
Sociedad Argentina de Informática e Investigación Operativa
Materia
Ciencias Informáticas
microhistology
neural network
botanical composition
herbivore diet
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/185599
Acceder
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spelling Development of a Backpropagation Neural Network to Assist Cell Identification in Herbivore Diet at the Semiarid Chaco of North-West ArgentinaCostaguta, RosannaLarcher, LeddaCiencias Informáticasmicrohistologyneural networkbotanical compositionherbivore dietRaising goats is a strong component of regional economies and a main activity of little farmers in Argentina. Knowing the diet is fundamental to correct nutritional lacks resulting from grazing native species, as it will help to design management strategies both for the native forage resource and for the nutritional state of the animal. This fact has a preponderant relevance when goat production is done at natural areas. Microhistology is one of the more frequently used methodology to determine the botanical composition of herbivorous diet. The specialist working at a microscope, according to his training and experience, can identify the species taken by the animal and to which those cells belong. Neural network approaches are suited for recognition problems, this article presents a backpropagation neural network initially trained to identify the four most significant vegetal species found in goat diet that graze freely in the Semiarid Chaco of North-West Argentina.Sociedad Argentina de Informática e Investigación Operativa2002info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf272-277http://sedici.unlp.edu.ar/handle/10915/185599spainfo:eu-repo/semantics/altIdentifier/issn/1660-1079info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-11-05T13:29:19Zoai:sedici.unlp.edu.ar:10915/185599Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-11-05 13:29:20.004SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Development of a Backpropagation Neural Network to Assist Cell Identification in Herbivore Diet at the Semiarid Chaco of North-West Argentina
title Development of a Backpropagation Neural Network to Assist Cell Identification in Herbivore Diet at the Semiarid Chaco of North-West Argentina
spellingShingle Development of a Backpropagation Neural Network to Assist Cell Identification in Herbivore Diet at the Semiarid Chaco of North-West Argentina
Costaguta, Rosanna
Ciencias Informáticas
microhistology
neural network
botanical composition
herbivore diet
title_short Development of a Backpropagation Neural Network to Assist Cell Identification in Herbivore Diet at the Semiarid Chaco of North-West Argentina
title_full Development of a Backpropagation Neural Network to Assist Cell Identification in Herbivore Diet at the Semiarid Chaco of North-West Argentina
title_fullStr Development of a Backpropagation Neural Network to Assist Cell Identification in Herbivore Diet at the Semiarid Chaco of North-West Argentina
title_full_unstemmed Development of a Backpropagation Neural Network to Assist Cell Identification in Herbivore Diet at the Semiarid Chaco of North-West Argentina
title_sort Development of a Backpropagation Neural Network to Assist Cell Identification in Herbivore Diet at the Semiarid Chaco of North-West Argentina
dc.creator.none.fl_str_mv Costaguta, Rosanna
Larcher, Ledda
author Costaguta, Rosanna
author_facet Costaguta, Rosanna
Larcher, Ledda
author_role author
author2 Larcher, Ledda
author2_role author
dc.subject.none.fl_str_mv Ciencias Informáticas
microhistology
neural network
botanical composition
herbivore diet
topic Ciencias Informáticas
microhistology
neural network
botanical composition
herbivore diet
dc.description.none.fl_txt_mv Raising goats is a strong component of regional economies and a main activity of little farmers in Argentina. Knowing the diet is fundamental to correct nutritional lacks resulting from grazing native species, as it will help to design management strategies both for the native forage resource and for the nutritional state of the animal. This fact has a preponderant relevance when goat production is done at natural areas. Microhistology is one of the more frequently used methodology to determine the botanical composition of herbivorous diet. The specialist working at a microscope, according to his training and experience, can identify the species taken by the animal and to which those cells belong. Neural network approaches are suited for recognition problems, this article presents a backpropagation neural network initially trained to identify the four most significant vegetal species found in goat diet that graze freely in the Semiarid Chaco of North-West Argentina.
Sociedad Argentina de Informática e Investigación Operativa
description Raising goats is a strong component of regional economies and a main activity of little farmers in Argentina. Knowing the diet is fundamental to correct nutritional lacks resulting from grazing native species, as it will help to design management strategies both for the native forage resource and for the nutritional state of the animal. This fact has a preponderant relevance when goat production is done at natural areas. Microhistology is one of the more frequently used methodology to determine the botanical composition of herbivorous diet. The specialist working at a microscope, according to his training and experience, can identify the species taken by the animal and to which those cells belong. Neural network approaches are suited for recognition problems, this article presents a backpropagation neural network initially trained to identify the four most significant vegetal species found in goat diet that graze freely in the Semiarid Chaco of North-West Argentina.
publishDate 2002
dc.date.none.fl_str_mv 2002
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
info:eu-repo/semantics/publishedVersion
Objeto de conferencia
http://purl.org/coar/resource_type/c_5794
info:ar-repo/semantics/documentoDeConferencia
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status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/185599
url http://sedici.unlp.edu.ar/handle/10915/185599
dc.language.none.fl_str_mv spa
language spa
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/issn/1660-1079
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.format.none.fl_str_mv application/pdf
272-277
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repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
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