Classification of Food Spices by Proximate Content: Principal Component, Cluster, Meta-Analyses

Proximate composition of six food spices commonly used in South-East Nigeria are classified by principal component analysis (PCAs) of constituents and spices cluster analysis (CAs). Samples are grouped into two classes. Compositional PCA and spice CA permit classificating them and group the similar...

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Detalles Bibliográficos
Autor: Torrens Zaragozá, Francisco
Tipo de recurso: artículo
Fecha de publicación:2016
País:España
Institución:Universidad Católica de Valencia San Vicente Mártir
Repositorio:RIUCV. Repositorio de la Universidad Católica de Valencia San Vicente Mártir
Idioma:inglés
OAI Identifier:oai:riucv.ucv.es:20.500.12466/237
Acceso en línea:http://hdl.handle.net/20.500.12466/237
Access Level:acceso abierto
Palabra clave:Nutrition
Meta-analysis
Food spices
Nutrición
Metaanálisis
Especias alimenticias
3309 Tecnología de Los Alimentos
3206.08 Nutrientes
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spelling Classification of Food Spices by Proximate Content: Principal Component, Cluster, Meta-AnalysesTorrens Zaragozá, FranciscoNutritionMeta-analysisFood spicesNutriciónMetaanálisisEspecias alimenticias3309 Tecnología de Los Alimentos3206.08 NutrientesProximate composition of six food spices commonly used in South-East Nigeria are classified by principal component analysis (PCAs) of constituents and spices cluster analysis (CAs). Samples are grouped into two classes. Compositional PCA and spice CA permit classificating them and group the similar ones. The first PCA axis explains 61% of the variance; first two, 93%; first three, 99; etc. Different behaviour of species depends on ash, fibre, fat, moisture, etc. Macronutrients (protein, carbohydrate, fat) contents are adequate. Carbohydrate amounts are high. Fat quantities are moderate. Fat is closer to protein than to carbohydrate.Se clasifica la composición de los constituyentes principales de seis especias alimenticias comúnmente usadas en el sudeste de Nigeria por análisis de componentes principales (ACPs) de los constituyentes y análisis de agregados (AAs) de especias. Las muestras se agrupan en dos clases. El ACP de composición y AA de especias permiten clasificarlas y agruparlas según se asemejen. El primer eje ACP explica el 61% de la varianza, los dos primeros, el 93%, los tres primeros, el 99%, etc. El diferente comportamiento de las especias depende de la ceniza, fibra, grasa, humedad, etc. Los contenidos de macronutrientes (proteína, carbohidrato, grasa) son adecuados. Las cantidades de carbohidrato son altas. Las cantidades de grasa son moderadas. La grasa está más cerca de la proteína que del carbohidrato.20192019-10-2320162016-03-0120162016-03-01journal articlehttp://purl.org/coar/resource_type/c_6501info:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/20.500.12466/237reponame:RIUCV. Repositorio de la Universidad Católica de Valencia San Vicente Mártirinstname:Universidad Católica de Valencia San Vicente MártirInglésengopen accesshttp://purl.org/coar/access_right/c_abf2Attribution-NonCommercial-NoDerivatives 4.0 Internacionalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessoai:riucv.ucv.es:20.500.12466/2372026-06-19T08:32:07Z
dc.title.none.fl_str_mv Classification of Food Spices by Proximate Content: Principal Component, Cluster, Meta-Analyses
title Classification of Food Spices by Proximate Content: Principal Component, Cluster, Meta-Analyses
spellingShingle Classification of Food Spices by Proximate Content: Principal Component, Cluster, Meta-Analyses
Torrens Zaragozá, Francisco
Nutrition
Meta-analysis
Food spices
Nutrición
Metaanálisis
Especias alimenticias
3309 Tecnología de Los Alimentos
3206.08 Nutrientes
title_short Classification of Food Spices by Proximate Content: Principal Component, Cluster, Meta-Analyses
title_full Classification of Food Spices by Proximate Content: Principal Component, Cluster, Meta-Analyses
title_fullStr Classification of Food Spices by Proximate Content: Principal Component, Cluster, Meta-Analyses
title_full_unstemmed Classification of Food Spices by Proximate Content: Principal Component, Cluster, Meta-Analyses
title_sort Classification of Food Spices by Proximate Content: Principal Component, Cluster, Meta-Analyses
dc.creator.none.fl_str_mv Torrens Zaragozá, Francisco
author Torrens Zaragozá, Francisco
author_facet Torrens Zaragozá, Francisco
author_role author
dc.contributor.none.fl_str_mv
dc.subject.none.fl_str_mv Nutrition
Meta-analysis
Food spices
Nutrición
Metaanálisis
Especias alimenticias
3309 Tecnología de Los Alimentos
3206.08 Nutrientes
topic Nutrition
Meta-analysis
Food spices
Nutrición
Metaanálisis
Especias alimenticias
3309 Tecnología de Los Alimentos
3206.08 Nutrientes
description Proximate composition of six food spices commonly used in South-East Nigeria are classified by principal component analysis (PCAs) of constituents and spices cluster analysis (CAs). Samples are grouped into two classes. Compositional PCA and spice CA permit classificating them and group the similar ones. The first PCA axis explains 61% of the variance; first two, 93%; first three, 99; etc. Different behaviour of species depends on ash, fibre, fat, moisture, etc. Macronutrients (protein, carbohydrate, fat) contents are adequate. Carbohydrate amounts are high. Fat quantities are moderate. Fat is closer to protein than to carbohydrate.
publishDate 2016
dc.date.none.fl_str_mv 2016
2016-03-01
2016
2016-03-01
2019
2019-10-23
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv http://hdl.handle.net/20.500.12466/237
url http://hdl.handle.net/20.500.12466/237
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution-NonCommercial-NoDerivatives 4.0 Internacional
http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution-NonCommercial-NoDerivatives 4.0 Internacional
http://creativecommons.org/licenses/by-nc-nd/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:RIUCV. Repositorio de la Universidad Católica de Valencia San Vicente Mártir
instname:Universidad Católica de Valencia San Vicente Mártir
instname_str Universidad Católica de Valencia San Vicente Mártir
reponame_str RIUCV. Repositorio de la Universidad Católica de Valencia San Vicente Mártir
collection RIUCV. Repositorio de la Universidad Católica de Valencia San Vicente Mártir
repository.name.fl_str_mv
repository.mail.fl_str_mv
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