Identifying type of sugar adulterants in honey: Combined application of NMR spectroscopy and supervised machine learning classification.

Rachineni, Kavitha; Rao Kakita, Veera Mohana; Awasthi, Neeraj Praphulla; Shirke, Vrushali Siddesh; Hosur, Ramakrishna V; Chandra Shukla, Satish

Rachineni, Kavitha; Rao Kakita, Veera Mohana; Awasthi, Neeraj Praphulla; Shirke, Vrushali Siddesh; Hosur, Ramakrishna V; Chandra Shukla, Satish.

Afiliación

Rachineni K; Export Inspection Agency - Mumbai, E-3, Industrial Area (MIDC), Andheri East, Mumbai, 400 093, India.
Rao Kakita VM; UM-DAE Centre for Excellence in Basic Sciences, University of Mumbai, Kalina Campus, Santacruz, Mumbai, 400 098, India.
Awasthi NP; Export Inspection Agency - Mumbai, E-3, Industrial Area (MIDC), Andheri East, Mumbai, 400 093, India.
Shirke VS; Export Inspection Agency - Mumbai, E-3, Industrial Area (MIDC), Andheri East, Mumbai, 400 093, India.
Hosur RV; UM-DAE Centre for Excellence in Basic Sciences, University of Mumbai, Kalina Campus, Santacruz, Mumbai, 400 098, India.
Chandra Shukla S; Export Inspection Agency- Chennai (Head Office), 6th Floor CMDA Tower-II, No: 1 Gandhi Irwin Road, Egmore, Chennai, 600008, India.

Curr Res Food Sci ; 5: 272-277, 2022.

Article en En | MEDLINE | ID: mdl-35141528

Palabras clave

Deep learning; Honey; Machine learning; NMR; Sugar Adulteration; Supervised classification

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Curr Res Food Sci Año: 2022 Tipo del documento: Article País de afiliación: India Pais de publicación: Países Bajos

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