Objective To establish a rapid identification model for 5 different types of vegetable oils (Camellia oil, soybean oil, corn oil, sunflower seed oil and peanut oil) and adulterated Camellia oil, using attenuated total reflectance-Fourier transform infrared spectroscopy (ATR-FTIR) and chemometrics methods such as cluster discriminant analysis. Methods The 99 samples of 5 different types of vegetable oils, including Camellia oil, soybean oil, corn oil, sunflower seed oil, and peanut oil were collected. According to the mass percentage of 5%-95%, soybean oil, sunflower seed oil, corn oil, 1:1 corn soybean oil, and palm oil was mixed into the Camellia oil, and 196 samples of the adulterated Camellia oil were obtained. Their infrared spectrum were collected in 600‒4000 cm‒1 region. The models for partial least squares discriminant analysis (PLS-DA), principal component analysis discriminant analysis (PCA-LDA), K-nearest neighbor (KNN), and data driven soft independent modeling of class analogy (DD-SIMCA) were established and compared to determine the optimal recognition model. Results The infrared spectra of each sample group had similar characteristic peaks, peak positions, and peak shapeswere with slight differences. The discriminant model established by DD-SIMCA could completely separate Camellia oil samples from those of other types of vegetable oil. By comparison of PLS-DA, PCA-LDA, and KNN models, it was found that the predicted values of each sample in the training and testing sets of the classification of 5 types of edible vegetable oils samples using PLS-DA and PCA-LDA models were accurate and reliable. Except for peanut oil, the recognition and prediction accuracy of the training and testing sets of other edible vegetable oils were both 100.0%. The quantitative analysis of Camellia oil adulteration using ATR-FTIR combined with PLS could be accurately carried out, which could be used for qualitative and quantitative analysis of adulterated soybean oil, corn oil, sunflower seed oil, etc. The results were reliable, and the lowest limit of detection could reach 5%. Conclusion Adulterated Camellia oil can be determined accurately and efficiently based on ATR-FTIR combined with chemometric methods.
| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |