Presentation Type
Poster
Student
Yes
Track
Other
Abstract
Enhancing food quality measurement is a necessity to guarantee food safety and adherence to health regulations. Current methods involve lab testing which are time-consuming, costly, destructive and require skilled workers. Spectroscopy has the potential to overcome these challenges. This study employs a multi-mode point spectroscopy method to distinguish food products according to their spectral characteristics,. The system records fluorescence, excited at 365 and 405 nm, visible-near infrared (Vis-NIR) and short-wave infrared (SWIR) spectra. The three main subjects of the study are olive oil, milk, and honey. Samples were kept in a transparent cell culture pot, and Gray and White Spectralon were used to calibrate the spectroscopy equipment. The results showed that various dietary samples exhibit unique spectral patterns across a range of wavelengths. Fluorescence spectra at excitation wavelengths of 365 nm and 405 nm, respectively, helped to distinguish between olive oil and milk types. In the 440–1900 nm wavelength range, the spectra of several food samples revealed distinct spectral lines for every kind of sample. Principal Component Analysis (PCA), which reveals clusters and relationships among related products, validated the difference among the food samples. The results imply that multi-mode point spectroscopy is a quick and effective way to differentiate between various food samples.
Start Date
2-6-2024 1:00 PM
End Date
2-6-2024 2:00 PM
Included in
Biomedical Devices and Instrumentation Commons, Electrical and Computer Engineering Commons, Medicine and Health Sciences Commons
Multimode Point Spectroscopy for Food Authentication
Volstorff A
Enhancing food quality measurement is a necessity to guarantee food safety and adherence to health regulations. Current methods involve lab testing which are time-consuming, costly, destructive and require skilled workers. Spectroscopy has the potential to overcome these challenges. This study employs a multi-mode point spectroscopy method to distinguish food products according to their spectral characteristics,. The system records fluorescence, excited at 365 and 405 nm, visible-near infrared (Vis-NIR) and short-wave infrared (SWIR) spectra. The three main subjects of the study are olive oil, milk, and honey. Samples were kept in a transparent cell culture pot, and Gray and White Spectralon were used to calibrate the spectroscopy equipment. The results showed that various dietary samples exhibit unique spectral patterns across a range of wavelengths. Fluorescence spectra at excitation wavelengths of 365 nm and 405 nm, respectively, helped to distinguish between olive oil and milk types. In the 440–1900 nm wavelength range, the spectra of several food samples revealed distinct spectral lines for every kind of sample. Principal Component Analysis (PCA), which reveals clusters and relationships among related products, validated the difference among the food samples. The results imply that multi-mode point spectroscopy is a quick and effective way to differentiate between various food samples.