Unveiling the physical properties predictive of oil binding capacity in an interesterified palm-based fat

被引:0
|
作者
Marsh, Melissa Abigail [1 ]
Bean, Brennan [2 ]
Maleky, Farnaz [3 ]
Martini, Silvana [1 ]
机构
[1] Utah State Univ, Dept Nutr Dietet & Food Sci, Logan, UT 84322 USA
[2] Utah State Univ, Dept Math & Stat, Logan, UT USA
[3] Ohio State Univ, Dept Food Sci & Technol, Columbus, OH USA
基金
美国食品与农业研究所;
关键词
cooling rate; high-intensity ultrasound; oil binding capacity; oil loss; oil migration; HIGH-INTENSITY ULTRASOUND; CRYSTALLIZATION BEHAVIOR; COOLING RATE; SOYBEAN OIL; MIGRATION; SONOCRYSTALLIZATION; MICROSTRUCTURE; TEMPERATURE; OLEOGELS;
D O I
10.1002/aocs.12830
中图分类号
O69 [应用化学];
学科分类号
081704 ;
摘要
This paper identifies physical properties of an interesterified palm-based fat (EIEPO) that predict oil binding capacity (OBC). A 100% EIEPO sample, 50% EIEPO sample diluted with 50% soybean oil (SBO), and a 20% EIEPO sample diluted with 80% SBO were used to test how saturation level impacts OBC. All samples were crystallized using either a fast (6.4 degrees C/min) or slow (0.1 degrees C/min) cooling rate as well as with or without the application of high-intensity ultrasound (HIU; 20 kHz) to generate a wide range of physical properties. Immediately after crystallization, the sample's physical properties, including crystal microstructure, solid fat content (SFC), viscoelasticity (G ', G '', and delta), melting behavior, hardness, and OBC (centrifuge method) were quantified. The samples were then stored for 48 h at 22 and 5 degrees C and the aforementioned physical properties were measured again, with one additional measurement for the samples stored at 5 degrees C-OBC using a filter paper method (OBCp). The results indicate that OBC can be optimized in a palm-based fat by modifying the physical properties which was achieved via the processing conditions. Both measurements of OBC were significantly correlated with SFC, hardness, delta, and enthalpy. A model was developed to predict a sample's OBCc using the following dominant variables-SFC, hardness, peak temperature, enthalpy, and the number of crystals. These results suggest that OBC can be predicted using a sample's SFC, hardness, peak temperature, enthalpy, and number of crystals and that SFC, hardness, and enthalpy are main drivers of OBC. image
引用
收藏
页码:767 / 782
页数:16
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