Monitoring of water content of apple slices using low‐field nuclear magnetic resonance during drying process

Author:

Guan Yeqing1,Hua Zhuqing1,Cheng Yudou1,He Jingang1,Zhang Yang1,Guan Junfeng1ORCID

Affiliation:

1. Institute of Biotechnology and Food Science Hebei Academy of Agriculture and Forestry Sciences Shijiazhuang PR China

Abstract

AbstractIn an aim to examine water content, distribution, and state of apple slices during hot air drying, this study determined the inversion spectra of transverse relaxation time (T2) of apple slices during the drying process at different temperatures using low‐field nuclear magnetic resonance (LF‐NMR) and magnetic resonance imaging (MRI). The results showed that drying temperatures was negatively correlated with water content and positively correlated with drying rate. The relaxation peak area of free water decreased, while those of semi‐bound and bound water increased and subsequently decreased. The water content of apple slices had quadratic polynomial correlations with signal amplitudes of LF‐NMR (peak areas of total, free, and semi‐bound), R2 of these regression fitting equations were basically above 0.8 and 0.9. The models of total and free water had good prediction performance, suggesting that LF‐NMR is suitable for rapid non‐destructive testing of water in apple slices during hot air drying.Practical applicationsIn this work, the amount of water in apple slices at any given time during hot air drying can be predicted well‐using regression fitting equation models of the peak areas of total, free, and semi‐bound water. This information can then be used to improve the quality of dried products and clarify the distribution and states of water during drying. Therefore, LF‐NMR can be used for rapid non‐destructive testing of water in apple slices during hot air drying. And it provided references for further investigation of optimized drying methods and conditions for different apple species and achieved accurate and non‐destructive monitoring of water in fruits during processing based on LF‐NMR.

Publisher

Wiley

Subject

General Chemical Engineering,Food Science

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