“…The methodology proposed  seems to be advantageous… as it is less time-consuming… and provides higher recognition and prediction abilities”


Application Scientist Christopher Nones

Christopher Nones

BSc, PgDipSci, MSc


Technical Specialist
 
Vaughan Langford Syft Technologies Director - Applications & Marketing

Dr. Vaughan Langford

BSc(Hons), PhD


Principal Scientist / Consultant

Increasing global demand for virgin olive oils has resulted in an increasingly competitive market. A very important factor in production of the highest quality oils is the geographical origin of the olives. Climate, soil, and local expertise all contribute to great-tasting olives. Protected designations of origin (PDO) exist to legally uphold origin labeling as a way of distinguishing olive oils of differing origins and to protect against fraudulent products.

Origin authentication creates new analytical challenges, because reliable, efficient, and economic tests are required. In order to successfully achieve this, a technique has to be robust, highly sensitive, and highly selective. This challenge has been investigated thoroughly in a recent study by an international group of scientists headed by the University of Granada, Spain. In their study the SIFT-MS technique was applied to analysis of volatile aroma compounds in quality olive oils from across the Mediterranean region.  Rather than targeting specific compounds, the researchers adopted a technique pioneered by Dr. Joeri Vercammen (Interscience BVBA) that utilizes a SCAN approach for obtaining the volatile fingerprint of the oil.  This has a distinct advantage compared to targeted analysis in that impurity volatiles – arising, for example, due to fraud – can be detected very readily.

The high sensitivity and selectivity of a Syft Technologies’ Voice200 SIFT-MS instrument was coupled with principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA).  Combined with SIFT-MS analysis, PCA and PLS-DA are powerful chemometric tools that discriminate between different origins based on their characteristic volatile compound profiles. SIFT-MS performed very well in this study. The authors noted that “Spanish samples showed 100% sensitivity, specificity and accuracy in calibration, cross validation and external validation; the model for Moroccan oils also showed very satisfactory results (with perfect scores for almost every parameter in all the cases).”

The authors concluded that the combined SIFT-MS-chemometric approach overcomes limitations of other analytical techniques, which include time-consuming sample preparation and sample analysis, the need for highly skilled analysts, and the high cost per analysis.

In contrast, the high sensitivity and selectivity of SIFT-MS, combined with minimal sample preparation and high-throughput analysis, makes wide-scale origin authentication of olive oil viable. For more information on automated SIFT-MS screening, contact us today!