CIBICI   14215
CENTRO DE INVESTIGACION EN BIOQUIMICA CLINICA E INMUNOLOGIA
Unidad Ejecutora - UE
artículos
Título:
Composition of Honey from Córdoba (Argentina): Assessment of North/South provenance by chemometrics.
Autor/es:
BARONI MV; ARRUA C; NORES ML; FAYÉ P; DIAZ MP; CHIABRANDO GA; WUNDERLIN DA
Revista:
FOOD CHEMISTRY
Editorial:
Elsevier
Referencias:
Año: 2009 vol. 114 p. 727 - 733
ISSN:
0308-8146
Resumen:
We report the characterisation of honey samples produced in Córdoba (Argentina) and their classification by geographical provenance (North/South) using chemometrics. Twenty-two variables were analysed considering both chemical properties and mineral profile. Honey samples were found to meet the international specifications for the evaluated parameters. Classification of honey in according to its geographical provenance (North/South) was achieved by pattern recognition techniques applied to 15 out of 22 variables. Glucose, pH, free acidity, free amino acids, calcium and zinc were selected by stepwise discriminant analysis, explaining the classification of honey according to their geographical origin. Application of k-nearest-neighbour classification procedure to these six selected variables produced a successful assignation (99% correct) of honey to its provenance. On the other hand only 83% right assignation was observed, when the 15 variables were used, confirming that the use of all available features is unnecessary to get good geographical discrimination. these six selected variables produced a successful assignation (99% correct) of honey to its provenance. On the other hand only 83% right assignation was observed, when the 15 variables were used, confirming that the use of all available features is unnecessary to get good geographical discrimination. these six selected variables produced a successful assignation (99% correct) of honey to its provenance. On the other hand only 83% right assignation was observed, when the 15 variables were used, confirming that the use of all available features is unnecessary to get good geographical discrimination. k-nearest-neighbour classification procedure to these six selected variables produced a successful assignation (99% correct) of honey to its provenance. On the other hand only 83% right assignation was observed, when the 15 variables were used, confirming that the use of all available features is unnecessary to get good geographical discrimination.