Novel biosensors and smart tools for ultrasensitive detection of olive oils adulteration

Summary of the project implementation and the most relevant results                     

Rezumatul implementării proiectului și rezultatele cele mai importante

In this project, an analytical system consisting of several electrochemical and optical biosensors specially designed for the ultrasensitive detection of compounds or specific to extra virgin olive oil or of markers present in adulterating oils was created. The data obtained with the biosensors were analyzed using advanced statistical methods to create specific models for different types of oils: extra virgin olive oils, deodorized or refined olive oils, olive pomace oils, seed oils (sunflower, corn, soybean, rapeseed, grape seed, etc.) as well as olive oils to which other types of oil have been added, all of less economic importance. The information included in these statistical models allowed the rapid and precise detection of adulteration of olive oils at concentration levels between 1% and 5%, thus with a very good sensitivity.

The implementation stages of the project primarily included the manufacture of new electrochemical and optical biosensors using different nanomaterials, electron exchange mediators and enzymes. Nanomaterials are useful for increasing the active surface of biosensors, facilitating electron transfer, and immobilizing the enzyme on the active surface of biosensors. Enzymes provide specific detection because they are biocatalysts of specific chemical transformations, processes that occur at a very low rate in the absence of enzymes. Electron exchange mediators increase the speed of electron transfer and therefore the response of the biosensor will be retained in a shorter time and with better sensitivity. Biosensors transform the information from the solution to be analyzed (compounds present, their concentration) into an electrical signal (current) that is recorded to a computer, which uses a specific application for such measurements. The interface between the computer and the biosensor is the potentiostat/galvanostat equipment that ensures the application and recording of electrical signals with very good precision.

In order to have representative data, the responses of several different biosensors, made in this project, were recorded in extracts from olive oils of different qualities, olive cake oils, vegetable oils and samples of adulterated olive oils. For the identification and quantification of biomarkers in the extracts, determinations were made using high-performance liquid chromatography coupled with mass spectrometry.

The analysis of the data obtained experimentally was carried out using statistical programs that allowed the differentiation and classification of oils according to their biological origin, the differentiation and classification of olive oils according to their quality, as well as the differentiation and classification of extra virgin olive oils adulterated with other oils. The methods used were principal component analysis - PCA, cluster analysis - HCA, discriminant analysis solved by the method of partial least squares - PLSDA, soft and independent modeling of class analogy - SIMCA, neural networks - multilevel perceptron (ANN) and machine learning (ML). It was also established that there are very good correlations between the responses of the biosensors and the results of the chromatographic analyzes using multiple regression methods – PLS2. The results obtained from the analysis of more than 250 oil samples, pure and adulterated at the laboratory level in different percentages, are promising, and therefore such an analytical system can be used to determine the adulteration of extra virgin olive oil with other vegetable oils.

The obtained results were published in high quality journals, were presented at international conferences and a patent application was submitted.