Literature DB >> 33023319

Effects of ultrasonic vacuum drying on the drying kinetics, dynamic moisture distribution, and microstructure of honey drying process.

Mengmeng Jiang1, Jun Sun1, Mohammed Obadi1, Xiting Bai2, Wenxue Zhu3.   

Abstract

The aim of this study was to study the strengthening effect of ultrasonic vacuum technique on the drying kinetics, moisture distribution, and microstructure of honey using low-field nuclear magnetic resonance and scanning electron microscopy. Results showed that ultrasonic vacuum drying technique could substantially shorten the drying time from 600 to 60 min, compared with vacuum drying. The sonochemical effects of ultrasonic vacuum drying were enhanced with the increased ultrasonic power and were more obvious in the initial stage of drying. This finding is consistent with the effective water diffusion coefficient results. The non-linear fitting analysis of experimental data on seven kinds of thin-layer drying mathematical models showed that logarithmic model is more suitable for describing the law of moisture change in honey during ultrasonic vacuum drying than the other models because of its higher regression coefficient value (≥0.99) and smaller reduced chi-square and root mean square error values (≤0.01). In addition, low-field nuclear magnetic resonance results showed that the increase in ultrasonic power accelerated the migration of bound water to immobilized water in honey samples. Scanning electron microscopy results showed that the porous structure formed by increasing the ultrasonic power is also conducive to the rapid migration and drying of moisture. In conclusion, ultrasonic vacuum drying technique is an effective and safe way for drying viscous materials compared with vacuum drying technique.

Entities:  

Keywords:  Drying; honey; microstructure; ultrasonic power; ultrasonic vacuum technique

Year:  2020        PMID: 33023319     DOI: 10.1177/1082013220962628

Source DB:  PubMed          Journal:  Food Sci Technol Int        ISSN: 1082-0132            Impact factor:   2.023


  1 in total

1.  Mathematical modeling and multivariate analysis applied earliest soybean harvest associated drying and storage conditions and influences on physicochemical grain quality.

Authors:  Roney Eloy Lima; Paulo Carteri Coradi; Marcela Trojahn Nunes; Sabrina Dalla Corte Bellochio; Newiton da Silva Timm; Camila Fontoura Nunes; Letícia de Oliveira Carneiro; Paulo Eduardo Teodoro; Carlos Campabadal
Journal:  Sci Rep       Date:  2021-12-02       Impact factor: 4.379

  1 in total

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