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Dumancas, Gerard G., Ellis, Helena (2022) Comprehensive examination and comparison of machine learning techniques for the quantitative determination of adulterants in honey using Fourier infrared spectroscopy with attenuated total reflectance accessory. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 276. 121186 doi:10.1016/j.saa.2022.121186

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Reference TypeJournal (article/letter/editorial)
TitleComprehensive examination and comparison of machine learning techniques for the quantitative determination of adulterants in honey using Fourier infrared spectroscopy with attenuated total reflectance accessory
JournalSpectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy
AuthorsDumancas, Gerard G.Author
Ellis, HelenaAuthor
Year2022 (August)Volume276
PublisherElsevier BV
DOIdoi:10.1016/j.saa.2022.121186Search in ResearchGate
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Mindat Ref. ID16404703Long-form Identifiermindat:1:5:16404703:7
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Full ReferenceDumancas, Gerard G., Ellis, Helena (2022) Comprehensive examination and comparison of machine learning techniques for the quantitative determination of adulterants in honey using Fourier infrared spectroscopy with attenuated total reflectance accessory. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 276. 121186 doi:10.1016/j.saa.2022.121186
Plain TextDumancas, Gerard G., Ellis, Helena (2022) Comprehensive examination and comparison of machine learning techniques for the quantitative determination of adulterants in honey using Fourier infrared spectroscopy with attenuated total reflectance accessory. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 276. 121186 doi:10.1016/j.saa.2022.121186
In(2022) Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy Vol. 276. Elsevier BV

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