Implementation of NIR technology for at-line rapid detection of sunflower oil adulterated with mineral oil

Pierre A. Picouet, Pere Gou, Risto Hyypiö, Massimo Castellari (Corresponding Author)

Research output: Contribution to journalArticleScientificpeer-review

3 Citations (Scopus)

Abstract

Three experimental setups, based on near infrared technology (NIR), were tested for rapid “at-line” assessment of sunflower oil adulteration by mineral oil. Experimental setups included a commercial portable NIR, coupled to both reflexion (S1) and immersion probes (S2), and a prototype of a multichannel Quasi Imaging Visible NIR spectrometer (QIVN) coupled to an immersion probe (S3). Independent calibration and validation samples sets were prepared with mineral oils (MOs) content up to 10% (w/w), and calibrations were developed using partial least square (PLS) regressions. Root mean square error of prediction (RMSEP) ranges from 0.23 to 1.26% (w/w) MOs, depending on the NIR setup. The best performances were obtained with S1, which provides satisfactory calibrations, and low number of false positives starting from levels of mineral oil around 1%. S3 still provides acceptable calibrations, and could be practically used to detect mineral oil at concentrations higher than 2.5% (w/w) MOs.

Original languageEnglish
Pages (from-to)18-27
Number of pages10
JournalJournal of Food Engineering
Volume230
DOIs
Publication statusPublished - 1 Aug 2018
MoE publication typeA1 Journal article-refereed

Fingerprint

Mineral Oil
mineral oil
sunflower oil
Technology
Calibration
calibration
Immersion
probes (equipment)
adulterated products
spectrometers
Least-Squares Analysis
prototypes
sunflower seed oil
least squares
lipid content
image analysis
prediction

Keywords

  • At-line detection
  • Mineral oil detection
  • Near infrared spectroscopy
  • Sunflower oil

Cite this

Picouet, Pierre A. ; Gou, Pere ; Hyypiö, Risto ; Castellari, Massimo. / Implementation of NIR technology for at-line rapid detection of sunflower oil adulterated with mineral oil. In: Journal of Food Engineering. 2018 ; Vol. 230. pp. 18-27.
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abstract = "Three experimental setups, based on near infrared technology (NIR), were tested for rapid “at-line” assessment of sunflower oil adulteration by mineral oil. Experimental setups included a commercial portable NIR, coupled to both reflexion (S1) and immersion probes (S2), and a prototype of a multichannel Quasi Imaging Visible NIR spectrometer (QIVN) coupled to an immersion probe (S3). Independent calibration and validation samples sets were prepared with mineral oils (MOs) content up to 10{\%} (w/w), and calibrations were developed using partial least square (PLS) regressions. Root mean square error of prediction (RMSEP) ranges from 0.23 to 1.26{\%} (w/w) MOs, depending on the NIR setup. The best performances were obtained with S1, which provides satisfactory calibrations, and low number of false positives starting from levels of mineral oil around 1{\%}. S3 still provides acceptable calibrations, and could be practically used to detect mineral oil at concentrations higher than 2.5{\%} (w/w) MOs.",
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Implementation of NIR technology for at-line rapid detection of sunflower oil adulterated with mineral oil. / Picouet, Pierre A.; Gou, Pere; Hyypiö, Risto; Castellari, Massimo (Corresponding Author).

In: Journal of Food Engineering, Vol. 230, 01.08.2018, p. 18-27.

Research output: Contribution to journalArticleScientificpeer-review

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