A statistical strategy to assess cleaning level of surfaces using fluorescence spectroscopy and Wilks’ ratio

Research output: Contribution to journalJournal articleResearchpeer-review

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A statistical strategy to assess cleaning level of surfaces using fluorescence spectroscopy and Wilks’ ratio. / Stoica, Iuliana-Madalina; Babamoradi, Hamid; van der Berg, Franciscus Winfried J.

In: Chemometrics and Intelligent Laboratory Systems, Vol. 165, 2017, p. 11-21.

Research output: Contribution to journalJournal articleResearchpeer-review

Harvard

Stoica, I-M, Babamoradi, H & van der Berg, FWJ 2017, 'A statistical strategy to assess cleaning level of surfaces using fluorescence spectroscopy and Wilks’ ratio', Chemometrics and Intelligent Laboratory Systems, vol. 165, pp. 11-21. https://doi.org/10.1016/j.chemolab.2017.03.014

APA

Stoica, I-M., Babamoradi, H., & van der Berg, F. W. J. (2017). A statistical strategy to assess cleaning level of surfaces using fluorescence spectroscopy and Wilks’ ratio. Chemometrics and Intelligent Laboratory Systems, 165, 11-21. https://doi.org/10.1016/j.chemolab.2017.03.014

Vancouver

Stoica I-M, Babamoradi H, van der Berg FWJ. A statistical strategy to assess cleaning level of surfaces using fluorescence spectroscopy and Wilks’ ratio. Chemometrics and Intelligent Laboratory Systems. 2017;165:11-21. https://doi.org/10.1016/j.chemolab.2017.03.014

Author

Stoica, Iuliana-Madalina ; Babamoradi, Hamid ; van der Berg, Franciscus Winfried J. / A statistical strategy to assess cleaning level of surfaces using fluorescence spectroscopy and Wilks’ ratio. In: Chemometrics and Intelligent Laboratory Systems. 2017 ; Vol. 165. pp. 11-21.

Bibtex

@article{83389ea58d2a4ccd85ab10e6ebc687f0,
title = "A statistical strategy to assess cleaning level of surfaces using fluorescence spectroscopy and Wilks{\textquoteright} ratio",
abstract = "There is a high demand for techniques able to monitor on-line, in real-time, the bio-contamination level of contact surfaces in the food industry. Such techniques could help to react promptly whenever failures in the cleaning or sanitation operations occur, keep the safety parameters in control at any time during production, and ultimately tailor the operations towards more sustainable and efficient practices. However, monitoring surface areas such as conveyor belts comes with a distinct set of challenges from the construction materials used in food processing equipment such as compositional-heterogeneity, background signals and continuous changes due to wear and tear. In this work we demonstrate the potential of front-face fluorescence spectroscopy in combination with Wilks{\textquoteright} ratio statistics for monitoring large surface areas fouled under industrial working conditions. The technique was tested in both off-line and on-line mode, for a polymer-based conveyor surface, which presents an intrinsic natural variation across its running length and which was contaminated artificially for a proof of principle. Results show that any potential contamination will shift the variance and covariance structure of the in-control fluorescence landscapes modeled with PARAFAC, and detected this shift as a deviation from the reference clean state in a Wilks{\textquoteright} ratio based monitoring charts.",
keywords = "Biofouling, Conveyor belts, Fluorescence, PARAFAC, Process monitoring, Wilks{\textquoteright} ratio statistics",
author = "Iuliana-Madalina Stoica and Hamid Babamoradi and {van der Berg}, {Franciscus Winfried J}",
year = "2017",
doi = "10.1016/j.chemolab.2017.03.014",
language = "English",
volume = "165",
pages = "11--21",
journal = "Chemometrics and Intelligent Laboratory Systems",
issn = "0169-7439",
publisher = "Elsevier",

}

RIS

TY - JOUR

T1 - A statistical strategy to assess cleaning level of surfaces using fluorescence spectroscopy and Wilks’ ratio

AU - Stoica, Iuliana-Madalina

AU - Babamoradi, Hamid

AU - van der Berg, Franciscus Winfried J

PY - 2017

Y1 - 2017

N2 - There is a high demand for techniques able to monitor on-line, in real-time, the bio-contamination level of contact surfaces in the food industry. Such techniques could help to react promptly whenever failures in the cleaning or sanitation operations occur, keep the safety parameters in control at any time during production, and ultimately tailor the operations towards more sustainable and efficient practices. However, monitoring surface areas such as conveyor belts comes with a distinct set of challenges from the construction materials used in food processing equipment such as compositional-heterogeneity, background signals and continuous changes due to wear and tear. In this work we demonstrate the potential of front-face fluorescence spectroscopy in combination with Wilks’ ratio statistics for monitoring large surface areas fouled under industrial working conditions. The technique was tested in both off-line and on-line mode, for a polymer-based conveyor surface, which presents an intrinsic natural variation across its running length and which was contaminated artificially for a proof of principle. Results show that any potential contamination will shift the variance and covariance structure of the in-control fluorescence landscapes modeled with PARAFAC, and detected this shift as a deviation from the reference clean state in a Wilks’ ratio based monitoring charts.

AB - There is a high demand for techniques able to monitor on-line, in real-time, the bio-contamination level of contact surfaces in the food industry. Such techniques could help to react promptly whenever failures in the cleaning or sanitation operations occur, keep the safety parameters in control at any time during production, and ultimately tailor the operations towards more sustainable and efficient practices. However, monitoring surface areas such as conveyor belts comes with a distinct set of challenges from the construction materials used in food processing equipment such as compositional-heterogeneity, background signals and continuous changes due to wear and tear. In this work we demonstrate the potential of front-face fluorescence spectroscopy in combination with Wilks’ ratio statistics for monitoring large surface areas fouled under industrial working conditions. The technique was tested in both off-line and on-line mode, for a polymer-based conveyor surface, which presents an intrinsic natural variation across its running length and which was contaminated artificially for a proof of principle. Results show that any potential contamination will shift the variance and covariance structure of the in-control fluorescence landscapes modeled with PARAFAC, and detected this shift as a deviation from the reference clean state in a Wilks’ ratio based monitoring charts.

KW - Biofouling

KW - Conveyor belts

KW - Fluorescence

KW - PARAFAC

KW - Process monitoring

KW - Wilks’ ratio statistics

U2 - 10.1016/j.chemolab.2017.03.014

DO - 10.1016/j.chemolab.2017.03.014

M3 - Journal article

AN - SCOPUS:85017469037

VL - 165

SP - 11

EP - 21

JO - Chemometrics and Intelligent Laboratory Systems

JF - Chemometrics and Intelligent Laboratory Systems

SN - 0169-7439

ER -

ID: 179123500