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Application of in-line Raman spectroscopy to monitor crystallization and melting processes in milk fat.
Xu, Guangya; O'Shea, Norah; Drouin, Gaetan; Pacheco-Pappenheim, Sara; O'Donnell, Colm P; Hogan, Sean A.
Afiliação
  • Xu G; Food Chemistry and Technology Department, Teagasc Food Research Centre, Moorepark, Fermoy, Cork, Ireland; School of Biosystems and Food Engineering, University College Dublin, Dublin 4, Ireland.
  • O'Shea N; Food Chemistry and Technology Department, Teagasc Food Research Centre, Moorepark, Fermoy, Cork, Ireland.
  • Drouin G; Food Chemistry and Technology Department, Teagasc Food Research Centre, Moorepark, Fermoy, Cork, Ireland.
  • Pacheco-Pappenheim S; Food Chemistry and Technology Department, Teagasc Food Research Centre, Moorepark, Fermoy, Cork, Ireland; Dairy Processing and Technology Centre, University of Limerick, Sreelane, Limerick, Ireland.
  • O'Donnell CP; School of Biosystems and Food Engineering, University College Dublin, Dublin 4, Ireland.
  • Hogan SA; Food Chemistry and Technology Department, Teagasc Food Research Centre, Moorepark, Fermoy, Cork, Ireland. Electronic address: Sean.A.Hogan@teagasc.ie.
Food Res Int ; 191: 114690, 2024 Sep.
Article em En | MEDLINE | ID: mdl-39059946
ABSTRACT
Anhydrous milk fat (AMF) and its fractions are used as ingredients in a wide range of food applications. Obtaining the appropriate solid fat content (SFC) is essential to achieve the desired product texture. At present, in-line monitoring techniques to control milk fat crystallization and melting are largely unavailable. The thermal behaviour of milk fat (AMF and four of its fractions) was monitored in a temperature-controlled vessel using an in-line Raman analyser and compared with thermograms generated using differential scanning calorimetry (DSC). The major stages of milk fat crystallization and melting were identified using the in-line Raman analyser. Thermal data from DSC showed excellent linear correlations with Raman spectral data (R2 value of 0.97 for the onset of milk fat crystallisation). Partial least squares regression (PLSR) models were developed using Raman spectra to predict SFC with coefficient of determination (R2Cs) from 0.929 to 0.992 and root mean standard error of calibration (RMSECs) ranging from 3.20 to 10.36%. Results demonstrated Raman spectroscopy has significant potential as a way of monitoring milk fat crystallization and melting processes.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Análise Espectral Raman / Varredura Diferencial de Calorimetria / Cristalização / Leite Limite: Animals Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Análise Espectral Raman / Varredura Diferencial de Calorimetria / Cristalização / Leite Limite: Animals Idioma: En Ano de publicação: 2024 Tipo de documento: Article