期刊
FOOD CHEMISTRY
卷 107, 期 1, 页码 537-544出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.foodchem.2007.08.024
关键词
chestnuts; Castanea sp.; chemical composition; multivariate analysis; pattern recognition
Chestnuts like other foodstuffs may be characterized by their chemical composition. The chemical composition of ascorbic acid, total acidity, pH, starch, refraction index (degrees Brix), moisture, ashes, insoluble fibre, soluble fibre, total dietary fibre, total proteins, cations (Na, K, Ca, Fe, Cu, Zn, Mn, Mg) and phosphorous was determined in 19 local chestnut varieties from three areas of production in the island of Tenerife. Significant differences were found between the mean values of moisture, starch, total phenols contents, total soluble and non-soluble fibre, Ca, Cu, K, Mg and Zn, obtained according to the area of production. Distribution patterns of the samples were established for correlating the chemical composition of the chestnuts and varieties, using different chemometrics tools such as cluster analysis, principal component analysis, factor analysis and linear discriminant analysis (LDA). Initially, cluster analysis made it possible to establish a primary relationship between the variables. When applying stepwise LDA the chestnut samples were well classified within their area of production. Also, when the stepwise LDA was used on the chestnut samples from area of production 2, 100% of the chestnut samples were also correctly classified within their variety. (c) 2007 Elsevier Ltd. All rights reserved.
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