Detection of Olive Oil Adulteration With Rapeseed and Sunflower Oils Using Mos Electronic Nose and Smpe‐ms

Abstract

The study analyzed the effectiveness of two types of electronic nose systems to detect adulteration of extra virgin olive oil (EVOO) with rapeseed and sunflower oils. Tested methods included volatile analysis with the electronic nose based on MOS sensors (HS‐E nose) and by direct coupling of SPME to MS (SPME‐MS). Volatile compounds were analyzed also by SPME‐GC/MS. Samples of EVOO were mixed with different proportions, ranging from 5 to 50% (v/v), of seed oils and fingerprints of volatile profiles of all samples were generated. In order to obtain as much chemical information as possible and to find a volatile marker to detect adulterations of EVOO with seed oils, principal component analysis (PCA) and partial least squares (PLS) analyses were applied to the data. The application of PCA and PLS analyses to the data from two electronic noses and SMPE‐GC/MS were sufficient to differentiate the adulterated samples from pure EVOO. Excellent results were obtained in the prediction of the percentage of adulteration by PLS analysis. SPME‐GC‐MS analysis with subsequent PCA yielded good results; however, it was time‐consuming. The two electronic noses, with subsequent PCA treatment of data, offering the advantages of rapidity and reliability, enabled detection of olive oil adulteration with different contents of seed oils. PRACTICAL APPLICATIONS Virgin olive oil is highly appreciated by consumers due to its nutritional benefits. Thus, its adulteration with low‐grade olive oils or cheaper vegetable oils could potentially be very profitable for sellers or raw material suppliers and may yield large economic profits. In this way, authentication of virgin olive oils has become an interesting subject from both commercial and health perspectives. It has been proved that the two proposed types of electronic nose systems facilitate reliable detection of rapeseed and sunflower oils in extra virgin olive oil. Both MOS and MS electronic noses are faster than the conventional SMPE‐GC/MS analysis. These well‐correlated methodologies, offering the advantages of rapidity and reliability, opened up a new way of detecting adulteration of virgin olive oils.

Electronic Nose as a Tool for Monitoring the Authenticity of Food. A Review

“…Volatile compounds were identified by the SPME-GC/MS technique. The same techniques (HS-E nose, SPME-MS, and SPME-GC/MS) were also applied to detect adulteration of olive oil with rapeseed and sunflower oils (Mildner-Szkudlarz and Jeleń 2010). In both studies, PCA and PLS analyses were applied to the data from two e-noses and chromatographic analyses.…”

“…In both studies, PCA and PLS analyses were applied to the data from two e-noses and chromatographic analyses. The authors reported that all methods of oil aroma analysis allowed discrimination between non-adulterated and adulterated samples and detection of different contents (5-50% v/v) of hazelnut, rapeseed, and sunflower oil adulterants in olive oil (MildnerSzkudlarz and Jeleń 2008;Mildner-Szkudlarz and Jeleń 2010). When HS-E nose data were used, the PLS model predicted hazelnut adulteration of virgin olive oil with a correlation coefficient of 0.997 and an accuracy of 2.85% (MildnerSzkudlarz and Jeleń 2008), rapeseed oil adulteration with a correlation coefficient of 0.989 and an average error of 4.41%, and sunflower oil adulteration with a correlation coefficient of 0.990 and an average error of 4.20% (Mildner-Szkudlarz and Jeleń 2010).…”

“…When HS-E nose data were used, the PLS model predicted hazelnut adulteration of virgin olive oil with a correlation coefficient of 0.997 and an accuracy of 2.85% (MildnerSzkudlarz and Jeleń 2008), rapeseed oil adulteration with a correlation coefficient of 0.989 and an average error of 4.41%, and sunflower oil adulteration with a correlation coefficient of 0.990 and an average error of 4.20% (Mildner-Szkudlarz and Jeleń 2010). When SPME-MS data were used, PLS models predicted rapeseed oil adulteration of virgin oil with a correlation coefficient of 0.994 and an average error of 3.12%, whereas those in the case of sunflower adulteration were 0.992 and 3.26%, respectively (Mildner-Szkudlarz and Jeleń 2010). A good agreement between chromatographic analyses (SPME-fast-GC-FID and/or SPME-GC/MS) and e-nose (HS-E nose or SPME-MS) data was found, but the two latter methods were less time-consuming than GC methods; thus, they seem to be very promising for routine detection of extra virgin olive oil adulteration with cheaper plant oils (MildnerSzkudlarz and Jeleń 2008;Mildner-Szkudlarz and Jeleń 2010).…”

Rapid detection of vegetable cooking oils adulterated with inedible used oil using fluorescence quenching method with aqueous CTAB-coated quantum dots

“…They are recognized as good alternatives to sensitive laboratory-based techniques in some situations [18]. Sensors like electronic noses [19][20][21] and thin film based chips [22] have been reported for identification and classification of vegetable cooking oils. Nanomaterials such as gold nanoparticles [23], quantum dots [24], and carbon-based nanomaterials [25] have been investigated in biosensing strategies to enhance target recognition, amplify the signal, and improve the sensitivity.…”

Uso de semioquímicos en el control de plagas. Estudios básicos y de aplicación

“…This multivariate method has been extensively employed for studies on food volatiles (Jabalpurwala et al, 2009;Elaissi et al, 2010;Giri et al, 2010;Mildner-Szkudlarz & Jelen;Zhang et al, 2010). But regarding to insects, PCA has been employed only to study the volatiles of Hymenopteran species (Steiner et al, 2007;Coppee et al, 2008).…”