Qualitative analysis of edible oil oxidation using an olfactory machine

Karami, Hamed; Rasekh, Mansour; Mirzaee‐Ghaleh, Esmaeil

doi:10.1007/s11694-020-00506-0

Cited by 67 publications

(50 citation statements)

References 54 publications

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“…Anisidine index indicates the secondary products of oxidation produced as the result of peroxides destruction (Bonilla, Atares, Vargas, & Chiralt, 2012). According to the strict standard regulation in Iran, the oils with acidity index above 0.6 and peroxide levels more than 5 are considered as the spoiled oil (Karami, Rasekh, & Mirzaee‐Ghaleh, 2020).…”

Section: Resultsmentioning

confidence: 99%

Application of the E‐nose machine system to detect adulterations in mixed edible oils using chemometrics methods

Karami

Rasekh

Mirzaee‐Ghaleh

2020

J Food Process Preserv

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Foodstuff adulteration involves addition of any low‐cost substances to the high‐price materials to reduce the content of the expensive components, and hence decrease the production cost and reach to the maximum profit. An electronic nose was used in this study to detect the adulterations in mixed edible oils. The acidity, peroxide, anisidine, and Totox values of the edible oil samples were measured according to the official American Oil Chemist Society (AOCS) standard. The results were analyzed by Cluster analysis (CA), principle component analysis (PCA), principal component regression (PCR), linear discriminant analysis (LDA), and artificial neural network (ANN) methods with accuracy of 95, 98, 98, 88, and 97.3%, respectively. According to the results, the ANN method with structure of 8‐7‐5 showed the highest accuracy in classification of oil adulteration. Its correct classification ratio, mean square errors, and correlation (r) were 97.3%, .117211, and .0963, respectively. The results also indicated that the proposed method can be used as an alternative of the official AOCS methods to innovatively detect the edible oil adulteration with high accuracy and speed. Practical applications Lipid oxidation is one of the major causes of food spoilage especially in those containing oil. AOCS has developed various methods to evaluate the oxidation status of the oil assets. However, these chemical tests are time‐consuming, destructive, and costly and require several glassware and reagents. E‐nose could be used for real‐time monitoring of the volatile components of the food to evaluate different features of the product. Generally, E‐nose evaluates mixture of smells released form a sample and is a reliable, nondestructive, cost‐effective, and portable method with high feasibility and speed as well as simple use. CA, PCA, and ANN methods were also applied for qualitative differentiation of different adulteration percentages in oxidized and nonoxidized oils.

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Section: Resultsmentioning

confidence: 99%

Application of the E‐nose machine system to detect adulterations in mixed edible oils using chemometrics methods

Karami

Rasekh

Mirzaee‐Ghaleh

2020

J Food Process Preserv

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“…The detection system includes nine MOS (Table 2), which electrical properties change according to the adsorption phenomena that occurs on the sensors surface when in contact with volatile compounds. The same or similar MOS have been previously used due to their capability to detect different aroma compounds of olive fruits [34] and vegetable oils [17,22,35,36]. The MOS sensors are porous layers heated by a filament that undergoes a redox reaction when it comes in contact with a reducing or oxidizing volatile compound, changing the electrical resistance across the circuit proportionally to the compound concentration.…”

Section: E-nose Analysis 231 Lab-made Devicementioning

confidence: 99%

“…Samples (0.5 mL) were then put into a glass vial (25 mL) and placed in the sampling chamber during 13 min (to allow obtaining a headspace with a volatile fraction representative of the sample) at 28 • C (temperature recommended by the International Olive Council for olive oils sensory analysis) [5]. Although several gas sample pre-concentration procedures exist, the static headspace technique was chosen due to its simplicity and rapid acquisition of a representative sample of the oil's volatile fraction, allowing an easy on-line and in-situ implementation, being widely implemented with both lab-made and commercial E-noses [30,35,36]. At the same time, the E-nose system was cleaned during 13 min using air flow (pumped under vacuum) or nitrogen flow (UN 1066, Linde 089 cyl 02/15) for the standard solutions or olive oils analysis, respectively, enabling reaching a stable signal baseline, indicative of a cleaned environment.…”

