Detection of camellia oil adulteration using chemometrics based on fatty acids GC fingerprints and phytosterols GC–MS fingerprints

•Fatty acids and sterols with chemometrics were used to authenticate camellia oil.•PCA can differentiate camellia oil using triterpene alcohols.•PLS-DA can help discriminate the specific adulterated oil types.•PLS can be successfully applied for the adulterated level prediction.•Less than 22 key mar...

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Vydáno v:Food chemistry Ročník 352; s. 129422
Hlavní autoři: Shi, Ting, Wu, Gangcheng, Jin, Qingzhe, Wang, Xingguo
Médium: Journal Article
Jazyk:angličtina
Vydáno: England Elsevier Ltd 01.08.2021
Témata:
accuracy
adulterated products
Adulteration
calcium oxide
Camellia
Camellia - chemistry
Camellia oil
Chemometrics
corn oil
detection
Discriminant Analysis
Fatty acid
fatty acids
Fatty Acids - analysis
food chemistry
Food Contamination - analysis
Fraud - prevention & control
Gas Chromatography-Mass Spectrometry
Informatics
Least-Squares Analysis
olive oil
peanut oil
Phytosterols
Phytosterols - analysis
Plant Oils - chemistry
prediction
Principal Component Analysis
rapeseed oil
rice bran oil
rice oil
sesame oil
soybean oil
squalene
sunflower oil
triterpenoids
vegetables
Adulteration
Fatty acid
Camellia oil
Chemometrics
Phytosterols
ISSN:0308-8146, 1873-7072, 1873-7072
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Shrnutí:•Fatty acids and sterols with chemometrics were used to authenticate camellia oil.•PCA can differentiate camellia oil using triterpene alcohols.•PLS-DA can help discriminate the specific adulterated oil types.•PLS can be successfully applied for the adulterated level prediction.•Less than 22 key markers with VIP scores were useful for PLS optimization. The fatty acid, squalene, and phytosterols, coupled to chemometrics were utilized to detect the adulteration of camellia oil (CAO) with palm superolein (PAO), refined olive oil (ROO), high oleic- sunflower oil (HO-SUO), sunflower oil (SUO), corn oil (COO), rice bran oil (RBO), rice oil (RIO), peanut oil (PEO), sesame oil (SEO), soybean oil (SOO), and rapeseed oil (RAO). CAO was characterized with higher triterpene alcohols, thus differentiated from other vegetable oils in principle component analysis (PCA). Using partial least squares-discriminant analysis (PLS-DA), CAO adulterated with PAO, ROO, HO-SUO, SUO, COO, RBO, RIO, PEO, SEO, SOO, RAO (5%–100%, w/w), could be classified, especially higher than 92.31% of the total discrimination accuracy, at an adulterated ratio above 30%. With less than 22 potential key markers selected by the variable importance in projection (VIP), the optimized PLS models were confirmed to be accurate for the adulterated level prediction in CAO.
Bibliografie:ObjectType-Article-1
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content type line 23
ISSN:0308-8146
1873-7072
1873-7072
DOI:10.1016/j.foodchem.2021.129422