Geographical identification of Italian extra virgin olive oil by the combination of near infrared and Raman spectroscopy: A feasibility study

Abstract

The potential of the combination of near infrared (NIR) spectroscopy and Raman spectroscopy to differentiate Italian and Greek extra virgin olive oil (EVOO) by geographical origin was evaluated. Near infrared spectroscopy and Raman fingerprints of both study groups (extra virgin olive oil from the two countries) were pre-processed, merged by low-level and mid-level data fusion strategies and submitted to partial least-squares discriminant analysis. The classification models were cross-validated. After low-level data fusion, the partial least-squares discriminant analysis correctly predicted the geographical origins of extra virgin olive oils in cross-validation with 93.9% accuracy, while sensitivity and specificity were 77.8% and 100%, respectively. After mid-level data fusion, the partial least-squares discriminant analysis correctly predicted the geographical origins of extra virgin olive oils in cross-validation with 97.0% accuracy, while sensitivity and specificity were 88.9% and 100%, respectively. In this preliminary study, improved discrimination of Italian extra virgin olive oils was achieved by the synergism of near infrared spectroscopy and Raman spectroscopy as compared to the discrimination obtained by the separate laboratory techniques. This pilot study shows encouraging results that could open a new avenue for the authentication of Italian extra virgin olive oil.

Exploring the use of NIR and Raman spectroscopy for the prediction of quality traits in PDO cheeses

“…Wang et al ( 34 ) developed chemometric models using Vis–NIR and Raman spectral data fusion for the assessment of commercial infant formula storage temperature and time, with a RMSE VAL of 0.7 for the mid-level data fusion to predict storage time at both 20° and 37°C. Again, Bragolusi et al ( 19 ) in their preliminary study on the differentiation of Italian and Greek extra virgin olive oil, they merged NIR and Raman spectra by low and mid-level fusion and submitted to PLS-DA analysis. In cross-validation the accuracy was 94% for the low-level and 97% for the mid-level fusion.…”

“…Adhesiveness, chewiness, and cohesiveness had relatively low R 2 CAL and R 2 VAL values in all three type of data, suggesting that they might be challenging to predict using these spectroscopic/chemometric techniques. In the scientific literature, the highest number of publications incorporating data fusion techniques is alcoholic beverages (27%) [e.g., ( 18 )] followed by fruit and vegetables (17%) [e.g., ( 50 )] and oils (13%) [e.g., ( 19 )]. Milk and dairy products cover the smallest percentage (only 5%) ( 49 ), therefore, it is difficult to compare our results with the current literature.…”

“…After scaling, the NIR and Raman spectra were concatenated and stored as single matrix to be used for the spectra analysis. This is called low-level data fusion ( 18 , 19 ). No other mathematical preprocessing was applied to the spectra.…”

Combination of vibrational spectroscopy, mass spectrometry and chemometrics in an innovative food chemistry laboratory of the Italian health authority and research organization for animal health and food safety: Istituto Zooprofilattico Sperimentale delle Venezie (IZSVe)

“…These merging strategies were explored to merge different analytical techniques and thus reveal the sophistication of extra-virgin olive oil with soft refined olive oils, 3 the counterfeiting of Italian EVOO, 4 the adulteration of spices 5 and the mislabeling of frozen-thawed fish. 6…”

Nutritional labelling of food products purchased from online retail outlets: screening of compliance with European Union tolerance limits by near infrared spectroscopy

“…[15][16][17] The method is a cost-effective, non-destructive, rapid technique that does not use organic solvents. NIR spectroscopy has been applied to estimate the food composition for nutritional fact labels, 18 evaluate authenticity and provenance [19][20][21][22][23][24][25][26] and to monitor in-line food production and processes. 27 The application of NIR spectroscopy is based on calibration models that rely on quantitative values obtained by reference methods.…”