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.

Multivariate optimization of an analytical method for the analysis of Abruzzo white wines by ICP OES

Ruggieri F.
;
D'Archivio A. A.;Foschi M.;
2020-01-01

Abstract

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.
File in questo prodotto:
File Dimensione Formato  
Anal. Methods_2020_12_2772–2778.pdf

non disponibili

Tipologia: Documento in Versione Editoriale
Licenza: Creative commons
Dimensione 415.56 kB
Formato Adobe PDF
415.56 kB Adobe PDF   Visualizza/Apri   Richiedi una copia
Pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11697/165411
Citazioni
  • ???jsp.display-item.citation.pmc??? 1
  • Scopus 7
  • ???jsp.display-item.citation.isi??? 6
social impact