Rapid screening for hazelnut oil and high-oleic sunflower oil in extra virgin olive oil using low-field nuclear magnetic resonance relaxometry and machine learning.

Hou, Xuewen; Wang, Guangli; Wang, Xin; Ge, Xinmin; Fan, Yiren; Jiang, Rui; Nie, Shengdong

Hou, Xuewen; Wang, Guangli; Wang, Xin; Ge, Xinmin; Fan, Yiren; Jiang, Rui; Nie, Shengdong.

Afiliação

Hou X; School of Medical Instrument and Food Engineering, University of Shanghai for Science and Technology, Shanghai, China.
Wang G; School of Medical Instrument and Food Engineering, University of Shanghai for Science and Technology, Shanghai, China.
Wang X; School of Medical Instrument and Food Engineering, University of Shanghai for Science and Technology, Shanghai, China.
Ge X; School of Geosciences, China University of Petroleum, Qingdao, China.
Fan Y; School of Geosciences, China University of Petroleum, Qingdao, China.
Jiang R; School of Medical Instrument and Food Engineering, University of Shanghai for Science and Technology, Shanghai, China.
Nie S; School of Medical Instrument and Food Engineering, University of Shanghai for Science and Technology, Shanghai, China.

J Sci Food Agric ; 101(6): 2389-2397, 2021 Apr.

Article em En | MEDLINE | ID: mdl-33011981

Assuntos

Espectroscopia de Ressonância Magnética/métodos; Azeite de Oliva/análise; Óleo de Girassol/análise; Análise Discriminante; Contaminação de Alimentos/análise; Aprendizado de Máquina

Palavras-chave

LF-NMR; adulteration; classification; extra virgin olive oil; machine learning

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Espectroscopia de Ressonância Magnética / Azeite de Oliva / Óleo de Girassol Tipo de estudo: Diagnostic_studies / Evaluation_studies / Screening_studies Idioma: En Revista: J Sci Food Agric Ano de publicação: 2021 Tipo de documento: Article País de afiliação: China

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