The spectral treasure house of miniaturized instruments for food safety, quality and authenticity applications: A perspective

Judith Müller-Maatsch*, Francesca Romana Bertani, Arianna Mencattini, Annamaria Gerardino, Eugenio Martinelli, Yannick Weesepoel, Saskia van Ruth

*Corresponding author for this work

Research output: Contribution to journalComment/Letter to the editorAcademicpeer-review

Abstract

Background: Optical technologies, relying on spectral analysis, are more and more implemented in portable devices for food analysis. Thereby, each food safety, quality or authenticity provision as well as each technology requires the generation of a dedicated spectral database with reference data. Currently, knowledge on how these databases might be connected or transferred across food commodities, targeted compounds or devices are very limited. Hence, repetitive work is conducted and technologies are not optimally used. Scope and approach: This perspective focuses on the currently available technologies and approaches for data handling and database transfer across miniaturized devices and technologies for food safety, quality and authenticity assessments. Key findings and conclusions: For almost every food commodity or target compound a miniaturized spectroscopic device can be applied with the respective database to compare findings. Recent developments in optical spectroscopy allow more possibilities for their use as well as facilitate the production of portable devices. A multifunctional device hyphenating several sensors and broadening the application range is still not marketed. Newly developed software architecture, accessing and extracting data, helps to overcome sample heterogenicity or spurious measured data. In addition, several data fusion approaches using machine learning and deep learning strategies are available to fuse spectroscopic data with itself or other non-spectroscopic data. Following the research results presented in this field, spectral data can possibly be re-used and shared across instruments and locations, highly increasing the applicability of data sets. Thereby, obstacles such as policy or confidentiality are taken into account.

Original languageEnglish
JournalTrends in Food Science and Technology
DOIs
Publication statusE-pub ahead of print - 8 Feb 2021

Keywords

  • Data fusion
  • Data portability
  • Fluorescence
  • Machine learning
  • Miniaturized
  • Portable devices
  • Spectral databases
  • Spectral imaging
  • Spectroscopy

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