Determination of maize hardness by biospeckle and fuzzy granularity

Autores
Weber, Christian; Dai Pra, Ana L.; Passoni, Lucia I.; Rabal, Hector Jorge; Trivi, Marcelo; Poggio Aguerre, Guillermo J.
Año de publicación
2014
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
In recent years there has been renewed interest in the development of novel grain classification methods that could complement traditional empirical tests. A speckle pattern occurs when a laser beam illuminates an optically rough surface that flickers when the object is active and is called biospeckle. In this work, we use laser biospeckle to classify maize (Zea mays L.) kernel hardness. A series of grains of three types of maize were cut and illuminated by a laser. A series of images were then registered, stored, and processed. These were compared with results obtained by floating test. The laser speckle technique was effective in discriminating the grains based on the presence of floury or vitreous endosperm and could be considered a feasible alternative to traditional floating methods. The results indicate that this methodology can distinguish floury and vitreous grains. Moreover, the assay showed higher discrimination capability than traditional tests. It could be potentially useful for maize classification and to increase the efficiency of processing dry milling corn.
Fil: Weber, Christian. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico La Plata. Centro de Investigaciones Opticas (i); Argentina. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas; Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Agrarias y Forestales; Argentina
Fil: Dai Pra, Ana L.. Universidad Nacional de Mar del Plata. Facultad de Ingeniería; Argentina
Fil: Passoni, Lucia I.. Universidad Nacional de Mar del Plata. Facultad de Ingeniería; Argentina
Fil: Rabal, Hector Jorge. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico La Plata. Centro de Investigaciones Opticas (i); Argentina. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas; Argentina. Universidad Nacional de La Plata. Facultad de Ingenieria; Argentina
Fil: Trivi, Marcelo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico La Plata. Centro de Investigaciones Opticas (i); Argentina. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas; Argentina. Universidad Nacional de La Plata. Facultad de Ingenieria; Argentina
Fil: Poggio Aguerre, Guillermo J.. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico La Plata. Centro de Investigaciones Opticas (i); Argentina
Materia
BIOSPECKLE
DRY MILLING
LASER
MAIZE HARDNESS
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/12030
Acceder
id CONICETDig_10fbbfa55848c16086aa5cddfa708213
oai_identifier_str oai:ri.conicet.gov.ar:11336/12030
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Determination of maize hardness by biospeckle and fuzzy granularityWeber, ChristianDai Pra, Ana L.Passoni, Lucia I.Rabal, Hector JorgeTrivi, MarceloPoggio Aguerre, Guillermo J.BIOSPECKLEDRY MILLINGLASERMAIZE HARDNESShttps://purl.org/becyt/ford/4.1https://purl.org/becyt/ford/4In recent years there has been renewed interest in the development of novel grain classification methods that could complement traditional empirical tests. A speckle pattern occurs when a laser beam illuminates an optically rough surface that flickers when the object is active and is called biospeckle. In this work, we use laser biospeckle to classify maize (Zea mays L.) kernel hardness. A series of grains of three types of maize were cut and illuminated by a laser. A series of images were then registered, stored, and processed. These were compared with results obtained by floating test. The laser speckle technique was effective in discriminating the grains based on the presence of floury or vitreous endosperm and could be considered a feasible alternative to traditional floating methods. The results indicate that this methodology can distinguish floury and vitreous grains. Moreover, the assay showed higher discrimination capability than traditional tests. It could be potentially useful for maize classification and to increase the efficiency of processing dry milling corn.Fil: Weber, Christian. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico La Plata. Centro de Investigaciones Opticas (i); Argentina. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas; Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Agrarias y Forestales; ArgentinaFil: Dai Pra, Ana L.. Universidad Nacional de Mar del Plata. Facultad de Ingeniería; ArgentinaFil: Passoni, Lucia I.. Universidad Nacional de Mar del Plata. Facultad de Ingeniería; ArgentinaFil: Rabal, Hector Jorge. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico La Plata. Centro de Investigaciones Opticas (i); Argentina. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas; Argentina. Universidad Nacional de La Plata. Facultad de Ingenieria; ArgentinaFil: Trivi, Marcelo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico La Plata. Centro de Investigaciones Opticas (i); Argentina. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas; Argentina. Universidad Nacional de La Plata. Facultad de Ingenieria; ArgentinaFil: Poggio Aguerre, Guillermo J.. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico La Plata. Centro de Investigaciones Opticas (i); ArgentinaWiley2014-09info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/12030Weber, Christian; Dai Pra, Ana L.; Passoni, Lucia I.; Rabal, Hector Jorge; Trivi, Marcelo; et al.; Determination of maize hardness by biospeckle and fuzzy granularity; Wiley; Food Science & Nutrition; 2; 5; 9-2014; 557–5642048-7177enginfo:eu-repo/semantics/altIdentifier/doi/10.1002/fsn3.130info:eu-repo/semantics/altIdentifier/url/http://onlinelibrary.wiley.com/doi/10.1002/fsn3.130/fullinfo:eu-repo/semantics/altIdentifier/url/https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4237485/info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:37:59Zoai:ri.conicet.gov.ar:11336/12030instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 09:38:00.095CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Determination of maize hardness by biospeckle and fuzzy granularity
title Determination of maize hardness by biospeckle and fuzzy granularity
spellingShingle Determination of maize hardness by biospeckle and fuzzy granularity
Weber, Christian
BIOSPECKLE
DRY MILLING
LASER
MAIZE HARDNESS
title_short Determination of maize hardness by biospeckle and fuzzy granularity
title_full Determination of maize hardness by biospeckle and fuzzy granularity
title_fullStr Determination of maize hardness by biospeckle and fuzzy granularity
title_full_unstemmed Determination of maize hardness by biospeckle and fuzzy granularity
title_sort Determination of maize hardness by biospeckle and fuzzy granularity
dc.creator.none.fl_str_mv Weber, Christian
Dai Pra, Ana L.
