A partial least squares-based approach to assess the light penetration depth in wheat flour by near infrared hyperspectral imaging. Issue 1 (February 2020)
- Record Type:
- Journal Article
- Title:
- A partial least squares-based approach to assess the light penetration depth in wheat flour by near infrared hyperspectral imaging. Issue 1 (February 2020)
- Main Title:
- A partial least squares-based approach to assess the light penetration depth in wheat flour by near infrared hyperspectral imaging
- Authors:
- Laborde, Antoine
Jaillais, Benoît
Bendoula, Ryad
Roger, Jean-Michel
Jouan-Rimbaud Bouveresse, Delphine
Eveleigh, Luc
Bertrand, Dominique
Boulanger, Anthony
Cordella, Christophe BY - Abstract:
- Near infrared hyperspectral imaging technique has been used for adulteration detection in food samples for several years. However, the sensor cannot screen beyond a certain material thickness. This work studies a method to determine the penetration depth of near infrared radiations in the context of detection. The case of wheat flour in a polylactic acid sample holder is investigated. A sample holder is specially designed to have the wheat flour thickness vary from 0.5 to 3.5 mm. Hyperspectral images are acquired and the partial least squares regression method is used to determine the amount of polylactic acid in each spectrum. Partial least squares prediction results are interpreted using sensor considerations and the Kubelka–Munk theory. Thereafter, the Kubelka–Munk model is fitted and the penetration depth is determined for each wavelength using the reflectance profiles. Similarities between these results and partial least squares regression coefficients lead to the conclusion that partial least squares, combined with the near infrared spectra, is able to characterize the detection depth. The value is calculated by fitting two linear models on the partial least squares prediction results. As a result, 1.80 mm is found to be the detection depth, defined as the maximum thickness of wheat flour to ensure the detection of polylactic acid through the background. Reflectance profiles also show that the penetration depth is highly dependent on the wavelength. This study aimed atNear infrared hyperspectral imaging technique has been used for adulteration detection in food samples for several years. However, the sensor cannot screen beyond a certain material thickness. This work studies a method to determine the penetration depth of near infrared radiations in the context of detection. The case of wheat flour in a polylactic acid sample holder is investigated. A sample holder is specially designed to have the wheat flour thickness vary from 0.5 to 3.5 mm. Hyperspectral images are acquired and the partial least squares regression method is used to determine the amount of polylactic acid in each spectrum. Partial least squares prediction results are interpreted using sensor considerations and the Kubelka–Munk theory. Thereafter, the Kubelka–Munk model is fitted and the penetration depth is determined for each wavelength using the reflectance profiles. Similarities between these results and partial least squares regression coefficients lead to the conclusion that partial least squares, combined with the near infrared spectra, is able to characterize the detection depth. The value is calculated by fitting two linear models on the partial least squares prediction results. As a result, 1.80 mm is found to be the detection depth, defined as the maximum thickness of wheat flour to ensure the detection of polylactic acid through the background. Reflectance profiles also show that the penetration depth is highly dependent on the wavelength. This study aimed at providing a method that could be used to evaluate the penetration depth and the detection depth in other contexts than a polylactic acid target in wheat flour. … (more)
- Is Part Of:
- Journal of near infrared spectroscopy. Volume 28:Issue 1(2020)
- Journal:
- Journal of near infrared spectroscopy
- Issue:
- Volume 28:Issue 1(2020)
- Issue Display:
- Volume 28, Issue 1 (2020)
- Year:
- 2020
- Volume:
- 28
- Issue:
- 1
- Issue Sort Value:
- 2020-0028-0001-0000
- Page Start:
- 25
- Page End:
- 36
- Publication Date:
- 2020-02
- Subjects:
- Hyperspectral imaging -- near infrared spectroscopy -- penetration depth -- partial least squares regression -- detection
Near infrared spectroscopy -- Periodicals
543.5 - Journal URLs:
- http://www.uk.sagepub.com/home.nav ↗
http://www.nirpublications.com/jnirs.html ↗
http://journals.sagepub.com/toc/JNS/current ↗ - DOI:
- 10.1177/0967033519891594 ↗
- Languages:
- English
- ISSNs:
- 0967-0335
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
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- British Library DSC - BLDSS-3PM
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