首页|Addition of external water improves the quality attributes of vacuum-frozen and thawed apple slices
Addition of external water improves the quality attributes of vacuum-frozen and thawed apple slices
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NSTL
Elsevier
Vacuum freezing is an innovative rapid freezing technique with various advantages and huge potential for diverse applications. This study aimed at investigating variations in the moisture, main quality, microstructure, and mechanical properties of vacuum-frozen and thawed apple slices resulting from the use of different amounts of external water added prior to freezing. Increased external water content (30%) contributed to lower frozen temperature and less water loss in vacuum-frozen apple samples, and higher drip loss, equivalent vitamin C content, lower relative electrical conductivity, lower soluble solids content and lower total color difference in thawed samples. Slices of thawed samples with more added external water before vacuum freezing displayed higher density of moisture distribution and reduced microstructure destruction. They also displayed higher elastomeric and less viscous behaviors, as assessed with stress-relaxation analysis, and increased hardness and chewiness and reduced cohesiveness, as assessed with texture profile analysis. The quality of thawed apple slices with 30% pre-added external water was closest to that of the fresh apples. The traditional contact plate freezing treatment produced the worst quality. Thus, vacuum freezing with 30% pre-added external water is recommended for the rapid freezing processing of apple slices.
Low frequency nuclear magnetic resonanceMicrostructureQualityStress-relaxationThawingVacuum freezing
Wang H.、Xia T.、Zhao R.、Hu Z.、Xie H.、Xue Y.、Ba L.、Shamim S.
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School of Food Science Nanjing Xiaozhuang University
Key Laboratory of Modern Agricultural Equipment Ministry of Agriculture and Rural Affairs
College of Light Industry Liaoning University
State Laboratory of Bioelectronics School of Biomedical Engineering and Department of Physics Southeast University
NSTL
Elsevier
