Prediction of phase stability of UHT reconstituted skim milk after ambient storage using Raman spectroscopy

被引:0
|
作者
Shao, Yijing [1 ,2 ]
He, Lili [3 ]
Zheng, Haotian [1 ,2 ]
机构
[1] North Carolina State Univ, Dept Food Bioproc & Nutr Sci, Food Rheol Lab, Raleigh, NC 27695 USA
[2] North Carolina State Univ, Southeast Dairy Foods Res Ctr, Raleigh, NC 27695 USA
[3] Univ Massachusetts, Dept Food Sci, Amherst, MA 01003 USA
关键词
UHT; Reconstituted milk; Raman spectroscopy; Shelf-life; Stability prediction; PROTEIN SECONDARY STRUCTURE; AGE GELATION; CASEIN MICELLES; WHEY-PROTEIN; FT-RAMAN; HEAT; PH; SEDIMENTATION; DISSOCIATION; MICROSCOPY;
D O I
10.1016/j.idairyj.2024.106142
中图分类号
TS2 [食品工业];
学科分类号
0832 ;
摘要
Milk is a colloidal system, and phase separation within such systems, such as excessive sedimentation and age gelation, is a quality defect in UHT-treated milk that remains challenging to predict. This study aims to investigate the feasibility of using Raman spectroscopy to characterize UHT reconstituted skim milk (RSM) and predict the degree of phase separation in UHT-RSM after storage. UHT-RSM samples after processing (M0) and threemonth storage (M3) were vacuum-concentrated and analyzed by Raman spectroscopy. After 7.5 months of storage, the total solids depletion (TSD) of UHT-RSM was used to quantitatively reflect the degree of phase separation. Two independent partial least squares regression models were constructed using TSD7.5-month as the response variable and pre-processed Raman spectra collected from M0 and M3, respectively, as predictor variables. The nuances in UHT-RSM samples captured by Raman spectroscopy are crucial in developing the PLS regression models. Results showed that both M0 and M3 Raman spectra were relatively effective in predicting the phase separation condition (TSD7.5-month) of UHT-RSM at a later stage of storage (R2Pred = 0.74 and 0.85, respectively). This study demonstrated a new approach for forecasting the phase stability of UHT-RSM products based on spectral information. While there is a space for optimization of the presented prediction models, the technical approach shows good potential to be utilized by ingredient manufacturers and UHT milk processors to assist the ingredient screening process. Future research is encouraged to improve prediction accuracy within the framework of this novel approach.
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页数:11
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