Spices are usually ground for applications and the resulting particle size of the powders is an important product attribute in view of the release of flavour. However, inhomogeneity of the original material may lead to variations in the physicochemical characteristics of the particles. This variation and its linkage to particle size may be examined by particular imaging techniques. This study aimed to explore the potential of Fluorescence Lifetime Imaging Microscopy (FLIM) to characterize spice powders according to particle size variations and correlation with their pigment contents to reveal the chemical information contained within the FLIM data. Ginger powder was used as a representative powder model. The FLIM profiles of the individual samples and populations revealed that FLIM coupled with the phasor approach has the capacity to characterize spice powder according to particle size. Meanwhile, Principal Component Analysis of pre-processed FLIM data revealed clustering of particle size groups. Further correlation analysis between the pigment compound contents and FLIM data of the ginger powders indicated that FLIM reflected chemical information of ginger powder and was able to visualize endogenous fluorophores. The current study revealed the potential of FLIM to characterize ginger powder particles. This approach may be extrapolated to other spice powder products. The new knowledge is a step further in paving the way for the application of innovative techniques, already prevalent in other domains, to food quality and authentication.
Fluorescence lifetime imaging microscopy as a tool to characterize spice powder variations for quality and authenticity purposes: A ginger case study.
Qing Han,S. Erasmus,A. Bader,Christos Fryganas,Christopher T. Elliott,S. V. van Ruth
Published 2023 in Food Research International
ABSTRACT
PUBLICATION RECORD
- Publication year
2023
- Venue
Food Research International
- Publication date
2023-12-01
- Fields of study
Medicine, Materials Science
- Identifiers
- External record
- Source metadata
Semantic Scholar, PubMed
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