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| Optimal sample thickness based on single integrating sphere technique and authentication of oil-tea camellia seed oil |
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| DOI： |
| KeyWord:oil-tea camellia seed oil authentication single integrating sphere technique optical parameters Monte Carlo algorithm sample thickness qualitative model |
| FundProject:湖南省科技计划重点研发项目（2022NK2048）；湖南省教育厅科学项目（18B192，20A515）；湖南省自然科学基金（2020JJ4142）；湖南省林业杰青培养科研项目（XLK202108-7） |
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| Abstract: |
| To reduce light loss in the spectral data acquisition process using single integrating sphere technique,the sample thickness resulting in the minimum light loss for the detection of oil-tea camellia seed oil was investigated, and the ability of distinguishing adulterated oil-tea camellia seed oil at this optimal sample thickness was researched. The Monte Carlo (MC) algorithm was used to simulate the measurement of samples under the single integrating sphere technique, and the simulated reflectance (MR) and transmittance (MT) were taken as the actual values,the data collected by the single integrating sphere were taken as the predicted values, and the mean relative error (MRE) and the root mean square error (RMSE) between the actual values and the predicted values were taken as the evaluation indexes to determine the optimal sample thickness. Two hundred and thirty sets of samples were prepared with different adulteration ratios, and the spectral data of adulterated oil-tea camellia seed oil with the optimal sample thickness were collected to obtain the absorption coefficients (μa) and approximate scattering coefficients (μs′) of the samples by combining with the inverse doubling (IAD) algorithm. After pre-processing the μa and μs′ by mean centering, the samples were divided into training and test sets using the Kennard-Stone (K-S) algorithm in the ratio of 7∶ 3. Multiclassification qualitative identification models based on support vector machine (SVM) and random forest (RF) were established, respectively. The results showed that the MRE and RMSE of both MR and MT were relatively small when the sample thickness was 14 mm.The discriminative accuracies of the SVM models established for μa and μs′ were 97.10% and 95.65%, respectively, and the discriminative accuracies of the RF models established were 98.55% and 97.10%, respectively. Therefore, based on the single integrating sphere technique under the optimal sample thickness, combined with SVM and RF models, the fast authentication of oil-tea camellia seed oil can be effectively realized. |
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