Academic Bibliography

 Search 200 years of publications by Ghent University researchers.
Advanced search
Add to list
  1. Search results
  2. Laser-induced fluorescence spectrosco...

Laser-induced fluorescence spectroscopy enhancing pistachio nut quality screening

Indy Magnus, Fatemeh Abbasi (UGent) , Hugo Thienpont and Lien Smeesters
(2024) FOOD CONTROL. 158.
Author
Organization
Abstract
Food safety and quality has become increasingly important in our society, driving the development of novel optical food sensing technologies. Optical sensing technologies have shown good product identification performances, while offering a non-destructive measurement and the possibility for in-line applications. They are, however, currently often limited in their sensitivity and product variability. We therefore pursue the development of a novel pistachio nut screening methodology offering a multi-defect detection, simultaneously detecting shells, tree parts and aflatoxins, by combining fluorescence spectroscopy with advanced chemometrics. Specifically, both one- and two-photon induced fluorescence are investigated, in combination with Linear Discriminant Analysis, Quadratic Discriminant Analysis and K-Nearest Neighbors algorithm, enabling to optimize both the hardware and software parameters. Optimal results were obtained combining the fluorescence spectra using 385 nm excitation with Quadratic Discriminant Analysis, showing a classification accuracy of 99.2% for the healthy pistachio kernels, together with a false positive rate of only 0.8%. This excellent classification accuracy, while considering a multi-defect challenge, is exceeding the state-of-the-art, paving the way towards an improved pistachio screening, benefitting the food processing industry.
Keywords
Food Science, Biotechnology, Fluorescence spectroscopy, Two-photon induced fluorescence, Pistachio, nuts, Non-destructive food classification, Quadratic discriminant, analysis, Sequential forward search

Citation

Please use this url to cite or link to this publication:

MLA
Magnus, Indy, et al. “Laser-Induced Fluorescence Spectroscopy Enhancing Pistachio Nut Quality Screening.” FOOD CONTROL, vol. 158, 2024, doi:10.1016/j.foodcont.2023.110192.
APA
Magnus, I., Abbasi, F., Thienpont, H., & Smeesters, L. (2024). Laser-induced fluorescence spectroscopy enhancing pistachio nut quality screening. FOOD CONTROL, 158. https://doi.org/10.1016/j.foodcont.2023.110192
Chicago author-date
Magnus, Indy, Fatemeh Abbasi, Hugo Thienpont, and Lien Smeesters. 2024. “Laser-Induced Fluorescence Spectroscopy Enhancing Pistachio Nut Quality Screening.” FOOD CONTROL 158. https://doi.org/10.1016/j.foodcont.2023.110192.
Chicago author-date (all authors)
Magnus, Indy, Fatemeh Abbasi, Hugo Thienpont, and Lien Smeesters. 2024. “Laser-Induced Fluorescence Spectroscopy Enhancing Pistachio Nut Quality Screening.” FOOD CONTROL 158. doi:10.1016/j.foodcont.2023.110192.
Vancouver
1.
Magnus I, Abbasi F, Thienpont H, Smeesters L. Laser-induced fluorescence spectroscopy enhancing pistachio nut quality screening. FOOD CONTROL. 2024;158.
IEEE
[1]
I. Magnus, F. Abbasi, H. Thienpont, and L. Smeesters, “Laser-induced fluorescence spectroscopy enhancing pistachio nut quality screening,” FOOD CONTROL, vol. 158, 2024.
@article{01HQWP6MVVMQ5AWMMNV8Q67ZEZ,
  abstract     = {{Food safety and quality has become increasingly important in our society, driving the development of novel optical food sensing technologies. Optical sensing technologies have shown good product identification performances, while offering a non-destructive measurement and the possibility for in-line applications. They are, however, currently often limited in their sensitivity and product variability. We therefore pursue the development of a novel pistachio nut screening methodology offering a multi-defect detection, simultaneously detecting shells, tree parts and aflatoxins, by combining fluorescence spectroscopy with advanced chemometrics. Specifically, both one- and two-photon induced fluorescence are investigated, in combination with Linear Discriminant Analysis, Quadratic Discriminant Analysis and K-Nearest Neighbors algorithm, enabling to optimize both the hardware and software parameters. Optimal results were obtained combining the fluorescence spectra using 385 nm excitation with Quadratic Discriminant Analysis, showing a classification accuracy of 99.2% for the healthy pistachio kernels, together with a false positive rate of only 0.8%. This excellent classification accuracy, while considering a multi-defect challenge, is exceeding the state-of-the-art, paving the way towards an improved pistachio screening, benefitting the food processing industry.}},
  articleno    = {{110192}},
  author       = {{Magnus, Indy and Abbasi, Fatemeh and Thienpont, Hugo and Smeesters, Lien}},
  issn         = {{0956-7135}},
  journal      = {{FOOD CONTROL}},
  keywords     = {{Food Science,Biotechnology,Fluorescence spectroscopy,Two-photon induced fluorescence,Pistachio,nuts,Non-destructive food classification,Quadratic discriminant,analysis,Sequential forward search}},
  language     = {{eng}},
  pages        = {{11}},
  title        = {{Laser-induced fluorescence spectroscopy enhancing pistachio nut quality screening}},
  url          = {{http://doi.org/10.1016/j.foodcont.2023.110192}},
  volume       = {{158}},
  year         = {{2024}},
}
Altmetric
View in Altmetric
Web of Science
Times cited: