Vibrational spectroscopy and chemometrics to assess authenticity, adulteration and intrinsic quality parameters of edible oils and fats

Nunes, Cleiton Antônio

doi:10.1016/j.foodres.2013.08.041

Cited by 150 publications

(75 citation statements)

References 39 publications

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“…The intrinsic parameters such as free fatty acids (Nunes, 2014) of edible oils could depend on different factors including geographical origin. In particular for determining the minor constituents of edible oils with less than 1-2%, isolation might be needed (Zamora et al, 2001).…”

Section: Discussionmentioning

confidence: 99%

Detection of olive oil adulteration by low-field NMR relaxometry and UV-Vis spectroscopy upon mixing olive oil with various edible oils

2017

Grasas y Aceites

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SUMMARY:Adulteration of olive oil using unhealthy substitutes is considered a threat for public health. Low-field (LF) proton (1H) nuclear magnetic resonance (NMR) relaxometry and ultra-violet (UV) visible spectroscopy are used to detect adulteration of olive oil. Three different olive oil with different oleoyl acyl contents were mixed with almond, castor, corn, and sesame oils with three volumetric ratios, respectively. In addition, Arbequina olive oil was mixed with canola, flax, grape seed, peanut, soybean, and sunflower seed oils with three volumetric ratios. Transverse magnetization relaxation time (T 2 ) curves were fitted with bi-exponential decaying functions. T 2 times of each mixture of olive oils and castor oils, and olive oils and corn oils changed systematically as a function of volumetric ratio. To detect the adulteration in the mixtures with almond and sesame oils, both LF 1 H NMR relaxometry and UV-Vis spectroscopy were needed, where UV-Vis-spectroscopy detected the adulteration qualitatively. In the mixtures of Arbequina olive oil and flax, peanut, soybean, and sunflower seed oils, both T 21 and T 22 values became longer systematically as the content of the olive oil was decreased. The unique UV-Vis maximum absorbance of flax oil at 320.0 nm shows the adulteration of olive oil qualitatively. KEYWORDS: Adulteration detection; Low-field NMR relaxometry; Olive oil; UV-Vis spectroscopyRESUMEN: Detección de la adulteración de aceite de oliva mediante relaxometría magnética nuclear de campo bajo y espectroscopía UV-Vis sobre mezcla de aceite de oliva con diversos aceites comestibles. La adulteración del aceite de oliva con sustituyentes menos saludables es una amenaza para la salud pública. En este trabajo, la detección de la adulteración del aceite de oliva se demuestra utilizando tanto relaxometría magnética nuclear de campo bajo (LF) de protones ( 1 H) (RMN) y espectroscopía visible y ultra-violeta (UV). Tres muestras de aceites de oliva con diferentes contenidos en oleico se mezclaron con aceites de almendra, ricino, maíz y sésamo con tres relaciones volumétricas. Además, el de arbequina de California se mezcló con cánola, lino, semilla de uva, cacahuete, soja y aceites de girasol con tres relaciones volumétricas. Las curvas de tiempo de relajación de magnetización transversal (T2) fueron completadas con funciones de decaimiento biexponencial. Los tiempos T2 determinados para cada mezcla de aceite de oliva con ricino y maíz cambian sistemáticamente conforme las relaciones volumétricas. Para detectar la adulteración de los aceites de oliva con aceites de almendra y de sés-amo, se necesitan tanto relaxometría LF 1H RMN como la espectroscopía UV-Vis. En las mezclas de aceite de oliva arbequina con aceites de lino, maní, soja y girasol, ambos valores T21 y T22 se hicieron mayores sistemáti-camente conforme el porcentaje de aceite de oliva se reduce en la mezcla. El máximo de absorbancia UV-Vis del aceite de lino a 320,0 nm demostrará la adulteración del aceite de oliva cualitativamente.

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Section: Discussionmentioning

confidence: 99%

Detection of olive oil adulteration by low-field NMR relaxometry and UV-Vis spectroscopy upon mixing olive oil with various edible oils

2017

Grasas y Aceites

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“…Official methods and recommended practices have been established by the American Oil Chemists' Society to assess olive oil quality [8]. However, some of these methods are quite expensive, non-green techniques, and require fulfillment of straight standardized procedures to ensure accuracy.…”

