NIR laser-based imaging techniques to monitor quality attributes of apple slices during the drying process: Laser-light backscattering &amp; biospeckle imaging techniques

Arefi, Arman; Sturm, Barbara; Raut, Sharvari; Gersdorff, Gardis von; Hensel, Oliver

doi:10.1016/j.foodcont.2022.109289

Cited by 6 publications

(1 citation statement)

References 29 publications

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“…In LF-NMR, the state and content of water in the sample are monitored by analyzing the transverse relaxation time (T 2 ) of hydrogen ions in different states of existence in the magnetic field (Long et al, 2017;Song et al, 2016). Hyperspectral imaging, NIR imaging, and Magnetic resonance imaging (MRI) have been studied to monitor physiochemical changes in apple slices during the drying process (Arefi et al, 2021(Arefi et al, , 2023Kamal, Cheng, et al, 2019). Among these, MRI technique reveals the migration of water in the sample by analyzing changes in color and brightness (Song et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

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

Guan,

Hua,

Cheng

et al. 2023

J Food Process Engineering

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In 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.

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