Discrimination of different oil types and adulterated safflower seed oil based on electronic nose combined with gas chromatography-ion mobility spectrometry

Han, Lujia; Chen, Min; Li, Yiting; Wu, Shasha; Zhang, Li; Tu, Kang; Pan, Leiqing; Wu, Jie; Song, Liang

doi:10.1016/j.jfca.2022.104804

Cited by 29 publications

(7 citation statements)

References 38 publications

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“…Additionally, the AUC and F values were 0.992 and 0.983, respectively. The results obtained in this research were consistent with other products, such as different oil types and adulterated safflower seed oil [58], minced mutton mixed with pork [59], oranges [60], and tomato paste [61]. Moreover, in another study, the electronic nose was used by Gomez, et al [62] to identify the ripening state of tomatoes, and the results revealed that the electronic nose was able to discriminate the ripening states of tomatoes.…”

Section: Linear Discriminant Analysis (Lda)supporting

confidence: 86%

Nondestructive Technique for Identifying Adulteration and Additives in Lemon Juice Based on Analyzing Volatile Organic Compounds (VOCs)

et al. 2023

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In light of the frequent occurrence of counterfeit food sold in global commercial markets, it is necessary to verify the authenticity of tasty natural-plant-based products by checking their labels, as well as their pricing and quality control. Lemon juice has repeatedly been the victim of fraud attempts by manufacturers to lower the price of products. Electronic noses are used in many fields, including the beverage industry, for classification and quality control. This involves the detection and differentiation of volatile organic compounds (VOCs) released from food. This study evaluated pure lemon juice and 11 counterfeit samples (water, lemon pulp, and wheat straw) using an electronic nose equipped with 8 metal oxide sensors to detect fraud. Chemometric methods such as principal component analysis (PCA), linear and quadratic analysis (LDA), support vector machines (SVMs), and artificial neural networks (ANNs) were used to analyze the response patterns of the sensors. The outputs of eight sensors were considered as the input of the model and the number of lemon juice groups, and its adulterations were also considered as the output of the model. Of the total data, 60% (for training), 20% (for validation), and 20% (for testing) were used. According to the results, all models had an accuracy of more than 95%, and the Nu-SVM linear function method had the highest accuracy among all models. Hence, it can be concluded that the electronic nose based on metal oxide semiconductor sensors combined with chemometric methods can be an effective tool with high efficiency for rapid and nondestructive classification of pure lemon juice and its counterfeits.

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Section: Linear Discriminant Analysis (Lda)supporting

confidence: 86%

Nondestructive Technique for Identifying Adulteration and Additives in Lemon Juice Based on Analyzing Volatile Organic Compounds (VOCs)

et al. 2023

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“…Compared to single GC, the HS-GC-IMS technology effectively enhances the sensitivity of complex mixture analysis and has been extensively used to determine volatile flavor ingredient fingerprints for food classification and adulteration detection ( Han et al, 2022 ).…”

Section: Resultsmentioning

confidence: 99%

Volatile aroma compounds of passion fruit seed Oils: HS-GC-IMS analysis and interpretation

Zheng,

Wang,

Yang

et al. 2024

Food Chemistry: X

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“…Principal component analysis is an approach useful to describe the differences between samples by reducing the dimensionality of the data and visualising the information in the data Yang et al, 2022). Han et al (2022) used GC-IMS to determine the flavour fingerprint of safflower seed oil and its adulterated oil, and achieved oil type identification and adulteration detection of safflower seed oil through PCA pattern recognition, which divided the adulterated safflower seed oil samples into two distinguishable clusters based on the proportion of adulteration ≥40% and <40%. Cooling-assisted solid-phase microextraction (CA-SPME) coupled with gas chromatography-mass spectrometry (GC-MS) can also be used to successfully identify the adulteration of edible oils by the PCA method (Xu et al, 2022).…”

Section: Discrimination Of Phco From Five Other Oils Using Pcamentioning

confidence: 99%

Adulteration identification of Hainan camellia (Camellia oleifera Abel.) oil based on comprehensive two‐dimensional gas chromatography and quadrupole time‐of‐flight mass coupled with chemometrics spectrometry

Zheng,

Zhang,

et al. 2024

Int J of Food Sci Tech

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SummaryThe nutritional value of Hainan camellia oil is incomparable to other places, and Hainan camellia oil is expensive, so unscrupulous businessmen often mix other edible oils into them for illegal profit. This study detected the changes of volatile components in Hainan camellia oil adulterated with five edible oils (peanut, soybean, corn, rapeseed, and sunflower oils) using comprehensive two‐dimensional gas chromatography and quadrupole time‐of‐flight mass spectrometry (HS‐SPME‐GC × GC‐Q‐TOFMS). The principal component analysis (PCA) score plot showed that pure Hainan camellia oil (PHCO) and Hainan camellia oil samples were adulterated with other edible oils clearly to identify the adulteration separated from each other. The adulteration of PHCO could be accurately predicted using the developed PCA and OPLS‐DA models for concentrations as low as 5%. More importantly, several potential markers were found to identify the impersonate PHCO. Therefore, the volatile compound determination based on HS‐SPME‐GC × GC‐Q‐TOFMS proved to be an effective method for detecting adulteration of other edible oils in PHCO.

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Discrimination of different oil types and adulterated safflower seed oil based on electronic nose combined with gas chromatography-ion mobility spectrometry

Cited by 29 publications

References 38 publications

Nondestructive Technique for Identifying Adulteration and Additives in Lemon Juice Based on Analyzing Volatile Organic Compounds (VOCs)

Nondestructive Technique for Identifying Adulteration and Additives in Lemon Juice Based on Analyzing Volatile Organic Compounds (VOCs)

Volatile aroma compounds of passion fruit seed Oils: HS-GC-IMS analysis and interpretation

Adulteration identification of Hainan camellia (Camellia oleifera Abel.) oil based on comprehensive two‐dimensional gas chromatography and quadrupole time‐of‐flight mass coupled with chemometrics spectrometry

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