Passoni, Lucia I.
Rabal, Hector Jorge
Trivi, Marcelo
Poggio Aguerre, Guillermo J.
author Weber, Christian
author_facet Weber, Christian
Dai Pra, Ana L.
Passoni, Lucia I.
Rabal, Hector Jorge
Trivi, Marcelo
Poggio Aguerre, Guillermo J.
author_role author
author2 Dai Pra, Ana L.
Passoni, Lucia I.
Rabal, Hector Jorge
Trivi, Marcelo
Poggio Aguerre, Guillermo J.
author2_role author
author
author
author
author
dc.subject.none.fl_str_mv BIOSPECKLE
DRY MILLING
LASER
MAIZE HARDNESS
topic BIOSPECKLE
DRY MILLING
LASER
MAIZE HARDNESS
purl_subject.fl_str_mv https://purl.org/becyt/ford/4.1
https://purl.org/becyt/ford/4
dc.description.none.fl_txt_mv In recent years there has been renewed interest in the development of novel grain classification methods that could complement traditional empirical tests. A speckle pattern occurs when a laser beam illuminates an optically rough surface that flickers when the object is active and is called biospeckle. In this work, we use laser biospeckle to classify maize (Zea mays L.) kernel hardness. A series of grains of three types of maize were cut and illuminated by a laser. A series of images were then registered, stored, and processed. These were compared with results obtained by floating test. The laser speckle technique was effective in discriminating the grains based on the presence of floury or vitreous endosperm and could be considered a feasible alternative to traditional floating methods. The results indicate that this methodology can distinguish floury and vitreous grains. Moreover, the assay showed higher discrimination capability than traditional tests. It could be potentially useful for maize classification and to increase the efficiency of processing dry milling corn.
Fil: Weber, Christian. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico La Plata. Centro de Investigaciones Opticas (i); Argentina. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas; Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Agrarias y Forestales; Argentina
Fil: Dai Pra, Ana L.. Universidad Nacional de Mar del Plata. Facultad de Ingeniería; Argentina
Fil: Passoni, Lucia I.. Universidad Nacional de Mar del Plata. Facultad de Ingeniería; Argentina
Fil: Rabal, Hector Jorge. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico La Plata. Centro de Investigaciones Opticas (i); Argentina. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas; Argentina. Universidad Nacional de La Plata. Facultad de Ingenieria; Argentina
Fil: Trivi, Marcelo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico La Plata. Centro de Investigaciones Opticas (i); Argentina. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas; Argentina. Universidad Nacional de La Plata. Facultad de Ingenieria; Argentina
Fil: Poggio Aguerre, Guillermo J.. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico La Plata. Centro de Investigaciones Opticas (i); Argentina
description In recent years there has been renewed interest in the development of novel grain classification methods that could complement traditional empirical tests. A speckle pattern occurs when a laser beam illuminates an optically rough surface that flickers when the object is active and is called biospeckle. In this work, we use laser biospeckle to classify maize (Zea mays L.) kernel hardness. A series of grains of three types of maize were cut and illuminated by a laser. A series of images were then registered, stored, and processed. These were compared with results obtained by floating test. The laser speckle technique was effective in discriminating the grains based on the presence of floury or vitreous endosperm and could be considered a feasible alternative to traditional floating methods. The results indicate that this methodology can distinguish floury and vitreous grains. Moreover, the assay showed higher discrimination capability than traditional tests. It could be potentially useful for maize classification and to increase the efficiency of processing dry milling corn.
publishDate 2014
dc.date.none.fl_str_mv 2014-09
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/12030
Weber, Christian; Dai Pra, Ana L.; Passoni, Lucia I.; Rabal, Hector Jorge; Trivi, Marcelo; et al.; Determination of maize hardness by biospeckle and fuzzy granularity; Wiley; Food Science & Nutrition; 2; 5; 9-2014; 557–564
2048-7177
url http://hdl.handle.net/11336/12030
identifier_str_mv Weber, Christian; Dai Pra, Ana L.; Passoni, Lucia I.; Rabal, Hector Jorge; Trivi, Marcelo; et al.; Determination of maize hardness by biospeckle and fuzzy granularity; Wiley; Food Science & Nutrition; 2; 5; 9-2014; 557–564
2048-7177
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1002/fsn3.130
info:eu-repo/semantics/altIdentifier/url/http://onlinelibrary.wiley.com/doi/10.1002/fsn3.130/full
info:eu-repo/semantics/altIdentifier/url/https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4237485/
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Wiley
publisher.none.fl_str_mv Wiley
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.070432

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