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| 基于挥发性成分定性判别风味油茶籽油掺伪浸出油茶籽油PCA模型和逻辑回归模型的对比分析 |
| Comparative analysis between PCA model and logistic regression model for qualitative identification of flavor oil-tea camellia seed oil adulteration with leaching oil-tea camellia seed oil based on volatile components |
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| DOI： |
| 中文关键词: 风味油茶籽油 浸出油茶籽油 挥发性成分 主成分分析模型 逻辑回归模型 定性判别 |
| 英文关键词:flavor oil-tea camellia seed oil leaching oil-tea camellia seed oil volatile component principal component analysis model logistic regression model qualitative identification |
| 基金项目: |
| Author Name | Affiliation | | SUN Tingting1,2, CHEN Zhiqing1,2, LIU Jianbo3, REN Jiali1,2,ZHONG Haiyan1,2, ZHOU Bo1,2 | 1.Hunan Key Laboratory of Forestry Edible Sources Safety and Processing, Changsha 410004，China
2.School of Food Science and Engineering, Central South University of Forestry and Technology, Changsha 410004, China
3.Food and Drug Inspection Institute of Yueyang City Inspection and Testing Center, Yueyang 414000, Hunan, China |
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| 中文摘要: |
| 为了解决风味（原香和烤香）油茶籽油掺伪浸出油茶籽油的定性判别问题，设计高、低两个掺伪梯度，基于挥发性成分构建并对比分析了定性判别风味油茶籽油掺伪浸出油茶籽油的主成分分析（PCA）模型和逻辑回归模型。结果表明：逻辑回归模型定性判别风味油茶籽油掺伪浸出油茶籽油的能力较强，优于PCA模型；高掺伪梯度下定性判别原香和烤香油茶籽油掺伪浸出油茶籽油，PCA模型的最低检出限分别为20%和60%，而逻辑回归模型的最低检出限均为10%；低掺伪梯度下定性判别原香和烤香油茶籽油掺伪浸出油茶籽油，PCA模型的判别不准确，而逻辑回归模型的最低检出限均为4%。逻辑回归模型能很好地定性判别风味油茶籽油掺伪浸出油茶籽油。 |
| 英文摘要: |
| Based on volatile components, principal component analysis (PCA) and logistic regression (LR)models were constructed and compared to solve the problem of qualitative identification of flavor (original/roasted) oil-tea camellia seed oil adulterated with leaching oil-tea camellia seed oil under high and low adulteration gradients.The results showed that LR model had a good ability to qualitatively identify the flavor oil-tea camellia seed oil adulterated with leaching oil-tea camellia seed oil, which was better than that of PCA model. Under the high adulteration gradient, the detection limit of the PCA model for original/roasted oil-tea camellia seed oil adulterated with leaching oil-tea camellia seed oil was 20%/60%, and the detection limit of the LS model was 10%/10%, respectively. Under the low adulteration gradient, the detection limit of LR model for original/roasted oil-tea camellia seed oil adulterated with leaching oil-tea camellia seed oil was 4%/4%, but the discriminative ability of the PCA model was not accurate.The LR model can qualitatively identify flavor oil-tea camellia seed oil adulterated with leaching oil-tea camellia seed oil. |
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