Application of Low-Field NMR to Analyze Water Characteristics and Predict Unfrozen Water in Blanched Sweet Corn

Water characteristics and prediction of unfrozen water in sweet corn treated with different blanching temperatures (20, 40, 50, 60, 70, 80, 90, and 100 °C/10 min) were investigated by low-field nuclear magnetic resonance (LF-NMR). Transverse relaxation analysis was firstly used to study the changes of water characteristics and distribution. Then, a chemometric method using partial least squares (PLS) method was employed to predict unfrozen water. Four relaxation components were discerned and pertained to vacuolar, cytoplasmic, and extracellular water, and cell wall protons, respectively. The intracellular water in sweet corn was transported to extracellular space after treatment and the loss of intracellular water increased with blanching temperature. Three groups of blanching temperatures were discriminated by principal component analysis. The PLS regression model based on LF-NMR data accurately predicted unfrozen water in blanched sweet corn with an adjusted determination coefficient of 0.97.

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