Pamela Galvin-King

Dr. Pamela Galvin-King


Research Focus & Metrics

Academic Career Length

9Years (2018-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 January 2018 in Food Chemistry
Verified
Journal Article
Open access
EWEwa Wielogorska
Ewa Wielogorska
OCOlivier Chevallier
Olivier Chevallier
CBConnor Black
Connor Black
PGPamela Galvin-King
Pamela Galvin-King
MDMarc Delêtre
Marc Delêtre
CEChris Elliott
Chris Elliott
Due to increasing number of food fraud incidents, there is an inherent need for the development and implementation of analytical platforms enabling detection and quantitation of adulteration. In this study a set of unique biomarkers of commonly found oregano adulterants became the targets in the development of a LC-MS/MS method which underwent a rigorous in-house validation. The method presented very high selectivity and specificity, excellent linearity (R2>0.988) low decision limits and detection capabilities (0.81). An assessment of 54 suspected adulterated oregano samples revealed that almost 90% of them contained at least one bulking agent, with a median level of adulteration of 50%. Such innovative methodologies need to be established as routine testing procedures to detect and ultimately deter food fraud.

16 July 2020 in Foods
Verified
Journal Article
Open access
PDF file
PGPamela Galvin-King
Pamela Galvin-King
Simon HaugheySimon Haughey
Simon Haughey
CEChris Elliott
Chris Elliott
The spice paprika (Capsicum annuum and frutescens) is used in a wide variety of cooking methods as well as seasonings and sauces. The oil, paprika oleoresin, is a valuable product; however, once removed from paprika, the remaining spent product can be used to adulterate paprika. Near-infrared (NIR) and Fourier transform infrared (FTIR) were the platforms selected for the development of methods to detect paprika adulteration in conjunction with chemometrics. Orthogonal partial least squares discriminant analysis (OPLS-DA), a supervised technique, was used to develop the chemometric models, and the measurement of fit (R2) and measurement of prediction (Q2) values were 0.853 and 0.819, respectively, for the NIR method and 0.943 and 0.898 respectively for the FTIR method. An external validation set was tested against the model, and a receiver operating curve (ROC) was created. The area under the curve (AUC) for both methods was highly accurate at 0.951 (NIR) and 0.907 (FTIR). The levels of adulteration with 100% correct classification were 50–90% (NIR) and 40–90% (FTIR). Sudan I dye is a commonly used adulterant in paprika; however, in this study it was found that this dye had no effect on the outcome of the result for spent material adulteration.

14 November 2018
Verified
Book Chapter
Closed access
PGPamela Galvin-King
Pamela Galvin-King
Simon HaugheySimon Haughey
Simon Haughey
CEChristopher T. Elliott
Christopher T. Elliott