Determining the geographic origin of potatoes with trace metal analysis using statistical and neural network classifiers.
J Agric Food Chem
; 47(4): 1568-75, 1999 Apr.
Article
en En
| MEDLINE
| ID: mdl-10564018
ABSTRACT
The objective of this research was to develop a method to confirm the geographical authenticity of Idaho-labeled potatoes as Idaho-grown potatoes. Elemental analysis (K, Mg, Ca, Sr, Ba, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, Mo, S, Cd, Pb, and P) of potato samples was performed using ICPAES. Six hundred eight potato samples were collected from known geographic growing sites in the U.S. and Canada. An exhaustive computational evaluation of the 608 x 18 data sets was carried out using statistical (PCA, CDA, discriminant function analysis, and k-nearest neighbors) and neural network techniques. The neural network classification of the samples into two geographic regions (defined as Idaho and non-Idaho) using a bagging technique had the highest percentage of correct classifications, with a nearly 100% degree of accuracy. We report the development of a method combining elemental analysis and neural network classification that may be widely applied to the determination of the geographical origin of unprocessed, fresh commodities.
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Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Oligoelementos
/
Solanum tuberosum
/
Metales
Tipo de estudio:
Prognostic_studies
País/Región como asunto:
America do norte
Idioma:
En
Revista:
J Agric Food Chem
Año:
1999
Tipo del documento:
Article
País de afiliación:
Estados Unidos