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Water Status and Predictive Models of Moisture Content during Drying of Soybean Dregs Based on LF-NMR

Authors :
Tianyou Chen
Wenyu Zhang
Yuxin Liu
Yuqiu Song
Liyan Wu
Cuihong Liu
Tieliang Wang
Source :
Molecules, Vol 27, Iss 14, p 4421 (2022)
Publication Year :
2022
Publisher :
MDPI AG, 2022.

Abstract

To explore the drying characteristics of soybean dregs and a nondestructive moisture content test method, in this study, soybean dregs were dried with hot air (80 °C), the moisture content was measured using the drying method, water status was analyzed using low-field nuclear magnetic resonance (LF-NMR) and the moisture content prediction models were built and validated. The results revealed that the moisture contents of the soybean dregs were 0.57 and 0.01 g/g(w.b.), respectively, after drying for 5 and 7 h. The effective moisture diffusivity increased with the decrease in moisture content; it ranged from 5.27 × 10−9 to 6.96 × 10−8 m2·s−1. Soybean dregs contained bound water (T21), immobilized water (T22) and free water (T23 and T23’). With the proceeding of drying, all of the relaxation peaks shifted left until a new peak (T23’) appeared; then, the structure of soybean dregs changed, and the relaxation peaks reformed, and the peak shifted left again. The peak area may predict the moisture content of soybean dregs, and the gray values of images predict the moisture contents mainly composed of free water or immobilized water. The results may provide a reference for drying of soybean dregs and a new moisture detection method.

Details

Language :
English
ISSN :
14203049
Volume :
27
Issue :
14
Database :
Directory of Open Access Journals
Journal :
Molecules
Publication Type :
Academic Journal
Accession number :
edsdoj.3780f4ae2d243b5a4b9ff33632ca58b
Document Type :
article
Full Text :
https://doi.org/10.3390/molecules27144421