A Laser-Based Method for the Detection of Honey Adulteration
In the present work, laser-induced breakdown spectroscopy, aided by some machine learning algorithms (i.e., linear discriminant analysis (LDA) and extremely randomized trees (ERT)), is used for the detection of honey adulteration with glucose syrup. In addition, it is shown that instead of the entir...
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Veröffentlicht in: | Applied sciences 2021-07, Vol.11 (14), p.6435 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | In the present work, laser-induced breakdown spectroscopy, aided by some machine learning algorithms (i.e., linear discriminant analysis (LDA) and extremely randomized trees (ERT)), is used for the detection of honey adulteration with glucose syrup. In addition, it is shown that instead of the entire LIBS spectrum, the spectral lines of inorganic ingredients of honey (i.e., calcium, sodium, and potassium) can be also used for the detection of adulteration providing efficient discrimination. The constructed predictive models attained high classification accuracies exceeding 90% correct classification. |
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ISSN: | 2076-3417 2076-3417 |
DOI: | 10.3390/app11146435 |