| Autor: |
Jianxun Han, Ruixue Sun, Xiuying Zeng, Jiukai Zhang, Ranran Xing, Chongde Sun, Ying Chen |
| Jazyk: |
angličtina |
| Rok vydání: |
2020 |
| Předmět: |
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| Zdroj: |
Molecules, Vol 25, Iss 9, p 2036 (2020) |
| Druh dokumentu: |
article |
| ISSN: |
1420-3049 |
| DOI: |
10.3390/molecules25092036 |
| Popis: |
Currently, the authentication of camellia oil (CAO) has become very important due to the possible adulteration of CAO with cheaper vegetable oils such as rapeseed oil (RSO). Therefore, we report a Fourier transform infrared (FTIR) spectroscopic method for detecting the authenticity of CAO and quantifying the blended levels of RSO. In this study, two characteristic spectral bands (1119 cm−1 and 1096 cm−1) were selected and used for monitoring the purity of CAO. In combination with principal component analysis (PCA), linear discriminant analysis (LDA), and partial least squares regression (PLSR) analysis, qualitative and quantitative methods for the detection of camellia oil adulteration were proposed. The results showed that the calculated I1119/I1096 intensity ratio facilitated an initial check for pure CAO and six other edible oils. PCA was used on the optimized spectral region of 1800–650 cm−1. We observed the classification of CAO and RSO as well as discrimination of CAO with RSO adulterants. LDA was utilized to classify CAO from RSO. We could differentiate and classify RSO adulterants up to 1% v/v. In the quantitative PLSR models, the plots of actual values versus predicted values exhibited high linearity. Root mean square error of calibration (RMSEC) and root mean square error of cross validation (RMSECV) values of the PLSR models were 1.4518–3.3164% v/v and 1.7196–3.8136% v/v, respectively. This method was successfully applied in the classification and quantification of CAO adulteration with RSO. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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