@article{LI2022, 
author = {Xueting LI and Xionghai YI and Xiang FAN and Wenxuan CAI and Xiaojun DENG and Dehua GUO and Tao DING and Han LIU and Bing NIU and Jing ZENG},
title = {Grade Identification of Olive Oil Based on Multi-element Analysis and Chemometrics},
year = {2022},
journal = {Food Science},
volume = {43},
number = {8},
pages = {317-323},
keywords = {extra virgin olive oil, refined olive oil, element, grade identification, chemometrics},
url = {https://www.sciopen.com/article/10.7506/spkx1002-6630-20210118-201},
doi = {10.7506/spkx1002-6630-20210118-201},
abstract = {Extra virgin olive oil and refined olive oil were evaluated by multi-element analysis combined with chemometrics. The results showed that principal component analysis (PCA) successfully distinguished extra virgin olive oil from refined olive oil, and a reliable orthogonal partial least squares discriminant analysis (OPLS-DA) model was established to identify the grade of olive oil. The results of OPLS-DA were consistent with those of PCA, and good clustering performance was observed on each grade of olive oil; cluster analysis also effectively discriminated the two grades of olive oil. Eight characteristic elements including Al, Fe, Cu, Ba, V, Sc, La and Zn were selected to distinguish them. Therefore, multi-element analysis combined with chemometrics can be used to discriminate extra virgin olive oil from refined olive oil.}
}