期刊
LWT-FOOD SCIENCE AND TECHNOLOGY
卷 49, 期 1, 页码 55-63出版社
ELSEVIER
DOI: 10.1016/j.lwt.2012.04.024
关键词
Honey; H-1 nuclear magnetic resonance; K-nearest neighbor; Soft independent modeling of class analogies; Partial least squares discriminant analysis
资金
- CAPES
- CNPq
- FAPESP
- FINEP
The potential of NMR spectroscopy to differentiate honeys concerning to the nectar employed in its production was evaluated. The application of chemometric methods to H-1 NMR spectra has allowed to discriminate the honeys produced in the state of Sao Paulo, being identified the signals of responsible substances for the discrimination. Application of PCA and HCA methods to H-1 NMR data have resulted in the natural clustering of the samples. Wildflower honeys were characterized by higher concentration of phenylalanine and tyrosine. Citrus honeys showed higher amounts of sucrose than other compounds, while eucalyptus honeys had higher amount of lactic acid than the others. Assa-peixe honeys showed spectra similar to eucalyptus and citrus. Sugar-cane honeys showed some signals similar to eucalyptus and citrus honeys, but also showed the tyrosine and phenylalanine signals. Adulterated honeys showed 5-hydroxymethylfurfural, citric acid and ethanol signals. KNN, SIMCA and PLS-DA methods were used to build predictive models for honey classification. In the commercial honeys prediction KNN, SIMCA and PLS-DA models correctly classified 66.7; 22.2 and 72.2% of the samples, respectively. (C) 2012 Elsevier Ltd. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据