Related Experiment Video
Updated: Aug 19, 2025
Chromatographic Fingerprinting by Template Matching for Data Collected by Comprehensive Two-Dimensional Gas Chromatography
Published on: September 2, 2020
Discrimination on potential adulteration of extra virgin olive oils consumed in China by differential scanning
Kaiyuan Huang1, Peihao Zhong2, Baojun Xu3
1Food 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.
Abstract:
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.
