Assessment of strawberry aroma through solid-phase microextraction-gas chromatography and artificial neuron network methods. Variety classification versus growing years.
In a previous work, the SPME-GC-MS method (chemical analysis) coupled with KSOM-ANN treatment of the results (statistical algorithm) has proved to be efficient to classify 70 strawberry samples harvested in the same year, through the 17 varieties to which they belonged, in a two-dimensional map. As an extension, the present study confirms that these results were not dependent on the year of strawberry production and discusses what effects were observed between results obtained in different years. Samples of different strawberry varieties were harvested during the three campaigns of 2000, 2001, and 2002 and analyzed independently. The chemical data matrix obtained in each case allowed the verification of the proposal that the same discriminative effect could be obtained independently of the year of production by using maps of different sizes. Therefore, 30 measures obtained from samples of 9 varieties in 2000, 54 measures from 13 varieties in 2001, and 80 measures from 20 varieties in 2002 were correctly classified by using 20, 35, and 56 hexagon maps, respectively. In a second analysis based on the 2002 production, the chemical differences between variety aromatic features were noted through the increasing size of the map used. Finally, results relative to 7 varieties cultivated in 2001 and 2002 and stored under exactly the same conditions were computed together for elaborating a single map. An interesting effect of double classification according to the year and the varieties was observed.
de Boishebert
Virginie
V
Equipe Périgourdine de Chimie Appliquée (EPCA), Laboratoire de Physico et Toxico Chimie des Systèmes Naturels, Université Bordeaux 1, CNRS (UMR 5472), B.P. 1043, 24001 Périgueux Cedex, France.
Urruty
Louise
L
Giraudel
Jean-Luc
JL
Montury
Michel
M
D031985:Fragaria / Q000737:chemistry* / Q000145:classification* / Q000254:growth & development; D005638:Fruit / Q000737:chemistry*; D008401:Gas Chromatography-Mass Spectrometry / Q000379:methods*; D016571:Neural Networks, Computer; D009812:Odorants / Q000032:analysis*; D013997:Time Factors