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Volatile Organic Compounds Profiles to Determine Authenticity of Sweet Orange Juice Using Head Space Gas Chromatography Coupled with Multivariate Analysis.
Zhou, Qi; Li, Guijie; Ou-Yang, Zhu; Yi, Xin; Huang, Linhua; Wang, Hua.
Afiliación
  • Zhou Q; Citrus Research Institute, Southwest University, Chongqing 400712, China.
  • Li G; National Citrus Engineering Research Center, Chinese Academy of Agricultural Sciences, Chongqing 400712, China.
  • Ou-Yang Z; Citrus Research Institute, Southwest University, Chongqing 400712, China.
  • Yi X; National Citrus Engineering Research Center, Chinese Academy of Agricultural Sciences, Chongqing 400712, China.
  • Huang L; Chongqing Collaborative Innovation Center for Functional Food, Chongqing University of Education, Chongqing 400067, China.
  • Wang H; Citrus Research Institute, Southwest University, Chongqing 400712, China.
Foods ; 9(4)2020 Apr 16.
Article en En | MEDLINE | ID: mdl-32316240
An efficient and practical method for identifying mandarin juice over-blended into not from concentrate (NFC) orange juice was established. Juices were extracted from different cultivars of sweet orange and mandarin fruits. After being pasteurized, the volatile organic compounds (VOCs) in the juice samples were extracted using headspace solid-phase microextraction, and qualitatively and quantitatively analyzed using gas chromatography-mass spectrometry detection. Thirty-two VOCs contained in both the sweet orange juice and mandarin juice were used as variables, and the identification model for discriminating between the two varieties of juice was established by principal component analysis. Validation was applied by using common mandarin juices from Ponkan, Satsuma and Nanfengmiju cultivars blended at series of proportions into orange juices from Long-leaf, Olinda, and Hamlin cultivars. The model can visually identify a blending of mandarin juice at the volume fraction of 10% or above.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Foods Año: 2020 Tipo del documento: Article País de afiliación: China Pais de publicación: Suiza

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Foods Año: 2020 Tipo del documento: Article País de afiliación: China Pais de publicación: Suiza