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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| 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 |
| Sumario: | 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. |
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