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Article . 2012
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Multivariate characterization of "Argentinean Misletoe", Ligaria cuneifolia (Loranthaceae) according to their mineral nutrient composition

Authors: Giménez, María Cecilia; Hidalgo, Melisa Jazmin; Petenatti, Elisa Margarita; del Vitto, Luis Angel; Marchevsky, Eduardo Jorge; Pellerano, Roberto Gerardo;

Multivariate characterization of "Argentinean Misletoe", Ligaria cuneifolia (Loranthaceae) according to their mineral nutrient composition

Abstract

El objetivo de este estudio fue caracterizar muestras de Ligaria cuneifolia recolectadas en tres zonas de la región noreste de Argentina, durante dos períodos de muestreo. En este trabajo los autores proponen un modelo matemático para la búsqueda de asociaciones entre el contenido mineral y otros factores como el origen geográfico o el periodo de muestreo. El monitoreo de las concentraciones de los elementos minerales, como método para el reconocimiento de patrones, es una herramienta prometedora en la caracterización y / o estandarización de fitofármacos. En el presente trabajo se pudieron detectar cantidades medibles de Al, Ca, Co, Cr, Cu, Fe, K, Li, Mg, Mn, Na, P, Sr y Zn que fueron detectadas en muestras fitomedicinales de L. cuneifolia por espectroscopía de emisión óptica de plasma acoplado inductivamente (ICP-OES). Finalmente, esta metodología permitió realizar determinaciones confiables del contenido mineral en el control de calidad farmacéutica de plantas medicinales.

The aim of this study was to characterize samples of Ligaria cuneifolia collected from three areas of the north-east region of Argentina, during two sampling periods. In this work, the authors propose a mathematical model for searching associations among mineral contents and other factors such us geographic origin or sampling period. Mineral monitoring as a pattern recognition method is a promising tool in the characterization and/or standardization of phytomedicines. In the present work measurable amounts of Al, Ca, Co, Cr, Cu, Fe, K, Li, Mg, Mn, Na, P, Sr, and Zn were detected in phytopharmaceutical derivatives of L. cuneifolia by inductively coupled plasma optical emission spectrometry (ICP-OES). Finally, this methodology allows reliable determinations of mineral content in pharmaceutical quality control of medicinal plants.

Fil: Marchevsky, Eduardo Jorge. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Luis. Instituto de Química de San Luis. Universidad Nacional de San Luis. Facultad de Química, Bioquímica y Farmacia. Instituto de Química de San Luis; Argentina

Fil: Pellerano, Roberto Gerardo. Universidad Nacional de La Pampa. Facultad de Ciencias Exactas y Naturales. Departamento de Química; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina

Fil: del Vitto, Luis Angel. Universidad Nacional de San Luis. Facultad de Química, Bioquímica y Farmacia; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina

Fil: Hidalgo, Melisa Jazmin. Universidad Nacional del Chaco Austral; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina

Fil: Petenatti, Elisa Margarita. Universidad Nacional de San Luis. Facultad de Química, Bioquímica y Farmacia. Departamento de Farmacia; Argentina

Fil: Giménez, María Cecilia. Universidad Nacional del Chaco Austral; Argentina

Country
Argentina
Keywords

PCA, PATTERN, ICP-OES, https://purl.org/becyt/ford/1.4, COMPOSITION, https://purl.org/becyt/ford/1, MINERAL

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green