PMID- 36435104
OWN - NLM
STAT- MEDLINE
DCOM- 20221206
LR  - 20221206
IS  - 1873-7072 (Electronic)
IS  - 0308-8146 (Linking)
VI  - 405
IP  - Pt B
DP  - 2023 Mar 30
TI  - Discrimination on potential adulteration of extra virgin olive oils consumed in 
      China by differential scanning calorimeter combined with dimensionality reduction 
      classification techniques.
PG  - 134996
LID - S0308-8146(22)02958-2 [pii]
LID - 10.1016/j.foodchem.2022.134996 [doi]
AB  - Thermal properties of extra virgin olive oil (EVOO) consumed in China were 
      investigated through differential scanning calorimetry (DSC), Principal Component 
      Analysis (PCA) dimension reduction analysis combined with K-nearest neighbors 
      (KNN) and support vector machine (SVM) models were used to determine whether oil 
      samples would be EVOO. Both models exhibited a 100% ability to distinguish EVOO 
      from non-EVOO. Additionally, the discrimination test of canola oil was still 
      limited from EVOO adulteration due to its similarity of cooling profiles with 
      EVOO. Canola oil was artificially added into EVOO in 5%, 10%, 20% and 30% and DSC 
      test results collected were detected in computer models. Both models effectively 
      identified even 5% canola oil adulterated in EVOO; however, KNN (93.75%) model 
      exhibited much higher accuracy than SVM (43.92%). In conclusion, DSC combined 
      with KMN model analysis was more available for the adulteration detection of 
      EVOO.
CI  - Copyright (c) 2022 Elsevier Ltd. All rights reserved.
FAU - Huang, Kaiyuan
AU  - Huang K
AD  - Food Science and Technology Program, Department of Life Sciences, BNU-HKBU United 
      International College, Zhuhai, China; Department of Chemistry, The Hong Kong 
      University of Science and Technology, Hong Kong, China.
FAU - Zhong, Peihao
AU  - Zhong P
AD  - Food Science and Technology Program, Department of Life Sciences, BNU-HKBU United 
      International College, Zhuhai, China; Artificial Intelligence Program, The 
      University of Edinburgh, Edinburgh, United Kingdom.
FAU - Xu, Baojun
AU  - Xu B
AD  - Food Science and Technology Program, Department of Life Sciences, BNU-HKBU United 
      International College, Zhuhai, China. Electronic address: baojunxu@uic.edu.cn.
LA  - eng
PT  - Journal Article
DEP - 20221119
PL  - England
TA  - Food Chem
JT  - Food chemistry
JID - 7702639
RN  - 0 (Rapeseed Oil)
RN  - 0 (Olive Oil)
SB  - IM
MH  - Rapeseed Oil
MH  - Olive Oil
MH  - China
MH  - *Drug Contamination
MH  - Calorimetry, Differential Scanning
OTO - NOTNLM
OT  - Adulteration
OT  - Edible oil
OT  - Extra virgin olive oil
OT  - K-nearest neighbors model
OT  - Principal component analysis
COIS- Declaration of Competing Interest The authors declare that they have no known 
      competing financial interests or personal relationships that could have appeared 
      to influence the work reported in this paper.
EDAT- 2022/11/27 06:00
MHDA- 2022/12/07 06:00
CRDT- 2022/11/26 18:32
PHST- 2022/08/27 00:00 [received]
PHST- 2022/11/13 00:00 [revised]
PHST- 2022/11/15 00:00 [accepted]
PHST- 2022/11/27 06:00 [pubmed]
PHST- 2022/12/07 06:00 [medline]
PHST- 2022/11/26 18:32 [entrez]
AID - S0308-8146(22)02958-2 [pii]
AID - 10.1016/j.foodchem.2022.134996 [doi]
PST - ppublish
SO  - Food Chem. 2023 Mar 30;405(Pt B):134996. doi: 10.1016/j.foodchem.2022.134996. 
      Epub 2022 Nov 19.