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Characterization of the flavor profile of UHT milk during shelf-life via volatile metabolomics fingerprinting combined with chemometrics.
Xi, Yanmei; Yang, Yan; Chi, Xuelu; Wang, Weizhe; Sun, Baoguo; Ai, Nasi.
Afiliación
  • Xi Y; Key Laboratory of Geriatric Nutrition and Health, Ministry of Education, Beijing Technology & Business University, Beijing 100048, China.
  • Yang Y; Key Laboratory of Geriatric Nutrition and Health, Ministry of Education, Beijing Technology & Business University, Beijing 100048, China.
  • Chi X; Key Laboratory of Geriatric Nutrition and Health, Ministry of Education, Beijing Technology & Business University, Beijing 100048, China.
  • Wang W; Key Laboratory of Geriatric Nutrition and Health, Ministry of Education, Beijing Technology & Business University, Beijing 100048, China.
  • Sun B; Key Laboratory of Geriatric Nutrition and Health, Ministry of Education, Beijing Technology & Business University, Beijing 100048, China.
  • Ai N; Key Laboratory of Geriatric Nutrition and Health, Ministry of Education, Beijing Technology & Business University, Beijing 100048, China. Electronic address: ainasi@btbu.edu.cn.
Food Res Int ; 191: 114705, 2024 Sep.
Article en En | MEDLINE | ID: mdl-39059956
ABSTRACT
Ultra-high temperature (UHT) milk is popular among consumers. However, its flavor and texture change in its shelf life. Flavor is highly determinative for the success of dairy products and for consumers' willingness to buy. It is important to milk producers to ensure the optimal flavor of their products in the shelf life. In order to be able to control and predict the flavor quality of UHT milk during the shelf life, this study compared the variations in sensory quality, volatile aroma release and backbone flavor factors and developed a discriminant model to assess flavor quality based on flavouromics data of five competing milk sample during storage. Using partial least squares discriminant analysis (PLS-DA) with Electronic-nose (E-nose) data excellent classification sensitivity and specificity were achieved compared to models based on gas chromatography-mass spectrometry (GC-MS) data. The PLS-DA model using E-nose data exhibited a 100% correct classification rate for the storage period, and a 92% correct rate based on the eight variable importance in the projection (VIP) elements screened for volatile components from different groups. The discriminative model developed herein based on E-nose combined with chemometrics demonstrated advantages such as speed, efficiency, and environmental friendliness. This method shows promise as a precise tool for analyzing aroma changes in UHT milk during its shelf life, and provide support for controlling the flavor substances and milk product development.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Gusto / Leche / Almacenamiento de Alimentos / Compuestos Orgánicos Volátiles / Metabolómica / Nariz Electrónica / Cromatografía de Gases y Espectrometría de Masas / Odorantes Límite: Animals / Humans Idioma: En Revista: Food Res Int Año: 2024 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Gusto / Leche / Almacenamiento de Alimentos / Compuestos Orgánicos Volátiles / Metabolómica / Nariz Electrónica / Cromatografía de Gases y Espectrometría de Masas / Odorantes Límite: Animals / Humans Idioma: En Revista: Food Res Int Año: 2024 Tipo del documento: Article País de afiliación: China
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