Open AccessAPPLICATION OF MULTIVARIATE METHODS TO THE DIFFERENTIATION OF PERUVIAN WINES
Author(s) -
Ana Lucía Paredes-Doig,
María del Rosario Sun Kou,
Elizabeth Doig-Camino,
Gino Picasso,
Adolfo La Rosa-Toro
Publication year - 2022
Publication title -
infoanalítica (quito - impresa)/infoanalítica (quito - en línea)
Language(s) - English
Resource type - Journals
eISSN - 2602-8344
pISSN - 2477-8788
DOI - 10.26807/ia.v10i1.218
Subject(s) - multivariate statistics , principal component analysis , electronic nose , factorial analysis , multivariate analysis , factorial experiment , food science , materials science , mathematics , chemistry , statistics , nanotechnology
This work presents the results of the sensing analysis of Peruvian wines of known (Commercial wines) and handmade brands, using electronic noses (E-noses) which consist of an array of sensors based on tin oxide doped with Pd or Pt, and some with zeolite coating. The combinations of the sensors were performed seeking to obtain the best discrimination of the wines with the multivariate methods, with a high level of confidence and a good distribution of the results. The Principal Component Analysis (PCA), cluster and factorial results showed that the electronic noses allowed to efficiently identify wines of known brand from those of handmade brand, revealing the way in which the wines have been produced. On the other hand, the multivariate methods applied to the electronic noses made up of SnO2 sensors doped with palladium showed a clear differentiation of Borgoña-type wines from wines of handmade brand and evidenced the formation of agglomerations between red and Rosé wines. The application of PCA, cluster and factorial obtained in this study allowed to obtain good results in the differentiation of wines, even with electronic noses formed with a low number of sensors.