Section: Sample Conditioning and Analysismentioning

confidence: 99%

Application of a lab-made electronic nose for extra virgin olive oils commercial classification according to the perceived fruitiness intensity

Teixeira

Dias

Rodrigues

et al. 2021

Talanta

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An electronic nose, comprising nine metal oxide sensors, has been built aiming to classify olive oils according to the fruity intensity commercial grade (ripely fruity or light, medium and intense greenly fruity), following the European regulated complementary terminology. The lab-made sensor device was capable to differentiate standard aqueous solutions (acetic acid, cis-3-hexenyl, cis-3-hexen-1-ol, hexanal, 1-hexenol and nonanal) that mimicked positive sensations (e.g., fatty, floral, fruit, grass, green and green leaves attributes) and negative attributes (e.g., sour and vinegary defects), as well as to semi-quantitatively classify them according to the concentration ranges (0.05-2.25 mg/kg). For that, unsupervised (principal component analysis) and supervised (linear discriminant analysis: sensitivity of 92% for leave-one-out cross validation) classification multivariate models were established based on nine or six gas sensors, respectively. It was also showed that the built E-nose allowed differentiating/discriminating (sensitivity of 81% for leave-one-out cross validation) extra virgin olive oils according to the perceived intensity of fruitiness as ripely fruity, light, medium or intense greenly fruity. In conclusion, the gas sensor device could be used as a practical preliminary non-destructive tool for guaranteeing the correctness of olive oil fruitiness intensity labelling.

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“…Their Enose system composed of six commercial SMOs was able to successfully discriminate between twenty-seven and identify five Moroccan virgin olive oil cluster samples based on the analysis carried out by techniques such as PCA and LDA. Karami et al constructed a portable Enose system consisting of eight SMO sensors for investigating the oxidative degree of edible oil along with identifying the presence of adulterants [97]. In combination with CA, PCA, SVM, PLS regression, and quadratic discriminant analysis (QDA) techniques, the developed Enose device was able to successfully detect the levels of oxidation in edible oil with different levels of precision and also profile the level of different adulterants in the sample of oxidised oil compared to the non-oxidized sample.…”

Section: Oilsmentioning

confidence: 99%

An Outlook of Recent Advances in Chemiresistive Sensor-Based Electronic Nose Systems for Food Quality and Environmental Monitoring

John

Murugappan

Nisbet

et al. 2021

Sensors

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An electronic nose (Enose) relies on the use of an array of partially selective chemical gas sensors for identification of various chemical compounds, including volatile organic compounds in gas mixtures. They have been proposed as a portable low-cost technology to analyse complex odours in the food industry and for environmental monitoring. Recent advances in nanofabrication, sensor and microcircuitry design, neural networks, and system integration have considerably improved the efficacy of Enose devices. Here, we highlight different types of semiconducting metal oxides as well as their sensing mechanism and integration into Enose systems, including different pattern recognition techniques employed for data analysis. We offer a critical perspective of state-of-the-art commercial and custom-made Enoses, identifying current challenges for the broader uptake and use of Enose systems in a variety of applications.

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Qualitative analysis of edible oil oxidation using an olfactory machine

Cited by 67 publications

References 54 publications

Application of the E‐nose machine system to detect adulterations in mixed edible oils using chemometrics methods

Application of the E‐nose machine system to detect adulterations in mixed edible oils using chemometrics methods

Application of a lab-made electronic nose for extra virgin olive oils commercial classification according to the perceived fruitiness intensity

An Outlook of Recent Advances in Chemiresistive Sensor-Based Electronic Nose Systems for Food Quality and Environmental Monitoring

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