Journal
FOOD HYDROCOLLOIDS
Volume 128, Issue -, Pages -Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.foodhyd.2022.107604
Keywords
Heat treatment; Fourier transform infrared spectroscopy; Nuclear magnetic resonance; beta-casein; Milk; Phenotypes; Structure
Categories
Funding
- VU International Postgraduate Research Scholarship (VUIPRS)
- Teagasc - the Agriculture and Food Development Authority (Walsh Scholarship Programme, Ireland)
- Victoria University [2019039]
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This study assessed the effect of heat treatment on the physical properties of bovine milk samples with different beta-casein phenotypes. The results showed that increasing the heat treatment temperature decreased the level of intramolecular beta-sheets and increased the presence of aggregated beta-sheet structures in A1/A2 beta-CN milk.
This study assessed the effect of heat treatment on the physical properties of bovine milk samples possesing different beta-casein ( beta-CN) phenotypes. After heat treatment at 72 degrees C/15 s, 121 degrees C/2.6 min, or 140 degrees C/3 s, beta-CN milks were analysed using Fourier Transform Infrared (FTIR) spectroscopy, Nuclear Magnetic (1H NMR) resonance, and a number of physicochemical measurements. Principal Component Analysis (PCA) was used to provide a discrimination of samples. In contrast to significant amounts of intramolecular beta-sheet, beta-turn, and random coil, in A1/A1, A1/A2, and A2/A2 beta-CN milks, respectively, increasing the heat treatment temperature decreased the level of intramolecular beta-sheets in all three types of bovine milk. The main difference involved a higher presence of aggregated beta-sheet structures in A1/A2 beta-CN milk likely due to the presence of tyrosine. A1/ A1 and A1/A2 beta-CN milks were characterised with greater amounts of calcium and phosphorus, and a higher net negative zeta potential than A2/A2 beta-CN milk. Furthermore, A2/A2 beta-CN milk was composed of larger casein micelle particles with lower levels of kappa-CN compared to the other beta-CN milk phenotypes. These findings may assist in predicting the behaviour of beta-CN milks during relevant industrial processing.
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