Analysis and comparison of SIMCA models for denominations of origin of wines from de Canary Islands (Spain) builds by means of their trace and ultratrace metals content

被引:37
作者
Barbaste, M
Medina, B
Sarabia, L
Ortiz, MC
Pérez-Trujillo, JP
机构
[1] Univ Burgos, Dept Math & Computat, Burgos 09001, Spain
[2] DGCCRF, F-33405 Talence, France
[3] CNRS, UMR 5034, F-64053 Pau, France
[4] Univ Burgos, Dept Chem, Burgos 09001, Spain
[5] Univ La Laguna, Fac Chem, Dept Analyt Chem Nutr & Food Sci, San Cristobal la Laguna 38201, Tenerife, Spain
关键词
SIMCA models; model similarity; cluster analysis; canarian wines; trace and ultratrace metals; ICP-MS;
D O I
10.1016/S0003-2670(02)00979-0
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
Various models have been constructed and analysed for eight denominations of origin of wines bottled in the Canary Islands, using their content in different metals, with the Soft Independent Modelling Class Analogy (SIMCA) technique. The metals were grouped in three blocks: "rare earths", "lead isotope ratios" and "other metals". The model constructed with all the variables was taken as the reference model. This model has adequate sensibility and specificity. The contribution of each element to the model of each denomination of origin (DOs), as well as their capacity to discriminate between the DOs is shown. Cluster analysis, using the Ward method, of the SIMCA distances between the different DOs reveals the similarity of the different denominations of origin. Using only the rare earths or the lead isotope ratios it is not possible to construct adequate models for the different DOs given the low specificity obtained. The models constructed with the other metals, alone or combined with the lead isotope ratios, gave similar results to those obtained using all the variables. Finally, the similarity of the models was analysed by a weighted distance between the sensibilities and specificities of each of them compared with the rest. Cluster analysis using the Ward method shows the models which are similar as to their sensibility and specificity. The innovative aspect of the work lies in the use of cluster analysis to demonstrate the similarity between the SIMCA boxes of a model, and the definition of the distance between models based on the sensibility and specificity for the eight DOs with the five groups of variables considered. (C) 2002 Elsevier Science B.V. All rights reserved.
引用
收藏
页码:161 / 174
页数:14
相关论文
共 14 条
[1]   Typification of vinegars from Jerez and Rioja using classical chemometric techniques and neural network methods [J].
Benito, MJ ;
Ortiz, MC ;
Sánchez, MS ;
Sarabia, LA ;
Iñiguez, M .
ANALYST, 1999, 124 (04) :547-552
[2]  
Coomans D., 1982, THESIS VRIJE U BRUSS
[3]  
DERDE M P, 1989, Journal of Chemometrics, V3, P375, DOI 10.1002/cem.1180030206
[4]  
FORINA M, Q PARVUS 3 0 EXTENDA
[5]  
FORINA M, 1987, CURRENT CHEM, V141
[6]  
MASSART DL, 1983, INPERTRETATION ANAL
[7]  
*MATHW, MATLAB HIGH PERF NUM
[8]   Psychophysical parameters of colour and the chemometric characterisation of wines of the certified denomination of origin 'Rioja' [J].
Meléndez, ME ;
Sánchez, MS ;
Iñiguez, M ;
Sarabia, LA ;
Ortiz, MC .
ANALYTICA CHIMICA ACTA, 2001, 446 (1-2) :159-169
[9]  
ORTIZ MC, 1995, CHEMOMETR INTELL LAB, V28, P273, DOI 10.1016/0169-7439(94)00080-3
[10]   TYPIFICATION OF ALCOHOLIC DISTILLATES BY MULTIVARIATE TECHNIQUES USING DATA FROM CHROMATOGRAPHIC ANALYSES [J].
ORTIZ, MC ;
SAEZ, JA ;
PALACIOS, JL .
ANALYST, 1993, 118 (07) :801-805