Section: Introductionmentioning

confidence: 99%

Perception of olive oils sensory defects using a potentiometric taste device

Veloso

Silva

Rodrigues

et al. 2018

Talanta

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A B S T R A C TThe capability of perceiving olive oils sensory defects and intensities plays a key role on olive oils quality grade classification since olive oils can only be classified as extra-virgin if no defect can be perceived by a human trained sensory panel. Otherwise, olive oils may be classified as virgin or lampante depending on the median intensity of the defect predominantly perceived and on the physicochemical levels. However, sensory analysis is time-consuming and requires an official sensory panel, which can only evaluate a low number of samples per day. In this work, the potential use of an electronic tongue as a taste sensor device to identify the defect predominantly perceived in olive oils was evaluated. The potentiometric profiles recorded showed that intraand inter-day signal drifts could be neglected (i.e., relative standard deviations lower than 25%), being not statistically significant the effect of the analysis day on the overall recorded E-tongue sensor fingerprints (Pvalue = 0.5715, for multivariate analysis of variance using Pillai's trace test), which significantly differ according to the olive oils' sensory defect (P-value = 0.0084, for multivariate analysis of variance using Pillai's trace test). Thus, a linear discriminant model based on 19 potentiometric signal sensors, selected by the simulated annealing algorithm, could be established to correctly predict the olive oil main sensory defect (fusty, rancid, wet-wood or winey-vinegary) with average sensitivity of 75 ± 3% and specificity of 73 ± 4% (repeated K-fold cross-validation variant: 4 folds×10 repeats). Similarly, a linear discriminant model, based on 24 selected sensors, correctly classified 92 ± 3% of the olive oils as virgin or lampante, being an average specificity of 93 ± 3% achieved. The overall satisfactory predictive performances strengthen the feasibility of the developed taste sensor device as a complementary methodology for olive oils' defects analysis and subsequent quality grade classification. Furthermore, the capability of identifying the type of sensory defect of an olive oil may allow establishing helpful insights regarding bad practices of olives or olive oils production, harvesting, transport and storage.

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Section: Introductionmentioning

confidence: 99%

“…The economic value of olive oils make this food product very prone to fraud, including mislabeling of olive oil commercial category, geographical or olive cultivar origin [3][4][5][6][7]. So, several gas-, liquid-and mass-spectrometry chromatography, DNA and spectroscopy based methods have been developed to assess olive oil quality and authenticity as well as to detect possible adulterations [3,5,6,[8][9][10][11][12][13][14][15][16]. Electrochemical sensors have also been extensively used, including electronic noses and electronic tongues (E-tongues), individually or in combination, mainly with the aim of identifying possible adulterations or classifying olive oils according to quality level, geographical origin or olive cultivar [16][17][18][19][20][21][22][23][24][25][26][27][28].…”

Section: Introductionmentioning

confidence: 99%

Sensory intensity assessment of olive oils using an electronic tongue

Veloso

Dias

Rodrigues

et al. 2016

Talanta

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a b s t r a c tOlive oils may be commercialized as intense, medium or light, according to the intensity perception of fruitiness, bitterness and pungency attributes, assessed by a sensory panel. In this work, the capability of an electronic tongue to correctly classify olive oils according to the sensory intensity perception levels was evaluated. Cross-sensitivity and non-specific lipid polymeric membranes were used as sensors. The sensor device was firstly tested using quinine monohydrochloride standard solutions. Mean sensitivities of 14 7 2 to 257 6 mV/decade, depending on the type of plasticizer used in the lipid membranes, were obtained showing the device capability for evaluating bitterness. Then, linear discriminant models based on sub-sets of sensors, selected by a meta-heuristic simulated annealing algorithm, were established enabling to correctly classify 91% of olive oils according to their intensity sensory grade (leave-one-out cross-validation procedure). This capability was further evaluated using a repeated K-fold cross-validation procedure, showing that the electronic tongue allowed an average correct classification of 80% of the olive oils used for internal-validation. So, the electronic tongue can be seen as a taste sensor, allowing differentiating olive oils with different sensory intensities, and could be used as a preliminary, complementary and practical tool for panelists during olive oil sensory analysis.

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Vibrational spectroscopy and chemometrics to assess authenticity, adulteration and intrinsic quality parameters of edible oils and fats

Cited by 150 publications

References 39 publications

Detection of olive oil adulteration by low-field NMR relaxometry and UV-Vis spectroscopy upon mixing olive oil with various edible oils

Detection of olive oil adulteration by low-field NMR relaxometry and UV-Vis spectroscopy upon mixing olive oil with various edible oils

Perception of olive oils sensory defects using a potentiometric taste device

Sensory intensity assessment of olive oils using an electronic tongue

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