Abstract
Shrinkage is a common phenomenon during the drying of fruits and vegetables. The research aimed to study the mechanism of drying shrinkage and investigate the potential use of low-field nuclear magnetic resonance (LF-NMR) for online monitoring changes in shrinkage. The effects of drying parameters (temperature, power, and vacuum) on shrinkage of three types of materials banana (fruit), carrot (vegetable), and Pleurotus eryngii (an edible fungus) were studied in the different drying processes of hot air drying (HAD), microwave vacuum drying (MVD), infrared drying (IRD), and infrared freeze-drying (IFD). During drying, material shrinkage mainly occurred in the early and middle drying stages with different characteristics of retention volume and shrinkage equilibrium point of moisture content. The drying shrinkage was significantly related to the change of MC in vacuolar compartment (p < 0.05). Reducing the drying time from drying beginning to the LF-NMR A23/A22(1), i.e., when the water content between vacuolar compartment and cytoplasm was equal, was beneficial for reducing shrinkage, and the volume retention rate increased by 39.13%. The shrinkage model of BP-ANN based on LF-NMR had a high prediction accuracy of shrinkage more than 95% and was excellent with the R2 of 0.9989 and RMSE of 0.0087. The shrinkage control strategy based on LF-NMR provided a reference for the development of artificial intelligence drying equipment.
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Funding
We acknowledge the financial support from the National First-class Discipline Program of Food Science and Technology (no. JUFSTR20180205), Jiangsu Key Laboratory of Advanced Food Manufacturing Equipment & Technology (nos. FMZ202003 and FM-2019–03), Postgraduate Research & Practice Innovation Program of Jiangsu Province (KYCX19-1816), and Special funds for Taishan Industry Leading Talents Project, all of which enabled us to carry out this study.
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Sun, Q., Zhang, M., Mujumdar, A.S. et al. Research on the Vegetable Shrinkage During Drying and Characterization and Control Based on LF-NMR. Food Bioprocess Technol 15, 2776–2788 (2022). https://doi.org/10.1007/s11947-022-02917-x
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DOI: https://doi.org/10.1007/s11947-022-02917-x