Determination of maize hardness by biospeckle and fuzzy granularity
- Autores
- Weber, Christian; Dai Pra, Ana L.; Passoni, Lucía I.; Rabal, Héctor J.; Trivi, Marcelo Ricardo; 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.
- Materia
-
Óptica, Acústica
Ciencias Agrarias
laser
biospeckle
dry milling
maize hardness - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- http://creativecommons.org/licenses/by/4.0/
- Repositorio
- Institución
- Comisión de Investigaciones Científicas de la Provincia de Buenos Aires
- OAI Identificador
- oai:digital.cic.gba.gob.ar:11746/5872
Ver los metadatos del registro completo
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Determination of maize hardness by biospeckle and fuzzy granularityWeber, ChristianDai Pra, Ana L.Passoni, Lucía I.Rabal, Héctor J.Trivi, Marcelo RicardoPoggio Aguerre, Guillermo J.Óptica, AcústicaCiencias Agrariaslaserbiospeckledry millingmaize hardnessIn 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.Wiley2014-09info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttps://digital.cic.gba.gob.ar/handle/11746/5872enginfo:eu-repo/semantics/altIdentifier/doi/10.1002/fsn3.130info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by/4.0/reponame:CIC Digital (CICBA)instname:Comisión de Investigaciones Científicas de la Provincia de Buenos Airesinstacron:CICBA2025-09-29T13:40:12Zoai:digital.cic.gba.gob.ar:11746/5872Institucionalhttp://digital.cic.gba.gob.arOrganismo científico-tecnológicoNo correspondehttp://digital.cic.gba.gob.ar/oai/snrdmarisa.degiusti@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:94412025-09-29 13:40:12.515CIC Digital (CICBA) - Comisión de Investigaciones Científicas de la Provincia de Buenos Airesfalse |
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 Óptica, Acústica Ciencias Agrarias laser biospeckle dry milling 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, Lucía I. Rabal, Héctor J. Trivi, Marcelo Ricardo Poggio Aguerre, Guillermo J. |
author |
Weber, Christian |
author_facet |
Weber, Christian Dai Pra, Ana L. Passoni, Lucía I. Rabal, Héctor J. Trivi, Marcelo Ricardo Poggio Aguerre, Guillermo J. |
author_role |
author |
author2 |
Dai Pra, Ana L. Passoni, Lucía I. Rabal, Héctor J. Trivi, Marcelo Ricardo Poggio Aguerre, Guillermo J. |
author2_role |
author author author author author |
dc.subject.none.fl_str_mv |
Óptica, Acústica Ciencias Agrarias laser biospeckle dry milling maize hardness |
topic |
Óptica, Acústica Ciencias Agrarias laser biospeckle dry milling maize hardness |
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. |
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 |
https://digital.cic.gba.gob.ar/handle/11746/5872 |
url |
https://digital.cic.gba.gob.ar/handle/11746/5872 |
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 |
dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/4.0/ |
eu_rights_str_mv |
openAccess |
rights_invalid_str_mv |
http://creativecommons.org/licenses/by/4.0/ |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Wiley |
publisher.none.fl_str_mv |
Wiley |
dc.source.none.fl_str_mv |
reponame:CIC Digital (CICBA) instname:Comisión de Investigaciones Científicas de la Provincia de Buenos Aires instacron:CICBA |
reponame_str |
CIC Digital (CICBA) |
collection |
CIC Digital (CICBA) |
instname_str |
Comisión de Investigaciones Científicas de la Provincia de Buenos Aires |
instacron_str |
CICBA |
institution |
CICBA |
repository.name.fl_str_mv |
CIC Digital (CICBA) - Comisión de Investigaciones Científicas de la Provincia de Buenos Aires |
repository.mail.fl_str_mv |
marisa.degiusti@sedici.unlp.edu.ar |
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1844618607943745536 |
score |
13.070432 |