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

    17 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

    Keywords

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

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