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...
| Autor: | |
|---|---|
| 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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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 |
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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/ |
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openAccess |
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application/pdf |
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reponame:RIUCV. Repositorio de la Universidad Católica de Valencia San Vicente Mártir instname:Universidad Católica de Valencia San Vicente Mártir |
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Universidad Católica de Valencia San Vicente Mártir |
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RIUCV. Repositorio de la Universidad Católica de Valencia San Vicente Mártir |
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RIUCV. Repositorio de la Universidad Católica de Valencia San Vicente Mártir |
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