Non-Invasive Detection of Adulterated Olive Oil in Full Bottles Using Time-Domain NMR Relaxometry

Abstract

A fast procedure using time-domain nuclear magnetic resonance (TD-NMR) to detect olive oil adulteration with polyunsaturated vegetable oils in filled bottles is proposed. The 1 H transverse relaxation times (T 2 ) of 37 commercial samples were measured using low-field nuclear magnetic resonance (LF-NMR) spectrometer and a unilateral nuclear magnetic resonance (UNMR) sensor. Results obtained with LF-NMR revealed better feasibility when compared with the UNMR sensor, with higher signal-to-noise (S/N) ratio and larger difference in the T 2 decays. Principal component analysis (PCA) exhibited tight and well-separated clusters of pure olive oil (OO), pure soybean oil (SO), and blends of OO/SO (adulterated samples). Soft independent modeling of class analogies analysis (SIMCA) classification model indicated that five brands of olive oil commercialized in Brazil were adulterated with polyunsaturated fatty acids, further confirmed by high-resolution NMR. Overall, LF-NMR provided a fast procedure for screening olive oil authenticity directly in the sealed bottles.

A taste sensor device for unmasking admixing of rancid or winey-vinegary olive oil to extra virgin olive oil

“…Thus, different analytical techniques have been developed to detect olive oil adulterations (e.g., MALDI-TOF/MS technique; mid infrared, Raman, fluorescence or visible spectroscopy; DNA-targeted approaches; ion mobility spectrometry; nuclear magnetic resonance; dielectric technique; ultrasounds technique; gas chromatography; etc. ), namely to identify and/or quantify the addition of other vegetable oils like camellia, canola, corn, grapeseed, hazelnut, peanut, rapeseed, soya, sesame, soybean and sunflower oils (De Melo Milanez and Pontes, 2015;Sun et al, 2015;Alouache et al, 2016;Jabeur et al, 2016;Kalaitzis and El-Zein, 2016;Nigri and Oumeddour, 2016;Mu et al, 2016;Rashvand et al, 2016;Srigley et al, 2016;Farley et al, 2017;Georgouli et al, 2017;Jergović et al, 2017;Liu et al, 2017;Ok, 2017;Philippidis et al, 2017;Santos et al, 2017;Uncu et al, 2017) or the admixture of lower quality or refined olive oils (Nigri and Oumeddour, 2016;Jergović et al, 2017). Although EVOO have a long history of economic adulteration, its detection still is a challenging task due to the diverse composition of cultivars and the limitations of existing detection methods (Ou et al, 2015;Srigley et al, 2016).…”

Inverse Laplace transform and multiexponential fitting analysis of T2 relaxometry data: a phantom study with aqueous and fat containing samples

“…Corn oil was used as it closely matches the spectrum and longitudinal relaxation times of subcutaneous abdominal fat [30] and was best described by bimodal T2 distributions and biexponential model for 100% of the voxels [12]. Dairy cream of variable fat content was used as they provide a mixed aqueous and fatty environment with measurable contribution from each component with the short T2 component being indicative of the fat fraction [31].…”

“…Free water exhibits pure monoexponential decay with long T2 values while water in tissue bound to lipids and proteins has a different relaxation behaviour with shorter T2 values [9][10][11]. Materials mimicking adipose tissue relaxation such as corn oil present biexponential decay with a shorter and a longer T2 component, indicating the presence of two proton components in the fatty acid chains [12]. Clinical T2 relaxometry sequences measure signal from aqueous or fatty components indiscriminately within a single voxel.…”

Rapid screening for hazelnut oil and high‐oleic sunflower oil in extra virgin olive oil using low‐field nuclear magnetic resonance relaxometry and machine learning

“…demonstrated that EVOO significantly differs from polyunsaturated oils extracted from corn, canola, sunflower and soybean. However, this configuration could not distinguish EVOO from HO 24 . Hence, a more effective data mining approach is necessary to exploit the information provided in relaxation curves.…”