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Multivariate optimization of an analytical method for the analysis of Abruzzo white wines by ICP OES.
Ruggieri, Fabrizio; D'Archivio, Angelo Antonio; Foschi, Martina; Maggi, Maria Anna.
  • Ruggieri F; Dipartimento di Scienze Fisiche e Chimiche, Università degli Studi dell'Aquila, Via Vetoio, 67010 Coppito, L'Aquila, Italy. fabrizio.ruggieri@univaq.it.
  • D'Archivio AA; Dipartimento di Scienze Fisiche e Chimiche, Università degli Studi dell'Aquila, Via Vetoio, 67010 Coppito, L'Aquila, Italy. fabrizio.ruggieri@univaq.it.
  • Foschi M; Dipartimento di Scienze Fisiche e Chimiche, Università degli Studi dell'Aquila, Via Vetoio, 67010 Coppito, L'Aquila, Italy. fabrizio.ruggieri@univaq.it.
  • Maggi MA; Hortus Novus, Via Aldo Moro 28 D, 67100 L'Aquila, Italy.
Anal Methods ; 12(21): 2772-2778, 2020 06 04.
Article en En | MEDLINE | ID: mdl-32930308
An inductively coupled plasma-optical emission spectrometry (ICP OES) method was optimized and applied for determining the concentration of 14 elements (Ba, Ca, Co, Cu, Fe, K, Li, Mg, Mn, Na, Ni, Sr, V, and Zn) in three representative white wines of the Abruzzo region (Italy). In order to optimise an ICP OES method a three level factorial design for three variables was used. The intensity of the emission lines for analytes was simultaneously maximised by using Derringer's desirability function. Using this approach, the optimal experimental conditions for wine analysis of 0.48 L min-1, 1.8 mL min-1 and 0.5 L min-1 for the nebulizer gas flow rate, sample uptake rate and auxiliary gas flow rate respectively were achieved. A total of 46 white wine samples of the three varieties were analysed by using the optimised experimental conditions. Linear Discriminant Analysis (LDA) and Partial Least Squares Linear Discriminant Analysis (PLS LDA) allowed an acceptable classification of the three varietal samples.

Texto completo: 1 Banco de datos: MEDLINE Idioma: En Año: 2020 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Idioma: En Año: 2020 Tipo del documento: Article