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<dc:title>Influence of a Measurement Procedure and Evaluation of Transflectance Sensing System for Quantifying Sunflower Oil Adulterations in Olive Oil. A Proof of Concept</dc:title>
<dc:creator>Castro Reigía, David</dc:creator>
<dc:creator>Sierra, M.</dc:creator>
<dc:creator>García, I.</dc:creator>
<dc:creator>Sanllorente Méndez, Silvia</dc:creator>
<dc:creator>Sarabia Peinador, Luis Antonio</dc:creator>
<dc:creator>Ortiz Fernández, Mª Cruz</dc:creator>
<dc:subject>Adulteration</dc:subject>
<dc:subject>ASCA</dc:subject>
<dc:subject>NIR spectroscopy</dc:subject>
<dc:subject>Olive oil</dc:subject>
<dc:subject>PLS</dc:subject>
<dc:description>The development of NIR instruments and/or their modification to adapt the measurements for each problem and improve its performance are crucial steps for the optimal measurement procedures. In this work, it is presented the development of an accessory for cuvettes designed to have the possibility to collect NIR spectra in transflectance mode. In that sense, it is aimed to investigate how different factors in the measurement procedure using this accessory influence both the NIR spectra and the subsequent calibration models for detecting adulterations with sunflower oil in olive oil. The purpose is to show how a proof of concept can be developed using chemometric tools. For that, every measurement condition influencing the spectra was evaluated with ASCA, visualizing how the use of different NIR devices, the sensor arrangement regarding the cuvette, the activation of the internal compensation system of temperature of the sensor, or the concentration levels of the adulterant affected the resulting spectra. Afterwards, every possible combination of the factors was explored through eight different PLS calibration models and their validation to examine if the factors also influenced the calibration models built for quantifying the sunflower oil present in the olive oil. It was found that not only were all factors significant regarding NIR measurements but also when quantifying adulterants. The best results of this proof of concept were obtained by arranging the sensor in a horizontal disposition regarding the cuvette and activating the internal compensation system of temperature. The capability of detection of the method for the particular oils used was 1.4% for probabilities of false positive and false negative of 0.05.</dc:description>
<dc:date>2025-07-29T11:44:42Z</dc:date>
<dc:date>2025-07-29T11:44:42Z</dc:date>
<dc:date>2025-08</dc:date>
<dc:type>info:eu-repo/semantics/article</dc:type>
<dc:identifier>0886-9383</dc:identifier>
<dc:identifier>https://hdl.handle.net/10259/10774</dc:identifier>
<dc:identifier>10.1002/cem.70054</dc:identifier>
<dc:identifier>1099-128X</dc:identifier>
<dc:language>eng</dc:language>
<dc:relation>Journal of Chemometrics. 2025, V. 39, n. 8, e70054</dc:relation>
<dc:relation>https://doi.org/10.1002/cem.70054</dc:relation>
<dc:rights>http://creativecommons.org/licenses/by-nc-nd/4.0/</dc:rights>
<dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
<dc:rights>Attribution-NonCommercial-NoDerivatives 4.0 Internacional</dc:rights>
<dc:publisher>Wiley</dc:publisher>
</ow:Publication>
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