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Artículo

Simplified tea classification based on a reduced chemical composition profile via successive projections algorithm linear discriminant analysis (SPA-LDA)

Gonçalves Dias Diniz, Paulo Henrique; Pistonesi, Marcelo Fabian; Álvarez, Mónica Beatriz; Fernández Band, Beatriz SusanaIcon ; Ugulino de Araújo, Mário César
Fecha de publicación: 03/2015
Editorial: Academic Press Inc Elsevier Science
Revista: Journal Of Food Composition And Analysis
ISSN: 0889-1575
Idioma: Inglés
Tipo de recurso: Artículo publicado
Clasificación temática:
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Resumen

In this study, several possible approaches for simultaneous discrimination of teas based on a linear discriminant analysis with variables selected by the successive projections algorithm (SPA-LDA), featuring selection from the chemical composition according to variety (black or green tea) and geographical origin (Argentina or Sri Lanka), are explored. Chemical composition (moisture, ash, caffeine, fluoride, polyphenols, and 15 elements from both tea leaves and infusions) was used as input data for identification of the differentiating characteristics of tea samples. Thus, a strategy that allows tea discrimination using a reduced number of chemical parameters was developed. SIMCA (softindependent modeling of class analogy) and PLS-DA (partial least squares-discriminant analysis) were used along with SPA-LDA for comparison. The elemental fingerprint (chemical signature) can be used for identifying the variety and origin of the tea, and SPA-LDA provided the most successful result (100% correct classification), despite having selected just three chemical parameters (namely K, Al, and Mg). The result is extremely positive from the viewpoint of chemical analyses, because quantifications made using fewer elements naturally provide simpler, faster and less expensive methods.
Palabras clave: Camellia Sinensis , Tea Leaves , Tea Infusions , Food Composition , Food Analysis , Elemental Fingerprint , Classification , Spa-Lda Feature Selection
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info:eu-repo/semantics/openAccess Excepto donde se diga explícitamente, este item se publica bajo la siguiente descripción: Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Unported (CC BY-NC-SA 2.5)
Identificadores
URI: http://hdl.handle.net/11336/40474
DOI: http://dx.doi.org/10.1016/j.jfca.2014.11.012
URL: https://www.sciencedirect.com/science/article/pii/S0889157514002130
Colecciones
Articulos(INQUISUR)
Articulos de INST.DE QUIMICA DEL SUR
Citación
Gonçalves Dias Diniz, Paulo Henrique; Pistonesi, Marcelo Fabian; Álvarez, Mónica Beatriz; Fernández Band, Beatriz Susana; Ugulino de Araújo, Mário César; Simplified tea classification based on a reduced chemical composition profile via successive projections algorithm linear discriminant analysis (SPA-LDA); Academic Press Inc Elsevier Science; Journal Of Food Composition And Analysis; 39; 3-2015; 103-110
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